Security and Privacy Applications for Smart City Development [1st ed.] 9783030531485, 9783030531492

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Studies in Systems, Decision and Control 308

Sharvari Chandrashekhar Tamane Nilanjan Dey Aboul-Ella Hassanien   Editors

Security and Privacy Applications for Smart City Development

Studies in Systems, Decision and Control Volume 308

Series Editor Janusz Kacprzyk, Systems Research Institute, Polish Academy of Sciences, Warsaw, Poland

The series “Studies in Systems, Decision and Control” (SSDC) covers both new developments and advances, as well as the state of the art, in the various areas of broadly perceived systems, decision making and control–quickly, up to date and with a high quality. The intent is to cover the theory, applications, and perspectives on the state of the art and future developments relevant to systems, decision making, control, complex processes and related areas, as embedded in the fields of engineering, computer science, physics, economics, social and life sciences, as well as the paradigms and methodologies behind them. The series contains monographs, textbooks, lecture notes and edited volumes in systems, decision making and control spanning the areas of Cyber-Physical Systems, Autonomous Systems, Sensor Networks, Control Systems, Energy Systems, Automotive Systems, Biological Systems, Vehicular Networking and Connected Vehicles, Aerospace Systems, Automation, Manufacturing, Smart Grids, Nonlinear Systems, Power Systems, Robotics, Social Systems, Economic Systems and other. Of particular value to both the contributors and the readership are the short publication timeframe and the world-wide distribution and exposure which enable both a wide and rapid dissemination of research output. ** Indexing: The books of this series are submitted to ISI, SCOPUS, DBLP, Ulrichs, MathSciNet, Current Mathematical Publications, Mathematical Reviews, Zentralblatt Math: MetaPress and Springerlink.

More information about this series at http://www.springer.com/series/13304

Sharvari Chandrashekhar Tamane Nilanjan Dey Aboul-Ella Hassanien •

•

Editors

Security and Privacy Applications for Smart City Development

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Editors Sharvari Chandrashekhar Tamane Department of Information Technology Jawaharlal Nehru Engineering College MGM University Aurangabad, Maharashtra, India

Nilanjan Dey Department of Information Technology Techno India College of Technology Kolkata, West Bengal, India

Aboul-Ella Hassanien Department of Information Technology Faculty of Computers and Information Cairo University Giza, Egypt

ISSN 2198-4182 ISSN 2198-4190 (electronic) Studies in Systems, Decision and Control ISBN 978-3-030-53148-5 ISBN 978-3-030-53149-2 (eBook) https://doi.org/10.1007/978-3-030-53149-2 © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 This work is subject to copyright. All rights are solely and exclusively licensed by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Springer imprint is published by the registered company Springer Nature Switzerland AG The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland

Preface

The main purpose of this book publication is to cover the fundamental concepts of smart city, its privacy and security along with recent research development in the field of computer technology related to smart city infrastructure and cybersecurity community. Security in Smart City Applications may provide solutions for problems such as overcrowded cities, lack of resources and insufficient transportation choices. It also includes various real-time/offline applications and case studies in the fields of engineering, computer science, information security, interdisciplinary tools and cases of IoT, big data and smart city with modern tools and technologies. This book also focuses on new application areas to implement smart city projects along with IoT and technologies, smart city and future luxuries, the interdisciplinary tools and cases of IoT, IoT and Smart City Applications, security and privacy in the smart city.

Objective of the Book The main objective of this book publication is to explore the concepts of security and privacy applications for smart city development along with the recent research development. As the population grows and resources become scarcer, the efficient usage of these limited goods becomes more important. Smart cities are a key factor in the consumption of materials and resources. Built on and integrating with big data, the cities of the future are becoming a realization today. The integration of big data and interconnected technology along with the increasing population will lead to the necessary creation of smart cities. To continue providing people with safe, comfortable and affordable places to live, cities must incorporate techniques and technologies to bring them into the future.

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Organization of the Book The book consists of a total 11 chapters related to the security and privacy applications for smart city development. The first part consists of three chapters which tell about technologies, challenges and issues associated with security and privacy of smart cities. Smart cities help to improve the quality of daily life, encourage justifiable development and improve the functionality of urban systems. Even if many smart innovative applications are existing, it can’t help to address security and privacy issues as it comes. One should be aware of possible security and privacy threats while designing and implementing new applications. Traditional cybersecurity protection strategies cannot be applied directly to these intelligent applications because of the heterogeneity, scalability and dynamic characteristics of smart cities. The motivation of these factors generated interest in me to include chapters in this part that covers information about smart city security and privacy: technologies, open challenges and issues and to pave the way for further exploration. By 2025, the world will have 80 billion sensor devices providing greater connectivity based on enormous amounts of data. With the right systems in place along with quality control and data analysis, it is possible to ensure that smart city infrastructure and assets are optimized for efficiency, sustainability and safety. The second part is elaborated on the smart infrastructure. Fourth chapter from this part explained a Comprehensive Proposal for Blockchain-Oriented Smart City Architecture. Cities are now transforming from digital cities to smart cities that are more technology oriented. A city becomes “smart” when it is instrumented, interconnected, adaptive, autonomous, learning, self-repairing and robust. Parts of its infrastructure and facilities are digitally connected to deliver services to their citizens. The purpose of the third part is to provide Smart City Applications and its services. The deployment and implementation of innovative applications along with its challenges for advanced cities are made available in five different chapters of this part. These applications include technological solutions for various problems like: Smart Rain Water Harvesting, Smart Street Lighting, Digital Identity Management, Solar Energy for Sustainable and Efficient Development, Intelligence Transport System in Smart Cites and Emerging Communications Applications. These applications are discussed in sixth to eleventh chapters.

Target Audience The target audience of this book will be composed of professionals and researchers working in the fields of security and privacy Smart City Applications, big data, IoT and smart cities, e.g., software/hardware engineering/science field, researchers, academicians, advanced-level students, technology developers, doctors and

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biologists. Furthermore, the book will provide insights and support executives concerned with recent technologies that have magnetized much attention as big data analytics for smart and connected cities. The target audience can get more insights on big data and analytics, they may discover new things for marketing and at the same time they learn how to protect big data from risk and fraud, and they can use various technologies provided in this book to develop their applications (Table 1).

First Part: Security and Privacy in Smart Cities: Technologies, Challenges and Issues Nowadays, the rapid growth in the urban population increases proper utilization of resources, services and infrastructure. These needs can be fulfilled by connecting and communicating various IoT devices with each other over the Internet to establish smart systems. Table 1 Organization of the book

First Part: Security and Privacy in Smart Cities: Technologies, Challenges and Issues Second Chapter First Chapter Open Challenges in Smart Cities: Privacy Privacy and Security Technologies and Security Third Chapter Security and Privacy Issues in Smart City: Threats and their Countermeasures Second Part: The Smart Infrastructure Fourth Chapter A Comprehensive Proposal for Blockchain-Oriented Smart City Architecture Third Part: The Imperative Applications of Smart City Development Fifth Chapter Sixth Chapter Smart Rain Water Harvesting for Smart Smart Street Lighting in Smart Cities: A Cities Transition from Traditional Street Lighting Eighth Chapter Seventh Chapter Solar Energy for A New Approach for Ninth Chapter Sustainable and Intelligence Transport System in Digital Identity Efficient Development Smart City Management using of Smart City Blockchain Technology Tenth Chapter Eleventh Chapter Application of Internet of Things in Blockchain technology and emerging Mishap Avoidance Due to Swamping: A communications applications Novel Approach

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This part elaborates information about technologies, challenges and various issues about security and privacy in smart cities. The intention of the first chapter is to provide the information about the concept of a smart city, the features it inhibits and the vulnerabilities it is exposed to. From IoT, through cloud computing, big data, authors have touched on various security threats that could possibly be faced in a smart city. Knowing all the threats, authors have elaborated possible solutions on it. A simple machine learning algorithm is demonstrated that can possibly determine the probability of future threats in order to reduce revenue losses. Review studies of a few smart cities have been elaborated and touched upon which is followed by future research directions. The chapter is concluded by proposing a layered architecture solution with attack and prevention schemes. The second chapter has provided Open Challenges in Smart Cities. The construction of smart cities is no longer a future endeavor. Even though the implementation of smart city comes with enormous conveniences, the realistic implementation is challenged in different aspects. Two of the major aspects along with the design, maintenance and implementation costs are privacy and security. The frameworks introduced for smart city impose many challenges regarding privacy and security of the citizens. Open networks, smart phones, computers, etc., are used for the communication in the smart city, making the sensitive data vulnerable to attacks. It is also vital to deal with the privacy issues. Thus, maintaining security and ensuring the privacy in the smart city is necessary and turning out as an open challenge. The present chapter proposes Cloud Data Security Model (CDSM) for the better security of data using the cloud storage mechanism. The CSDM proposes four different categories of cloud accounts with special permissions to access the data. Moreover, with the data access record, the owner is completely aware of who is accessing the data. The focus of the third chapter is on the Security and Privacy Issues in Smart City: Threats and Their Countermeasures. Nowadays, there are large variety of applications available for the technologies like smart cities, smart phones, IoT and cloud computing. Applications those are installed on user’s devices have access to user data. Vast amount of data has to be handled on a network and cloud. While handling such user data, security and privacy must be provided to protect sensitive data. The data may consist of personal data, medical data, financial records or any other form which must be kept confidential. This chapter discusses the basics of smart city, its applications and needs, security and privacy issues, data protection schemes, possible attacks and solutions that can be provided to protect user.

Second Part: The Smart Infrastructure IoT plays a very important role in industry. With minimum investment, it gives good results. This engrossed several organizations to make use of IoT and gain insights of data to make important decisions. These decisions are benefited to improve productivity, work effectiveness, marketing capability, etc. for growing their businesses.

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The fourth chapter from this part provided a Comprehensive Proposal for Blockchain-Oriented Smart City Architecture. The astounding technological advancements and massive urbanization calls for the advent of “smart cities” to ensure the best living standards of its residents. Smart cities use information and communication technologies (ICT) to generate efficiencies, improvise sustainability, encourage economic development, allow business to thrive, boost innovation, assure judicious energy and resource consumption, reduce wastage and enhance quality of life for people. This thus requires perpetual storage of data related to basic components of a smart city and its continual surveillance. The fundamental characteristics of a blockchain make them the most lucrative platform to store valuable data essential for smooth functioning of smart cities. It also ensures the privacy, authenticity and confidentiality of this data. This chapter first identifies the essential elements of a smart city, then provides a detailed literature on the existing techniques to realize a smart city, highlights their shortcomings and explains how blockchain contributes toward their effective implementation.

Third Part: The Imperative Applications of Smart City Development This part discusses various applications of smart city development. The fifth chapter focuses on Smart Rain Water Harvesting for smart cities. Urbanization is the core process in the development of the economy of every nation which boosts economic growth and development at one side, the demand for facilities and resources on the other side. Nowadays, the most common solution for the healthy growth of urban islands is to make cities smart. Therefore, smart development aims to provide a better quality of life in the context of existing urban planning issues which focuses on providing the infrastructure services and utilities to urban settlements with the integration of modern technology. Sustainable development is one of the most important components of smart city planning and development. This sustainability can be achieved through smart planning and management of natural resources which include optimum use, recycle and reuse. In the present book chapter, various components of the smart city, the importance of water sustainability in smart cities, the role of climate change and smart water management for smart cities have been discussed. The sixth chapter provides information about Smart Street Lighting in Smart Cities: A Transition from Traditional Street Lighting. The world population has grown exponentially in the last few decades. In the most of the world’s big cities, it is very difficult to provide the resources like energy, water, transportation and other essential services to the public due to the increase in the demands on resources and infrastructure. Internet of Things (IoT) is a technology that makes possible to keep the cities green and safe by interconnecting the devices, vehicles and infrastructure so that the energy and water consumption can be reduced and quality of the people

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can be improved. The objective of the smart cities could be to increase the economic growth, to construct a clean and sustainable environment, to enhance the income of the people and to make the transparent governance of the city. This chapter provides the need for Smart Street Lighting in smart cities and the suggestions for the implementation. Smart Street Lighting Framework which reduces the cost and the energy consumption is proposed. The present implementations of intelligent street lighting around the world are also discussed. The seventh chapter focuses on the information about the Digital Identity Management in smart cities using a blockchain technology. With the improvement of technology and use of the emerging technologies, the evolution of smart cities has become smoother. But on the same side, the security of the data is becoming a major concern. The blockchain technology has emerged as the most secure distributed peer-to-peer network. In this chapter, we present an approach to manage our online identities using highly secured blockchain technology. The chapter deals with privacy and sovereignty of the user identities along with ensure their security so that identities can’t be misused. On the other hand, the approach ensures the transparency and control of the user’s identity. In the result analysis, the chapter presents the output of the functions depicting the flow of the application. The eighth chapter has sought to first highlight Solar Energy for Sustainable & Efficient Development of Smart City. The Government of India has announced a new plan to build an ultra-mega solar project to meet the increasing growth in energy demand. The plan is to achieve renewable energy capacity of 175 GW by 2021. Small solar parks can be made an integral part of Smart Cities so as to fulfill any additional such requirements. Apart from rooftop solar, the solar energy can be harnessed in other forms like solar street lighting, solar water heaters, solar pumps, solar traffic signals, solar concentrator-based cooking. There has been unparalleled transformation of living from rural to predominantly urban living in India over the last two decades. The smart cities have a large number of developments in the infrastructure services and smart solutions in various aspects like toll collection, parking, traffic management, etc. The power sector assures solar and smart metering electricity supply with at least 10 % of power required by smart cities in India. The ninth chapter presented the Intelligence Transport System in Smart City. The smart city phrase was coined in 1990. This illustrates the development of urban cities with the latest technology, innovation and globalization. This phrase advocates improved urban planning. It utilizes information technology to meet urban challenges to enhance the new global knowledge economy. Last decade, the phrase has been used by various technology companies, for example, to integrate the operation of urban infrastructure and services such as buildings, transportation, electrical and water distribution, and public safety. A smart city is one in which information and communication technology (ICT) advocates improvement into and control over the various systems that affect the lives of residents. The tenth chapter highlighted about application of IoT in Mishap Avoidance Due to Swamping Approach. Swamping is one of the most dangerous natural disasters that affect the affected part of the world, causing human deaths, destruction of places, lessening economic growth and affecting health of human beings.

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According to economics times published dated October 14, 2019, 1900 deaths occur in overall monsoon in India, including 382 in Mumbai. A total of 46 people were reported as missing, and overall 25 lakhs people in 22 states got affected due to swamping mishap which has been reported causing human deaths. The work presented in the chapter is to address swamping issues by flood prevention system which reports the symptoms of danger in advance so that the chances of survival will be more in affected areas. The system provides alarm in advance by giving them the knowledge of affected places and helps to point out the location of victim places, sometimes also to protect valuable properties. The major goal of this chapter is to predict the flood and give warning signals to the people by triggering the alarm. It has also proposed an IoT system, based on wireless sensor network (WSN) in which water-level sensors are distributed over a region that monitors the level of the water. The eleventh chapter provided a clear overview on the principle behind blockchain technology followed by the state-of-the-art applications of blockchain in various sectors while laying emphasis on new emerging blockchain applications. May 2020

Sharvari Chandrashekhar Tamane Professor and Head, Department of Information Technology Jawaharlal Nehru Engineering College MGM University Aurangabad, MS, India [email protected]; [email protected] Nilanjan Dey Assistant Professor, Department of Information Technology Techno India College of Technology, Kolkata, WB, India [email protected] Prof. Aboul-Ella Hassanien Faculty of Computers and Artificial Intelligence Cairo University Chair at Scientific Research Group in Egypt (SRGE) [email protected]

Acknowledgements

Education is the best friend. An educated person is respected everywhere. Education beats the beauty and the youth. —Acharya Chanakya

The Editors… We are extremely happy and proud while handing over this book on Security and Privacy Applications for Smart City Development. We feel truly blessed by Almighty and are thankful to our beloved family members who always stand by our side and encourage us. We are thankful to all authors, who dedicatedly shared their views on various topics, skills that went into authoring this book and also listened carefully to all suggestions made by us. We thank each of the authors for devoting their time, patience, perseverance and efforts toward this book; we think that it will be a great asset to all researchers in this field! We are grateful to the Springer team for their encouragement and support in completing this book in time. Without their support and knowledge, we wouldn’t have ventured into starting this book, which ultimately led to this! We shall always be thankful to all the students, researchers, academicians, industry experts for their support and contribution in some manner. We would like to express our gratitude toward all who supported, shared, talked things over, read, wrote, offered comments, allowed us to quote their remarks and assisted in editing, proofreading and design; through the book journey. We dedicate this book to all researchers, who are working on smart city development projects and hope this book shall give them insights into their work. Last but not least, we would like to thank our readers, who have trust in our work and hope to find the guidance they are looking for.

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Acknowledgements

Acknowledgement Talk to yourself once in a day, otherwise you may miss meeting an intelligent person in this world. —Swami Vivekanand

Sharvari Chandrashekhar Tamane Professor and Head Department of Information Technology Jawaharlal Nehru Engineering College MGM University Aurangabad, MS, India [email protected]; [email protected] Nilanjan Dey Assistant Professor Department of Information Technology Techno India College of Technology Kolkata, WB, India [email protected] Prof. Aboul-Ella Hassanien Faculty of Computers and Artificial Intelligence Cairo University Chair at Scientific Research Group in Egypt (SRGE) [email protected]

About This Book

The main objective of this book publication is to explore the concepts of security and privacy applications for smart city development along with the recent research development. As the population grows and resources become scarcer, the efficient usage of these limited goods becomes more important. Smart cities are a key factor in the consumption of materials and resources. Built on and integrating with big data, the cities of the future are becoming a realization today. The book consists of various chapters related to the security and privacy applications for smart city development. Topics covered: • • • • •

Privacy and Security Technologies Challenges in Smart Cities Security and Privacy Issues in Smart Cities Smart City Architecture Smart City Applications: – – – – – – –

Smart Rain Water Harvesting Smart Street Lighting Digital Identity Management Solar Energy for Sustainable and Efficient Development of a Smart City Intelligent Transport System Mishap Avoidance Due to Swamping Using IoT Emerging Communications Applications Using Blockchain Technology.

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Contents

Security and Privacy in Smart Cities: Technologies, Challenges and Issues Privacy and Security Technologies for Smart City Development . . . . . . Gauri Vaidya, Prabhleen Bindra, Meghana Kshirsagar, and Sharvari Chandrashekhar Tamane

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Open Challenges in Smart Cities: Privacy and Security . . . . . . . . . . . . . Smita Kasar and Meghana Kshirsagar

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Security and Privacy Issues in Smart City: Threats and Their Countermeasures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . S. S. Magare, A. A. Dudhgaonkar, and S. R. Kondekar

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The Smart Infrastructure A Comprehensive Proposal for Blockchain-Oriented Smart City . . . . . . Pratyusa Mukherjee, Rabindra Kumar Barik, and Chittaranjan Pradhan

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The Imperative Applications of Smart City Development Smart Rain Water Harvesting for Smart Cities . . . . . . . . . . . . . . . . . . . S. G. Taji, V. R. Saraf, and D. G. Regulwar

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Smart Street Lighting in Smart Cities: A Transition from Traditional Street Lighting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 117 S. Umamaheswari Blockchain Technology Enabled Digital Identity Management in Smart Cities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 135 Saptarshi Sinha and Chittaranjan Pradhan Solar Energy for Sustainable Development of a Smart City . . . . . . . . . . 155 Samir Telang, Arvind Chel, Renuka Nafdey, and Geetanjali Kaushik

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Contents

Intelligent Transport System for a Smart City . . . . . . . . . . . . . . . . . . . . 171 Samir Telang, Arvind Chel, Anant Nemade, and Geetanjali Kaushik Application of Internet of Things in Mishap Avoidance Due to Swamping: A Novel Approach . . . . . . . . . . . . . . . . . . . . . . . . . . 189 Neil Patel and Ramchandra Mangrulkar Blockchain Technology and Emerging Communications Applications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 207 R. Teeluck, S. Durjan, and V. Bassoo

About the Editors

Sharvari Chandrashekhar Tamane is a Professor and Head of Department of Information Technology in Jawaharlal Nehru Engineering College, MGM University, Aurangabad, Maharashtra, India. She has 23 years of teaching experience in Jawaharlal Nehru Engineering College, Aurangabad. She was awarded Ph.D in 2013. Recently she has been awarded the “Best HoD of the year” at the CSI TechNext India 2019-Awards to Academia. She is a Chairman of “Board of Studies” (BoS) for Dept. of “Information Technology” at MGM University, Aurangabad. She is the active member of BoS committee for “Computer Science & Engineering” for Dr. Babasaheb Ambedkar Marathwada University, Aurangabad and Dr. Babasaheb Ambedkar Technological University, Lonere, MS, India. Her research interests include big data analytics, watermarking, neural network, machine learning, artificial intelligence, fuzzy logic, wavelet analysis, etc. She is an Editorial Board Member of various international journals. Dr. Tamane edited books on “Privacy and Security Policies in Big Data” and “Big Data Analytics for Smart and Connected Cities” with IGI Global, USA. She is author of 10 chapters published by IGI Global, USA and Springer. She is author of a book, “Data Structures Using C”, and published more than 60 research papers in international conferences and journals. She has also worked as a Reviewer for many SCIE, Scopus indexed journals. She has been invited as a panelist for the International Conference at Mauritius in the panel discussion toward “Sustainable Development Goals in India” and for the International Conference at Women in Data Science (WiDS) 2019 Pune in the panel discussion toward “Upskilling, Careers and Career Paths in Data Science”. She has also been invited to many institutes to deliver keynote speeches and expert talks and also delivered webinars/online seminars on various research areas. She has organized many special sessions in international conferences. She has also worked as Program Chair for IEEE- and CSI-sponsored international conferences, held at JNEC. Nilanjan Dey is Assistant Professor in the Department of Information Technology at Techno International New Town (formerly known as Techno India College of Technology), Kolkata, India. He is Visiting Fellow of the University of Reading, UK. He is Visiting Professor at Duy Tan University, Vietnam. He was an honorary xix

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Visiting Scientist at Global Biomedical Technologies Inc., CA, USA (2012–2015). He was awarded his Ph.D. from Jadavpur University in 2015. He is Editor-in-Chief of the International Journal of Ambient Computing and Intelligence, IGI Global. He is Series Co-Editor of Springer Tracts in Nature-Inspired Computing, Springer Nature, Series Co-Editor of Advances in Ubiquitous Sensing Applications for Healthcare, Elsevier, and Series Editor of Computational Intelligence in Engineering Problem Solving and Intelligent Signal Processing and Data Analysis, CRC. He has authored/edited more than 75 books with Springer, Elsevier, Wiley and CRC Press and published more than 300 peer-reviewed research papers. His main research interests include medical imaging, machine learning, computer-aided diagnosis, data mining, etc. He is the Indian Ambassador of the International Federation for Information Processing (IFIP)—Young ICT Group. Aboul-Ella Hassanien is Founder and Head of the Egyptian Scientific Research Group (SRGE) and Professor of Information Technology at the Faculty of Computer and Artificial Intelligence, Cairo University. Professor Hassanien has more than 1000 scientific research papers published in prestigious international journals and over 50 books covering such diverse topics as data mining, medical images, intelligent systems, social networks and smart environment. Professor Hassanien won several awards including the Best Researcher of the Youth Award of Astronomy and Geophysics of the National Research Institute, Academy of Scientific Research (Egypt, 1990). He was also granted a scientific excellence award in humanities from the University of Kuwait for the 2004 Award and received the superiority of scientific in technology—University Award (Cairo University, 2013). Also he was honored in Egypt as the best researcher in Cairo University in 2013. He was also received the Islamic Educational, Scientific and Cultural Organization (ISESCO) Prize on Technology (2014) and received the State Award of Excellence in engineering sciences, 2015. He Holds the Medal of Sciences and Arts from the first class from President of Egypt in 2017.

Security and Privacy in Smart Cities: Technologies, Challenges and Issues

Privacy and Security Technologies for Smart City Development Gauri Vaidya, Prabhleen Bindra, Meghana Kshirsagar, and Sharvari Chandrashekhar Tamane

Abstract The ever-increasing rate of urban population and latest technological advances including the IoT, sensors, big data, cloud computing and data analytics has replaced the standard methods of service delivery to the citizens. The IoT devices collect real-time and integrated data by monitoring an individual’s daily activities with the aim of providing efficient services including but not restricted to smart transportation, waste management, personalized healthcare and recommendations. As personal and sensitive information is being collected by these devices, security and privacy challenges are crucial paradigms for concern. While safety and privacy have always been significant study areas, there is a need for a broader perspective to protect personal data with evolving technological challenges. This chapter introduces the security and privacy issues faced by the existing infrastructure. Some case studies are discussed with the measures undertaken for data privacy and security. The chapter concludes with open research challenges grounded on security and privacy. Keywords Privacy · Security · Internet of things · Big data · Cloud computing · Smart city

G. Vaidya (B) · P. Bindra Graduate Student, Computer Science and Engineering Department, Government College of Engineering, Aurangabad, India e-mail: [email protected] P. Bindra e-mail: [email protected] M. Kshirsagar Postdoctoral Researcher, Biocomputing and Development Systems Lab, Lero, The Irish Software Research Centre, University of Limerick, Limerick, Ireland e-mail: [email protected] S. C. Tamane Department of Information Technology, Jawaharlal Nehru Engineering College, MGM University, Aurangabad, India e-mail: [email protected] © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 S. C. Tamane et al. (eds.), Security and Privacy Applications for Smart City Development, Studies in Systems, Decision and Control 308, https://doi.org/10.1007/978-3-030-53149-2_1

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G. Vaidya et al.

1 Introduction The way smart cities are defined globally differs in the context of what the citizens of a country may seek. For developing and underdeveloped countries the citizens may aspire for a smarter infrastructure whereas the western countries may look at more digitization and automation [1]. With IoT being the driving force for sensing, and collecting data these days, every minute detail of an individual is monitored. Integrated data collected through different smart services can prompt unsafe bits of knowledge about a person. For example, the behavior of a person can be analyzed from a person’s transaction timings or from his/her medical data. Smart infrastructure [2] forms the basis of a smart city and is essential to pace up the growth of urbanization in a city. It includes smart homes, smart mobility, smart governance, smart environment and smart economy. Smart homes [3, 4] are furnished with numerous sensors and various smart technologies such as smart meters, smart televisions, smart speakers equipped with virtual personal assistants, etc. to name a few. These devices not only track consumption patterns of users, but also record security passwords, sleep patterns, and child behavior. Smart healthcare [5] crucially records patient sensitive data, such as a patient’s medical history which is critically very personal and cannot be shared without a person’s consent. Various social networks can access a person’s health records thereby compromising with sensitive data [6]. Smart mobility [7] aims at developing advanced and sustainable ways to improve travel experience along with environment-friendly fuels for efficient management of public and private transport. Due to ineffective and inappropriate management of vehicles, various ill-effects such as increased pollution and traffic congestion have signaled the demanding need to come up with appropriate smart mobility solutions. Smart transportation [8] helps pace up with the fast-growing urban population and encourages in effectively managing the city traffic, automatic street-lights, automatic pothole detection, etc. being the new addition to the system. An extension to smart transportation includes location-based services like navigation. Many organizations sell sensitive information such as a user’s place and time for minting cash from a business perspective. There is a strong need to protect such data from being leaked [9, 10]. Intelligent manufacturing [11] too has been a key feature in development. The manufacturing sectors have been on par excellence and achievement with the least human interference. From handling raw materials to producing finished products, data analytics is used for the analysis of machinery to know about which parts may fail and thus taking necessary measures in advance, running various simulation processes for finding better ways of doing things has enhanced manufacturing and effectiveness in recent years. Smart governance [12] has also been a significant development since the advent of smart cities. By facilitating better choices and planning, making transparent and trustworthy transactions, the effectiveness in the delivery system of public services has increased. Smart economy [13] drives the economic development of a city by experimenting and promoting strategies through tourism, local assets, and resource management. Internal and external threats, data proliferation, strong

Privacy and Security Technologies …

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Table 1 Security and privacy challenges in smart city Dimension

Challenges

Smart homes

Data tampering, data and identity thefts, eavesdropping, denial of service (DoS), software exploitation [14]

Smart healthcare

Physical attacks, DoS, trust, data manipulation [15]

Smart mobility

Sybil attacks, DoS, DDoS, flash events, security of software platform [16]

Smart transportation

Broadcast and message tampering, jamming, man in the middle, eavesdropping, device hijacking, sybil [17]

Smart governance

Accessibility, DoS, transparency, trust [18]

Intelligent manufacturing

DoS, cloud security, botnets, data tampering, malware [19]

Smart economy

Internal and external threats, data proliferation, strong regulation at national and international level [20]

regulation at the national and international levels can be regarded as a few threats posed due to the wide domains economy plays a role in. There is an observed pattern among the challenges faced by each of the domains mentioned above. Table 1 depicts these challenges in terms of privacy and security threats. Domains which involve data transfer have a threat of data theft and data tempering whereas those which involve data storage are affected by trust and software attacks threats. This study of patterns of threats is useful while implementing digital technologies in determining which technology covers most of the threats for that domain. With advancement of technology and countries shifting towards the digital world, it is important to study and review the security and privacy threats for developing sustainable smart city architectures. It is equally important to study the approaches of certain cities which have excelled in overcoming the challenges faced by them with upcoming digital technologies. In this study, we bring upon the potential threats possessed while storing, accessing and retrieving data collected using IoT devices, stored on various cloud platforms or processed using big data techniques. Through the course of this study, we present forthcoming technologies which shall play a vital role in the coming future to overcome these challenges. We present a machine learning based approach which can identify the probabilistic chances of identifying a threat that could be faced in a specific domain. This could help in identifying the revenue losses caused due to lack of security to this information. Although people have benefited a lot from the above applications, ensuring that personal data of an individual is retained, not used without his prior consent, and not vulnerable to cyber-attacks is a must. In the coming sections we learn about the recent developments in the diverse domains of smart cities. We also touch upon the privacy and security threats faced. We then study about the issues, threats and problems faced in smart city developments for data security. We propose a few emerging technological solutions to overcome the barriers faced and build secure smart city networks. In the final sections of the chapter we highlight a few smart cities which have excelled

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in certain domains and have emerged as models to be followed. Discussions, future scope and research opportunities available are presented to conclude the chapter. In this chapter, we introduce security and privacy issues existing in the current scenario and discuss the steps taken towards the privacy of the data and the laws for data usage. Existing system infrastructure for the collection of digital information, it’s components along with security measures at each layer of the infrastructure are presented. The analysis of integrating traditional methodologies with emerging technologies is discussed. The chapter concludes with possible solutions to overcome the threats in smart city architecture.

2 Background There are many factors that have led the notion of smart cities to be the buzzword of the moment. The percentage of people residing in urban areas has drastically increased in the last decades and anticipated to develop more in the future as seen in Fig. 1. Sustainability, quality of life, education, income source, transport, etc. are the services that attract people to migrate to urban regions. About 68% of the total

Fig. 1 World population growth in urban areas. Data Source World Data Bank (2019) [23]

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world’s population is expected to live in urban areas by 2050, particularly in Asia and Africa [21]. Developments and urbanization have become so crucial that the capital city of the state sometimes contributes to half of the country’s GDP, for example, the capital city of South Korea. According to Forbes’s recent study, London stands to be the smartest city in the globe with the use of the latest technologies across more than one dimension. In addition to advancing technological developments, there are other elements that add to the city’s top ranking. The Cross rail project, which is Europe’s largest project is being carried out in London i.e. smart cities also have the potential to earn global resources and exports for the country in which they reside. This has led to the trend of the use of the latest technologies to a large extent where every physical thing is connected to the Internet. The smart cities are characterized by the following characteristics in terms of digitalization: Internet of Things (IoT), Big Data and Cloud Services to integrate and draw significant insights from them. Most cities are developing rapidly in terms of intelligence using these digital technologies. Louisville is the smart city in the U.S. that is now on the track of becoming smarter through the IFTTT platform (if this is then that) and community-wide applets. For example, the home color can be changed if there is an emergency in their area which helps in taking immediate actions. Songdo has a very strong network of cameras and sensors that helps people to find everything from home. For example, a hair stylist may advise them from home as well as plan a trip with their travel agency by being at home via video conferencing. Similarly, Copenhagen is known for its free data exchange, as they have achieved great heights through proper management of waste, lights, energy and buildings. They may be carbon neutral by 2025 through this. These best smart city examples prove that our future is already here. However, this great future also brings with it, two major issues: security and privacy of the data, which has the potential to destroy the whole system infrastructure [22].

2.1 Security The increasingly complex network structure of the smart city systems due to digital communication, connected devices and network systems is often less secured. 80% of the data is heterogeneous owing to the modifications in the device status as per the activities of an individual like sleeping, eating, location, etc. [23]. These devices are interconnected through a wireless network and follow open network protocols or APIs which can readily be attacked with a tiny piece of code. Man-in-the-middle, Distributed Denial of Service (DDoS), Device Hijacking and Permanent Denial of Service (PDoS) are some commonly caused threats to smart devices. For example, the smart houses’ keypad can be locked by an attacker initiating with control over the thermostat, or the un-protectable wears could cause identity threat by obtaining information, or the device could be completely damaged with control over the thermostat, transmitting the data to the cloud and then feeding inappropriate information for its operation [24].

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Security is the prime concern for data; various tools for securing data have come up. Cui et al. have put forth the security threats and issues faced within a smart city like botnet attacks on IoT sensors, possible artificial intelligence (AI) threats, autonomous vehicles (AV) if once hacked can pose a threat to driverless vehicles. Unencrypted healthcare data can also create privacy threats. Security requirements include privacy protection, authentication, confidentiality and availability of data. Technologies like blockchain, cryptography, biometrics, machine learning and data mining, game theory, and ontology can be used to maintain security and privacy of the system [25].

2.2 Privacy Data analytics is prominent in every sector in today’s world for decision-making processes, and thus data is a significant factor. However, as stated previously, as each activity of an individual is being tracked, this data is an important asset of an individual, right from his personal health habits to his thoughts on social media. From the embedded information acquired, the analytics could easily find out the social habits and status of the individual. This information becomes even more vulnerable when integrated with health information. However, while discussing social media, there is at least an indirect consent an individual agrees before sharing or using the service. While discussing IoT devices, there is no such input media for the device to ask for approval nor can the individual grant consent themselves. This has resulted in important research: The government and private bodies, which are consistently aiming at a better quality of life for people or the people who are the generators of the data; this challenging research has opened a wide horizon of alternatives and further discussions about the extent they assert the privacy of the data [26]. According to He, the IoT network, the clients and the application communicate in a wireless environment, which is susceptible to attacks of an individual’s personal data. The following seven requirements must be taken into account while designing any application for maintaining security or privacy of the data: mutual authentication, non-traceability, no verification table, session key agreement, perfect forward secrecy, and attack resistance. He evaluated the Liu et al.’s methodology to secure the network through public and private keys by claiming that if the public key is forged, there is no way to verify the legality of the public key, making it insecure. He proposes a framework that first verifies whether the public key is legal or not by introducing a new key called session key that will never be disclosed even if the public key is forged [27]. Kuan Zeng et al. [28] proposed smart city architecture based on which security measures have been recommended. Security and privacy issues existing in the system have been described. Storing data directly over the cloud may endanger data over hacking. A probable solution suggested is encrypting and storing data over the cloud using cipher text. This ensures that the cloud servers cannot directly access stored data. Smart cities require a trustworthy and dependable control of data. Social network data can be used to analyze and diagnose certain medical diseases

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as follows. Speaking specifically for healthcare and social data privacy and security [29], proposes a Mobile Healthcare Social Network (MHSN) data privacy scheme. An encryption algorithm for storing health and social data on the respective cloud by generating cipher text has been proposed. As known, data is collected using sensors. This data is stored over the cloud after consent by the data owner, in a cipher text format thereby making sure of the privacy aspect. It works on the public key and master key concepts, using which attribute and secret keys are generated. To further maintain privacy, health data is not completely de-encrypted. It is first partially decrypted at the cloud level followed by user-level decryption. Another privacy-preserving application specified is to prevent tampering of smart meters [30]. The Global Positioning System (GPS) details may reveal personal details of a vehicle such as its location, speed, etc. With AdSense and e-advertisements gaining popularity, public agencies sell this sensitive data which requires confidentiality to private agencies for commercial profits. Various techniques mentioned in [30, 31] include dummy-based methods (wherein a dummy location along with the actual location is forwarded creating anonymity), k-anonymity (which hides confidential details of users and service providers using third-parties called anonymizers) [31, 32], cryptography, and differential privacy. The authors mainly focus on differential privacy for preserving GPS data. Continuing further, Zhang also suggests, smart navigation for intelligent transport wherein the threat for data leak to the road service unit (RSUs) from querying vehicles can be resolved by encrypting source and destination locations using AES and Elgamal schemes. A group signature is created using credentials disseminated by trusted authorities. Group signatures also help authorities trace malicious activity if any. Location privacy is thus maintained using distributed RSUs. To summarize, we may conclude that it is necessary to come up with new security measures on a daily basis in order to tackle mundane and trivial issues in a smart infrastructure.

3 Issues, Controversies, Problems Towards Smart City Development As emphasized above, we realize how important it is to maintain security and privacy in a smart city. However, while addressing any issue, it is important to study the trends of it in detail. These trends give an exact idea about what issue needs to be addressed. We have analyzed the data available from standard reports and studied them from the perspective of data threats. In this chapter, a predictive survey over a dataset has been performed to highlight the same. The dataset included various data thefts and breaches with their details on smart cities over the past few years. Based on this data, specific data analytics has been performed to understand the trends of data threats in smart cities with respective technologies.

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The number of IoT devices is increasing at a regular pace in the infrastructure of smart cities. There has been a regular growth of around 10% every year. However, the statistics of the increase in the data threats are quite surprising. Only in the single year 2016–17, the data threats have increased by 600%, which is more than the total number of IoT devices in the world. In order to study the threats pattern, it is important to know the environments where organizations prefer to store private and sensitive information of the users. The Thales Report by International Data Corporation (IDC) states that cloud services, mobile payments, social media, and IoT devices are the top-rated environments where sensitive data is stored. The traditional ways of storing sensitive data in encryption mode in databases have been replaced by digital transformation and using technologies like cloud, IoT, Big Data and Blockchain [32, 33]. This emphasizes the need for service providers to ensure the following (Fig. 2): 1. Data protection technologies like tokenization, encryption and data anonymity techniques for data safety have been applied before sending the data to the center before storing data over the cloud. 2. Data from various infrastructures when integrated needs to be encrypted before sending further for any process. As cloud, IoT and Big Data [33–35]have sensitive data stored and these technologies are also significant in smart cities point of view, we study the trends of each one of them in detail.

Fig. 2 Analysis of platforms used to store personal information. Data Source International Data Corporation (2019) [33]

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3.1 Cloud Services Cloud services including Software as a Service (SaaS), Infrastructure as a Service (IaaS) and Platform as a Service (PaaS) are being used these days for data storage purpose due to their efficient properties like better technology management, scalability, interoperability, data mobility, remote control, and effective cost. Though the use is ever increasing due to their advantages, there is an increasing concern for growing data threats over cloud services. A recent study has proved that most of the data breaches have occurred due to a lack of data privacy policy, cloud services fail to ensure the privacy of the data and others. The operational structure of cloud services need to be stronger in terms of access controls over the data like who can access the data, and up to what level of privacy can data access be granted [35, 36]. A detailed analysis of frequent data threats in smart cities is as follows (Fig. 3): • Security of customers’ data is at stake if the cloud provider fails to protect the data due to poor security practices, application vulnerabilities, and others. This leads to data breaches like insider attacks, data theft, etc. • Security breach/attacks at the service provider rank as a top concern for data threat vulnerabilities. • Lack of a data privacy policy or privacy service level agreement is the comprehensive cause of data attacks which puts even public cloud’s data at stake. • Lack of visibility into security practices at the end of the service creates an invisible entry for attackers.

Fig. 3 Category wise cloud threats. Data Source International Data Corporation (2019) [33]

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• There has been an increase in vulnerabilities from shared infrastructure as a cloud is the central storage for data from all resources. • Managing encryption keys across multiple cloud environments is a significant challenge for ensuring data privacy. • Privileged user abuse at the cloud or SaaS vendor managing, monitoring and deploying multiple cloud-native security tools. • Lack of control over the location of data/data residency concerns meet.

3.2 Internet of Things The infrastructure of smart cities is at its pace of betterment due to the increasing benefits of connected devices over networks which have made it possible to connect every device and person with each other with its own pros and cons. As already mentioned, the benefits of IoT devices have been proved by their increasing demands and smart applications in the industry from homes to offices, traffic to health, covering every aspect of an individual’s life. Factors like weak web interface for asking consent of private information, lack of security structures in the devices and others leads to data threats like misuse of data, Denial of Service (DoS), man-in-the-middle attacks to name a few [36, 37]. A detailed study of security concerns of IoT devices is as follows (Fig. 4):

Fig. 4 Category wise IoT devices’ threats. Data Source International Data Corporation (2019) [33]

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• There are increased chances of attacks on IoT devices due to insecure interfaces of these devices which may further lead to malfunctioning of the devices and cause damage at a higher scale. • The sensitive information generated by these devices is a rising issue of concern. The data obtained from various sensors and devices are in different formats and there needs to be standard policy and communication protocol for the interoperability of this data in the security ecosystem. • Easily available data if combined with additional information through social media and IoT devices, all the private information about a person revealing his identity can be obtained. There is a need for validation of the integrated data before being used for any analytical purpose. • Lack of improvised privacy policies according to rising trends in the industry regarding access control of the data, use of the data, the extent of the use of the data often attract attackers to easily penetrate into systems. • The operational system of managing IoT devices is not as efficient as needed by the current industry. Any information that can reveal any identity-related data of an individual when identified must be protected and encrypted. The infrastructure needs to be compatible with such management of data. For this technical expertise is the need of the hour.

3.3 Big Data The IoT devices generate a plethora of data that needs to be processed and analyzed for the implementation of public services and better management. Big data is also promoting open data initiatives for the betterment of the human community and a better future [37–39]. While big data has many business-related opportunities and applications, it proves to be a menace when data security is taken for granted. Distributed frameworks, real-time security, access controls and lack of management of a large amount of data generated often risk the data to attacks. Following are the data threats in terms of big data that need to be contemplated (Fig. 5): • As big data processing frameworks are non-SQL, they lack security constraints like encryption of passwords and personal information before transferring among systems and are prone to attacks. • Data anonymization techniques are not applied before performing analysis which can lead to personal identity insights after processing the data. The data which was not sensitive while entering into the system proves harmful after performing analysis over it. • Often data anonymization techniques are weakly implemented leading to data leakages and identity thefts. • Lack of privacy violations from data originating in multiple countries often leads to cyber-attacks from remote parts of the world.

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Fig. 5 Category wise big data threats. Data Source International Data Corporation (2019) [33]

• Security frameworks within the big data ecosystem must be compatible with the growing data risks in the industry. The system needs to be updated on a regular basis for data security concerns. • Granular auditing is needed on a regular basis to determine the parts of the system where private information can be located.

4 Proposed Solution Having discussed the threats faced in building a smart city architecture, in this section we shall discuss upcoming technologies which prove to be potential solutions to overcome the aforementioned issues. All these techniques can be applied on every level of the architecture in order to enhance security. These techniques help secure the data and prevent attacks like tampering, DoS, and other network threats. We can implement the below mentioned solution at every level of network security in order to prevent data thefts and secure the system. A combination of multiple solutions can provide even better security and preserve privacy of trusted user data. We propose a Naive Bayes approach to predict the possibility of threats in a specific domain given the past record of attacks.

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4.1 Cryptography Cryptography and encryption have always been the most frequently employed security technique. Encryption techniques can be deployed at each layer of infrastructure in order to build a secure environment. Cryptographic methodologies ensure confidentiality, authenticity, integrity, trust, and key management in any system [39, 40]. Popular techniques and algorithms include symmetric cryptographic encryption protocols and asymmetric cryptographic encryption protocols. Blockchain, as we shall discuss further, is an advanced technology that uses this technique for storing and securing records in blocks. With the coming of these fast-paced technologies, cryptographic solutions have gradually started declining and are deployed less in use.

4.2 Blockchain A blockchain is a shared, distributed ledger that records transactions, agreements, and contracts. It provides a transparent and secure platform for storing and managing data. In a smart city framework, we can integrate the blockchain platform at network and database levels as blockchain itself is a distributed database. For every block that is inserted in the chain, a unique hash is assigned, making it difficult to hack and intrude the chain. Blockchain thus provides a reliable, trustworthy, efficient and scalable environment for preventing any security attack [40, 41]. Blockchains can protect the privacy within the block as every individual user has their own unique digital signature. Also, information can only be exchanged when permitted by the owner, thereby highly securing personal data. We can prevent various threats, and identification thefts using the technology. Speaking specifically regarding the various facilities provided in a smart city, blockchain can be implemented in each individual unit. For example, in the healthcare sector, blockchain can be implemented to provide a unified platform for storing records, data authorization as well as managing data identity. In smart governance, blockchain provides efficiency, accountability, trust, and transparency [41, 42]. Blockchain is, therefore, emerging as a transitional solution to overcome security and privacy issues of the digital world.

4.3 Game Theory Game theory provides a mathematical, reliable, distributed and defensible mechanism with a responsive action mechanism. Game theory can effectively prevent DoS, eavesdropping, and cyber-physical security attacks using static techniques such as a static zero-sum game, Stackleberg game, Bayesian game, etc. The classic privacy

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protection algorithms have as well incorporated game theory. With the growing pace of smart cities, it can be rightly concluded that game theory will play a significant role in protecting data privacy in the near future [42, 43].

4.4 Machine Learning and Data Science Structured and unstructured data has always been a driving force in a smart city. However, data is processed and filtered, i.e. converted into smart data before drawing insights from them. But even with the growing smart data, the risk of data attacks has grown exponentially as compared to the last few decades. Machine learning and data science work hand-in-hand with big data and can be used as tools to protect and secure our system. Various machine learning algorithms can be used in order to train models that can predict future threats encountered in a smart city [43–46]. To understand the concept in detail, let’s consider a simple scenario. Within a smart city, hundreds of breaches are attempted each day which may harm the data integrity of the system. The cyber security cell of each smart city can record every detail of the breach in terms of the type of attack, the domain (home, transport, business, etc.) along with the losses incurred. Through a thorough investigation, we can also identify the particular attack that has occurred. This database can be fed to a probabilistic model to predict the future chances of any such attack. We refer to Naïve Bayes Classifier (a probabilistic machine learning model) in this example. Explaining it mathematically, in the Naïve Bayes classifier, we calculate the posterior probability, given the likelihood, prior probability, and evidence. posterior =

prior × likeli hood evidence

(1)

If A and B are two events, posterior represents the probability of occurrence of A given event B has occurred (P (A|B)). Prior probability represents an occurrence of B given event A has already occurred (P (B|A)). Likelihood and evidence represent P (A) and P (B) respectively. Thus, P(B) =

P(B|A) × P(A) P(B)

(2)

Coming back to smart city, if we’re given the following dataset, we can determine the probability of threat using the above-mentioned technique. From the data represented in Table 2, we can calculate the probability of a data tampering theft on a smart transportation environment as:

Privacy and Security Technologies … Table 2 Sample dataset of threats in a smart home

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Domain

Attack type

Transportation

• • • • •

DDoS Data tampering Device hijacking Sibil Data tampering

Home

• Data tampering

Governance

• Cloud theft • Identity theft

Healthcare

• Data tampering • Data manipulation

P(Data T ampering|T ranspor tation) P(T ranspor tation|Data T ampering) × P(Data T ampering) = P(T ranspor tation) (3) P(T ranspor tation Data T ampering) × P(Data T ampering) P(T ranspor tation) 0.2 × 0.4 = 0.5 =

P(Data T ampering|T ranspor tation) = 0.16

(4) (5)

Thus, we may conclude that there could be a 16% chance within this small dataset itself for a possibility of data tampering in smart transportation. If we scale the dataset we can come up with more such insights. Taking this a step ahead, we can also calculate approximate revenue losses that could incur and take steps well in advance. A possible solution could be implementing a blockchain that will secure the data and prevent the attack so as to minimize revenue as well as other losses. Machine learning and data science can find many more such applications in order to provide a safe and secure environment (Fig. 6).

5 Review of Smart Cities As mentioned above, smart buildings, smart mobility, smart energy infrastructure, and smart water meters form the basis of the people in the city to live efficiently. Smart city initiatives are being taken by many of the advanced cities in the world to cope with the challenges faced by their respective citizens with the best use of

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Fig. 6 The landscape of vulnerabilities and solutions. Data Source [10, 24]

digital technologies. Following is the review of the example smart cities which are renowned for their best solutions: • Smart Buildings A smart building refers to a block that is built with innovative ways by taking into account energy and material efficiency, comfort and well being of people thus maximizing productivity with minimizing resource requirements [46, 47]. One of the examples of such smart buildings is Software Development Block 1 (SDB 1), Infosys campus at Pocharam in Hyderabad, India. The key characteristics of this building are water efficiency, energy efficiency, and day lighting management. The building consists of 18% recycled material. 100% water recycling strategies and 90% natural day-light arrangements are used to reduce the overall maintenance cost. This building has also adopted radiant cooling technologies, thus, reducing 50% of its total energy requirements. Several data mining and machine learning algorithms are used to study the temperature and patterns of air conditions in the building to predict the needs in the future. This helps in efficient energy management of the building. SDB has proved the importance of merging towards innovative ways to build infrastructure than the traditional ways to achieve sustainability. • Smart Mobility Mobility is a wide term including all the means of the mobility of an individual including but not restricted to private cars, bikes, and public buses. Mobility has been an issue of concern for many of the smart cities and there are a few examples of it in terms of pacing technologies. The efficiency and quality of public buses have been improved through Bus Rapid Transit (BRT) and is being used successfully in 197 countries across the world. Argentina, Chile, Columbia, Brazil, Ecuador, Mexico and Uruguay have adopted bicycle-sharing transport systems with a vast lane

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network for bicycles. Mobile applications have proven themselves very important in the successful implementation of this information. Mobile applications for bike sharing systems, efficient parking and electric charging stations are the next targets for these cities [47, 48]. This has contributed to saving 232 tons of carbon dioxide emissions in its few years of beginning. Car sharing, popularly known as ZipCar is another concept that is gaining importance nowadays in Europe and the USA. Each ZipCar reduces around 15 cars in a city which ultimately leads towards environment sustenance [48, 49]. • Smart Water Meters Water meters are the need of the hour for planning controlled use of water. Smart meters aim at scalable and low-cost water management solutions. With a smart meter for water, a user can keep a track of water consumption, water loss and water leakage in order to efficiently predict the need of water in his/her house in a day [50]. The most recent and live example of smart water meters is in Mumbai, India, which are controlled remotely. With smart water meters, 50% of water leakage losses have been reduced which accounts for 16% more water savings as compared to the global average of reduced water loss [49, 51]. • Smart Waste Management Smart waste management helps to efficiently manage waste disposal, its reuse and recycling, thereby contributing to the nation’s economy. Santander, a smart city in Spain is well known for its smart waste collection strategies. GPS connected vans are used for the collection of waste bins and are optimized using optimal routing networks. This has covered the issue of visiting empty bins and overflowing bins. This leads to reduced emission of carbon dioxide and transport loads for the collection of waste [50, 52]. • Smart Healthcare Every country tries to improve the quality of its healthcare services as the citizens are the country’s biggest asset. India has initiated the “Smart Health India” campaign to reach out to every corner of the country for quality health services at low prices for general chronic diseases. In Singapore, digital technologies are widely used for such monitoring. The technologies are developed with a patient-centered approach ensuring the ease and services required by the people. The daily lives of people are monitored by sensors in the environment and sent automatically to service providers which record and update the status of a person’s health. Basic details like pulse rate, blood pressure, etc. are forwarded to providers and can be visible over smart devices such as phones, and fit bands. The healthcare network is planned to be centralized to avoid duplication of services and for immediate actions depending upon the nature of the disease [51, 53].

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6 Discussions The issues, solutions and review of a few smart cities opens up many opportunities and scopes for open research. We arrive at opportunities to overcome the barrier and threats posed over the privacy and security of user sensitive data. We arrive at a few important questions as to what causes such threats to the data. Is it companies minting money, or the carelessness for security by agencies which lead to the breach in data. With advancements in technology, the world is even advancing in building techniques to break into the system and mishandle data. We aim towards creating systems in the city which make it hard to access data where-so-ever it is being accessed from. We are ourselves responsible for our data security and privacy. We should agree and allow use of the data which we feel would not harm our identity, personal security, and monetary benefits. Open research opportunities to overcome these challenges are discussed in the next section.

7 Future Research Directions The above-reviewed analysis of the smart cultures adopted in a city prompts every emerging smart city to adopt technologically advanced and up-to-date solutions. Sharma and Park [52, 54] propose a smart city architecture based on the blockchain through which we can decentralize various domains at a city level wherein each domain forms a new block. Smart homes, hospitals, offices, and buildings can altogether form independent entities but on a larger scale are integrated into the smart city chain. At the bottommost level, we can aim to centralize and create a database that can store details of every minute activity within the framework. For example, say, data from smart meters can analyze and calculate both water as well as energy consumption patterns, smart televisions, smart plugs, smart geysers, sensors, and various smart appliances can be collected over regular intervals over a single platform which later forms a single entity, that is, a smart home. Similar cases can be followed and implemented for other domains. Using this architecture, users can identify a single platform through which they can make bill payments, monitor and record all the expenses and pay taxes as well. Such a smart city based architecture will benefit the citizens and government agencies. With the aim to minimize security and privacy threats in a smart environment, we can emerge with custom solutions that merge multiple proposed solutions such as applying different cryptographic techniques along with game theory in order to enhance privacy. Wide machine learning models can be trained which can on an early basis identify breaches and threat possibilities so as to take preventive measures in advance.

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8 Conclusions Through the course of this chapter, we bring across the concept of a smart city, the features it inhibits and the vulnerabilities it is exposed to. From IoT, through cloud computing, big data, we have touched on various security threats that could possibly be faced in a smart city. Knowing all the threats, we elaborate on possible solutions using which we can eliminate and overcome them. We have demonstrated a simple machine learning algorithm that can possibly determine the probability of future threats in order to reduce revenue losses. Review studies of a few smart cities have been elaborated and touched upon which is followed by future research directions. We end the chapter by proposing a layered architecture solution with attack and prevention schemes.

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Open Challenges in Smart Cities: Privacy and Security Smita Kasar and Meghana Kshirsagar

Abstract Construction of smart cities is no longer a future endeavor. Even though the implementation of smart city comes with enormous conveniences, the realistic implementation is challenged in different aspects. Two of the major aspects along with the design, maintenance and implementation costs are privacy and security. The frameworks introduced for smart city impose many challenges regarding privacy and security of the citizens. Open networks, smart phones, computers etc. are used for the communication in the smart city, making the sensitive data vulnerable to attacks. It is also vital to deal with the privacy issues. Thus, maintaining security and ensuring the privacy in the smart city is necessary and turning out as an open challenge. The present paper proposes Cloud Data Security Model (CDSM) for the better security of data using the cloud storage mechanism. The CSDM proposes four different categories of cloud accounts with special permissions to access the data. Moreover, with the data access record, the owner is completely aware of who is accessing the data. Keywords Smart city · Privacy · Security · Challenges · CSDM

1 Introduction Consider that someone in a smart city tries to order food online. With the unique identification number entered; cheese sandwiches and pizza are ordered. The system denies accepting the order. Investigating the reason for the same, the system informs S. Kasar (B) Department of Computer Science and Engineering, Maharashtra Institute of Technology, Aurangabad, Maharashtra, India e-mail: [email protected] M. Kshirsagar Department of Computer Science and Information Systems, University of Limerick, Limerick, Ireland e-mail: [email protected] © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 S. C. Tamane et al. (eds.), Security and Privacy Applications for Smart City Development, Studies in Systems, Decision and Control 308, https://doi.org/10.1007/978-3-030-53149-2_2

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about the recent test done for cholesterol and due to the high level of cholesterol as per the reports, cheese intake is not allowed. Further the system also identifies few sample cases from the friend list of the person who has placed the order, with the consequences of being hospitalized. The concern here is not about ineligibility of having cheese sandwiches but the amount of personal data available with the system that is simply taking the online orders for food. This scenario and probably many more similar scenarios are easily possible in smart city which are result of technology embedded in our daily activities. The scenario surely describes privacy invasion due to technology. With respect to the divisional reports from United Nations, the percentage of people living in urban areas is 55% of the world’s population. It is projected that by 2050 this percentage of urban dwellers will rise to 68%. The number of people living in the urban areas is increasing day by day. From the recent reports, it is also anticipated that the number of urban occupiers in China would be 255 million and in Nigeria would be 189 million. The projection for increase in the urban people in India would be 416 million additional. With these huge numbers, lot of efforts are required for sustainable planning of urbanization. Technology has become integral part of our work life and everyone is comfortable with it. But unknowingly we have allowed the technology involvement in our personal lives too. The threat to privacy is due to technological impact on the collection of huge volume of information that can be personal, transmission of this collected information, time of retention, and the various types and formats in which information that can be attained [1]. Technology based products are used worldwide irrespective of the geographical distances. The best example of which is the smart phone. Neither the use of smart phone depends on urbanization nor the use of products like washing machine, coffee maker, microwave etc. Unlike this the technology-based services are mostly used in urban areas since most of the services are chargeable. Urban people also face time crunch, so they prefer outsourcing and using of technology-based services. Urbanization accompanies economic growth and development. Maximum use of technology-based services and the interconnected systems leads to the formation of smart city. Many of these services initially started as helping hand to the society but now are integral part of day to day life. Internet of Things (IoT) is majorly an interconnection of physical objects connected through internet. IoT based products are considered as integral part in smart cities [2]. Smart home automation, Healthcare system etc. are essential and supportive for senior citizens and patients with physical disabilities. These systems would help them in their day to day activities and take care of their security. But the data generated from the use of technology-based products and services is huge. The user is unaware of the data distribution in terms of privacy invasion and security. As the technology involvement adds contentment to our lives it is also necessary to contemplate the security aspects of the data available online. Security concerns arise since the personal data available online could be altered or misused by anyone. Managing the precious data is important and significant in the design of smart city since efficiency and the convenience provided in the smart city depends on the transmission, retrieval, and mining of data [3]. It is obligatory to fulfill the triad of confidentiality, integrity and availability in the smart city. The infrastructure

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and critical services digitally connected in the smart city may be prone to information warfare with high risk of disrupting the entire network intentionally. The IoT based infrastructures are also at high risk. The monitoring must be done frequently to keep the network free from malicious contents and several types of attacks. The two major challenges in view of the public and private data generated by the user in large number are security and privacy. It is necessary to realize that the challenges of security and privacy still exists but more incident in smart city. The motivation for proposing the secure Cloud Data Security Model (CDSM) is with a vision of upgrading the quality of life of an individual and the society but with appropriate security and maintaining the privacy needed by every individual. The model proposed also keeps the track of usage of our own information. The related work section gives a brief outline of the work and different models already given by researchers. Further section discusses about the privacy concerns, different categories of privacy violation and the security aspects. The Cloud Data Security Model (CDSM) is discussed in the next section followed by conclusion and references.

2 Related Work With the increase in the number of cities worldwide, Security and Privacy are vital topics to be discussed. Many researchers have provided the fundamental approaches to overcome these challenges. In [4] the authors discuss about the urbanization related problems and risks of uncertainties possessed with the advent of smart city. A detail overview of major security problems and present solutions to it are discussed [5]. Along with the security problems, several factors and dimensions influencing the smart city are presented. In this paper [6] a framework identifying the different types of privacy concerns arising due to the use of smart technologies was presented. In order to specify the use of smart technology like CCTV cameras, transport systems, etc. the paper practices the term data cities. The use of these technologies generates massive amounts of data. In [7], the authors observed the concerns by proposing a model that denotes the major essentials of smart cities along with their interaction. In [8], the authors discussed about the regulations on violations, and it is stated that these regulations do not suit the importance and criticality of security and privacy issues. The significant rise in the quantity of vehicles is increasing with the growing size of city and the urban population. This lead to many difficulties for managing the stream of traffic and eventually drastic rise congestion, accidents, and air pollution. Many researchers are trying to use the developments in different technologies like sensors and medium of communication to reduce the current problems in upcoming smart cities. In this survey, a review of the diverse technologies used for the traffic management are discussed. The use of social media in order to empower fast and more accurate detection of traffic congestion and mitigation is highlighted. Along with these difficulties, study of the security threats that may risk the effectiveness and threaten the lives of drivers are also emphasized [9].

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The application of Internet-enabled devices to expand Smart Cities, also to monitor and trace, entails the thorough study of recent technologies and their integration and interaction with people. IoT should provide provision for overall communications and contact to different types of services. It needs to come up with different types of solution for the communication of two or more machines. The paper [10] proposes homogeneous and apt mechanism for the detection of devices that are interconnected and installed globally. An infrastructure called “digcovery” is defined that offers the framework in which the sensors used by the end users can be a part of the framework and will be available. It helps the smart devices to detect, interact, and access the resources through its Elastic Search engine [10]. Smart technologies play a vital role in maintainable economic development. These solutions change the way of machine working usually without human involvement. The paper consists of overview of communication between various wi-fi devices which are used in smart healthcare systems, smart grids, smart industry, smart meters, smart houses, etc.[11]. In [12], a three-dimensional Shenzhen City web platform based on the web virtual reality geographical information system is presented. A global browser working to collect several types of data from the city including the historical data about the traffic. Using this data, a three-dimensional analysis and visualization are shown. Huge amount of data can be visualized using this, and the GIS-based navigational scheme allows access to different sources of data. The design of system uses existing geographic human–computer interaction research results [12]. With the expansion of smart meters, like the Advanced Metering Infrastructure (AMI) and IoT, each smart city is furnished with several kinds of electronic devices. These devices along with their supporting technology allows the city to be smarter considering various aspects with respect to accessibility and applications. The paper reviews the notion of the smart city with their numerous advantages and limitations. Also, the use of IoT based devices are discussed along with their applications into different perspectives of smart cities are discussed. The probable application with respect to the development of smart city along with benefits and limitations is provided in this paper [13]. The basis of communications between machines is highly significant in the unconventional applications and services in the smart cities. These also play a key role in the automation of industries and vehicles too. In this work [14], the authors have presented the current improvements in LTE system with the detail performance analysis with respect to the system settings. The evaluations performed show that large number of devices can be supported in the system with some assumptions and less overhead. The overview of different scenarios and methods for communication between the machines in fifth generation (5G) systems are also presented [14]. The Internet of Things (IoT) can provide open access to data in the digital era and can be used to form a network of heterogeneous systems. The involvement of heterogenous devices and the services to be provided make the task of building a general architecture very complex. In the paper [15], the authors have focussed on an urban IoT system classified in to some application domain in order to support the aim of smart city with the recent advancement in the technology and communication. These systems should provide and support value-added services for the administration and

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better livelihood of the people of the city. A wide-ranging survey of the technologies and architecture is discussed along with the technical solutions. The strategies adopted in the given project is performed in collaboration with the city municipality [15]. Intelligent Transport Systems are a key component in Smart Cities. Such systems should be able to collect data from multiple s sources and analyse this information and provide to stakeholders as and when required. The paper [16] has focused to use Big Data analytics in order to give an insight about the road mishaps leading to the traffic congestion with the aim of developing a model that will be able to work using the semantics with respect to mishaps on road. Preliminary analysis will be performed on the data collected from two different sensor types in Greater Manchester, UK in order to explore the possibility of using journey time and traffic volumes for the formation of clusters [16]. The vital service to be provided to the people in the smart cities is the emergency response. The strategies used for the management of these responses also give certain set of rules to manage the incidents. But few of the incidents are not anticipated and the deficiency of proper data management for quick and efficient retrieval should be majorly focussed. The paper [17] propose an information infrastructure to support retrieval of data in case of emergency retrieval in the case of road accidents, natural disaster, attacks outbreak of diseases etc. The proposed infrastructure will consider all the data generated from various resources like smart mobile devices, sensors etc. in order to build a complete realization of the situations causing emergency. It will also provide awareness and help emergency teams on the scene. The proposed data analytics will help in improvisation of the response to coordinate serious incidents and real-time incident management. This management focusses on using the resources effectively and will also help to save lives and reduce injuries, resulting in the improvement in quality of life [17]. Smart Cities use Information and Communication Technologies (ICT) to manage the resources and services offered proficiently to the stakeholders in the city. The authors in [18] proposed to achieve smart city by considering and combining the existing infrastructure and available technologies. The people can be asked to cooperate towards data gathering of the city using their smartphones. The proposed vision is achieved by providing a common access mechanism to the various data sources in the city. This helps to reduce the complexity on a large level in the data ecosystem of the city [18]. The important vision of smart city is to get better the quality of day to day life of all the stakeholders in the smart city with the help of various technologies and devices. The society welfare, both social and economic, is a major aspect to be achieved through various policies and action plans for improvement. However, the privacy of citizens and other stakeholders should also be focussed. This paper emphasizes on balancing privacy protection and improved quality of life. This is achieved by providing a public policy with privacy using Big Data [19]. Mobile crowd sensing is a new class of mobile IoT applications where sensors and mobile devices together collect the data of interest over a large area and share it. The huge data generated through the sensors are to be processed and analysed in order to generate an abstract of useful information for end users. A Cloud based

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system is used to acquire sensor data from mobile devices. The data is collected in a flexible and energy-efficient manner. The processing of the data that is collected is carries out in a unique way. The filtering and collection of sensor data is managed by the resources within the cloud and then this data is transmitted into the cloud. The evaluation show that the system provides scalable performance when tested within the cloud and even on the mobile devices [20]. The growth in the field of Internet of Things is one of sources of a great business in the digital age of urban development. The vision of the smart city improvises the life of people by providing smart healthcare, smart transport, smart parking, smart environment, etc. The major challenge lies in the huge and real-time processing of data leading to appropriate decisions. In the paper [21], an architecture based on Big Data analytics is proposed. The proposed scheme collects data related to the city services using data acquisition and aggregation module. Then this data is preprocessed and analyzed for decisions which will be taken by the decision module. Variety of datasets are analyzed to validate this architecture. Reliable datasets were also tested on Hadoop server to verify the threshold value [21]. For the formation of policies in smart city the urban data and software design are focused. The role of urban data platforms for the delivery of smart city initiatives, with a view to establishing a typology for effective strategic investments in urban data interfaces that are aligned to governance objectives are promoted. The urban data platforms play vital role in the development of governance models [22]. The paper [23] provides a wide-ranging overview of practices in the fundamental foundations, research, emerging trends, and future planning of smart cities. The paper also reviews the presently available approaches with their strengths and flaws. The models and approaches are evaluated and compared for predictable challenges. For the successful future operational management of sewerage network, the prediction of flooding in the real time is necessary. With the advancement in technology the real time report for managing can be predicted. The study presents the design and development of a prototype for an existing sewerage network [24]. The paper [25] proposes a cloud-based framework with a provision to the common people of the city and officials for the building permit process. The framework which is given as transparent with better efficiency and with a user-friendly approach. The comparison with the present permit systems is exclusively given. The proposed structure provides a workflow for pre-permitting decision. It also provides integration with data analytics module for improvement. When the users interact with the system different aspects like the type of request, location and time are considered. The proposed cloud-based framework demonstrates the combination of front-end and data mining sections. It also focusses on the utilization of techniques for mining knowledge from the data generated [25]. The existing smart city research involves futuristic scope of applications including smart transportation that will warn the drivers about the congestion, smart parking etc. These futuristic approaches mainly depend on the collection of data from devices like sensors and mobiles. The big data infrastructure follows the veracity, volume, velocity, variety, and value of data. Recommender systems can very well address the challenges of big data by taking care of veracity. The huge volume of data

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can be handled by applying machine learning algorithms and the data velocity can be handled by analytics algorithms. The relevant information can be extracted using machine intelligence and data analytics [26]. The smart cities have begun with smart, safe, and sustainable services. These services are generally spread throughout since they are based on exclusive IoT solutions or using diverse IoT standards. Thus there is a strong urge to initiate a system or methodology in order to bridge the city that is disconnected and also offer interoperability. The interworking models selected are centred on the status of the cities to relate to each other [27].

3 Privacy Concerns Information about people is gathered, analyzed and stored in order to take better decisions and give personalized experience to the user. Companies use this data to offer better services and marketing the target products to the consumers. Information privacy is the combination of communications privacy and data Privacy. Information privacy is the ability to communicate with others without those communications being monitored by other persons or organizations. Data Privacy is the ability to limit access to one’s personal data by other individuals and organizations in order to exercise a substantial degree of control over that data and its use [28]. Some privacy concerns in the interconnected smart city may be specific to segments like employment, healthcare, home automation etc [29]. But there are many multiple dimensions of privacy invasion affecting lives of each one irrespective of any segment. In carrying out several days to day activities using technology empowerment we surrender our personal information like name, mobile number, email etc. to the organizations. Likely the companies collect huge data for marketing their products. Even if we navigate the web just for refreshment, still there is a risk to privacy. The risk and threat of selling the online collected personal data during various transactions, to other parties. The impact on the collection of huge volume of information that can be personal, transmission of this collected information, time of retention, and the various types and formats in which information that can be attained is exceptional and major influencing factors for privacy invasion. In cyber technology privacy is majorly threatened by Data gathering, Data Mining and Data merging (Table 1).

3.1 Security Concerns In smart city, cyber physical systems used, face vulnerabilities and risks. The city has public and private cameras installed at different places, almost everywhere in the infrastructure. Theses cameras, if not protected by means of strong authentication, are vulnerable to attacks and may collect the information causing violation of privacy. The public cameras usually for governance or traffic management also violates the privacy as it can be used for spying. Different methods like RFID and WiFi are

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Table 1 Categories of privacy violation Category

Violation

Description

Communication privacy

Cookies

Cookies can be used by web servers to identify and track users whenever they refer the different pages on a website

Identity theft

Someone using our identity or personal information to commit fraud or crime

Eavesdropping

Someone tries to steal information in real time while the communication between two parties take place

DOS

Denial of service attack is when the server is flooded with requests so that it is not able to serve the legitimate users

Spoofing

Communication is sent from an unknown source but disguised as trusted source

RFID

It consists of a microchip, also called as tag and a reader. The tag is an electronic circuit to retain the data, and an antenna to broadcasts data by radio waves

Cyberbullying

Use of electronic communication to harass somebody by sending threatening messages

Data gathering

methods for gathering and maintaining private information of an individual, usually without permission from the respective user

Data exchange

Includes various methods for transmission of data which is personal from corner to corner, without the awareness and permission of owner of data

Data mining

To discover patterns in huge data with a goal inorder to extract information such as consumer profiles

Data Privacy

used for the interconnection amongst the smart systems. The developers of these systems usually give attention for higher connectivity and less emphasis on security issues. These systems are weakly protected and face critical hacking problems. The cyber physical systems include various physical objects such as sensors, computing elements, network interconnection etc. interconnected. When these types of systems are incorporated especially in important areas like traffic control, they may cause huge complications.

4 Proposed Model In order to improvise security and reduce privacy related issues in the smart city, Cloud Data Security Model (CDSM) is proposed as given in Fig. 1.

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Fig. 1 CDSM in smart city

It is proposed that the data will be on a secure cloud applying minimum encryption. Third party service provider or government can propose accounts for citizens on the secure cloud. The secure cloud will provide four different categories for securing the data. The categories are as follows (Table 2). The category 1 is the most secured category where exclusive access is provided only to the owner. This category can include healthcare data, finance or banking data etc. In order to maintain safety of data, every access will ask for password. The data access permission for this category will be exclusive to the owner of data. The category 2 is OTP protected where access can be granted to trusted sources on request to the owner. The access will be only for viewing the data and no modification will be permitted. The access will be charged and granted to the recipient only for fixed duration of time. Here the recipient can be blocked or unblocked by the owner. A record for the data accessed will be preserved as well. Category 3 allows Blanket Table 2 Categories for data access in the proposed model CDSM Categories

Description

Data access permissions

Category 1

Password protected (highest security)

Exclusive access only to owner

Category 2

OTP protected

Access granted on request for fixed duration without permission to modify

Category 3

Blanket permission

Access granted without modification permission

Category 4

Free Domain (Lowest Security)

Access to all with permission to modify

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permission for accessing the data in this category. An example of data in this category could be our resume which can be accessible to all but without modification. A record of visitors accessing can be retained. The last category is the free domain data which is the general data without any secure permissions. The categorization of owner’s data will solely depend on the owner, probably the owner may not put any data in the free domain category or put all the data in highest security. The monetary charges to the cloud service provider will be paid according to the amount of data in each of the categories. The proposed model serves as ‘no surprise’ model, where the owner has preserved complete record of the visitors accessing his data. This helps in preventing privacy invasion. The owner has completed right to segregate his/her data in any of the categories provided.

4.1 Conclusions The vision of digitally interconnected smart city should be to upgrade the quality of life but in secure manner. One of the challenges is to ensure personal privacy with the advent of the technology embedded in our lives. In the smart city we expect strong digital interconnection, giving rise to the risk of security breaches. Special security mechanisms are necessary for IoT based structures and cyber physical systems in smart city. Eventually huge data generated and collected from all these resources need to channelize in proper and harmless manner. Thus, it is crucial to design approaches dealing with the data management, so as to provide confidentiality. The proposed Cloud Data Security Model, in the form segregation of data in different categories on cloud will help to secure our data and maintain privacy as well. With the help of records maintained the owner has preserved the information of people accessing his data. While everyone expects high contentment in their life, implementation of technology should be planned carefully and in highly secured manner. When communities of ethical people come together and work towards the improvement of the quality of life of everyone in the society with the help of technology, then the city is rightly smart.

References 1. Tavani, H.T.: Ethics and Technology. Wiley Publications 2. Gershenfeld, N., Krikorian, R., Cohen, D.: The internet of things. Sci. Am. 291(4), 76–81 (2004) 3. Braun, T., Fung, B.C.M., Iqbal, F., Shah, B.: Security and privacy challenges in smart cities. Sustainable Cities and Society 2018, 499–507 (2018) 4. Batty, M., Axhausen, K.W., Giannotti, F., Pozdnoukhov, A., Bazzani, A., Wachowicz, M., Ouzounis, G., Portugali, Y.: Smart cities of the future. Eur Phys J Spec Top 214(1), 481–518 (2012)

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Security and Privacy Issues in Smart City: Threats and Their Countermeasures S. S. Magare, A. A. Dudhgaonkar, and S. R. Kondekar

Abstract Nowadays, there is a large variety of applications available for technologies like smart cities, smartphones, IoT and cloud computing. Applications that are installed on user’s devices have access to user data. The vast amount of data has to be handled on the network and cloud. While handling such user data, security and privacy must be provided to protect sensitive data. As the data may consist of personal data, medical data, financial records or any other form which must be kept confidential. This chapter will discuss the basics of smart city, its applications, and needs, security and privacy issues, data protection schemes, possible attacks and Solutions that can be provided to protect the user. Keywords Smart city · Smart governance · Smart surveillance · Privacy leakage · Data sensing · DDoS · MiTM

1 Introduction The Smart city provides the ICT services to enhance the urban life and to increases the stakeholder access. This smart city fundamentally hitches a superfluity of IT revolutions hitting us at spectacular rapidity to make cities smarter for the people. The Smart city architecture consist of a perception, network and application layer. Perception layer is responsible for collecting data from internal/external data sources. Network layer transmits the data from perception layer to data storage center and S. S. Magare (B) · A. A. Dudhgaonkar · S. R. Kondekar Department of MCA, Jawaharlal Nehru Engineering College, MGM University, Aurangabad, MH, India e-mail: [email protected] A. A. Dudhgaonkar e-mail: [email protected] S. R. Kondekar e-mail: [email protected] © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 S. C. Tamane et al. (eds.), Security and Privacy Applications for Smart City Development, Studies in Systems, Decision and Control 308, https://doi.org/10.1007/978-3-030-53149-2_3

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last layer i.e. application layer consist of various applications used for analyzing, processing and recognizing data [1]. To satisfy the demand of hi-tech smart cities the cloud computing concept is implemented for using virtualized on-demand network services. In smart-city contest cloud computing is becomes more popular in internet users. It is used in various Governments, public and private sectors. Since last few years, internet is used for download various software’s, watch movies, play Games from computer server. Visit social network sites, avail online shopping, online banking, and video calls faculties regularly via internet. Based on clients’ demand Cloud computing delivers matching varieties of applications through internet. Thus, cloud based services are epitome for not only corporate organizations but also favorable for individuals. Security and privacy of cloud computing are critical issue to maintain the trust in a smart city. The CSP is responsible for safety of information of smart city residents because he needs to ensure secured communication between authorized users by secured data exchange multimedia system. Concept of trusted cloud computing with improved services, extended efficiency and trusted on-demand service with proper utilization of centralized resources are widely implemented under in Smart Cities [2]. Smart city makes the citizen’s life smarter but while doing this smart city may face Legal and ethical issues and security and privacy concerns that need to be tackle. Smart city drives the vast amount data. Data security and privacy protection is necessary when transmitting the user data. Security and Privacy issues are crucial areas and the ethical concern surrounding the smart city and plays a vital role. Whenever data travels on wireless networks, security must be provided for safe media transmission because users are always concern about privacy leakage over insecure channels. This chapter highlights the major Security and Privacy issues that need to be considered while designing a smart city and planners must think about safeguard adjacent to security vulnerabilities. The recent technology approaches users to use the latest trends in their day to day life. Technologies can be used for various purposes such as personal, name, and workplace, social and commercial and transportation. These applications have access to the user’s device and may track location. Transportation applications are widely used now. These applications access the user location to track the user’s ride and also stores the card information such as commercial application have to provide strong security services to their users. While handling commercial applications it needs to deal with financial data and here is the most probability that cyber-attack may happen. The user unknowingly shares the confidential data such as card details or bank details and the OTP which may result in cyber-attack and fraud may take place. User needs to be aware while sharing data, some user put their devices in always ON mode, this may be risky. In our day to day life, we are allowing applications to access location data through the GPS, which may store origination and destination information such information can be misused if stolen. In a business and technology environment, the Internet of things is not a topic among the developing trends and new technologies. IoT enables us to connect with

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a wide variety of electronic gadgets, networks of machinery, devices and appliances and sensors. The domain like health care system home automation and industrial Automation uses IoT applications, which results in achieving goals that make the internet prevalent. IoT application mode in smart-city consists of the inter-connection of a huge number of devices with a higher-level control system [3]. Health care industries are now becoming more technology-oriented to compete for recent drifts. They are using cloud-based services, which enables patients to access their medical records and lab test records at any time. The patient may book an appointment from any place and such patient data is used by the health system to analyze purpose. The rest of the chapter is organized as follows. Background Section overviews the Smart city components such as Smart Services, Smart Living, and Smart Energy, Smart Industry, Smart Environment and challenges to the smart city, followed in next section by Security and privacy section highlights the issues that may arise and the risk associated with the smart city with their countermeasure. Table 1 gives the solution/countermeasure to the respective risk. Chapter concludes with protection schemes and the future research directions.

2 Background The smart city is an urban environment that is surrounded by several sensors, devices, machines and IoT (Internet of things). The smart city is an innovative city that improves the quality of life efficiency of urban operation and series. While emphasizing security attacks, [4] has also taken into consideration the security of infrastructure and data privacy.

2.1 Components of Smart City The smart city consists of various components like smart energy, Smart Environment, Smart Industry and so on. Figure 1 shows the different components of a smart city. • Smart Energy Smart Grid, Smart Surveillance and smart recycle are sub-components of smart energy. The smart grid provides optimized generation and distribution that allows serving more consumers and it can be monitored using a smart meter. In the smart grid, renewable energy can be integrated. A smart grid has lower maintenance and operational cost. Consumers have better control over their household consumption. Smart energy improves reliability and efficiency in power. Smart Surveillance devices can be managed remotely to monitor facilities in all aspects. It helps to provide security at a public place [5].

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Fig. 1 Components of smart city

• Smart Services A smart parking solution enables the driver to identify available space to park a vehicle and also allows the driver to pay parking fees. By controlling traffic lights traffic congestions can be controlled. Smart lighting plays an important role in the day to day life. Using smart lightning government authorities can switch ON/OFF street lights from a remote place and can control the brightness of the lights in the traffic area. A smart healthcare system allows health monitoring remotely using real-time patient data. Wearable devices such as smartwatch consist of various health features like heartbeat rate and heath tracking. • Smart Living Smart governance can be improved with the use of social media networks. The social network can collect feedback based upon a particular system and this data is analyzed and used for improvement purposes. Certain city-region contents can be hosted on social networks [6]. In home-automation users can connect household devices using sensors, Bluetooth and wifi connecting technologies. It is easy to control household devices from a remote place and wirelessly. • Smart Environment Information and communication technology is effectively used in smart Environment resource management with the use of e-governance, e-people, and the Internet of Things. The smart environment is developed to support a sustainable environment

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and climate in a smart city. Smart Environment can be used to monitor weather, water, and air pollution, forest fire detection and snow-level monitoring. • Smart Industry The smart industry improves the operational visibility and efficiency of the industry. Smart industry uses smart predictive monitoring, supply chain management, and condition monitoring and it makes real-time decision making. Predictive maintenance ensures machines’ health and provides corrective measures so equipment malfunction can be detected in early-stage and unplanned downtime will not happen. Supply chain management results in enhanced customer support service and optimized production. The demand and supply chain can be monitored smoothly and helps the industry to monitor several suppliers, product demand, and product condition and can keep track of inventory [7].

2.2 Challenges of Smart City In spite of delightful advantages, smart city has to face certain challenges when it comes to implementation work. The following are some challenges that have to tackle while developing and deploying smart city applications. • Infrastructure The first demand of the smart city is smart technology developed on IoT. This demands IT solutions providers with great demands. Most of the input devices used to collect data or communicate it needs input devices. All these devices require complicated and costly infrastructure for communication or sharing of data. This includes energy (solar/electricity) using wiring/wireless. Majority cities are already facing the challenges with old infrastructure, no planned city layout/master plans, underground wiring, transport tunnel, high-speed internet, wireless broadband services exist but there is limited access. Funding for new infrastructure is limited and new infrastructure is limited and new approval takes more time. While implementing the smart city infrastructure the priority/attention must be given to local problems. The main goal of connectivity is 3C which collaborates, Cooperate and Connect with residents, industries and academic and civic organization to identify, address and resolve with innovative solutions. • Security and Hackers As the smart word reveals that all the day to day life activities are based on IoT and sensor technology applications. This does the threat level to security. Being considered as ‘SMART’, there are chances of a break into it which may lead to shut down the entire city.

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A major portion of investment in a smart city is on resources and security. The companies are also working on developing the solutions to incorporate encryption techniques to increase security in new applications. • Privacy Concern Every human being wants to live life with dignity, peace, and a healthy environment. Nobody wants to be under surveillance of cameras and other sensory devices that are monitoring/observing you collect data. There must be a balance between surveillance of life and quality life. Cameras are installed to help police and reduce crime but nobody wants to be constantly being monitored. These cameras in public places may create fear and paranoia in law-abiding citizens. Another valid concern is the amount of data being collected from all smart sensors residents come into contact with each day. There must be a separation of collected data and the identity of the user whose data is collected. The Software organization can help all evaluate some of the anxieties of smart city residents by adding transparency and education to their solutions. Local government officials and community boards required to involve in the rollout and educational aspects as well [8]. • Education and Involvement of the Citizens Smart citizens are the basic pillars of Smart City. These smart citizens are active and enjoying the advantages of new technologies. Any new project implementation should involve educating the citizens and explain to them the benefits of the systems via the e-mails or notification through public media campaigns. The on-line education platforms can also be used to educate citizens. • Integration into Society The smart Transit program needs real-time updates. But if the population of the city cannot afford it or senior citizens are not able to cope with the demand for use of smart devices then how will smart technology reach or benefit these groups. Consideration of all ages and citizens must be done while planning of smart city solutions based on bringing together with technology rather than dividing the society based on economic or educational boundaries. • Insufficient Funds Making a smart city involves the implementation or deployment of digital technology supportive complex infrastructure. This infrastructure needs to have the provision of thousands of smart devices to integrate and collect data. To maintain and install all these smart devices the government needs to hire technically expert manpower. The city planner team must be hired. The right network needs to be installed and audited at the regular interval for the efficient running of the whole structure. To carry out all these activities the timely fund’s availability is the key to success and the biggest challenge.

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• Lack of Experienced Professionals The preparation of a smart city strategy for successful implementation of the smart city needs skied and experienced professionals. One needs to identify the area for technology implementation operating tools and technical experts. The count of professional requirements needs to identify before starting the project plan. • Best Network Connectivity The eyes and ears of the smart cities are the network of sensory devices like cameras, sensors installed at various locations. These devices are collecting and sending realtime data continuously. Processing and analysis of these data are immediately carried out and concern action will be taken. For all these activities we need a high-speed internet connection with a high data transfer rate.

3 Security and Privacy in Smart City When it comes to sensitive data, security and privacy issues are necessary to keep in mind. Smart city results in high-level operational interdependencies, due to this cascade attacks may happen. An attack not only threatens data but also damage infrastructure [9]. So it is necessary to provide security for infrastructure too. Data can be categorized as personal and impersonal and can be used in different ways. Customer data is widely used for marketing and advertisement purposes. The service provider should provide strong solutions to fight with possible attacks and misuse of data. Some issues are discussed below:

3.1 Issues • Privacy Leakage While Sensing Data In the smart home technique, all building area comes under surveillance to detect unusual activity and theft and it consists of all visual information related to the building. Such information needs to protect against hackers because they can use this information to track users’ leaving timing. While sensing data security must be provided to protect residential and private data. • Privacy While Storing and Processing Data Data used in smart city applications are stored on the cloud. There may be a threat of accessing these data form untrusted cloud servers because these data are open to cloud servers. If data is sent over cloud in the clear text then there might be a possibility that data may be hacked or used for unethical purposes. One way to avoid

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this situation is that Smart city Data should be encrypted and send in ciphertext format on a cloud server for storing and processing purposes. • Dependable and Trustworthy Control Smart city control flow is based upon an actuator and control system to eventuate the specific triggered operation. From the public and infrastructure domain, feedback and control systems are mainly targeted by the attackers and hackers. These systems should have authorized access to handle such data. Malicious data injections, spoofing and DoS attacks obstruct smart city applications.

3.2 Risks in the Smart City The rapid development of technologies such as mobile networks, smartphones, IoT, cloud computing resulted in increasing the demand for more security. Here authors highlighted some risks, Fig. 2 shows different risk factors associated with the smart city. • Software Development City government and vendors deploy some types of devices and control software systems without undertaking cyber security testing to ensure an end to end protection.

Fig. 2 Risks in smart city

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Such types of problems raised due to the market’s sensors and low powered devices do not have the right schemes to support encrypted networks. Government and authorities only care about functionality, modernity and advanced technologies, but they do not pay more attention to security-wise testing. • Man in the Middle Attackers are always ready to build attack combinations for new applications and devices. Man in the middle attack is a third unauthorized secret interception between communications of two parties. In MiTM attack each sender and receiver believes that both are communicating with each other. But data flow sends to attacker malicious channel. To defeat the MiTM attack smart city will have strong encryption over SSL connection [10]. • Data and Identity Theft and Authentication Identity theft is a major problem in cyber attack today. Generally, the data gathered from smart city infrastructure such as parking garages, EV charging stations provide the max amount of personal information then used for the fraudulent transaction such as banking transaction, core business, computer data hacking, smartphone devices data misuse, etc. • Device Hijacking One of the biggest concerns about smart cities is that the sensors and devices can be hacked or led fake data. By accessing user information from unauthorized devices hacker easily hijack the device control. These problems raised because our government provides inadequate security and privacy awareness training to vendors and has the inability to update the software every time. • Distributed Daniel of Services In DDoS attack the hacker attempt to prevent a user from accessing the services. Here, attacker usually sends a flood of messages requests in an attempt to overload the system and prevent the request from being successfully executed. Within a smart city, there are many hackers are ready to overwhelm many system devices by requesting a service simultaneously, which sometimes leads to damage to the device so badly. To overcome this problem it required replacement or reinstallation of hardware or software. • Virus, Worms and Malware Attack Multiple attacks rose from human error and deliberate employees by opening phishing emails and installing viruses or malware into computers. Today government system security is not up to date by configuring correct software applications. These phishing emails are used to release key user information to access that device. Also, malware injection attacks are done to take control of the user’s information in the cloud Ex.SQL injection [11].

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3.3 Protection Schemes for Smart City In a smart city, there is a need to secure communication networks that transfer user data, the application itself which manipulates this data, the mobile devices which run that application and cloud environment which process and store this information. Here authors highlighted some protection schemes. Table 1 shows the associated risks and their countermeasures. • Approved White List Application A white list application is approved software that is used to keep authorized access ways from running on the device. • Encryption for Data Protection Secure protocols such as Transport Layer Security (TLS) must be used when managing these devices and any unsecured protocol must be disabled. A User with the right encryption key can decrypt the provided information which has been encrypted [12]. • Authentication or Access Control To receive and transmitting data, each device in a smart city should be authenticated to ensure the data originates from a trusted device and not a fraudulent source to Table 1 Threats and their countermeasures in smart city S. no.

Threats

Countermeasures

1

Software development

The white list approved application Better training for vendors Use security frameworks

2

Man-in-the-middle

Authentication Encryption Security life cycle management Certificate

3

Privacy, data identity theft

Authentication Encryption Access controls

4

Device hijacking

Device identification Access control Security life cycle management

5

Denial of services

Authentication Encryption Access controls Application-level DDoS protection Security monitoring and analysis

6

Virus, worms and malware attacks

Use endpoint protection software Test regularly OS update

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protect against malicious attacks. It is a security technique that regulates who or what can view or use resources in a computing environment. Authentication or Access control results in providing strong security features and minimizes possible threats that may harm the organization. Access control falls into two categories; Physical access control and Logical access control. Physical access control restricts unauthorized access to campus and physical IT devices. Logical access control restricts unauthorized access to companies’ networks, system-related confidential files and sensitive data [13]. • Cloud Offloading and File Transfer It is the task of sending computation-intensive and files application components to a remote server. Offloading computing and file transfer to an external platform over a network can provide computing power and overcome hardware limitations of a device, such as limited computational power, storage, and energy [14]. • Data Integrity and Storage Protection Smart city operation depends upon accurate data. Data integrity ensures the accuracy of the data. Data integrity can be achieved by data backup, data validation, and data log. Storage protection restrict unauthorized access to alter and read any data. • System Updates Smart city devices must be updated and patched according to manufacturer specifications to prevent vulnerabilities. E.g. Code Guardian protects networks from intrinsic vulnerabilities, code exploits, embedded malware, and potential back doors that could compromise mission-critical operations. • URL, IP and Spam Filtering IP Filtering is used to block known spam sources, email harvesting and handle the needs of high volume email services. The main problem with blacklists is that they cannot differentiate obvious spam from an obvious legitimate email. URL Filtering is used to block the majority of spam, update the IP blacklists. It allows an enterprise to control Internet access by permitting and denying access to sites based on their category that a URL belongs to spam filters detect unsolicited, unwanted, and virus-infested email (called spam) and stops it from getting into email inboxes.

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• Data Anonymization Data Anonymization encodes the personal recognizable information which restricts the data to be openly made available. To obtain the prospective benefits of the sensitive-but-not-secret category, data is usually anonymized before being released. • Trusted Third Party Auditing In the system the task of allowing a third-party auditor (TPA) on behalf of the cloud client to verify the integrity of the dynamic data stored in the cloud. The company decides to go for an audit done by the third party to verify and set the standard and to improve quality management. • Security Monitoring and Analysis The captured data from endpoint devices and connectivity traffic is analyzed to detect security violations or potential system threats. Once detected then a range of action policies executed such as quarantining devices on anomalous behavior. • Security Lifecycle Management Service provider controls the security of many smart devices when in operation. Rapid over the air deice key replacement during cyber disaster recovery ensures minimal disruption. Also, secure device decommissioning ensures that scrapped devices will not be repurposed and exploited to connect to services without authorization. • End Point Protection Software It is used to apply security measures to monitor the device on the network for that would indicate an attack is in progress. • Regularity in Test To reduce the risk of vulnerabilities, perform regular tests on the networks when new device or updates are deployed. • Secure Framework Create and follow proper cybersecurity framework which contains policies regarding selecting new systems, management and access control via the entire life cycle of devices. • Benchmark Establishment Create and established a benchmark for normal operations. Once you have this then you can use software to determine when behavior is not normal and ascertain if the problem is a cyber attack. • Certificates The client creates a certificate Authority between devices and servers. Thus clients trust this CA certificate otherwise the attack will be detected and SSL connection won’t be established [15].

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4 Related Work The book [16] provides research on the application of the integration of interconnected technologies and big data analytics into the creation of smart city. This book also explore various real time/offline applications and case studies in the field of computer science, IoT and smart cities with modern tools and technologies. This book focused on IoT, big data, future horizon, future luxuries, interdisciplinary tool, and case of smart city. In paper [17], authors have introduced smart home research and presented the challenges faced by engineers and healthcare professionals. In paper [18], presented smart city framework with security features such as secure energy resources, comfortable driving experience, safe environment, public place security. They described three module to implement the concept of smart cities such as Power anti-theft, advanced traffic controlling system and Camera based surveillance and security system. The power anti-theft model was developed using GSM kit (used for communication), Arduino (used for Calibration) two metering unit (used for track net power) and LCD screen (used to display consumed energy). In camera based security system module, it uses weatherproof video link kit (used for long range footage), Ethernet shield (used for digitalized version) and camera set (used for real time monitoring). In traffic control system module, they have used same camera security to monitor traffic on different junction. Implementation of these modules helps to track record of public transportation, Parking, heavy traffic, to detect power theft through variation of reading of power units. In paper [19], they have proposed very fast decision tree method which recognizes from wrongly classified results for the purpose of filtering the noisy data from learning and retaining sharp classification accuracy of the convinced prediction model. A new technique call misclassified recall (MR), a pre-processing step for self-rectifying misclassified instances is formulated. Due to data transmission errors or faulty devices, misclassified instance are occurring in energy data prediction. Caching the data at the MR pre-processor, the one-pass online model is effectively shielded in case of intermitting problems at the wireless sensor network. In [20], authors have used Photovoltaic Geographical Information System software (PVGIS) to estimate production through solar resource, which calculated the radiation from images by satellite. In the case of wind power, data come from an anemometer station near to the designated location. These data are analyzed by IoT node to develop decision trees that optimize power management. They have connected IoT node to open weather services to obtain hourly weather forecast, Solar and wind data are analyzed, power generation is estimated and power consumption is calculated and an algorithm with decision trees decides control actions. The book [21] highlights the areas which ensures the internet-compatible IoT systems. To improve virtual machine placement in cloud computing environments they have proposed energy-efficient approaches. They have analyzed the real time big-data for industry and agriculture domain. In [22], the author has explained the types of denial of service attacks such as SYN flood, teardrop attack, ICMP

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flood and peer-to-peer attacks. Also, they have proposed defense techniques for DoS attacks with the corresponding advantages and disadvantages. In [23], the author has constructed a two dimensional frequently occurring framework. Author has identified the first dimension as the individual’s data that may belongs to most personal and confidential data and another dimension as the concerns of individuals regarding the purpose for which the data is collected. The purpose may be data surveillance or to provide different service. In [24], the author has identified the challenges such as inadequate funds, deficient in having IT professional, inconsistent connectivity of the network, and risks associated with the cyber-security that may delay the successful implementation of smart city.

5 Discussion While tackling security and privacy issues legal and ethical concerns must be taken into consideration. Ethical concerns follow the ethical standards that is what is good and what is bad. Legal concerns are based on rules and regulation which also indirectly based on ethical concerns. Legal documentation answers the questions as follows: Who will be responsible if the server goes down? Who will the user/data provider? How data will be transfer on the network? Information ethics ensures data creation and organization that follow privacy preservation policies. Authentication, Authorization, and Encryption are proved to be effective methods to deal with smart city data issues.

6 Future Research Directions Smart city applications are exposed to threats. As dependability of control has the highest priority, misbehaviors and malicious attacks become challenging. Smart City applications optimize complexity and make life easier. The secure communication factor must be handled carefully.

7 Conclusion Smart city enhance the urban life with optimize resources and better utilization which results in quality life. Powerful solutions have to provide secure access and manage Smart city-data, communication and infrastructure. The unusual activity must be tracked by the service provider to avoid possible attacks. The regular software and

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system update help to fix the new bugs and fight with worms and viruses. Individual and business privacy needs to be secure while processing and storing data. Acknowledgements This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors. The research was supported by the Department of Masters of Computer Applications, MGM’s Jawaharlal Nehru Engineering College, Aurangabad (MS).

References 1. Samih, H.: Smart cities and internet of things. J. Inform. Technol. Case Appl. Res. 21(1), 3–12 (2019) 2. Sarkar, M., Banerjee, S., Badr, Y., Sangaiah, A.K.: Configuring a trusted cloud service model for smart city exploration using hybrid intelligence. Int. J. Ambient Comput. Intell. 8(3), 1–21 (2017) 3. Adel, S., Elmaghraby, M.M.: Cyber security challenges in smart cities: safety, security, and privacy. J. Adv. Res. 5(4), 491–497 (2014) 4. Kitchin, R., Dodge, M.: The (in) security of smart cities: vulnerabilities, risks, mitigation, and prevention. In: Programmable City Working Paper 24, pp. 1–26 (2017) 5. Zhang, K., Ni, J., Yang, K., Liang, X., Ren, J., Shen, X.S.: Security and privacy in smart city applications: challenges and solutions. IEEE Commun. Mag. 55(1), 122–129 (2017) 6. Poletti, C., Michieli, M.: Smart cities, social media platforms and security: online content regulation as a site of controversy and conflict. City Territ. Archit. 5 (2018). https://doi.org/10. 1186/s40410-018-0096-2 7. Smart Manufacturing & Industrial IoT (IIoT) Solutions. Retrieved from https://www.telit.com/ industries-solutions/smart-factoryindustry-4-0/ 8. Sydney Stone: Key Challenges of Smart Cities & How to Overcome Them (2018). Retrieved from https://ubidots.com/blog/the-key-challenges-for-smart-cities/ 9. Aldairi, A., Tawalbeh, L.: Cyber security attacks on smart cities and associated mobile technologies. Procedia Comput. Sci. 109, 1086–1091 (2017). https://doi.org/10.1016/j.procs.2017. 05.391 10. Shi, Y.: Cloudlet mesh for securing mobile clouds from intrusions and network attacks. In: 3rd IEEE International Conference on Mobile Cloud Computing, Services and Engineering, pp. 109–118 (2015) 11. Tawalbeh, L.A., Tawalbeh, H., Song, H., Jararweh, Y.: Intrusion and attacks over mobile networks and cloud health systems. In: IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS), pp. 13–17 (2017) 12. Forcepoint: Cyber Edu-What is Data Encryption? Defined, Explained, and Explore. Retrieved from https://www.forcepoint.com/cyber-edu/data-encryption 13. Margaret Rouse: Access control (2018). Retrieved from https://searchsecurity.techtarget.com/ definition/access-control 14. Maçon-Dauxerre, E.: How smart energy helps consumers save money, energy providers make money and companies achieve compliance. In: TELIT Whitepaper (2018) 15. Smart Cities: Threat and Countermeasures. Retrieved from https://www.rambus.com/iot/smartcities/ 16. Dey, N., Tamane, S. (eds.): Big Data Analytics for Smart and Connected Cities. IGI Global (2018) 17. Poland, M.P., Nugent, C.D., Wang, H., Chen, L.: Smart home research: projects and issues. Int. J. Ambient Comput. Intell. 1(4), 32–45 (2009)

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The Smart Infrastructure

A Comprehensive Proposal for Blockchain-Oriented Smart City Pratyusa Mukherjee, Rabindra Kumar Barik, and Chittaranjan Pradhan

Abstract The astounding technological advancements and massive urbanization calls for the advent of “Smart cities” to ensure the best living standards of its residents. Smart cities use information and communication technologies (ICT) to generate efficiencies, improvise sustainability, encourage economic development, allow business to thrive, boost innovation, assure judicious energy and resource consumption, reduce wastage and enhance quality of life for people. This thus requires perpetual storage of data related to basic components of a smart city and its continual surveillance. The fundamental characteristics of a blockchain make them the most lucrative platform to store valuable data essential for smooth functioning of smart cities. It also ensures the privacy, authenticity and confidentiality of this data. This chapter first identifies the essential elements of a smart city, then provides a detailed literature on the existing techniques to realize a smart city, highlights their shortcomings and explains how blockchain contributes towards their effective implementation. Keywords Smart city · Blockchain · Distributed ledger · Smart citizen · Smart healthcare · Smart agriculture · Smart transportation · Smart energy utilization · Smart governance

P. Mukherjee (B) · C. Pradhan School of Computer Engineering, KIIT Deemed to be University, Patia, Bhubaneshwar, Odisha 751024, India e-mail: [email protected] C. Pradhan e-mail: [email protected] R. K. Barik School of Computer Application, KIIT Deemed to be University, Patia, Bhubaneshwar, Odisha 751024, India e-mail: [email protected] © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 S. C. Tamane et al. (eds.), Security and Privacy Applications for Smart City Development, Studies in Systems, Decision and Control 308, https://doi.org/10.1007/978-3-030-53149-2_4

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1 Introduction Current cities are characterized by a combination of numerous interconnected citizens, several business and trade, avid modes of transportation and communication, different services and utilities. Massive population density and rapid urbanization raise an array of technical, communal, economic and organizational obstacles which in turn jeopardize the economic and environmental sustainability of these cities. This accelerated growth has led to pollution, traffic congestion and socioeconomic disparity. With reference to this, a debate has cropped up to discuss the new technology-based solutions and approaches to ensure systematic urban planning, future viability and prosperity in these cities [1–3]. Smart city is a denotation addressed to a city that assimilates latest information and communication technologies (ICT) to upgrade the quality of living for its people. It also aims to generate efficiencies, improvise sustainability, encourage economic development, allow business to thrive, boost innovation, assure judicious energy and resource consumption, reduce wastage. This overarching goal is achieved by meliorating the basic essential urban services like electricity and water, transportation and connectivity along with business and trade, real estate, transparent governance etc. to curb down on the consumption, wastage and overall costs incurred. Al Waer and Deakin [4] in their work entitled “From Intelligent to Smart Cities” listed the factors that distinguish a smart city from its usual counterpart are: 1. The application of ICT to exhilarate the living standard and environment in the city. 2. The digitization of the city and its community. 3. The incorporation of ICT with governance system. 4. The territorialisation of activities that foster innovation and enhance the knowledge that the people proffer. The essential components of a Smart City are as followed in Fig. 1. The core aim of a smart city is to build a city that is solely for its people. Smart cities principally are cities which are smart enough to provide sustainable, eco-friendly urbanization to its citizens along with all smart facilities popularly called smart solutions, that can ease their life. Smart citizens will actually lead to a citizen-centric city which streamlines the demands of the people and then proffer solutions that

Fig. 1 Essential components of a smart city

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satiate these demands in the most sustainable and judicious ways [5, 6]. Healthcare is considered as the paramount essential facility and a city where healthy citizens reside is balanced in every scenario. Smart Health technology caches the data produced by the smart devices which can be analyzed by health care professionals for betterpersonalized diagnosis and treatment. This digital record keeping and analysis are both cost and time effective for both patients and hospitals [7]. Smart agriculture is a concept that uses modern technology to enhance the quantity and quality of agricultural products without incurring additional costs [8]. A smart building is an architecture that uses mechanized and programmed procedures to automatically control the building’s several facilities to provide basic comfort. This infrastructure helps residents and facility providers to improve performance, diminish energy consumption, optimizes space utilization and minimizes the environmental impact of rapid building constructions [9]. Identification of more attainable and affordable solutions to be transformed into future renewable and sustainable energy solutions is performed by Smart Energy Utilization. Smart Transportation aims to provide ingenious services relating to varied modes of transportation, traffic and parking management thus enabling accident avoiding, proper rerouting of vehicles in case of vandalisms etc. [10]. A smart industry is a highly digitized, collaborative and interspersed manufacturing systems that respond in real time to cater to the ever-altering demands and conditions in the production house, in the supply chain network [11]. Lastly, Smart Governance is about utilizing technology to promote and reinforce better planning and decision making by the ruling authorities. It enables government information to be more transparent and accessible by every section of the society. The absolute fulfilment of all these essential components or their combination plays a pivotal role in complete realisation of a smart city. The existing most popular IoT, Cloud Computing or Bigdata based models for the respective smart city components provide avid 24 * 7 surveillance, high density information storage and prompt analysis for smooth execution of that component. Therefore, it can be realized that the privacy and security of this information is greatly jeopardized as every detail of a citizen is minutely monitored. Thus there is a need for an efficient information collection and storage of while ensuring complete privacy, confidentiality and integrity. Means to ensure smart city architecture accompanied these necessary attributes is the principal motivation for this work. Blockchain is the latest proficient technology which enables to provide information storage along with ensured security and privacy of this information through hashing techniques as well as vigilant clauses to add or modify this information. It also does not employ any third party or web based service provider thereby not obliging a single entity with the prime responsibilities to maintain the safety. Hence, it can be effectively incorporated into the existing smart city architectures. This entire work is dedicated to realising smart city architecture assimilated with blockchain technology. Blockchain [12] is actually a public distributed database holding the encrypted ledger. It primarily differs from a database due to its decentralization. All records in database are centralized whereas in a blockchain, each participant has a copy of all the records. A set of most recent and previously not occurred or included records form a block. The first block of any blockchain is called a genesis. Each of

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Fig. 2 Block diagram of a blockchain

the successive blocks contain the hash of its preceding block. A hash [13] is noninvertible i.e. one wayness. From a particular input, its hash can be calculated but the vice versa is not possible. Also, hash is collision resistant which means it is difficult to find two different inputs with same hash value. This feature of blockchain make it secure as even a minute change in a block alters its hash which is reflected in each of the successive blocks and thus any kind of tampering is noticed. The basic block diagram of a blockchain has been illustrated in Fig. 2. Although each of the blocks or ledgers in a blockchain are visible to every peer in the blockchain network, they cannot to replaced, modified or newly added unless verified and validated by each and every peer. This is the Proof of Consensus [14]. Proof of Work [15] states that for a new node to be a part of the network or for any existing node to add or modify a block, apart from proof of consensus to be fulfilled, they also need to solve certain difficult mathematical equations or puzzles to prove their eligibility. Proof of Stake [16] states that for nodes to participate in a blockchain, they have to put something at stake. For example, each have to prove their identity and validate themselves. Since an intruder will never successfully pass the Proof of consensus, work and stake, he cannot tamper with a blockchain thus, making it highly secure and immune to intrusions. Blockchains are therefore capable to assure the privacy, secrecy and safety of all information vital for smooth functioning of a smart city. In this chapter, in Sect. 2, we first identify the essential components of a smart city and delve into how the respective components have been realised till date by studying the existing literature. Section 3 gives a detailed analysis of the shortcomings in already existing smart city components by scrutinizing them on the basis of several parameters, security and privacy being the prime one. After understanding the fundamentals of a block chain, Sect. 4 illustrates how blockchain can be utilized to build effective smart cities by incorporating each essential component with blockchain into the existing architecture. It also highlights how the proposed model enhances the privacy and security of each smart city component by inculcating blockchain technology. The conclusion and future scope of this work has been discussed in Sect. 6.

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2 Literature Survey Dey and Tamane [17] summarized the collaborative applications of IoT and Big Data Analytics in implementation of smart and connected cities in their book. They have also elaborated on IoT and the new industrial revolutions, digitally authenticated intrusion detection systems, smart traffic control systems, effective waste management, smart healthcare. Solanki et al. [18] have suggested a smart city framework focusing only on secured electricity supply, congenial driving experience, and a constant camera supervised environment. They achieved this real time power supply and theft monitoring, camera based safety and precaution, traffic control using an array of weatherproof sensors, GSM transmitter–receiver kits, day-night camera sets etc. Sarkar et al. [19] proposed a trusted cloud service model for smart city implementation. The entire liability of delivering better services and maintain trust amidst the clients is bestowed on a Client Service Provider (CSP). They have also used hybrid intelligence combining statistical methods, fuzzy logic and bio inspired algorithms to fulfill their objectives. The literature survey has been conducted smart city component wise by considering each of these categorically.

2.1 Smart Citizens Isin and Ruppert [20] defined a smart or digital citizen as the one who utilizes the information and communication technology (ICT) effectively to participate in issues related to society, governance and environment. He has to carefully understand the rights and facilities he is eligible to receive from a smart city and as well as his responsibilities and obligations towards the same. Contrary to the initial years, since early 2010s, citizens are being given precedence in building smart cities. Thus, they are allowed to act as human sensors and provide information to assist cities to become smarter. Projects such as Smart London and Smart Barcelona applied the policies like allowing citizens to participate in governance as suggested by Chourabi et al. [21], to develop a sense of ownership towards the city amongst the citizens by enabling them to engage with each other for effectively as described by Nam and Pardo [22]. Five possible characteristic or behavior can be marked for a smart citizen. According to Chourabi et al., Giffinger et al. [23], Willems et al. [24], they are as follows 1. Active: Active citizens diligently participate in decision making and execution processes in issues related to public life rather than leaving things to happen by themselves. 2. Independent: Independent citizens are self-decisive to choose the issues that matter to them and their cities and have control over the data they generate. 3. Aware: Aware citizens are well-acquainted with up-to-date information regarding what is happening in the city.

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Fig. 3 Flowchart of how smart citizens build smart cities

4. Educated: Educated citizens are once who are well equipped with knowledge and skills to suggest policies and improvisations towards better city life. 5. Creating Public Values: These citizens possess values that are of the communal interest and benefit the people. Smart cities are actually smart citizen driven. The citizens have to be vigilant enough and decisive to point out the problems they are facing in their daily life, encourage innovation and creativity to again design solution to these problems as illustrated in Fig. 3.

2.2 Smart Healthcare Smart healthcare can be defined as using latest electronic technology for better diagnosis of the ailments, improvised treatment of the patients, and enriched quality of lives. Figure 4 gives the three major goals of smart healthcare. Disease prevention is a procedure by which patients are constantly monitored and treated in order to avert the disease from occurring. Thus, the treatment begins even

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Fig. 4 Major goals of smart healthcare

before signs and symptoms of the ailment arises. In order to achieve this, the patient has to be under constant surveillance and smart healthcare has to accomplish this. It thus requires constant fitness check-ups, activity tracking and analysis, disease prediction. Patient-Generated Health Data (PGHD) is solely noted and informed by the patient himself. It is of extreme importance that the patient should inform each and every minutest details else it will be problematic to diagnose his ailment correctly. Medical practitioners must carefully study the history of the patient and physically examine him. A slightest carelessness in this regard may prove to be fatal for the patient. On the basis of these two, diagnostic tests are prescribed which are then performed and the actual ailment is revealed only after which necessary treatment is provided. Enabling information and data sharing between patients and health care providers play a key role in Smart Healthcare. mHealth and eHealth are thus vital components of the smart healthcare system. eHealth [25] stands for electronic health which uses computers and internet to store and manage medical records instead of paper files. mHealth [26] actually refers to mobile health and a practice of medication plus healthcare using mobile devices, computers and tablets. mHealth is thus a subset of eHealth. Internet of Medical Things help in identifying, monitoring, and intimidating health providers about the patient’s vital stats at an early stage in order to avoid any severity in further days. IoT devices can assist to track heart rates, glucose levels and sleep patterns and also reminds them of day to day medications. Data collected from these devices by monitoring the patients are analyzed and integrated instantly. These are then relayed immediately to doctors in real-time which improves the efficiency of healthcare system. Barger et al. [27] developed a Smart-House venture which imposes an array of sensors to monitor a person’s in-home movement. Okada et al. [28] have proposed a system that mainly scrutinizes the body movements during sleep because they are most proportionately related to the sleep–wake cycle. Any discrepancy in the sleep–wake patterns can potentially indicate an illness. A remote health care monitoring system was designed by Kiran et al. [29] that integrated the medical data from biomedical sensors and instantly translated it to the adjacent gateway for

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Fig. 5 Sources of big data in healthcare

auxiliary processing. Chiuchisan et al. [30] framed the architecture for a health care system to oversee patients at threat in smart Intensive Care Units (ICU). Big Data in Healthcare refers to the abundant health data accumulated from diverse sources. Three characteristics differentiate it from classical electronic medical data used for decision-making. It is available in exceptionally high amount; it moves at high pace and traverses the health care industry’s massive span; and, because it is assimilated from various sources, it is highly variable and diverse in structure and nature. Figure 5 illustrates the several big data sources in healthcare. Jayapandian et al. [31] and Sahoo et al. [32] recommended a distributed framework to store and analyse large amounts of EEG data (approximately 77 GB). Their system Cloudwave processed five EEG reports in 1 min, whereas the traditional system took more than 20 min. He et al. [33] proposed a private cloud-based architecture to handle voluminous amount of data requests from health-care service providers. Application of machine learning in the healthcare systems has offered new dimensions in the smart healthcare. Google has recently developed machine learning algorithms to diagnose cancerous tumors on mammogram. Kononenko [34] studied the prospects and contribution of machine learning in medical diagnosis. Cruz and Wishart [35] have analyzed the application of machine learning in cancer prediction and prognosis by studying the cancer susceptibility, prediction of survivability and recurrence. Deep learning algorithm are being utilized by Stanford University for investigating chances of skin cancer. Esteva et al. [36] analyzed clinical images to identify skin cancer subtypes, 2 using neural networks. AI-based applications can be used to study the current medical condition of patients and provide assistance in medical consultation.

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Fig. 6 Components of smart agriculture

2.3 Smart Agriculture Smart Agriculture has abundant potential to deliver a more qualitative, quantitative and sustainable agricultural production, based on more precise and resource-efficient approaches. It also improves the quality of life for farm workers by diminishing their heavy labour and tedious activities. Figure 6 represents some of the components of smart agriculture. ICT is being well exploited these days to enable smart farming. The capability to predict the output of the production allows prior planning for better product distribution. This also reduces the overall costs incurred, enhances profits reaped and also reduces crop wastage. Lee et al. [37] designed IoT based agricultural production system that predicts the production amount by gathering environmental information using sensors. This scheme also helps to improve harvest statistics by enabling efficient decision making. Satyanarayana and Mazaruddin [38] designed a scheme that studies the water distribution in the field, irrigation levels, rainfall predictions using GPS and Zigbee. IoT based devices can also be trained to monitor the crop growth and detect any anomalies to effectively avert any diseases or infestations that can harm the yield. Channe et al. [39] utilized IoT to study the details of soil properties for gauging its fertility and fertilizer requirements for cultivation. Because of inappropriate weather predictions and improper irrigation methods, farmers suffer huge financial losses.

2.4 Smart Buildings Smart buildings leverage smart devices such as sensors and the cloud to remotely supervise and automate a spectrum of building luxuries each designed as individual core systems ranging from heating, ventilation, air conditioning (HVAC), lighting, water supply, sanitation, fire detection, over crowdedness, parking lot and security or CCTV surveillance, but ultimately connected with each other and a centralized

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Fig. 7 Components of smart building

system. This thus ensures an enhanced efficiency, safety and comfort in a costeffective manner for the residents. It also reduces the environmental impact of these buildings and assures optimal space utilization. Figure 7 gives a diagrammatic representation of the components of smart building. A real-life example of smart building facility is the use of automated and optimized start/stop, this enables the building automation system to evaluate when it should put on or off the air conditioning system or illumination for a particular zone in the building. Smart lighting has been investigated by Ye and Huang [40] and Martirano [41]. Another feature is segregation of electrical loads into categories from critical to high priority to non-essential which are again sub grouped. Whenever load approaches the highest limit, the non-essential sub groups followed by the high priority ones are turned off. The critical load is always mandatorily turned on unless severe emergency. In a hospital, electricity supply in the operation theatre and intensive care units can be categorized as critical load. Ma et al. [42] proposed an occupancy-based model predictive control for building indoor climate management broadly focusing on HVAC (Heating, Ventilation and Air conditioning) systems. By carefully analyzing the occupancy percentage in room or area can help to reduce the discomfort and prove to be energy efficient by accordingly controlling the heating, cooling or ventilation based on it and also turning the HVAC system off when that portion is unoccupied. Li et al. [43] suggested a scheme that constantly monitors the temperature condition and environment inside a home by its householder even from outside through a network of sensors connected to each appliance and his device to make the most efficient decision in every circumstance. Neyestani et al. [44] designed a smart parking system to trace the arriving and departing times of different cars. This will thus enable to design such that maximum number of cars can be accommodated and also new parking lots can be constructed. Poland et al. [45] gave a detailed description of the smart home projects North America, Europe, Australia, New Zealand and Asia. The prime concern of their work is to enable elderly people to inhabitate such smart homes for a constant surveillance of their day-today well-being and health conditions. The authors have also elaborately highlighted several issues pertaining to construction of smart homes such as the ethical dilemma regarding whether to have an assistive technology at a person’s home, the financial constraints of such a wealthy implementation, malpractices, legal concerns, and privacy intrusions related to smart homes practical execution.

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2.5 Smart Energy Utilization A Smart Energy Utilization is basically an approach where smart electricity, thermal and gas grids are combined with latest automated technologies and coordinated to establish synergies between them in order to achieve an optimal solution for each individual sector and for the overall judicious energy consumption. The objectives associated with electricity loads distribution are to reduce energy demand and costs along with curbing CO2 emissions. These can be extended to reducing energy consumption, flattening the consumption distribution from peak to valley hours by accordingly shifting the load and providing real time information about the energy prices, instructing people to adopt judicious usage habits etc. Zedan et al. [46] proposed an interactive electricity consumption scheme. Fong et al. [47] proffered a Zigbee and IoT based unusual energy consumption prediction system. They have employed data stream mining to extract intelligent information from the remote big data collected using sensors and a very fast decision tree to learn from misclassified results termed as misclassified recall (MR). Dey et al. [48] have suggested a deep learning based energy consumption forecast system. Smart grid [49] is a network which collaborates digital communication technology with traditional electrical network to reduce electricity wastage and costs. It is capable to provide electrical power from multiple sources like wind mills, solar panels, nuclear power plants, thermal power stations etc. Phuangpornpitak and Tia [50] studied the opportunities and challenges of integrating renewable energy in smart grid system. Figure 8 shows the block diagram of a smart grid. Most households use liquified petroleum gas (LPG) as the cooking gas. This gas is highly inflammable and therefore must be carefully handled and any leakage

Fig. 8 Block diagram of a smart grid [49]

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must be prevented. Smart LPG cylinders not only monitor the gas amount, detect leakage but also automatically book the refill when the gas content goes below a certain threshold value. This is achieved by a communication between the cylinder and the user’s smart device. The booking is done by sending a message to the agency automatically. Surie et al. [51] studied the implication of wireless sensor networking of several everyday use objects in a smart home environment. The smart cylinders are designed to constantly monitor the weight of the cylinder, and also detect any change in odour or temperature of the. As soon as the weight of the cylinder is below a certain level, it displays a message to the user’s phone or any device synced with the cylinder to make him aware and also at the same time automatically send a message for a refill to the booking agency. By doing this the delivery system is quicker and easier. Whenever a change in the room temperature or odour is sensed using smart sensors, an alarm is played to make the residents aware of a leakage and also immediately closes the valve. This thus helps to avoid casualties and explosion. MacFadyen [52], Anandhakrishnan et al. [53] and da Silva Medeiros et al. [54] have proposed similar smart gas schemes by utilizing the functionalities of several sensors, LCD display, buzzer, microcontrollers and the IoT and Cloud technologies.

2.6 Smart Transportation and Connectivity Smart transport systems are able to manage traffic congestion without human intervention thus making travel smoother and safer. Traffic on the roads is constantly wirelessly monitored and transmitted to a central traffic control system which then imposes speed limit for vehicles to be followed in case of heavy congestions. Additional benefits like parking guidance can also be provided. By suggesting shortest route to the destination, smart transport system also help to curb the carbon emissions, resulting in a cleaner environment. If roads are jammed due to accidents, repair, school timings, processions etc., alternative routes are also informed to the drivers for better decision making. Figure 9 illustrates the several components of smart transportation. The other possible benefits of smart transportation can be thus summarized as reduction in waiting time for particular public vehicles, speed control and improvements depending on congestion on road as well as locality, travel time reduction, vehicle capacity management to reduce suffocation and enhance comfort and most importantly accident management to ensure more safer travel. Sherly and Somasundareswari [55] and Yongjun et al. [56] have presented an IoT based smart transportation system that provides a new way of traffic control along with parking assistance. Al Shammary and Saudagar [57] proposed a scheme of smart transportation application using global positioning system (GPS) which enables to advanced vehicle location. This reduces time of waiting for public transport to arrive and also manages rush in a particular vehicle as by knowing the position of each vehicle say a public bus, commuters can accordingly manage their travel. This scheme can also help to give the driver’s or commuter’s whereabout to another

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Fig. 9 Components of smart transportation system

device for example that of his family members. By doing this, a safer and hasslefree commutation can be ensured. A smart transportation system with automatic fare collection was proffered by Mrityunjaya et al. [58].

2.7 Smart Industries Smart industries facilitate fast, adjustable and intelligent production to attain more sustainability, higher efficiency, better receptivity needed to survive in competitive market. This is thus the generation of the fourth industrial revolution called the Industrial Internet of Thing (IIoT) and smart manufacturing. As a result, it is also addressed as “Industry 4.0”. This automation is achieved by use of robots, smart instruments and appropriate sensors to ease the production and manufacturing. Smart industries majorly depend on a highly interactive human machine interface. They also require monitoring tools and control systems to supervise the production and avoid wastage, unnecessary use of resources and raw materials. Figure 10 illustrates these Industry 4.0 Equipments. The various components of a smart industry is represented in Fig. 11. Smart Industries require digital factories [59] that use digital technology to model, communicate and perform the manufacturing process. It also requires connected factories to make the factory operations more consolidated and flexible. Advanced manufacturing and flexible manufacturing are a must these days to cater to the altering requirements of the customers as well as ever fluctuating market trends. Smart industries also facilitate smart working and smart products manufacturing.

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Fig. 10 Industry 4.0 equipments

Fig. 11 Components of smart industry

Shrouf et al. [60] presented an overview of smart industry architecture of an IoT based smart factory. This approach eases the management and energy efficiency of production. The integration of physical and digital aspects of production is called “cyber physical production (CPP)”. Lee [61] and Baheti and Gill [62] have studies the requirements and challenges of CPP systems in detail in their works. Lasi et al. [63] and Stock and Seliger [64] gave further insights into the Industry 4.0 revolution.

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2.8 Smart Governance Smart governance [65] is the process of incorporating modern technologies and ICT to create a more collaborative, interactive, transparent, and sustainable environment for the citizens and government. Smart governments can be based on four different models namely G2C, G2B, G2G and G2E: 1. Government to Citizen (G2C) model: The government interacts with the citizens and provides them a platform for citizens to voice their opinions and feedback about government policies and schemes. 2. Government to Business (G2B) model: Government communicates with businesses to facilitate economic growth. 3. Government to Government (G2G) model: This model creates a bridge of communication between government and its organizations to create a paperless, corruption-free system. 4. Government to Employee (G2E) model: The government communicates with employees and companies. Smart governments can be achieved by E-consultation, E-data and E-voting. Econsultation provides a conventional medium of interaction between government and its citizens. The citizens are empowered to voice their feedback about government policies which directly reach out to political leaders. Except for critical information pertaining to national security, easy access to data about government funds and investment is made more transparent and open by E-data. E-voting is a way of voting that uses electronic means to aid and take care of casting and counting votes. Figure 12 gives a diagrammatic representation of several features and various models of smart government. Mellouli et al. [66] studied the concept of citizen participation and open data in smart governments. For a good governance, ruling parties at the local, regional as well as national level must operate in complete synchronization where interoperability is an inherent feature. ICT adoption made information exchange very easy amidst the Fig. 12 Features and models of smart governance

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Table 1 Issues to generate smart citizen Parameter

Analysis

Technical awareness

Lack of required skills and knowledge regarding IoT devices and technologies may hinder reaping its benefits

Security and privacy

Confidentiality, integrity and privacy of the data collected is important for proper analysis

Unconsented sharing

After uploading a particular details in the cloud platform, automatically the details are shared with other applications sometimes without the permission of the user

government and its constituents. Jimenez et al. [67] emphasized on this interoperability in E-governments. Meijer and Bolívar [68] gave a systematic literature review on smart urban governance.

3 Analysis of Existing Literature Each and every minute detail regarding a citizen’s several aspects like his identity, health records, means of transport, communication, energy utilization is being tracked and analysed 24 * 7 by an array of sensors to obtain smart facilities. Maintaining the privacy and security of this data is very crucial. The challenges faced due to incorporation of IoT and Bigdata in day to day life for different components of a smart city are summarised in Tables 1, 2, 3, 4, 5, 6, 7 and 8 as follows.

4 Proposed Architecture On the basis of its fundamental features, incorporation of Blockchain along with existing technologies will prove to be more advantageous and beneficial. 1. All devices in the IoT setup are connected, identified, and authenticated through centralized cloud servers. These cloud servers are vulnerable to security breach and their failure can affect the entire IoT system. 2. Decentralized feature of blockchain thus make them more alluring. This ensures that computation and storage of data are spread across several devices and not on one centralized server. As a result of which, the situation where server failure leads to breakdown of the entire network will no longer persist. 3. Blockchains significantly minimize the installation and maintenance cost servers and make their scalability easy. 4. The security and confidentiality provided by blockchain ensures that data is safe and untampered. The successive blocks of blockchain store hash of previous block. Any change in the block alters the hash hence intrusion can be easily

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Table 2 Challenges to provide smart healthcare Parameter

Analysis

Design issues

Service oriented-architecture (SoA) of such schemes are a very robust, complex and conglomerated network and thus might incur performances and expenses issues

Data acquisition and cleansing Healthcare data is highly fragmented thus demands constant data acquisition and cleansing to pave way for new data Data discrepancy

A difference between training data and real-world data may lead to wrong conclusion being drawn and thereby resulting in wrong diagnosis and fatality in return

Effective and correct analysis

Machine learning applications usually function as a “black box” where the computerization of its decision-making isn’t open to human inspection or opinion. Thus, there is no proper means to judge the confidence and correctness of conclusions inferred by such applications

Datasets inconsistency

With time, the training datasets get outdated and contradict with the inevitable reality in changing medical practices, medications available and changes in disease characteristics and symptoms

Security and privacy

The information assembled should be confidential and safeguarded from any intrusion. Privacy regulations play a predominant role when it comes to sharing patient’s experiences on a wider scale

Table 3 Analysis of smart agriculture Parameter

Analysis

Connectivity

Uninterrupted connection capable to withstand severe weather and open space conditions, connecting every sensor, field, barn and storehouse is challenging

Durability

Drones and portable sensors need to be robust enough to function even in adverse climatic conditions

Choice of sensors

Compromising on the quality and selection of the sensors affects the accuracy of the collected data and its reliability

Expenses

Maintenance of the hardware and sensors is challenging as they are typically used in the field and can be easily damaged and need to be replaced more often that will in turn incur huge expenses

Technical awareness

Lack of required skills and knowledge among the farmers regarding IoT devices and technologies may hinder them from reaping its benefits

Integration

Improper integration of the various IoT products and platforms lead to abnormalities in functioning of these technologies and are rendered inefficient to deliver services to the farmers consumers

Security and privacy

Confidentiality, integrity and privacy of the data collected is important for proper analysis

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Table 4 Challenges faced to construct smart buildings Parameter

Analysis

Practical implementation

Practical measurement of the extent to which these buildings are making the residents comfortable, happy and productive needs to be carefully analyzed

Flexibility and scalability

The architectural design of such buildings needs to be flexible as well as scalable enough to cater to the ever growing and changing needs of its dwellers

Automation and mechanization

The technologies need to be embedded into the buildings seamlessly such that they can automatically manage, learn, anticipate as well as adapt on their own without human intervention and recognition

Interconnectivity

The monitoring devices need to be available to extract information every time and everywhere for smooth functioning

Security and privacy

Each and every detail of a household and the entire peripheral of a building is being constantly supervised hence the security and privacy of the information plays a pivotal role

Expenses

The cost of set up and maintenance needs to be carefully analyzed

Table 5 Issues to realize smart energy utilization Parameter

Analysis

Compatibility and interoperability

Every machinery or appliance cannot be equipped uniformly with advanced sensors and operating capabilities to effectively share data

Authentication

Millions of devices are interconnected in today’s world as a result of which “out of sight” devices become difficult to manage, enhance complexity and involve high security risks to identify and authenticate each of these

Changing supply

Generation of electricity from renewable sources is quite unpredictable thereby leading to intermittent supply. Also, availability of these renewable sources like sunlight, wind etc. are not under human control and ever fluctuating

Changing demand

The demands of the customers is ever changing and this leads to massive over consumption, non-uniform distribution, voltage issues and ever power outages

Security and privacy

Malware infiltrations and phishing attacks are a major concern as every nitty gritty of a citizen is available online in smart cities

detected. Also, by adding proof of consensus no modification can be made in the stored data unless all nodes agree. Unauthorized persons are not allowed to view the blockchain with providing substantial proof of work.

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Table 6 Challenges to enable smart transportation Parameter

Analysis

Connectivity

The monitoring devices need to be available to extract information every time and everywhere for smooth functioning

Synchronization

All the users, vehicles and other essential components of the system even though “out of sight” must be properly synched to retrieve valuable information

Increased investment The incorporation of modern technologies might enhance the cost to commute between places thus causing inconvenience for the commuters Inadequate skills

The commuters, drivers, analysts etc. need to be adequately skilled to operate the various systems in order to reap the benefits

Security and privacy Confidentiality, integrity and privacy of the data collected is important for proper analysis

Table 7 Issues for functioning of smart industries Parameter

Analysis

Obsolete machinery

Worn out machines and tools are maintained and used for many years in the factories as long as they are in working condition. This is because replacing them would be quite expensive

Increased investment The incorporation of modern technologies might enhance the cost of production and manufacturing, ultimately increasing the price of the items Connectivity

Industries still prefer wired connectivity, hence IoT that facilitates wireless connectivity can represent a shift in the network infrastructure design

Financing

IoT deployments, sensor setups, automated manufacturing etc. call for huge financial expenditures

Security and privacy The security of IoT concerns any step where data is stored, transmitted or analyzed. The machines must be protected from potential hacks, intrusion in production process Awareness

Whether the factory has the essential skill and manpower to design, develop, implement and maintain an IoT deployment is an important factor

4.1 Proposed Smart Citizen Identity Management Scheme Using Blockchain Every citizen uses multiple government authorized identity documents like Voted ID, PAN card, Passport, Aadhar Card etc. for almost any essential service such as opening a bank account, applying for a loan, acquiring a new sim card or purchasing air or flight tickets. Sharing multiple IDs for several requirements is neither secure nor reliable. This always leads to security breaches and privacy concern because every identity document that a citizen shares is always shared with a third-party

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Table 8 Challenges for smart governance Parameter

Analysis

Funding

Creating a digital infrastructure and making everything online needs a lot investment. Developing countries already face financial crunch due to other developmental activities, low tax collection, hefty international loans. So, establishing smart government there is challenging

Interaction gap

Good governance implies more people participation, whereas the government due to security and political reasons they try to maintain a public distance

Increased investment The incorporation of modern technologies might increase the taxation and revenue amounts thus causing difficulty for common people Inadequate skills

To reap the benefits of smart governance, basic knowledge of computer and internet is a mandatory. Rural people don’t have an easy access to the internet or digital systems. As a result, are debarred from the benefits of smart governance

Security and privacy Confidentiality, integrity and privacy of the data collected is important for proper analysis

for example a bank, telecom company, IRCTC or Air India without his categorical consent and is stored in an unknown location. All these third-party databases are extremely prone to data theft and hacking. Also, for signing into any platform one has to input the correct combination of user id and password. It is quite a challenging task for an individual to remember the id-password combination for various services. We hereby propose a Citizen Identity Management using Blockchain to attain Digital Citizenship. 1. Blockchain provides a solution to the above issues in traditional identity management systems by enabling citizens to manage their own identity by eliminating the intermediaries. 2. It also allows a sense of security by imposing that no third party can share these identities without the individuals consent. 3. Also, it avoids repeated upload of documents each time for any service. To practically implement this, Blockchain has to be combined with Inter Planetary File System (IPFS). It is a peer to peer protocol that caches an assemblage of hashed files. Any user can upload any file of his choice into the IPFS that stores a hash function of the file into a blockchain. Now suppose a third-party say a bank employee wants to extract this file related to the user, User simply informs him the hash obtained while storing the file into the IPFS within the blockchain. The bank employee will simply call the hash from the IPFS and get access to the file only with the user’s consent. Figure 13 gives illustration of the same.

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Fig. 13 Proposed citizen identity management using IPFS

4.2 Proposed Smart Healthcare Using Blockchain Blockchain has havoc applications in the domain of healthcare. The ledger technology facilitates the secure storage and transfer of patient medical records, manages the medicine supply chain. 1. Blockchain keeps an unsusceptible, decentralized and transparent record of all patient data. 2. Blockchain is private and conceals every medical data securely to protect its sensitivity. 3. The decentralized feature of this technology also enables patients, doctors and healthcare providers to share the same information quickly and safely. 4. The quick access to a patient’s past records through blockchain reduces the diagnosis time and provides better treatment. 5. Blockchain also eases the medical supply chain and provides drug traceability. Figure 14 gives a block diagram of the proposed smart healthcare using blockchain. Consider a scenario to check the patient’s blood glucose level. Using a smart device, his sugar levels can be examined regularly and related information can be fed into the blockchain. Effective analysis will firstly notify him to keep a check on his sugar consumption by sending him notifications on his smart phone. It will also intimidate him to undergo pathological tests after stipulated time intervals. The patient’s regular glucose levels, test undergone, test results can be directly accessed by the doctors and other health professionals thus giving better treatment

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Fig. 14 Proposed smart healthcare system using blockchain

and eliminating casualties by notifying him accordingly on his smart phone. Incorporating blockchain helps to keep data of each patient confidential thus preventing unauthorized access and utilization of his personal data.

4.3 Proposed Smart Agriculture Using Blockchain Blockchain in agriculture makes the process of growing, cultivating and supplying food simpler. The agriculture supply chain provides all involved participants in

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producing and consuming a single source of information. Blockchain tracks abundant commodities and production thus reducing illegal harvesting and shipping frauds. 1. Essential parameters for cultivation like soil, weather, irrigation and crop can be constantly monitored using network of sensors and the collected data is fed into a blockchain. This ensures the decentralized and secure availability of data, which is then analyzed for better decision making. It helps to enhance the crop quality, crop yield prediction, better irrigation management. 2. Blockchain makes the food supply chain more transparent and trustworthy. Farm origination details, transportation details, warehouse details, expiration dates, storage temperature everything is digitally linked to the food items within the blockchain. Consumers and stakeholders can explore everything to be assured of the food quality. 3. Blockchain gives a clear understanding of the price differences in the food distribution market to ensure highest traffic. 4. The information regarding billing and taxation is made unambiguous and equivocal. 5. Blockchain also assists in stock management and ordering refills in retail shops. Figure 15 gives a block diagram of the proposed smart agriculture using blockchain. Data regarding climatic conditions, soil fertility, irrigation etc. can be fed into blockchain by the farmers and existing technologies like IoT and Machine Learning can be applied to help them increase their yield. Blockchain will maintain privacy between different farmers thus encouraging healthy competition and avoiding intrusion and threats of personal data. The information regarding crop distribution and storage can also be fed into the blockchain thus removing middle men, enabling crop tracking and eliminating thefts. Marketing and retail related information when fed into blockchain will enable farmers to get correct idea regarding sales and profits earned, it will also notify when to replenish stocks from storage and help to analyze the demand–supply chain.

4.4 Proposed Smart Building Using Blockchain Smart buildings can be realized using the blockchain technology. All the necessary services can be provided to the dwellers by incorporating blockchain with IoT and other technologies. A particular home’s every nitty–gritty detail like heating, ventilation, air-conditioning as well as other facilities like water supply, electricity supply, parking, fire extinguishing and evacuation, crowd detection and 24 * 7 surveillance can be monitored and best decisions can be taken. 1. Blockchain can fed with the constant data about status of the HVAC system and then using IoT and data analytics, they can be turned on or off and regulated depending on the weather condition and the need of the resident. Blockchain provides the necessary decentralization, privacy and security of data.

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Fig. 15 Proposed smart agriculture system using blockchain

2. Information about water and electricity supply can be provided to dwellers to enable them to use it judiciously and reduce wastage. A further elaborate design can also help to intimidate residents about upcoming voltage fluctuation, power cut or no water supply situation on their mobile phones such that they can take necessary steps. 3. The several areas can be sensed constantly and the resident can be informed about any fire breakout and their nearest evacuation route. This will help to curd casualties and damage. 4. The crowd at a particular corridor or hall or room can be supervised and necessary buzzer can be ringed to enable people to evacuate. 5. The details about number of cars in the parking can be analyzed by incorporating sensor detected data into blockchain and new parking can be designed to cater to the needs. 6. The activities in commonly used areas within a building can be checked through CCTV surveillance and its privacy is assured using blockchain.

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Fig. 16 Proposed smart building system using blockchain

Figure 16 gives the block diagram of the proposed smart building. To successfully implement a smart building, every nitty–gritty about a particular household and the entire building needs to be constantly surveilled. Incorporating these information into a blockchain will thus prevent malware intrusions and enable confidentiality, integrity and privacy of this information.

4.5 Proposed Smart Energy Utilization Using Blockchain Incorporating blockchain into smart energy utilization can give myriads of benefits. 1. The amount of energy generated from several renewable sources of energy can be exploited and kept a track off by feeding the information into a blockchain. 2. The distribution department is again incorporated with a blockchain. On the basis of the demand and consumption, adequate supply can be provided to several power consumers. 3. Usage of smart meters enables to check on the utilization and supply can be cut off if not required or when consumption exceeds the threshold. This ensures uniform distribution. Figure 17 gives the block diagram of the proposed smart building. In order to actually facilitate homogenous distribution, 24 * 7 surveillance of demand and consumption of consumers is required. Blockchain plays a crucial role in this monitoring

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Fig. 17 Proposed smart energy utilization using blockchain

as a lot of personal information is constantly on the network and the fundamental concepts of blockchain ensures privacy and security of this information by avoiding any intrusion or malicious attacks.

4.6 Proposed Smart Transport Using Blockchain Blockchain can also revolutionize the transport industry by providing better tracking and reducing the waiting times to commute. 1. The details regarding the location of the public transports in a city can be fed into the blockchain so that it can be accessed by the numerous citizens because of its decentralised nature. It will reduce their waiting times and enable them to plan their journeys accordingly. Information regarding seat availability in a particular vehicle can also accessed by the commuters for better decision making. 2. Blockchain ease fleet management and tracking of delivery by removing middlemen as entire data can be accessed by all stakeholders. It assures on-time delivery and less customs issues. 3. The details of drivers can also be uploaded to ensure secured travel and also the commuter’s device can be linked to another device to share his location details with some other family member.

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Fig. 18 Proposed smart transportation using blockchain

4. Information regarding traffic congestion and shortest route to destination can be shard to the commuters. Figure 18 gives the illustration of the proposed smart transportation using blockchain technology. Blockchain helps transportation and commutation easy thus enhancing the connectivity between locations at the same time ensuring the privacy about each individuals details. By allowing vehicle tracking it reduces vehicle wait time and provides better traffic management. It also assures timely delivery by managing the fleet. Blockchain incorporation helps to authenticate drivers and reduce crimes. A commuter can also be linked to his family member using blockchain to ensure their safety while travel.

4.7 Proposed Smart Industry Using Blockchain There are numerous benefits of blockchain technology that can be availed by many different industries, because of its distributed and decentralized nature. 1. Blockchains offer greater transparency, distributed viewing and an unprecedented layer of accountability. It makes each business sector to act responsibly and with integrity towards the company’s growth, customer satisfaction.

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Fig. 19 Proposed smart transportation using blockchain

2. Blockchain eliminates the requirement for middlemen in many procedures such as payments and real estate. It facilitates faster transactions. 3. The immutable and incorruptible nature of blockchain makes it safe from falsified information and hacks. 4. Blockchain records each and every exchange of goods thus presenting an audit trail to trace where the goods originate from. This helps to improve security and prevent fraud in exchange-related operations. It also helps to verify the authenticity of the traded assets. Figure 19 gives the illustration of the proposed smart industry using blockchain technology.

4.8 Proposed Smart Government Using Blockchain A blockchain based government enables the citizens, businesses as well as the governments share information over a distributed but secure ledger. This therefore eliminates a single point of failure and inherently protects the sensitive data. 1. Blockchain enables government employees and citizens to register and authenticate their identities on it.

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Fig. 20 Proposed smart voting using blockchain

2. It also helps to manage assets, credentials, security and transactions securely. 3. It facilitates government activities and increases the ability to track digital as well as physical assets. Thus, blockchains help the government to earn the trust of the citizens. 4. Blockchain reduces the potential for corruption and abuse and enhances trust in government and online civil systems because of their immutability. 5. Blockchain helps to create a secure voting system that ensures that a vote is recorded only once for the specific candidate and permanently recorded on the blockchain. Figure 20 gives a diagram of the proposed smart voting using blockchain.

5 Discussion The proposed scheme is quite persistent to become an adequate smart city architecture with each component functioning effectively along with the necessary privacy and seclusion of the avid range of information scrutinized. Blockchain eliminates the necessity of any third party and service provider and equally distributes the responsibility on all the peers who are participant of the network. The several clauses and hashing technique forbids and intrusion of the information thus keeping the data intact with utmost security. It also establishes a more transparent architecture

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where every member has equal rights to view the information and removes any middle men. For example the farmer can directly check the distribution, storage, marketing, sales and profit earned for his crop, a voter can confidently cast his vote with no supposed malpractice or rigging etc. Hence apart from the general privacy, security and confidentiality of the information, the suggested scheme also adds certain exclusive features described in the previous section to each of the smart city components.

6 Conclusions Blockchain is thus a collaborative ecosystem that establishes trust between all the parties involved. It is a technology that offers decentralized and distributed database along with cryptographic security to share information in a safe manner. It can be concluded that blockchain addresses the challenges of urbanization by assuring better implementation of the smart city’s framework. By linking together multiple technologies like IoT and data analytics with blockchain, the smart city could begin to automatize basic city services like citizenship, healthcare, transportation, industries and governance. A detailed literature of all the essential components of a smart city has been provided in this paper. The existing technologies have been vigilantly analyzed and advantage of blockchain on them has been studied. Proposed schemes for the different blockchain components after incorporating blockchain has been provided. Although at an infancy, still blockchain if carefully implemented will give havoc benefits to establish smart city in practicality. The future scope of work in realization of smart city is the design of appropriate blockchains. We will next focus on actually implementing a blockchain in reality with all the essential components of a smart city. Exactly what data will be fed in the respective blockchain and what shall be the length of the blockchain will be a part of the further endeavors. The skills and expertise to design, implement and utilize a blockchain also needs to be measured. The real-life incorporation of blockchain technologies will also be analyzed in future scope of work.

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The Imperative Applications of Smart City Development

Smart Rain Water Harvesting for Smart Cities S. G. Taji, V. R. Saraf, and D. G. Regulwar

Abstract Urbanization is the core process in the development of the economy of every nation which boosts economic growth and development at one side, the demand for facilities and resources on the other side. Nowadays, the most common solution for the healthy growth of urban islands is to make cities smart. Therefore, smart development aims to provide a better quality of life in the context of existing urban planning issues which focuses on providing the infrastructure services and utilities to urban settlements with the integration of modern technology. Sustainable development is one of the most important components of smart city planning and development. This sustainability can be achieved through smart planning and management of natural resources which includes optimum use, recycle, and reuse. In the present book chapter, various components of the smart city, the importance of water sustainability in smart cities, the role of climate change, and smart water management for smart cities have been discussed. Keywords Smart city · Urbanization · Urban planning strategies · Rain water harvesting (RWH) · Smart water management · Water sustainability · Low impact development (LID) · Climate change

S. G. Taji (B) Department of Civil Engineering, SRES’s Sanjivani College of Engineering, Savitribai Phule Pune University, Kopargaon, Maharashtra 423603, India e-mail: [email protected] V. R. Saraf Department of Civil Engineering, Government College of Engineering, Jalgaon, Maharashtra 425002, India e-mail: [email protected] D. G. Regulwar Department of Civil Engineering, Government College of Engineering, Aurangabad, Maharashtra 431005, India e-mail: [email protected] © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 S. C. Tamane et al. (eds.), Security and Privacy Applications for Smart City Development, Studies in Systems, Decision and Control 308, https://doi.org/10.1007/978-3-030-53149-2_5

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1 Introduction 1.1 Background Urbanization is the core process in the development of the economy of every nation. Expansion of the city can be overlooked through any of the countries in the world. Around 3 million people around the world are migrating to the cities every week [1]. According to UN DESA [2], the urban population will reach 6.3 billion in 2050 as compared to 3.6 billion in 2011 [2]. Though urbanization increases economic growth and development on one side, the demand for facilities and resources has been increasing on another side. Many researchers have studied the impact of urbanization on the catchment and discussed its adverse effects [3, 4]. Increasing urbanization demands more facilities and more resources; this creates an imbalance in demand and supply. Thus, managing resources and facilities (e.g. water supply, solid waste management, sanitation, etc.) in urban areas becomes a challenging task for the urban planner and local governing bodies. Though novel solutions have been developed to tackle these challenges, still some issues not yet been addressed. For instance, most of the arid-region cities are on the verge of severe water shortage and could be worst in the near future [5]. The well known Cape Town city water crisis (in the year 2017–2018) is an alarming situation for everyone. Therefore, for managing the urban environment, the integrated solution is required on an urgent basis to make the growth of cities healthier. This integrated solution should cope up with current challenges as well as future projection (e.g. population growth, climate change, etc.) in a sustainable way. The development of a smart city has become a trend to solve such challenges and issues in urban areas [6]. In most of the countries, smart city development aims to provide a better quality of life with improved services over the traditional urban planning strategies [7, 8]. However, the goals of smart cities have been shifted from sustainable development to technology advancement [7, 9, 10].

1.2 Motivation As discussed in the last section, the development of smart cities to solve different issues in urban areas, nowadays, has become common. The same scenario can be noticed in India as well. India, one of the fastest-growing countries in developing nations, is the world’s second-highest populated country with a population of about 1.3 billion [11]. According to Census data in India, about 216 million (25.7%) people were residing in urban areas in 1991 which becomes 286 million (27.8%) in 2001 and 377 million (31.15%) in 2011. This trend of urban growth has a massive impact on available resources, their supply, and management (especially water) in urban areas. This impact can be well understood by looking to the NITI Aayog report, where it is estimated that water demand will double of the supply by 2030 and around 21 cities

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in India including Delhi, Bangalore, Hyderabad, and Chennai will run out of ground water if no preventive actions are taken [11]. In addition to this, un-planned expansion of urban areas has also severely impacted the natural drainage system of the urban catchment, where many tier-1 cities are lacking modern drainage infrastructure (e.g. Delhi, Mumbai, Kolkata, Chennai, etc.). Similar to previous discussed solution, planning and development of the smart city to tackle various challenges in urban areas, the Government of India with the coordination of the Ministry of Urban Development has initiated the “Smart Cities Mission” in the year 2015 for the development of 100 cities across the India [12]. However, mission objectives and the statement does not mention any use of ICT and only promising the development of basic urban services like efficient water and energy supply, solid waste management, etc. [13]. Moreover, Smart Cities Council India [14] reported that there is a lack of innovative water storage and reuse method in India, due to which, most of the Indian cities are on the verge of the water crisis. It is surprising to note that only 18% of rainwater is used effectively in India and the rest of it enters the rivers and then most of it reaches the ocean [15]. With this perspective, the present chapter discusses the concept of a smart city along with the importance of water sustainability in smart cities. The study includes discussion on various important components of water sustainability in smart cities, and case study on smart rainwater harvesting. The methodology proposed in the present chapter can be employed to make effective use of smart technology to improve water sustainability in smart cities. The contribution of the present chapter can be summarized as (i) an attempt has been made to propose a new definition of the smart city which would consider the use of technology to improve quality of life in urban area under the constraint of resources and sustainability; (ii) the study has proposed the conceptual structure of smart water management and smart rainwater harvesting which works on real-time data as input for decision making; (iii) the proposed methodology in the case study of the chapter uses an android platform to work out the design of the rainwater harvesting at the individual level, which can be applied at any other place to improve the water conservation; and (iv) this study can be an add-on to the existing literature of sustainability and role of climate change in smart cities. The present chapter has been organized in a total of six sections, including the introduction (Sect. 1) as discussed above, which are as follows: Sect. 2 discusses various definitions of the smart cities available in the literature and proposes a new definition. Various aspects of sustainability, the role of climate change, and smart water management for water sustainability in smart cities through the integration of technology have been described in Sect. 3. The detailed report of the case study on smart rainwater harvesting for smart cities has been presented in Sect. 4. The discussion and conclusion of the present study have been assigned to Sects. 5 and 6 respectively.

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2 The Concept of a Smart City Developed cities always play an important role in the country’s economy and growth. However, after the industrial revolution, these cities have expanded rapidly and become the center of complications regarding social, economic, and political aspects. The industry attracts the person from rural places to urban which leads to the development of unauthorized colonies and slum areas. In most cases, the slum areas have not considered getting access to various facilities of local bodies. When these unauthorized colonies demanding facilities, the extra pressure would be created on current management services which creates the gap between demand and supply, and therefore, challenges would start to become more complex. In recent years, development of smart city has becomes more common solution to tackle such issues. Since the 1990s, the government and researchers are using the term “smart cities” to distinguish the cities and promote these as innovative [8]. However, there is no universally accepted definition of smart cities and it may vary from nation to nation or even from city to city. Therefore, many researchers and experts have suggested different definitions of smart cities. Some of those are: • The British Standards Institution [16] defines the smart city as “Effective integration of various systems (viz. Physical, digital and human) in the built environment which provides sustainable, affluent and inclusive future for its citizens [16].” • Bhowmick et al. [17] define the smart city in their guide as “A city which uses its available resources for the benefits of its citizen with making balance its needs (viz. social, commercial and environmental) [17]. • Giffinger et al. [18] describe the smart city as “It is well-performing in forwardlooking six characteristics (viz. economy, people, governance, mobility, environment, and living), built as the ‘smart’ combination endowment with independent and smart citizens [18].” • Smart Cities Council India [14] defines a smart city as “It uses information and technology (ICT) to enhance its livability, workability, and sustainability [14].” • The U.S. Office of Scientific and Technical Information defines a smart city as “a city that monitors and integrates conditions of all of its critical infrastructures for better optimization of its resources, to plan its preventive measures, and monitor security aspects while maximizing the services to its citizens.” Though most of these definitions are describing a smart city in terms of advancement in technology, mobility, smart governance, quality of life, and sustainability, still there is a disconnection with what citizens are expecting about smart city means [19]. Besides, a smart city is a multidisciplinary concept [8] and need to define with consideration of all its components and aspects. Also, the concept of the smart city should not revolve around any particular goal and therefore, it should be based on some characteristics which can be used for the evaluation [18]. However, no such criteria or characteristics are reported in the literature, and hence, the concept and objectives of the smart city are different for different countries or regions. If we consider the smart city as a system that works on different components (e.g.

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Fig. 1 Components of smart city

infrastructure, governance, resources, technology, etc.), then it should connect these components smartly and work as a single unit efficiently. Therefore, one could define a smart city as “a system which makes use of all available new technologies to solve various problems (viz. social, environmental, economical and technical) under the constraint of resources and improves the standard of living through an integrated approach with sustainability”. Hence, a smart city should consider available resources as a constraint and should integrate new technologies to resolve urban issues with the goal of urban sustainability. Furthermore, a system of smart city which works on different components (as shown in Fig. 1) should be interconnected smartly for operation and control.

3 Water Sustainability in Smart Cities 3.1 Sustainability in Smart Cities Water is said to be the most manageable resource among all other natural resources due to its easiness in storage, transportation, and re-use. It is one of the essential resources required for many purposes like irrigation, domestic, or industrial use. However, supplying water (or any other resource) in rapidly growing urban cities now becomes a new challenge for the urban planner and analyst. UN DESA [2] predicted that the world’s urban population will increase by 72% in the year 2050 in

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comparison with the urban population in the year 2011 [2]. Thus, in the near future, the gap between demand and supply is expected to increase [20]. The figures and predictions indicate that the supply networks or facilities like food supply, transportation, sanitation, energy, water, etc., which are already stressed in the current state, will experience enormous pressure. To overcome these future challenges, most of the countries, are updating their cities in the form of infrastructure as well as services, and commonly referring to it as a smart city. But, in recent years, the goal of smart cities has shifted from sustainability to technological advancement only. Many researchers have carried out an extensive survey and found that instead of focusing on sustainability, smart city policies are more technologically oriented without being an efficient [7, 9, 10, 21]. The cities becoming smart without being sustainable and thus, making current issues more complicated [22]. Yigitcanlar et al. [21] reviewed the sustainability of smart cities and highlighted three major challenges of smart cities to provide sustainable outcomes as, complexities in practices, influential towards technology, and ad-hoc conceptualization [21]. Ahvenniemi et al. [9] compared eight smart city frameworks with eight sustainability frameworks and found that smart cities having a lack of environmental indicators to measure environmental sustainability [9]. Several studies also discussed different aspects of sustainability in smart cities and steps to achieve it [7, 10]. The solution through smart cities could be superior if it would be provided with sustainability [23]. Additionally, Girardi and Temporelli [24] discussed the methodology to assess the sustainability of the smart city as smartainability to measure energy efficiency and environmental sustainability [24]. If policies of smart cities shifted towards sustainability, the complications and future risks of current problems can be eliminated.

3.2 Role of Climate Change The dramatic change in climate made situations more critical and many organizations across the world have initiated the research projects to find an adaptive solution against it. The Intergovernmental Panel of Climate Change (IPCC) identified the root cause of climate change as human activities and their footprints [25]. Milly et al. [26] reported that around 10–30% runoff decreases by 2050 in Europe, Southern Africa, the Middle East, and Mid-Latitude America [26]. Urbanization and population increase the demand for resources on one side, availability of resources due to climate change is decreasing on the other side [5]. IPCC reports also confirmed that climate change creating an adverse impact on water availability and some other water-related issues [25]. Therefore, today’s smart cities are going to play an important role to deal with climate change through the implementation of new technologies [9]. For instance, Martin et al. [27] have stated that the reduction in carbon emission should be one of the goals of the smart city [27]. The advanced technologies, such as information and communication technologies (ICT), can be employed to achieve these goals by monitoring and maintaining the level of greenhouse gasses emission as low as possible [21]. Further, IPCC reports highlighted that sustainable

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development can reduce the impact of climate change. However, Gober [5] stated that the city’s sustainable solution becomes unsuccessful due to different policies for different resources management such as water and energy [5]. For example, taking water from more distant required a huge amount of energy for transportation and treatment. Therefore, for sustainable development to fight against climate change, cities should treat their resources (such as water and energy) as a linked resource with integrated planning and management [5]. In this integrated sustainable solution, attainment of one of the goals would aid to accomplish another goal. For instance, increasing taxation on a motor vehicle could promote public transport and make a considerable reduction in energy consumption as well as an emission [3]. Therefore, while fixing the goals of a smart city, the sustainability of four sectors should be considered to achieve sustainable outcomes, which are discussed below and shown in Fig. 2: • Resources Sustainability: this refers to the efficient management of natural resources (e.g. energy, water, etc.); • Environmental Sustainability: this refers to reduce the impact of various factors on the environment (such as reduce the emission of greenhouse gases for minimizing the impact of climate change); • Social Sustainability: this refers to improvement in policies for social services and maintains those as equal for each and everyone; and

Fig. 2 Four sectors for sustainable smart city

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• Economic Sustainability: this refers to implement various strategies for economic growth (such as enhance employment and business opportunities).

3.3 Smart Water and Technology Smart water is an important component among all other components of the smart city. As cities are growing in geographical area and population, no doubt, consumption as well as the demand for resources also going to be boosted. It is estimated that the withdrawal of groundwater is tripled in the last 50 years, but still, 40% of the world’s population is suffering from water scarcity [20]. This report also predicts that the demand for water will become more than 40% of supply by 2030 due to the combined effect of population and climate change. On the other side, traditional urban water management does not include such variations in planning, such as climate change and therefore, the existing system of water management system would not fulfill our future demand. Also, existing water management systems are more prone to water losses through leakages and pipe bursting [28]. Hence, we need to upgrade current strategies and resources management approach to cope up with future challenges. In a smart city, these issues can be addressed through adaptation of smart water management which refers to an integrated approach to manage resources and its infrastructure sustainably from source to delivery [29–32]. Here term sustainably refers to resources and environmental sustainability. Several studies have been carried out to propose and implement effective smart water management strategies in smart cities using technology. Most of them highlighted the use of information and communication technology (ICT) which plays an important role to address various issues associated with smart water [30, 33]. Gourbesville [29] stated that ICT solutions can be implemented in the water domain effectively which gives an alternative way for efficient water management in a smart city [29]. Lee et al. [28] proposed a new methodology for smart water grids (SWG’s) for water management with the integration of ICT [28]. Their methodology is based on five research areas (viz. platform, resources, intelligent network, management, and energy efficiency) to plan future smart city’s water infrastructure. Koo et al. [34] discussed big data plans using the internet of things (IoT) for the water industry to achieve better sustainability [34]. Similarly, Kadam et al. [35] have also discussed the use of big data analysis with the case study on the smart grid [35]. With the increasing number of sensors to collect real-time data for processing, the threat of security breach also increases. Hence, the security of every layer of cloud architecture must be ensured by the cloud service provider to keep the user’s information safe [36]. Some studies also employed ICT for monitoring groundwater quality and leakage detection analysis [33, 37]. Therefore, smart city vision and strategies should be coupled with smart water management and checked for sustainability. This can be achieved through six steps procedure as shown in Fig. 3.

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Fig. 3 Six steps for smart water management in a smart city

3.4 Smart Water Sustainability Smart water sustainability can relate to many issues associated with the water industry such as water security, availability, quality, recovery, and recharge. It can be described as, “water resource sustainability is how water should be available in sufficient quantity with good quality and should meet present demand as well as future to sustain the life” [38]. Many countries already started to act on sustainability which has different names in different countries (e.g. sustainable urban design in the United Kingdom, best management practices in Europe, low impact development in the USA, water sensitive urban design in Australia, etc.). Several studies have reported that low impact development (LIDs) and best management practices (BMPs) are suitable techniques for achieving sustainable development in urban areas [39–41]. The basic aim of these techniques is to minimize the quantity of storm water by accelerating the groundwater recharge as well as improve the quality of storm water through nonstructural measures and then necessary treatment can be carried out by providing a network of structural measures in the area according to site suitability [39]. Therefore, water sustainability is integrated urban planning which considers all the components of the urban cycle and combines it with water management. According to Wong and Brown [42], there are three important pillars which should be integrated into the development of water sustainable city as (i) city as the catchment of water supply; (ii) city as an ecosystem service provider; (iii) cities compromising water sustainable communities [42]. Therefore, based on the sustainable development approach, water

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Fig. 4 Water sustainability

needs to be utilized again and again, which would reduce demand and decreases the pressure on traditional sources of water (Fig. 4). For instance, a city should be capable to supply water of its demand by capturing rainfall-runoff [42]. Once a city initiated water sustainability, there may be alternative sources from where water can be supplied as groundwater or stored rainwater. Moreover, treating the waste water to acceptable limits would create an additional source of water which could help to minimize the demand of the consumer. Therefore, for better implementation of water sustainability, find new sources of water and reduce its consumption at one side, and increase its availability by tapping storm water on the other side.

3.5 Smart Water Management (SWM) in Smart Cities As the transformation of the city into a smart city become a common phenomenon, it also becomes a necessity to make every of its component to work as a smart. Therefore, water management in smart cities should be coupled with technology to transform it into smart water management. This component of the smart city should be incorporated with a centralized data acquisition and processing unit. In the traditional water management system, water is generally taken from natural sources (e.g. river, lake, etc.) and conveyed it to the treatment plant. During this transportation of water from a source to the treatment plant, supply lines may be subjected to leakages, pipe bursting, etc., which results in considerable loss of water. Moreover, there is no water quality monitoring after the treatment plant until it reaches the consumer. Such difficulties, in traditional water management systems, are resolved

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Fig. 5 The conceptual structure of smart water management (SWM)

by collecting the data manually (e.g., water levels in the reservoir, inspection of supply lines, preparation of future demand, collecting water samples for testing, etc.) and get the results as well as possible solutions. This manual collection of data and its computation for carrying out the result required a considerable time, which affects public services and delays the maintenance. Therefore, in smart cities, advanced technology (such as ICT) can be employed to work out those manual processes automatically to reduce its time for the collection of data and computation of the results. Once, the data is collected automatically and continuously over time, the expert can make their decisions on the basis of real-time data-based output. This can improve the accuracy of results and help to prepare future strategies. The conceptual structure of smart water management (SWM) is shown in Fig. 5, where SWM can be divided into two components: the real-world environment; and the virtual-world environment.

3.5.1

Real-World Environment

In a real-world framework, the real-time data should be collected regarding the source of water, its quantity, available storage, consumer and demand, variation in demand, and future projections of demand under changing the climate. Thereafter, this data will be stored in a centralized data storage unit in the virtual-world. The collection of these numerous data requires a giant network of instruments which then can be

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used to monitor the variations. For instance, water consumption data can be collected through automated meter readings (AMR) at the central data storage unit, which can be used to generate the bills and further analysis [34]. Such data are useful to plan further strategies for resource management and reduction consumption by framing new rules and regulations.

3.5.2

Virtual-World Environment

In the virtual-world framework, real-time data will be stored and used for further processing. This can be done by using any of the processing tools (e.g. GIS) and output will be generated. The output generated based on real-time data can be used to make a decision and framing new policies to balance future demand and supply. Furthermore, quality tracking sensors and leakage detection devices can also be introduced in the system to keep tracking the water quality and water loss up to the end-users. In the implementation phase, the new strategies should be monitored to overcome the bugs in the solution and re-framing it with more precision. In the virtual framework, the internet of things (IoT) concept can be employed through the big data collection in which all small components or objects are interconnected and communicate with each other with or without any human interaction [34]. Additionally, the use of IoT in smart home appliances has become common due to its affordability [43, 44]. Nowadays, storm water has adopted as a source of water and not a waste to dispose of it quickly [39]. Therefore, the working of a smart water management structure is shown in Fig. 6. For smart water management of rainwater, it can be divided into three-phase: i.

Collection Phase: In this phase, all the generated runoff either from rooftop or surface will be collected. However, losses take place due to infiltration and evaporation are less in urban catchments, which can be improved through low impact development (LIDs). ii. Storage Phase: The collected runoff will be stored in tanks (for every household) and ponds (constructed at an appropriate location in or nearby urban catchment). The excess water which exceeds the storage limit either diverted to natural stream through drainage system or routed through low impact zones to promote the ground water recharge. iii. Application Phase: At this phase, this stored water can be utilized for potable and non-potable uses like domestic use, industry, gardening, landscaping, etc. The re-use of rainwater in urban catchments reduces water demand, quantity of surface runoff, flooding, and pollutants due to the storm water. The data will be collected at every stage of rainwater harvesting and send to a centralized data storage unit, where all collected data will be stored. Thereafter, this data will be used in two different classes for monitoring: • Storage versus consumption and inflow versus outflow • Inflow versus outflow and groundwater recharge.

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Fig. 6 The conceptual structure of smart rainwater harvesting

These monitored data then processed at the processing unit for further analysis and used to draw the output. Then, the decision can be made for future planning by considering variation in demand and supply over time. However, climate change and population growth should be incorporated while making long term strategies.

4 Case Study 4.1 Background India is the world’s second-highest populated country after China with a population of about 1.3 billion. According to census reports in 2011, about 25.7% (216 million) of India’s population were residing in an urban area, which increased up to 27.8% (286 million) in 2001 and becomes 31.15% (377 million) in 2011. There are several factors involve in the urban population expansion like industrialization, improved facilities, opportunities for employment, new generation trends, and many others. This trend of urban growth has a massive impact on available resources, supply,

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and management. In general, urbanization and resource management are intricately connected. As water is one of the vital resources required for the survival of human beings, the availability of water has been decreased with the expansion of urban areas and populations [25]. Furthermore, in the South-Asian countries like India, where almost 90% of total annual rainfall receives in 4-months of monsoon period (June–September), and for the rest of the year, they need to get water from other sources like surface water or ground water [45]. India’s total annual average rainfall is 1100 mm with the variation of the lowest 100 mm in Rajasthan and the highest 10,000 in Cherapunji [46]. The report of the Government of India [15] estimates that a total of 4000 billion m3 /annum freshwater is available in India, among which, about 30% is usable water. This report further states that water consumption of India during the year 2006 was 829 billion m3 which is projected to be 1093 billion m3 in 2025. The figure indicates the increasing threat of water scarcity which may arise soon. The intensification in the growth of consumption of water can be seen from the reduction in the availability of water per capita per year in India, as it was 5177 m3 /year in 1951, drops dramatically to 1820 m3 /year in the year 2001 [15] and 1545 m3 /year in 2011, which is much below the universal water-stressed level of 1700 m3 /year [45]. In 2015, the Government of India (GoI) with the coordination of the Ministry of Urban Development has initiated the ‘Smart Cities Mission’ for the development of 100 cities across India to overcome many urban issues through smart solutions and sustainable development for the better quality of life [12]. The mission focused on compact and sustainable development but does not provide the actual concept of a smart city [13]. However, the Ministry of Urban Development (MoUD) has identified some core elements (e.g. adequate water and electricity supply, proper sanitation and solid waste management, good governance, robust IT development sustainable environment, etc.) which should be the part of the smart city [47]. The strategy of the mission have been classified into four classes as [14]: 1. Retrofitting where the existing built-up area would be improved to achieve smart goals; 2. Redevelopment refers to replacing the existing built-up area with enhanced infrastructure; 3. Greenfield development introduces smart solutions in vacant areas with provision for affordable housing to address the expanding population; and 4. Pan city where smart solutions would be applied to improve the services with the use of technology, information, and data. However, mission objectives and the statement does not mention any use of ICT and only promising the development of basic urban services like efficient water and energy supply, solid waste management, etc. [13]. Moreover, Smart Cities Council India [14] reported that there is a lack of innovative water storage and reuse method in India, due to which, most of the Indian cities are on the verge of the water crisis. But, any kind of smart solution for smart use of water has not been reported in the guidelines or manual. It is surprising to note that only 18% of rainwater is used effectively in India and the rest of it enters the rivers and then most of it reaches the

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ocean [15]. In the different countries like Slovakia, Israel, the water is generally used four to five times before disposing of, whereas in India, the water is used only once, or even not a single time in case of rainwater, before it disposed of [48, 49]. In this context, the present study has been carried out in Aurangabad city (Maharashtra State, India) to provide a smart solution on water scarcity by utilizing the rainwater. The study focused on the development of the new smart phone app to estimate the amount of rainwater that can be harvested from the individual rooftop, scope, and required dimension of the rainwater harvesting system.

4.2 Rainwater Harvesting System (RWH) In the rainwater harvesting system (RWH), the runoff generated from rainfall is captured and used for various purposes in the dry period. It may be of two types as rooftop rainwater harvesting and surface runoff harvesting. In the present study, rooftop rainwater harvesting has been employed and therefore, discussed in detail. The rooftop rainwater harvesting system consists of three phases: i.

Collection phase: In this phase, water is collected from the rooftop of houses, in which every roof works as catchment from where runoff will be generated; ii. Conveyance phase: In this phase, collected water from the rooftop conveyed through the pipe; and iii. Storage phase: In this phase, all conveyed water will be stored in the storage tank. The conceptual representation of the rainwater harvesting system is shown in Fig. 7. This method has proven to be useful for reducing storm water quantity [50] as well as increasing the availability of water in the dry period [49, 51]. Further, Oberascher et al. [52] have suggested the new smart rain barrels which work as micro low impact development (LID) to make the RWH system more effective through the integration of ICT [52]. However, the design and performance of the rainwater harvesting system also depend upon many other factors like a topography of the region, rainfall pattern, ground water level, etc. which need to consider during the planning stage [48].

4.3 Methodology In the present study, the design of the rooftop rainwater harvesting system has been worked out by considering the drinking water requirement of Boy’s Hostel (Government College of Engineering, Aurangabad, Maharashtra State, India) in the dry period. The design of rooftop RWH is based on guidelines provided by the Indian Standard 15797:2008, which was released by the Government of India in 2008. The methodology of the study is described below.

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Fig. 7 The conceptual representation of rooftop rainwater harvesting system

4.3.1

Estimation of Demand and Size of the Tank

Determination of water requirement is important to decide the storage capacity of the tank. The tank capacity can be computed by assuming that the tank is empty at the beginning of the rainy season (monsoon period starts in June) and get full of its capacity at the end of the rainy season or the beginning of the dry season. Therefore, by considering the average length of the dry season in a year, and water requirement, the volume of a tank can be computed as [49]: The volume of Tank (in liters) = T × D × N

(1)

where T = length of the dry season in days; D = per capita per day demand in liters; and N = number of the dry days in a year. 4.3.2

Rainwater Harvesting Potential

It is important to note that the volume of rainwater that can be harvested is directly depended upon the catchment area. Therefore, more will be the catchment area; higher will be the amount of runoff volume that can be harvested. Furthermore, the

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rainfall pattern also plays an important role in the availability of runoff volume. IS 15797:2008 provided average annual rainfall values for important cities of India, from where the available potential for rainwater harvesting can be estimated based on the type of roof and efficiency of the conveyance system. Therefore, runoff harvesting potential can be worked out as [49]: Rainwater Harvesting Potential (in liters) = A × Pavg × C × 1000

(2)

where A = catchment area or area of rooftop in m2 ; Pavg = average annual rainfall in meters; and C = coefficient of runoff, which accounts for collection efficiency, roof type, and first flush. IS 15797:2008 suggested coefficient of runoff for all situations as 0.80. 4.3.3

First Flush

When the first rain comes after a considerable span of the dry period, the runoff contains a great amount of bacteria, which has been washed from the roof due to dust particles, bird droppings, and decomposed insects. It may also contain any other waterborne metals, sediment, or chemical, which are the undesirable elements in the storage system. Therefore, it is necessary to divert the first runoff from the catchment to prevent the storage system from contamination.

4.3.4

Material Selection

The last step in the design of the RWH system is a material selection for the conveyance system as well as the storage tank. IS 15797:2008 suggests PVC material pipe for the conveyance system. However, material selection for the tank depends upon the type of construction, whether it is surface or underground tank. For surface water storage tanks up to the capacity of 50 m3 , polyethylene or polypropylene (Plastic) tanks and corrugated steel tanks can be used. However, the volume of the tank exceeds 50 m3 then IS 15797:2008 suggests using R.C.C. or ferrocement tanks. Additionally, a sand filter can also be employed in the storage elements for improving the quality of harvested rainwater.

4.4 Result and Discussion In the present study, the design of the RWH system has been worked out as follows:

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Estimation of Water Demand

The total capacity of Boy’s Hostel (N) = 264 Students. Total available rooftop area of the hostel (A) = 1148 m2 . Drinking water requirement per capita per day = 5 L. Length of the dry period (T) = 240 days. From the above data, the required volume of water can be estimated by using the relationship: The volume of water required in the dry season (in liters) from Eq. 1 = T × D × N = 240 × 5 × 264 = 316,800 L

4.4.2

Available Quantity of Rainwater for Harvesting

After computing the required quantity of water, it is necessary to estimate the available runoff for harvesting can be calculated using Eq. 2: Rainwater Harvesting Potential = A × Pavg × C × 1000 = 1148 × 0.71 × 0.80 = 652,064 L

4.4.3

First Flush Estimation

To prevent the contamination of stored water, the quantity of first flush runoff diverted is assumed as 15% of the total generated runoff less than 1 mm rainfall over the catchment area. Therefore, the volume of water needs to be diverted is given by, = 0.15 × catchment area (A) × 0.001 (rainfall) = 0.15 × 1148 × 0.001 = 0.172 m3 or 172.2 L Hence, approximately 170 L storage should be provided in the diverter to divert the first flush.

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Size of the Storage Tank

Now, the net amount of rainwater available for storage, = 652,064−170 = 651,894 L The required water is 316,800 L which is much less than the available potential of 651,894 L. Therefore, the excess amount of water can be used to recharge ground water through artificial recharge pit [49]. Therefore, for storing the required amount of water, 4 tanks with each dimension of 2 m (depth), 6 m (width), and 6.6 m (length) have been proposed.

4.4.5

Recharge of Ground Water

The excess available amount of water from the rooftop catchment of 335,094 L can be used to recharge ground water through the recharge pit. The required dimension of the recharge pit can be evaluated by estimating the runoff rate under a single event or storm and considering soil conditions. In the present study, the runoff rate has been worked out using the rational formula: Q = CIA

(3)

where Q = runoff rate in L/s. C = coefficient of runoff (taken as 0.95 for roofs as suggested in IS 15797:2008). I = rainfall intensity in mm/h. A = catchment area in hectares. In the present study, single storm of duration 6 h with rainfall intensity of 7.5 mm/h has been considered for computation of runoff rate [50]. Therefore, Q = 0.95 × 7.5 × 0.1148 = 0.818 L/s. For deciding the dimensions of the recharge pit, the infiltration capacity of soil should be considered, and hence, the soil is considered as sandy soil with the rate of infiltration of 1.5–1.75 cm/h [50]. Therefore, recharge pit of dimension 1 m (width) × 1 m (length) × 1.5 m (depth) is proposed for ground water recharge. This recharge pit should be filled with pebbles (20–50 mm) depth up to 0.5 m, coarse aggregate (5–20 mm) depth up to 0.45 m, and coarse sand (1.5–2 mm) depth up to 0.45 m from bottom to top. The pit should be covered with a small layer of fine sand (with depth up to 0.10 m) to trap the silt content for avoiding the clogging of subsequent layers. This top layer of fine sand should remove periodically for maintaining the performance of a recharge pit. Furthermore, an appropriate under drain and overflow

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Fig. 8 The conceptual representation of rooftop RWH system with recharge pit

pipe should also be provided to prevent the flooding in the vicinity of the recharge pit. The conceptual representation of the RWH system with the recharge pit is shown in Fig. 8.

4.4.6

Smartphone Application

Thanks to today’s technology to make things easier and much faster. The methodology of the present study has been incorporated in android application to reduce the computation time and get reliable results, even for common man, to implement rainwater harvesting individually (snapshot of the home screen is shown in Fig. 9). The smart phone app needs some input values and in return, it evaluates the available potential of rainwater harvesting and demonstrates the scope for the implementation. The overall working of the app has been divided into five steps as provide the location, roof type, roof size, water demand, and get the results as shown in Fig. 9. For example, a person located in the other city of India needs to give input data like name, location, average annual rainfall (optional and if not provided, the app uses default values from database which are based on values provided in IS 15797:2008), roof type and its dimensions (for calculating the area of catchment and coefficient of runoff), number of family members using water, water demand (if not provided, the

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Fig. 9 Rainwater harvesting smart phone app

app uses the default value of 135 L per capita per day), and purpose of RWH system (storage and use or ground water recharge) as shown in Fig. 10. Thereafter, with one click, just submit the input data, and the app returns with the total amount of water that is available for harvesting. It also provides the dimensions of rooftop RWH system along with its estimated cost. Additionally, the drawings and sketches have also been included in the result section of the app which would help to locate and construct the system (Fig. 11). For better performance of the system, the app also suggests some maintenance technique which would help to improve the service and life span of the system [53].

5 Discussion and Future Scope The increasing urban population has put extreme stress on water resources and expected to rise drastically in the upcoming years. Though solutions have been shifted from traditional to technological, still lack of sustainability in the solutions is serious concern. This concern needs immediate action to improve the sustainability of solutions, especially in smart cities. The emerging concept of smart water with

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Fig. 10 Required input data in the rainwater harvesting app

Fig. 11 Results generated and demonstrated by the smart phone app

the integration of ICT enables researchers to investigate its effectiveness in urban water sustainability [28, 29]. Therefore, rainwater harvesting in urban areas can be used as a solution to minimize pressure on natural water resources and improves sustainability. The present study focused on water sustainability in smart cities along with the case study of smart rain water harvesting in urban areas. The methodology adopted in the study has used an android application to provide design and maintenance guidelines. The design of the system has carried out by considering water availability and demand. The excess amount of water, more than the size of the tank, has been used for ground water recharge. The solution of the RWH has been made ‘smart’ by developing smart phone application which can be used at any other place to design and implement of RWH system. However, only making a smart phone application

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may not turn out the solution as smart, until it is adaptable in local conditions under variable climate conditions. Further, the smart solution should also affordable and fulfill user’s needs with the ability to implement at a larger scale. Therefore, further research is needed to evaluate the cost analysis of smart RWH. The availability of water for rainwater harvesting is governed by many factors like rainfall patterns, the geography of the area, etc. [50], which are also not considered in the present study. Although the performance of RWH depends upon local conditions, integration of ICT in the solution may help to improve the effectiveness of the solution over a larger scale. Therefore, future research can explore the suitability of rain water harvesting for a whole city. Further research can also be employed to evaluate the performance of various sustainable measures (e.g. rain water harvesting, infiltration type LIDs, etc.) under the climate change scenario. The use of harvested water for other purposes like industrial use can be explored in a smart city to improve sustainability. The present study discusses the use of rain water harvesting and therefore, a similar study can be carried out for smart waste water treatment and management with the integration of ICT. Additionally, the present study can also be strengthened by including other constraints like future demand, rainfall uncertainty, the effect of RWH on urban storm water quantity, quality improvement techniques, etc.

6 Conclusion The smart development which was previously adapted as a sustainable solution to numerous urban planning issues has become technological advancement only. The aim and objectives of smart cities become more technology-oriented and less concerned about tomorrow’s needs and today’s consumption. Threats like climate change, urbanization, population growth, availability of resources and its consumption, etc., have already been severe enough to plan and act on the mitigation. Though smart city goals seem to be sustainable, the involvements of citizens are exceptionally important to achieve those goals. While pursuing sustainability, the initiatives should be more concerned about optimizing and conserving natural resources. Therefore, the performance assessment of the smart city should not measure the efficiency of the smart solutions, but also included with its impact on environmental or social sustainability [9]. The integration of technology such as ICT, to achieve these goals could be superior if employed in the right direction. For instance, ICT driven water management would help to improve the efficiency of the system and could offer a more accurate solution like leakage detection, minimizing the losses, water quality monitoring, managing demand and supply, better services to the consumers, etc. It is time to apply all possible solutions to achieve a more sustainable solution in every possible way to preserve today’s natural resources for tomorrow’s generation.

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Smart Street Lighting in Smart Cities: A Transition from Traditional Street Lighting S. Umamaheswari

Abstract The world population has grown exponentially in the last few decades. In the most of the world’s big cities, it is very difficult to provide the resources like energy, water, transportation and other essential services to the public due to the increase in the demands on resources and infrastructure. Internet of Things (IoT) is a technology that makes possible to keep the cities green and safe by interconnecting the devices, vehicles and infrastructure so that the energy and water consumption can be reduced and quality of the people can be improved. The objective of the smart cities could be to increase the economic growth, to construct a clean and sustainable environment, to enhance the income of the people and to make the transparent governance of the city. This chapter provides the need for Smart Street Lighting in smart cities and the suggestions for the implementation. Smart Street Lighting Framework which reduces the cost and the energy consumption is proposed. The present implementations of Intelligent street lighting around the world are also discussed. Keywords Internet of Things · Light dependent resistor · LED

1 Introduction Well-lit streets are a basic necessity. Recently the Government of Delhi has proposed a plan to install around two lakh streetlights, with a priority to cover the reported dark spots. Various studies have brought to light the correlation between safety and lighting. It is important to adopt an effective model in terms of safety, energy consumption and cost. Conventionally used High Intensity Discharge (HID) lamps are to be turned ON and OFF manually. There is no option to regulate the intensity when there are no or very few passersby, leading to a spike in energy consumption. Hence, devising an alternative is necessary to attain the twin goal of an efficient S. Umamaheswari (B) Department of Computer Science, Dr G R Damodaran College of Science, Tamil Nadu, India e-mail: [email protected] © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 S. C. Tamane et al. (eds.), Security and Privacy Applications for Smart City Development, Studies in Systems, Decision and Control 308, https://doi.org/10.1007/978-3-030-53149-2_6

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street lighting system with automatic intensity control and optimal energy consumption. The automation of the Street light system can lessen the energy consumption and maintenance costs and also aids to identify crime activities and provides safe night time environment for all road users. The Smart street light system is primarily designed with the sensors technology to provide a remote streetlight maintenance and control. The proposed model, an integrated Smart City Platform, that connects the smart street lights via internet combines and taps the potential benefits of light-emitting diode (LED) lamps, internet connectivity, and cloud storage to serve as a reliable and energy efficient alternative. LED lamps with intensity control feature will have a longer lifetime and substantially reduce the energy requirement. The smart lighting module could also aid other applications of the Smart City Platform like real time traffic monitoring and smart parking systems. Apart from the automatic intensity control and other capabilities, smart street light networks support the other non-lighting applications of the Smart City platform. The street light connectivity enables quality and noise sensors to be deployed to offer real time monitoring. Connecting the street lighting to the Traffic sensors makes the monitoring the traffic and congestion levels more accurate. Smart street lighting can also support the Smart Parking by making the parking sensors to mount video cameras and to deploy vehicle detection software that provides vehicle occupancy data. The usage of the smart street lights will make the citizen satisfied since they can minimize the energy consumption, eliminate CO2 emissions, reduce light pollution and cost effective. Smart Street Lighting uses LED lamps, micro controllers, GPS module and sensors to control the lamps. A web application is to be developed to monitor the status of the lights. Any disruption could be tracked with the help of GPS and intimated to the respective authorities for further action. Less power consumption, increased life time of the LED lamps, less human intervention and cost effective are the important benefits of the Smart Street Lighting. The implementation of Smart Street Lighting makes the Smart City Platform an effective one. In this chapter, Sect. 2 describes the related work and related smart implementations, Sect. 3 provides the proposed Smart Street Lighting Framework, Sect. 4 highlights the issues and challenges in the smart street lighting implementation, Sect. 5 discuss the features of the proposed framework and Sect. 6 gives the Conclusion and Future directions.

2 Related Work A digital clock, a Liquid Crystal Display (LCD), a timer, an infrared control, alarm function and a photosensitive induction are combined to develop a product based on AT89S52 microcontroller. The Auto-alarm feature of this system is used to set off if any light is damaged. The electricity consumption is saved in this system [1]. A new smart street light controller with timing control and automatic photoelectric

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control is designed. The street lights are controlled based on the movement of vehicles and pedestrians. This new system saves the energy and extends the life of lighting equipment [2]. A Street monitoring system with wireless retrofitting of lamps which do not get power line faults is developed. The location of the lamps are identified though the Radios based on Chirp Spread Spectrum (CSS) modulation which provides the accurate location. This system is implemented in Open field and real world applications [3]. Wireless Sensor Networks based Lighting Automatic Control System (LACS) is proposed in [4]. The lighting intensity is optimized, adjusted according to the external lighting effects. The cost and energy consumption is reduced by minimizing the number of sensors used and the illumination distribution is done uniformly. An Intelligent street light system is designed with Pyroelectric Infrared (PIR) sensors based on Wireless Sensor Network (WSN). A wireless network is formed with the street lights. The PIR sensors are used to check the obstacles before the lamps so that the brightness of the light can be controlled automatically. The main objective is to reduce the power consumption [5]. The authors proposed a street light system with intelligent illumination control that optimizes the power consumption and illumination of the streets. This system has the movement detection based street light control with the aid of LED lights [6]. An Intelligent Street Lighting (ISL) system is developed by integrating latest technologies to offer easy maintenance and energy saving. The power theft is addressed in this system. This system operates in two modes namely Auto mode and Manual mode. The lights are switched ON/OFF based on the traffic intensity and weather conditions in the auto mode. The parameters related to the environmental conditions like rail, faults and traffic congestion are stored continuously in the computer [7]. A Zigbee-based street light control is designed with the objective to reduce the human errors in functioning of the street lights and the energy consumption of the system and make the maintenance easy. The wireless Zigbee network is monitored from a base station. The light sensors make the lights switched ON or OFF based on the intensity of the sunlight [8]. A cloud based automatic street lighting system which automatically updates the data to the lighting system is developed. The street lamps are controlled by using the Zigbee devices that transmit the data from the base station to the lighting system. The movement of human in a given range is identified by Infrared sensor. The dimming control circuit take care of the adjusting the brightness of the street lights to save the power. The data regarding the failure of lights or any other malfunctioning is sent to the monitoring system so that the measures are taken accordingly [9]. A sensor based Automatic Street Lighting system is designed to control the street lights based on the vehicle movement. The lighting system is controlled by the photoelectric sensors and LDR sensors [10]. Intelligent Street light system is designed using sensors which enable the street lights to adjust automatically according to the real-time traffic conditions and adjust according to environmental condition. Dynamic Street Lights with low cost Sensor are implemented which in turn reduces the energy consumption and CO2 emission.

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IR sensor, PIR sensors, low cost embedded controller and storage device are part of this system so as to reduce the energy consumption [11]. Wireless technology based Automatic Street light controlling system is designed to save the power. The lights are embedded with various sensors to identify CO2 , fog, light intensity and noise and GSM modules for wireless data transmission. The light control is achieved by capturing the signals from sensors and appropriate software routines. The usage of energy and theft of electricity is monitored by this system [12]. An automated framework for the street lights that gives solution to the vitality sparing is designed. The light control is done by sensing the movement of vehicles with an InfraRed transmitter and receiver. The status of the lights is monitored through the internet whenever necessary [13]. Energy conservation is a primary challenge that is prevailing all around the word. The development of smart cities with smart infrastructure leads to the conservation of energy and resources. The increasing demand for the smart environment motivates the development of innovative smart applications by applying the Big Data Analytics, Internet of Things and Cloud computing concepts. Integrating these concepts makes the smart application development ease. The analysis of the data captured from the real-time applications drives to make intelligent decisions in the industry [14, 15]. The management of one individual’s daily life is done with the implementation of Smart Home with the sensors and actuators to identify the changes in the households. This would be helpful to keep track of the activities of the in house patients. The forecasting of the energy conservation of the home appliances would be helpful for the users [16, 17]. Smart Traffic is one of the components of the Smart city project. GSM based local city transportation is done to provide a safe and secure environment with advanced automation and information engineering. The traffic control is done effectively during heavy traffic by diverting and channelizing the traffic. Trusted cloud services are offered for the smart city users by applying fuzzy objective decision making and bio-inspired bat algorithm [18, 19].

2.1 Related Implementations There are a few implementations of the Smart Street lighting. This section provides the details of various implementations of smart street lighting. Tvilight is a smart lighting platform which covers 300 towns and cities across 20 countries around the globe and provides optimized energy utilization and maintenance and reduced cost. This has a software suite and hardware setup to facilitate the lighting infrastructure all over the city. The CityManager component manages and monitors the lighting system all over the city and provides the user to get the analysis on the lighting infrastructure behavior. Another component of this platform DigiHub assists to collect the data from all the gateways that can be analysed and provide it to CityManager and other third-parties through open APIServices [20]. RoadSmart introduced the latest solar street light product named Solar Flyhorse Light. This has the combination of LEDs and patented lens to provide uniform

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lighting in the area. The sensors embedded in this system automate the lighting according to the environmental changes [21]. Another system, inteliLIGHT that applies many IoT communication technologies such as Sigfox, NB-IoT, LonWorksPLC and LoRaWAN [22]. The choice of the communication protocol depends of the local network coverage and other requirements. inteliLIGHT is a controller that automates the lighting operation. A grid view of the street lights and the lighting panels is provided by this system. The main features of this system includes autonomous lighting operation, optimized maintenance and cost, increased quality of light and makes the environment green. This is more apt for the Smart City Environment. AAEON Intelligent Lighting Controls considers the real-time factors to automate the intensity of the light. This system helps in shaping the smart cities into reality. Advanced automation of the lighting, effective maintenance, reduced energy utilization and cost are the benefits of this system. The Central Management System is used to manage the lighting network. The malfunctioning in the lighting and the failure of the lamps are notified to the operators. It supports a wide range of communication channels and manages protocol open sensors and actuators [23]. Itron and Elko are other smart street lighting systems which can make the public safe by providing effective lighting system. Cyient is another intelligent street lighting system that provides remote monitoring and control to detect the presence of human [24–26]. The street lighting systems proposed by these authors are implemented with sensors, GSM module, microcontrollers and wireless sensor networks. These systems lack in the monitoring of the status of the lights at the time of failure. In this chapter, Smart Street Lighting Framework with a Web Portal to monitor the lights is presented.

3 Smart Street Lighting 3.1 Smart City A smart city utilizes various types of sensors to provide information that is used for managing the assets and resources efficiently in an urban region. It includes data collected from citizens, devices, and assets that are processed. The smart city concepts integrate Information and Communication Technologies (ICT). IoT devices are used to automate all the processes in a Smart City project. Some of the applications in the smart city include Smart Healthcare, Smart Education, Smart Waste Management, Smart Transportation and Smart Governance. The mission of a Smart City is to offer cost effective and easy access to the services and infrastructure and a good quality lifestyle to the citizens of the country. Smart Street Lighting application makes the city smart by automating and lighting system which leads to effective energy utilization [27].

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3.2 Traditional Street Lighting The lighting industry is undergoing radical transformation fueled by increasing demand for sustainable and energy-efficient solutions, development of LED (Light Emitting Diodes) lighting, and rapid improvisation in semiconductor technology. LED is considered to be the most feasible alternative. It has the ability to consume lesser energy and also longer lifespan. High Intensity Discharge (HID) lamps are used in the present lighting system. Physical switches are used in the conventional manual system to turn ON and OFF the lights in the evening and morning. Manual switching uses man power which is not effective for changing seasons. Most of the lighting system in the highways is done through High Intensity Discharge lamps (HID) that consume high power. The intensity of the lights cannot be controlled according to the requirement so there is a need to switch on to an alternative method of lighting system i.e., by using LEDs.

3.3 Need for the Transition to Smart Street Lights The street lighting system utilizes considerable amount of electricity in every city. Movement of vehicles is sensed and the light intensity is reduced when not in use. In order to save or conserve energy, the automation system is used. Power utilization during unnecessary times can be cut by switching off the lights to save power. Street lights are one of the major power consuming factors in any city. There is a waste of power when the street lights are ON most of the time even after the sunrise. This problem can be avoided by having an automatic system which turns on and off the street lights at the given time. The automation of the street lighting system overcomes the limitations of the present HID lamps. Due to the changeable intensity according to the requirement, minimal power consumption and long life time when compared to the conventional HID lamps, the LEDs (light emitting diodes) are used as the light source. The LED intensity can be managed according to the need during non-peak hours whereas it is not possible in the case of HID lamps. The automated street lights are mainly used to eliminate the manual intervention to switch ON and OFF and to save energy. The automated street lights demonstrate the usage of the LEDs as the light source. Automation is implemented as it saves more time and power. The automated street light is a simple and useful concept that utilizes transistor as a switch to automatically switch ON and OFF the street light system. The lights are switched on automatically switches when the sunlight goes below the visible region of our eyes. The lights are switched OFF automatically when Sunlight falls on it. This process helps to save energy and reduce cost as well as the LED lamps are cheap in price.

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3.4 Smart Street Lighting Framework The Smart Street Lighting framework is designed with the support IoT. The main purpose of this system are. • • • • •

To make the lighting system automatic To reduce the cost of the lamps To reduce the energy consumption To reduce the time taken for detecting failures To develop a web portal to monitor the status of the lamps. The process flow of this system is as follows:

• The lamp posts, embedded with the sensors are installed in the streets of the city. • Turning the lights ON/OFF depends on the sunlight or any movement near the lamp post. • The signals from the sensors will be sent to the IoT Cloud. • Data analysis and report generation is done through a Web portal. • The respective authorities will receive the reports through email/SMS. • The detection of failure/malfunction of the lamps is intimated to the technician through a mobile-based web service. Figure 1 illustrates the functionality of the Smart Street Lighting System.

Fig. 1 System architecture of smart street lighting system

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When the smart street light is in operational, the light sensor below it senses the light intensity in the surrounding. If the day light (sunlight) is at high intensity automatically the system has to be switched OFF or the intensity of LED has to be decreased. On the contrary, if the day light is at low intensity, the system has to be turned on and has to increase the level of intensity. Figure 2 illustrates the flow of the Smart Street Lighting system. Another main functionality is when the system detects the presence of any kind of movement towards the street light or away from it, and then correspondingly the intensity has to be adjusted. Figure 3 depicts the flow when there is any movement near the lamp post. The data from cloud is retrieved and the alert is sent to the technician when there is a failure/malfunction in the lamps through a Web portal. The key objective of this portal is to receive the data from the sensors and store it in cloud permanently for further analysis. The functions of the Web portal are implemented in the following steps.

Fig. 2 Flow diagram of smart street lighting system

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Fig. 3 Flow diagram when there is any movement

• • • •

Capture the data from the sensors Connect the sensors to the Web portal Store the data in cloud Analyze the stored data to generate reports. The web portal will also be capable of performing the tasks given below.

• Remote on/off system in each area separately. – The system has to be turned on or off accordingly to the brightness level and according to the movement in the area near the post. • On-site Status Check. – Status of each post could be able to check given the post ID.

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• System Fault Detection/Alarm. – Automatic alerting if there is any failure in the post. • Anti-theft Detection/Alarm. – Fast notification in case if any person or group in case of theft. • Data Management (energy consumption report). – The usage of power in each post has to be saved for future references. • 24-h online Monitoring. – Monitoring of each post and checking the status of post given the unique post ID. • Detecting failures of any node. – If fail in any node the alert or notification has to be given to the web portal so that immediate measures could be taken. • To collect the data from various sensors – Each time the sensors senses the information has to be recorded in the database of the web portal. The environment set up of the web portal can be done with the following components. • Keil IDE Keil® Microcontroller Development Kit (MDK) is the development environment for the Arm-based microcontrollers that consist of the components required to create, build, test and debug embedded applications. • Embedded C Language used to implement embedded application programs. • Cloud Service Provider The cloud service is used to store the data captured from the sensors. The choice of the provider for data storage can be Amazon Web Services (AWS), Microsoft Azure, Google Cloud or IBM Cloud. • MySQL Server • Server Side scripting language • UI Design tools – HTML5, CSS3, jQuery and Flot chart • Data Analytics Tools – – – – –

Excel Hive Apache Hadoop NoSQL HDInsight

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– Sqoop • Cloud Analytical Tools – – – – – –

Delta Cloud Open Stack KVM Open QRM Eucalyptus Open Nebulla.

3.5 Technical Requirements Apart from being an important connected and remotely managed lighting source, the smart lighting poles provide improved network performance across the city. The poles can be deployed without interrupting the normal city activity like car and pedestrian traffic. The smart pole, a connected device also known as digital real estate for the Internet of Things offers necessary lighting without taking up extra space. In addition to providing a connected light source, it provides the cost effective benefits of LED and also improves the communication capabilities of citizens and businesses across the city. A smart lamp post is designed which can be communicated with the web portal. Figure 4 depicts the Smart Lamp Post. The elements and the functions of the smart lamp post are explained below.

Fig. 4 Smart lamp post

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Solar Panel: Solar panel is one of the primary component of solar street lights, as solar panel will convert solar energy into electricity. For an echo friendly smart street light instead of using the electrical energy we could make use of the solar energy. Also the post could be made in such a way that it uses the solar energy during the sunny days and in the absence of the light energy it could switch to electrical power mode. Lighting Source: LED is generally used as lighting source of modern solarstreet light, as the LED will offer much higher Lumens with lower energy consumption. LED technology centralizes and control to reduce energy usage and costs. In the street lighting system, the energy spent is proportional to the energy consumed and efficiency of the lamps. As a result, we could minimize the energy consumption by replacing the current street lights with more efficient LEDs and by controlling them dynamically. The usage of LED lights in the smart street lighting system is advantageous in the following ways. • Faster maintenance timeframes: Failure/malfunction of lamps are detected by a remote operating system to provide more reliable street lighting. • Improved road safety: The natural white light produced by the LED lamps provides better facial recognition that helps the people feel safer at night. The white light sources such as LEDs have a significant role to play, if it is introduced in residential areas. • Reduced energy consumption: The intensity of the street lights are made to the dimming levels between the hours of 11 pm and 5.30 am subsequently reducing the energy consumption. • Energy Conservation: The LED lights have the capability to reduce the energy utilization and CO2 emission. In addition, the lights used in the street lights should be able to dim the brightness and switch off to provide effective energy consumption. LEDs are the most appropriate lamps which can offer the above benefits. • Reduced light pollution: The lighting from the LEDs can be focused more easily wherever needed, e.g. road or pathways. This significantly reduces the light pollution in the sky. Rechargeable Battery: The electricity from solar panel is stored in the battery during the day and provided to the fixture during night. The battery life cycle makes the light lifetime longer and the backup days of the lights depend on the capacity of the battery. Light Dependent Resistor: Light Dependent Resistors (LDR) is utilized in dark/light sensor circuits. The change in the resistance level of an LDR depends on the illumination of the light. The resistance level of LDR is high when the light level is low. The LDR sensors can be used to regulate the intensity of the light. Motion Detection: Motion detection sensor detects any motion and brightens the light.

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GPS Device: The geographical position of the device where it is attached is identified by the GPS Device. The GPS device is attached in the lamp posts which can be used to identify the location of the lamp post at the time of failure. GSM Module: The technicians are informed about the failure in lamps through the messages sent by the GSM Module. Wireless Communication: The lights will transmit and receive data between each other through the wireless network. When a motion is detected near a light, the nearby lights will be turned on, so that enough lighting is provided to the pedestrians or cars. Microcontroller: The microcontroller will operate as the core unit and capable of performing the following functionalities: a. The data captured from the sensors are processed. b. Intensity of the light is controlled according to the results of data processing. c. Sending and receiving of the control signals through the wireless interface. Dimming: The lighting levels of LEDs are adjusted such that the lighting levels can be dimmed when there are no pedestrian or cars on the streets. Control: The lights are controlled in a smarter way to respond to the road user’s needs quickly with the help of intelligent algorithms.

3.6 Benefits of Smart Street Lights Light Emitting Diode (LED) lamps are used in street lighting system nowadays instead of HID lamps to have the dimming feature. More than 40% of the electrical energy utilized by the lightings in the highways can be saved by the usage of LED lamps. Automation, Power consumption and Cost effectiveness are the main advantages. The growth of automated street lighting systems is increased rapidly and become complex with rapid growth of industry and cities. Complex street lighting system is managed more economically with the development of automated lighting system. The automated street light system exploits the solar energy which is a renewable technology for the source of light instead of commonly used street lamps such as High Pressure sodium lamps, High Intensity discharge lamps, etc. The LED technology is advantageous over other traditional technologies as it offers several advantages like energy saving due to high electric luminous efficiency, reduced maintenance cost, long life, rapid start up speed, High color rendering index, etc. Due to the longer life time and cool light emission the LEDs are used for the street lights. The listed below are the main advantages of automated street lights: • Energy saving • Automatic functioning • Cost Efficient

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• Increased lifetime of street lights • Obstacle Detection • High sensitivity is high.

4 Issues and Challenges in Smart Street Lighting Implementation Most of the outdoor lighting is implemented with the help of street lights in the entire world and the technology is subject to advancements time to time. The initial investment of automatic street light system is higher when compared to the conventional street lights. Theft of the lamps in the automatic street light system is a main issue since they are non-wired and are much expensive. Even the street lights are being automatized, there are some disadvantages as: • Automatic street lights require lot of money to implement the necessary infrastructure since it differs from the traditional one. • Automatic Street light cannot be switched ON and OFF during the required time. • These lights are affected by the weather. Yet these disadvantages are not considered that big deal if the outdoor lighting company did manufacture them in a high quality standards. The maintenance cost can be reduced by using good equipment and having periodic checks. Transistors are used as switches to eliminate human intervention in the automatic street light system. The lights are switched ON when the light goes below ambient light. This system can be applied in several scenarios such as lighting in campuses, industries and parking lots of big shopping malls and can also be used for surveillance in commercial campuses and industries. As the development of automated systems are increasing day by day, the system will have the newly implementing advanced features, so that the problems or issues in the implemented system can be easily solved and fixed with more invented features.

5 Discussion Technology driven products and solutions has not only made our lives simple and smart, but also affected our environment adversely. Rapid development has its own repercussions—increase in greenhouse gas (GHG) emissions, occurrence of more heat waves, flooding, severe drought, melting glaciers, rising sea levels and climate change as a whole. The way out is to make sustainability a core principle in all development aspects from something as simple as street lighting to measures as complex as reducing inequalities. The proposed model would be a small step in the right direction by reducing the energy consumption. Other possibilities like using renewable energy sources like solar powered lamps could be considered. Any smart

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system has to be sustainable also. Else the adversaries would outweigh or nullify the benefits. Implementing sustainable, cost effective, smart systems would benefit both humans and the environment. Smart lighting module and the Smart City Platform would be one such. Recently, Nighttime lights are used to determine socio economic indicators and economic development in developing countries. Smart lighting system would help in determining these indicators better.

6 Conclusions and Future Directions This chapter presented the Smart Street Lighting System for Smart Cities. The architecture for the smart street lighting is suggested which uses the sensors, microcontroller, Wi-Fi module, GPS module, Cloud Storage and Internet Gateway. This system is an automated system that controls the entire lighting system in a particular region and can be monitored with the Web Application Interface to find out the status of the lights, failure of lights and so on. This system would benefit to the city authorities. A framework for Smart Street Lighting System with sensors, wireless module, GPS device and GSM module has been presented in this chapter. The intensity of the lights is adjusted automatically according to the sunlight and the movement of vehicles. The objective of this framework is to reduce the cost and energy. This framework could be improved by adding other modules such as WiFi that gives free hotspot to the pedestrians and Emergency button meant for the public in case of medical emergencies as well as other emergencies. Other sensors like water sensor, seismic sensor, sound sensor, image sensor etc. can be added along with the post for various purposes and most importantly security purposes.

Key Terms and Definitions 6LoWPAN IPv6 over Low Power Wireless Personal Area Networks: 6LoWPAN acts as an adaptation layer to transport IPv6 packets over 802.15.4 links. GPS Global Positioning System (GPS) is a radio navigation system that allows the users in the land, sea, and air to define their exact location, velocity, and time in all weather conditions, anywhere in the world. GSM Module Global System for Mobile Communications (GSM) is a communication standard designed for the mobile devices such as mobile phones and tablets in different locations developed by the ETSI (European Telecommunications Standards Institute). Internet Gateway An Internet gateway is used to filter the data on its way to or from other networks and allows the user to gain entrance into another network. Internet of Things The Internet of Things IoT refers to the interconnection of smart IP objects such as machines, objects, people or animal which are given with

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unique identifiers (UIDs) with the ability to transmit data over a network without human intervention. IR Sensor The IR sensor is an electronic sensor which is used to detect objects/obstacles/characteristics in its field of view. Light Dependent Resistor Light Dependent Resistor (LDR), also known as photo resistor or photo conductive cell is a resistor which has a resistance that varies depending of the light intensity. Light Sensor Light sensor is more commonly called as “photoelectric devices”. It converts the light energy into electricity. Lighting Control A lighting control is simply having a control of switching on and off. A lighting control system gives us ability to control the entire lighting system to be controlled together. Microcontroller AT89S52 A microcontroller is a SoC that offers data processing and storage capabilities. Microcontrollers consists of a processor core (or cores), memory (RAM), and erasable programmable read-only memory (EPROM) for storing the custom programs that run on the microcontroller. The AT89S52 is CMOS 8-bit, low-power, high-performance microcontroller with 8 K bytes of in-system programmable Flash memory. PIR Sensor PIR stands for Passive Infra-Red. The term “passive” indicates that it does not actively participate in emitting IR signals but it rather detects the infrared radiations coming from the surrounding areas. These sensors are mostly used in PIR-based motion detectors which are used in security alarms and automatic lighting applications. Relay Relay refers to a device that provides an electrical connectivity between two or more points in response to the application of a control signal. RESTful API A RESTful API is a program interface for the applications that use HTTPRequests to GET, PUT, POST and DELETE the data. This is Representational State Transfer (REST) technology based architectural approach to send and receive data in web services development.

References 1. Wu, H., Tang, M., Huang, G.: Design of multifunctional street light control system based on AT89S52 single-chip microcomputer. In: IEEE 2nd International Conferences on Industrial Mechatronics and Automation (ICIMA), pp. 134–137 (2010) 2. Wu, Y., Shi, C., Zhang, X., Yang, W., et al.: Design of new intelligent street light control system. In: 8th IEEE International Conferences on Control and Automation (ICCA), pp. 1423–1427 (2010) 3. De Dominicis, C.M., Flammini, A., Sisinni, E.: On the development of a wireless self-localizing streetlight monitoring system. In: IEEE Sensors Applications Symposium, pp. 233–238 (2011) 4. Mohamaddoust, R., Haghighat, A.T., Sharif, M.J.M., Capanni, N.: A novel design of an automatic lighting control system for a wireless sensor network with increased sensor lifetime and reduced sensor numbers. Sensors 11(9), 8933–8952 (2011) 5. Badgaiyan, C., Sehgal, P.: Smart street lighting system. Int. J. Sci. Res. (IJSR). ISSN (Online): 2319-7064 (2013)

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6. Deepak, K., Srivatsa, B., Preethi, R., Parinitha, G., Sumana, Kumar, A.: Smart street lights. In: IEEE Texas Instruments India Educators’ Conference (2013) 7. Rajput, K.Y., Khatav, G., Pujari, M., Yadav, P.: Intelligent street lighting system using GSM. Int. J. Eng. Sci. Invent. 2(3) 8. Deo, S., Prakash, S., Patil, A.: Zigbee-based intelligent street lighting system. In: 2nd International Conference on Devices, Circuits and Systems (ICDCS) (2014) 9. Karthikeyan, M., Saravanan, V., Vijayakumar, S.: A cloud-based automatic street light monitoring system. In: International Conference on Green Computing Communication and Electrical Engineering (ICGCCEE) (2014) 10. Khandelwal, D., Thomas, B.M., Mehndiratta, K., Kumar, N.: Sensor based automatic street lighting system. IJESR Rev. 2(2) (2015) 11. Jagadeesh, Y.M., Akilesh, S., Karthik, S., Prasanth: Intelligent Street Lights. SMART Grid Technologies 12. Bhosale, S., Gaware, K., Phalke, P., Wadekar, D., Ahire, P.: IoT based dynamic control of street lights for smart city. Int. Res. J. Eng. Technol. (IRJET) 04(05) 13. Bhagavan, K., Saisaketh, S., Mounika, G., Vishal, M., Hemanth, M.: IoT based intelligent street lighting system for smart city. Int. J. Eng. Technol., 345–347 (2018) 14. Dey, N., Tamane, S. (eds.): Big Data Analytics for Smart and Connected Cities. IGI Global (2018) 15. Internet of Things and Big Data Analytics Toward Next-Generation Intelligence. Springer, Berlin (2018) 16. Poland, M.P., Nugent, C.D., Wang, H., Chen, L.: Smart home research: Projects and issues. Int. J. Ambient Comput. Intell. 1(4), 32–45 (2009) 17. Dey, N., Fong, S., Song, W., Cho, K.: Forecasting energy consumption from smart home sensor network by deep learning. In: International Conference on Smart Trends for Information Technology and Computer Communications, pp. 255–265. Springer, Singapore (2017) 18. Solanki, V.K., Katiyar, S., Bhashkar Semwal, V., Dewan, P., Venkatasen, M., Dey, N.: Advanced automated module for smart and secure city. Proc. Comput. Sci. 78(C), 367–374 (2016) 19. Sarkar, M., Banerjee, S., Badr, Y., Sangaiah, A.K.: Configuring a trusted cloud service model for smart city exploration using hybrid intelligence. Int. J. Ambient Comput. Intell. 8(3), 1–21 (2017) 20. https://www.tvilight.com 21. https://www.roadsmart.org 22. https://intelilight.eu/ 23. https://www.aaeon.com/en/ 24. https://www.itron.com 25. https://www.elkoep.com/sc-lighting 26. https://www.cyient.com 27. Kunzmann, K.R.: Smart cities: a new Padigm of urban development. Crios, 9–20 (2014). https:// doi.org/10.7373/77140

Blockchain Technology Enabled Digital Identity Management in Smart Cities Saptarshi Sinha and Chittaranjan Pradhan

Abstract With the improvement of technology and use of the emerging technologies, the evolution of Smart Cities has become smoother. In a smart city environment the automation strategy is based on the deployed IoT devices that stream big data for the betterment of the services. But while doing this, the security of the data is becoming a major concern. In order to monitor daily to daily activities of the users, they are compromising their privacy rights. The Blockchain Technology has emerged as the most secured distributed Peer to Peer Network. In this chapter, we present an approach to manage our online identities using highly secured blockchain technology. The chapter deals with privacy and soverignity of the user identities along with ensuring their security so that identities can’t be misused. On the other hand the approach ensures the transparency and control of the user’s identity. In the result analysis the chapter presents the output of the functions depicting the flow of the application. We discuss the architecture integrating blockchain and accordingly we also discuss the related challenges and future work. Keywords Blockchain · Data security · Digital identity · Ethereum · Identity management · Privacy · Smart city

1 Introduction Smart City is an urban area that uses various electronic devices and integrates the power of Information and Communication Technology to manage the assets and give services to the people [1]. It uses digital technologies in order to enhance quality and performance of urban services. Smart city applications and IoT sensors collect and generate huge amounts of data while the big data systems associate with it utilizes S. Sinha · C. Pradhan (B) School of Computer Engineering, Kalinga Institute of Industrial Technology, Bhubaneswar, India e-mail: [email protected] S. Sinha e-mail: [email protected] © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 S. C. Tamane et al. (eds.), Security and Privacy Applications for Smart City Development, Studies in Systems, Decision and Control 308, https://doi.org/10.1007/978-3-030-53149-2_7

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these data to provide information to enhance the applications services. The real time streaming of user data on one hand is ensuring the improvement in lifestyle quality of citizens while on the other side, it is bearing the potential risk of data theft, security breach and violation of data privacy. In the case of security breach over user’s data and misuse of it especially Identity, is becoming a major concern now a day [2]. We look up to centralized and highly susceptible systems to hold up our most sensitive information while expecting our data to not be used in this elaborate data economy, we don’t ever get to know when a third party server is under attack, do we have any idea about which other parties or organizations are using our information and in what ways. Scary thoughts, well how about we look upon technology get the back control that we must have over our identities. The impact we have imagined with this implementation is immense, our communities, our daily lives, our digital footprints everything is pivoted by the use of a single intangible identity. Identity is the fundamental human rights of a person as per the Article 8 of the UN’s Convention on the rights of the child [3, 4]. Identity accounts for the sovereignty of the people. In the digital identity management system, our individual identities consist of sensitive data (such as Name, Date of birth, Address, Unique ID, Passport Number, Contact Number etc.) but they are stored in centralized systems which are often prone to hacks, data theft and malicious attacks. These sensitive data are key to our very important documents in our daily life. Thus security loss of these data can lead to loss in various ways. Therefore, along with implementing smart city services and providing the benefits of a smart city to the citizens, we must ensure the security of user’s identity and important information [5]. In this chapter, we aim at solving the problem in maintaining digital identity records by use of blockchain technology that aims at giving control of one’s personal data over that particular individual. Blockchain technology is a boost in the recent time where security is a major concern. Blockchain promises to improve cyber security and maintain user privacy. Our work explores how we can use this technology in our benefit to store the identity and use it in smart city architecture. The solution proposed in this chapter aims at establishing one’s control over his/her own data removing any third party control along with maintaining security and providing the benefits equally offered by a smart city. Our chapter organization is as follows: Sect. 2 gives the description of Smart city and cyber security. The detail of Smart city and data privacy is represented in Sect. 3. Section 4 presents the application of blockchain as a measure to enhance security and protect data privacy. The existing work on digital identity management is available in Sect. 5. The proposed work is presented in Sect. 6. Result analysis is given in Sect. 7. At the end, Sect. 8 discusses the conclusion part.

2 Smart City and Cyber Security Smart cities are firmly based on IoT Devices and sensors to improve services by automating the process and decreasing operational costs. Every citizen (users) of

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the smart city and the IoT devices are seamlessly connected with one another and the services are provided by the private cloud network [6, 7]. The private clouds are maintained by the third party servers and these IoT solutions are the compromising points of cyber security breaches. Any threat can enter the Smart City infrastructure at any compromised point, thus enabling the risk to grow quickly through the cloud network and when one connected device is hijacked it leaves other devices prone to penetration leading the whole infrastructure vulnerable [8]. The centralized cloud database of the Smart City infrastructure also stores the user’s data along with the devices in the ecosystem. When a cyber security breach occurs through a device then it can easily be concluded that the user’s data is vulnerable and can easily be exposed, misused and altered. As the database is governed by a third party service so the user may be unaware of the fact that their data are breached. The user’s data are the key to physical identity of the user in the Smart City ecosystem. Thus misuse of these data will have a negative impact on the society and may slow down the digitization and growth of Smart Cities [9].

3 Smart City and Data Privacy Not only security breach but also the devices itself can lead to the breach of data privacy of the user [10]. In the cities the IoT devices are running image processing for facial recognition using street cameras to analyse the behavior of its users and delivery better services based on that. Though it is aimed at providing better services but all users may not be comfortable with the process of invading privacy [11, 12]. Again in some cities the government officials sometime track down the citizens on the basis of their daily digital world interaction and thus the citizens don’t have control over the privacy of their data [13].

4 Blockchain as a Measure to Enhance Security and Protect Data Privacy Blockchain technology can be a great solution to prevent the security threats and maintain data privacy mainly due to its underlying secured architecture. Blockchain is a decentralized database that keeps record of all the transactions in the network. The transactions that are written once in the blockchain are immutable due to the features of cryptography in the blockchain. Again the blocks of transactions that are added in the blockchain network are validated and verified by various consensus algorithms like Proof of Work (PoW), Proof of Stake (PoS), Byzantine Fault Tolerance. Thus Blockchain technology provides security, data integrity by recording valid transactions in an immutable way. Again as a distributed database blockchain offers the concept of Smart Contract so that a user can maintain its data.

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In this chapter, we apply this Blockchain technology in order to maintain Identity of the citizens in a Smart City environment. We will discuss the approach to overcome the issues of maintaining and securing user data and its privacy that arise in a traditional Smart City ecosystem using the distributed Peer to Peer Blockchain network [14].

5 Existing Work on Digital Identity Management With the advancement of Blockchain technology and the rise of demand in maintaining a secure digital identity management system several applications have come into existence in different blockchain networks [15–17].

5.1 uPort uPort is an open source Digital Identity platform built on the top of ethereum network [18]. Anybody can register their digital identity on the ethereum network. The application mainly consist of three components namely uPort Mobile Application, Smart Contract and Libraries for the developers. When a user registers in the application, the private keys are stored on the device. In case of loss of phone, the user can recover its identity based on the nomination he/she can put on some of the trustees. uPort in its application maintain two different types of Smart Contracts. One is Controller Smart Contract and other is the Proxy Smart Contract. The request is sent from the application to the Controller Contract through the proxy contract. The user data are stored in IPFS. Other than this, uPort provides a developer library in order to integrate the application with the developer’s project.

5.2 ShoCard ShoCard is a mobile identity platform using bio-metrics built on the top of Bitcoin Network [19]. The main motive of the application is to maintain uniform identification across different regions. The application is built combining the power of blockchain technology, mobile applications and bio-metrics. Using a blend of blockchain-based data and facial recognition techniques, ShoCard both streamlines how airlines verify passenger identities as well as facilitating real-time data flows at the airport.

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5.3 Sovrin Sovrin is a consortium blockchain to manage identities online [18]. Sovrin is a permissioned ledger with a known set of validator nodes, known as stewards. It is designed to bring the trust, personal control and use of analog Id’s in the internet. The architecture of Sovrin application is divided into three layers namely Sovrin ledger, Sovrin agents and Sovrin clients. In addition to the above features of the existing application, we aim at providing a system for file upload and private notification system using the whisper protocol in the ethereum blockchain. The user can upload his/her Passport, Aadhar and other sensitive files that can be connected to the user account. The application will upload the files to the IPFS [20] and its hash will be stored on the blockchain through the ethereum smart contract along with the user details. The proposed application is designed to act as an all in one solution for controlling and managing Digital and Analog identity of the user.

6 Proposed Work Our proposed system is divided broadly into three modules; Register module, View module and Update module. The smart contract that runs on the ethereum is written in Solidity and the smart contract is tested in Remix platform [21, 22]. The overall flowchart of our proposed solution is shown in Fig. 1.

6.1 Register Module When a new user visits this application, he/she must register to get the benefits of the platform. This module is designed for the registration of new users. In order to register, the user must have an ethereum wallet with an account address. The unique account address will be the id of the user in this system. Other than this the user has to provide his/her details (like name, age, date of birth, home address details etc.). The smart contract function in this module is responsible for creating an account for the new user. The detail of this module is shown in Fig. 2. The code snippet of this module is shown in Fig. 3.

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Fig. 1 Proposed architecture

Fig. 2 Register module architecture

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Fig. 3 Register module code snippet

6.2 View Module This module is designed for viewing the details of a certain user. The details can be the user’s own details or the details of any other user. View Your Own Details When the logged-in User is trying to view its own user details, all the details fetch from the blockchain are shown.

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Fig. 4 View module architecture

View Details of Other Users Here we are considering two users. This case arrives when user1 wants to verify user2. In that situation the user1 would like to view the details of user2. Whenever this situation occurs, a notification will be send to user2 regarding accept or deny. If the user2 accepts the permission then only the user1 can view the details of user2. This module gives the transparency to a user who is viewing his/her details and guarantees that the user data are not misused. This feature not only removes the abstraction of user data usage in a centralized third party system but also ensures secure management of your identity. The detail of this module is shown in Fig. 4. The code snippet of this module is shown in Fig. 5.

6.3 Update Module When a user wants to update its own details, the update module will handle that. The user id will be available from the logged in wallet address. And the other parameters that are to be sent in this module are the fields that the user wants to update (like name, age, dob etc.). The functions in this module are payable i.e. some ether has to be spent while calling this function. The sensitive files that are considered as Id’s of the user can also be uploaded and the files will be linked to the account, all in one place. The files will be stored in IPFS (Inter Planetary File System) and their returned hash from the IPFS will be stored on the blockchain. This module is solely responsible for the data security that is the user data cannot be tampered or modified by a second person or a third party system. The underlying security is maintained by highly consensus non tamperable nature of blockchain.

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Fig. 5 View module code snippet

The detail of this module is shown in Fig. 6. The code snippet of this module is shown in Fig. 7.

Fig. 6 Update module architecture

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Fig. 7 Update module code snippet

7 Result Analysis The wallet address is the identification of the user. Any operation performed by the user is identified by the unique wallet address. To register one’s wallet address in our application, the user invokes register module. Here two wallet address are considered 1. 0x583031D1113aD414F02576BD6afaBfb302140225 which consist of 100 ethers and 2. 0xdD870fA1b7C4700F2BD7f44238821C26f7392148 that has 99.99999 ethers in it. Both address are not registered in the system. They are only the wallet address created in the ethereum blockchain ecosystem. On invoking the register module the following parameters are passed as input: • • • •

Name: Name of the user trying to register Age: Age of the user Dob: Date of birth of the user File1: Hash of any file uploaded to the system which is stored in IPFS providing identity (eg. Passport). During registration it is set to 0 • File2: Same as File1 but may be any different file. In this way two files which are the proofs of your identity can be linked in a single system. First time when wallet address 0x583031D1113aD414F02576BD6afaBfb302140225 calls the register function then it is successfully registered showing the message “Successfully registered new user” and data are stored in the Smart Contract. Since

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this address is updating the variable of the smart contract so it has to pay some ether. Due to this the balance of the wallet is changed to 99.999999999999759609 ether. Second time if we invoke the register module with the wallet address 0x583031D1113aD414F02576BD6afaBfb302140225 then an error is thrown showing the message “User is already registered”. If we invoke the register module with some different wallet address which is not registered with our application and the input parameters are passed correctly then the address is successfully registered and data are stored in the Smart Contract. In Table 1, the analysis is shown. Figure 8 shows the result of register module implementation. In order to view the details of the user the wallet address must be registered with our application and we consider the two address that were used to register. When the user wants to see his/her own details the view your own details module is called and the wallet address is sent as parameter by default. In order to view the details of any other registered user the function is called and the address of the other user is passed as the parameter. However the successful invoke of the function depends on the agreement of user2. Since the view module does not update the state of the Smart Contract so no ether has to be paid while calling the methods of the view module. In Tables 2 and 3, the analysis of view modules are shown. Figures 9 and 10 show the result of view module implementation. Update module can only be invoked by the registered users. Here we are considering the wallet address 0x583031D1113aD414F02576BD6afaBfb302140225 and the following parameters are passed. • • • •

Name: Updated name of the user Age: Updated age of the user Dob: Updated date of birth of the user File1: Hash of any file uploaded to the system which is stored in IPFS proving identity (eg. Passport) • File2: Same as File1 but may be any different file. In this way two files which are the proofs of your identity can be linked in a single system. On successful update the following message is shown: “User successfully updated”. Since the function updates state of the smart contract so the user has to pay some ether from its wallet. Due to this the balance of the wallet is reduced to 99.999999999999682938ether. If the address is not registered with our application the following error message is shown: “User is not registered”. In Table 4, the analysis of update module is shown. Figure 11 shows the result of update module implementation.

8 Conclusion Blockchain technology as a Peer to Peer Network system has attained a considerable amount of fame while dealing with security. The approach of managing one’s identity

Account address

0x583031D1113aD414F 02576BD6afaBfb302140225

0x583031D1113aD414F 02576BD6afaBfb302140225

0xdD870fA1b7C4700F2 BD7f44238821C26f7392148

Sl. no.

1

2

3

Table 1 Register module result analysis

Initial fund (ether)

99.999999999997497919

99.999999999999759609

100.00

Input parameters

{“string_name”: “William”, “string_age”: “20”, “string _dob”: “1/1/2000”, “string_file1”: “0000000000000000000000000000000”, “string_file2”: “0000000000000000000000000000000”}

{“string_name”: “John Doe”, “string _age”: “40”, “string_dob”: “12/1/1980”, “string_file1”: “0000000000000000000000000000000”, “string_file2”: “0000000000000000000000000000000”}

{“string _name”: “John Doe”, “string_age”: “40”, “string_dob”: “12/1/1980”, “string_file1”: “0000000000000000000000000000000”, “string_file2”: “000000000000000000”}

Final fund (ether)

99.999999999997257656

99.999999999999759609

99.999999999999759609

Output

{“string: Successfully registered new user”}

{“string: User is already registered”}

{“string: Successfully registered new user”}

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Fig. 8 Register module implementation

using blockchain technology is more secure than our traditional centralized third party system. In this approach, all the identities are stored in a distributed network that can only be accessed and modified by the identity owner. Thus a user is confirmed that his/her identity is not misused without his/her consent. The problem of Cyber Security and Data privacy that has been stated earlier in this chapter can be overcome by the approach using Blockchain technology. With the assurance of data privacy and security, the development of the Smart City projects will become much smoother and hassle free. Again securing the digital Identity in a secured network will help to verify users and secure the IOT Devices that are being used all over a Smart City Project. The future works related to this chapter are as follows: • Create an web application based on the solution discussed above to the problem of digital identity management • Create an android application.

Account address

0x583031D1113aD414F02576BD6afaBfb302140225

0xdD870fA1b7C4700F2BD7f44238821C26f7392148

Sl. no.

1

2

Table 2 View your details module result analysis Initial fund (ether)

99.999999999997257656

99.999999999999759609

Input parameters

NIL

NIL

Final fund (ether)

99.999999999997257656

99.999999999999759609

Output

0: address: 0xdD870fA1b7C4700F2BD7f44238821C26f7392148, 1: string: William, 2: string: 20, 3: string: 1/1/2000, 4: string: C063E0FCDF7F94063175CE8DFBBA1DE3031DEC83 E61B2F6A995A520F3D6451DF, 5: string: 5AA92D9F99EF55EB67F36397205FC27E0F517142C29 FA88A3D37378706E6C5BD

0: address: 0xdD870fA1b7C4700F2BD7f44238821C26f7392148, 1: string: John Doe, 2: string: 40, 3: string: 12/1/1980, 4: string: 289EF5309CE8ABB01056E966EE9F7C208F5789 CBB61773CF3D47DAF5A8A238E, 5: string: 16051F0C89D6B399CD0A69E23B7C26FB55F816 09717EAD1AE0FA179CF6B2BEFB

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Account address

0x583031D1113aD414F02576 BD6afaBfb302140225

0xdD870fA1b7C4700F2BD7 f44238821C26f7392148

Sl. no.

1

2

99.999999999997257656

99.999999999999759609

Initial fund (ether)

Table 3 View other’s details module result analysis

0x583031D1113aD414F02576BD6 afaBfb302140225

0xdD870fA1b7C4700F2BD7f442 38821C26f7392148

Input parameters

99.999999999997257656

99.999999999999759609

Final fund (ether)

0: address: 0xdD870fA1b7C4700F2 BD7f44238821C26f7392148, 1: string: John Doe, 2: string: 40, 3: string: 12/1/1980, 4: string: 0000000000000000 000000000000000, 5: string: 0000000000000000 000000000000000

0: address: 0xdD870fA1b7C4700F2 BD7f44238821C26f7392148, 1: string: William, 2: string: 20, 3: string: 1/1/2000, 4: string: 000000000000000 0000000000000000, 5: string: 0000000000000000 000000000000000

Output

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Fig. 9 View your details module implementation

Fig. 10 View other’s details module implementation

The main issue that can be arrived while implementing a blockchain network in a Smart City environment is computation power and to determine whether the city is ready to deliver such amount of energy. As a growing blockchain network the blockchain nodes should require higher computation power. The future research can be carried on in the direction of minimizing the computation power of the Blockchain nodes in a Smart City environment.

Account address

0x583031D1113aD414F 02576BD6afaBfb302140225

0xD183f015dB6f17087C 819ea8BD84a26cCC39dcB8

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100

99.999999999999759609

Initial fund (ether)

Table 4 Update module result analysis

{“string_name”: “Percy”, “string_age”: “29”, “string_dob”: “1/1/1990”, “string_file1”: “E289EF5309CE8ABB01056E966EE9F7C208 F5789CBB61773CF3D47DAF5A8A238E”, “string_file2”: “16051F0C89D6B399CD0A69E23B7C26FB55 F81609717EAD1AE0FA179CF6B2BEFB”}

{“string_name”: “Charlie”, “string _age”: “29”, “string_dob”: “1/1/1990”, “string_file1”: “E289EF5309CE8ABB01056E966EE9F7C208 F5789CBB61773CF3D47DAF5A8A238E”, “string_file2”: “16051F0C89D6B399CD0A69E23B7C26FB5 5F81609717EAD1AE0FA179CF6B2BEFB”}

Input parameters

100

99.999999999999682938

Final fund (ether)

{“string: User is not registered”}

{“string: User successfully updated”}

Output

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Fig. 11 Update module implementation

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5. Wilson, S., Moustafa, N., Sitnikova, E.: A digital identity stack to improve privacy in the IoT. In: World Forum on Internet of Things. IEEE (2018) 6. Dey, N., Fong, S., Song, W., Cho, K.: Forecasting energy consumption from smart home sensor network by deep learning. In: International Conference on Smart Trends for Information Technology and Computer Communications, pp. 255–265. Springer (2018) 7. Fong, S., Li, J., Song, W., Tian, Y., Wong, R.K., Dey, N.: Predicting unusual energy consumption events from smart home sensor network by data stream mining with misclassified recall. J. Ambient Intell. Hum. Comput. Springer 9, 1197–1221 (2018) (Springer) 8. Chow, S.S.M., He, Y.J., Hui, L.C.K., Yiu, S.M.: SPICE—simple privacy-preserving identitymanagement for cloud environment. In: International Conference on Applied Cryptography and Network Security, pp. 526–543. Springer (2012) 9. Mora, O.B., Rivera, R., Larios, V.M., Beltran-Ramirez, R., Maciel, R., Ochoa, A.: A use case in cybersecurity based in Blockchain to deal with the security and privacy of citizens and smart cities cyber infrastructures. In: International Conference on Smart Cities, pp. 1–4. IEEE (2018) 10. Dey, N., Tamane, S.: Big Data Analytics for Smart and Connected Cities. IGI Global (2018). ISBN 9781522562078 11. Poland, M.P., Nugent, C.D., Wang, H., Chen, L.: Smart home research: projects and issues. Int. J. Ambient Comput. Intell. IGI Glob. 1(4), 1–14 (2009) 12. Solanki, V.K., Katiyar, S., Semwal, V.B., Dewan, P., Venkatasen, M., Dey, N.: Advanced automated module for smart and secure city. Proc. Comput. Sci. Elsevier 78, 367–374 (2016) (Elsevier) 13. Birrell, E., Schneider, F.B.: Federated Identity management systems: a privacy-based characterization. IEEE Comput. Reliab. Soc., 36–48 (2013) 14. Peng, C., Akca, S., Rajan, A.: SIF: A Framework for Solidity Contract Instrumentation and Analysis, pp. 1–8 (2019) 15. Haddouti, S.E., El Kettani, E.-C.: Analysis of identity management systems using Blockchain technology. In: International Conference on Advanced Communication Technologies and Networking, pp. 1–7 (2019) 16. Camp, L.J.: Digital identity. IEEE Technol. Soc. Mag., 34–41 (2004) 17. Bernabe, J.B., Hernandez-Ramos, J.L., Gomez, A.F.S.: Holistic Privacy-Preserving Identity Management System for the Internet of Things. Mobile Information Systems, Hindawi, pp. 1– 20 (2017) 18. Dunphy, P., Petitcolas, F.A.P.: A First Look at Identity Management Schemes on the Blockchain. IEEE Secur. Priv. 16(4), 20–29 (2018) 19. Roos, J.: Identity Management on the Blockchain. Netw. Arch. Serv., 105–112 (2018). 20. Kumar, R., Tripathi, R.: Implementation of distributed file storage and access framework using IPFS and Blockchain. In: International Conference on Image Information Processing, pp. 246– 251 (2019) 21. Gupta, B.C.: Analysis of Ethereum Smart Contracts—A Security Perspective. Indian Institute of Technology Kanpur, pp. 1–59 (2019) 22. Sarkar, M., Banerjee, S., Badr, Y., Sangaiah, A.K.: Configuring a trusted cloud service model for smart city exploration using hybrid intelligence. Int. J. Ambient Comput. Intell. IGI Global 8(3), 1–21 (2017)

Solar Energy for Sustainable Development of a Smart City Samir Telang, Arvind Chel, Renuka Nafdey, and Geetanjali Kaushik

Abstract The Government of India has announced a new plan to build a mega solar project for meeting the increasing growth in energy. It is hoped to achieve renewable energy capacity of 175 GW by 2021. Small sized solar parks can be integral as a component of Smart Cities for being able to fulfil any additional requirements. Apart from rooftop solar, the solar energy can be utilized in other forms like solar pumps, solar street lighting, solar traffic signals, solar water heaters, solar concentrators based domestic cooking. There has been unparalleled transformation of living from rural to majorly urban living in India over the last two decades. The smart cities have significant developments planned within the infrastructure services and smart solutions in various aspects like toll collection, parking, traffic management etc. The power sector assures solar and smart metering electric power satisfying at least 10% of power required by the Indian smart cities. Keywords Smart city · Sustainable development · Solar energy · Smart solutions

S. Telang Research Center, Jawaharlal Nehru Engineering College, MGM University, N-6, CIDCO, Aurangabad, Maharashtra 431003, India e-mail: [email protected] A. Chel (B) Department of Mechanical Engineering, MGM’s Jawaharlal Nehru Engineering College, Aurangabad, Maharashtra 431003, India e-mail: [email protected] R. Nafdey Department of Physics, Shri Ramdeobaba College of Engineering and Management, Nagpur, Maharashtra 440013, India e-mail: [email protected] G. Kaushik Department of Civil Engineering, Hi Tech Institute of Technology, Waluj, Aurangabad, Maharashtra 431136, India e-mail: [email protected] © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 S. C. Tamane et al. (eds.), Security and Privacy Applications for Smart City Development, Studies in Systems, Decision and Control 308, https://doi.org/10.1007/978-3-030-53149-2_8

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1 Introduction to Solar Energy Application in India India promotes the utilization of renewable resources of energy all the way through different programs. Development of smart cities is associated with higher energy usage and increased requirement for the sustainable solutions in the energy sector. It has been mentioned that 10–12% of energy requirements of the smart cities will have to be met by solar energy. Almost 80% of the buildings would be transformed as energy efficient and green as per Green Building norms. However, some obstacles in the path of smooth execution of projects are the absence of manufacturing facilities for silicon wafers, land clearance and management of grid. The efficiency of solar generation and smart storage solutions needs to be further improved to better achieve these objectives. Government, state and local policies such as net metering, smart microinverters, intelligent solar system management are crucial for ensuring the success of solar rooftop. In this background it is of significance to discuss solar energy utilization for a smart city in this chapter. India promotes the utilization of solar energy all the way through the NSM (National Solar Mission) initiated after 2009. Our nation is unique world over in having a specialized ministry for the expansion of renewable energy, known as the MNRE (Ministry of New and Renewable Energy). Development of smart cities is associated with higher energy usage and increased requirement for the sustainable solutions in the energy sector [1, 2]. The Government of India has launched a new plan to build a mega solar project for meeting the growth in energy demand. The plan is to achieve by 2021 the renewable energy capability of 175 GW. Presently, India’s solar grid has a cumulative capacity of 12.5 GW [3]. Within three years the combined renewable capacity including wind, solar, small hydro and bio-energy has observed a boost from 35 to 57 GW. It has been mentioned that 10–12% of energy requirements of the smart cities will have to be met by solar energy. Almost 80% of the buildings would be transformed as energy efficient and green as per Green Building norms. In the past three years government has proposed various schemes such as solar PV plants on banks and tops of canals, solar roof tops, solar pumps etc. A solar park is an area marked for intensive development of solar power projects [4, 5] which promote developers through the provision of land, migration and lines for transmission, roads for access, availability of irrigation etc. Central government is setting up for ensuring the quick inclusion of solar energy and the other sources of renewable energy. This would include updation of transmission capacity and linking the solar parks with the nationwide grid. An estimated central financial assistance of Rs. 200 crores has been finalized to set up about 50 solar parks by 2020–2022. However, some obstacles in the path of smooth execution of projects are the absence of manufacturing facilities for silicon wafers, land clearance and management of grid. Another issue from the utilization of renewable energy used to power smart cities is the potential decline in the production of the solar arrays during the

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lack of sunlight. For the mitigation of the effects of the cloudy conditions, tech giant IBM plans to accurately predict cloud cover [6, 7]. It would ensure efficient planning of electricity loads. In a similar manner utilization of non-conventional energy sources like natural gas require proper infrastructure for their distribution. In addition, appropriate implementation of financial policies and regulatory functions are required. According to an Amazon India report, awareness among citizens has increased in the payment of sustainable products such as solar water heaters, solar street lights, smart meters etc. Usage of solar lamps and lanterns has gained significantly within the tier-II and tier-III Indian cities. Innovative concepts of organic gardening, hydroponics, home composting, drip irrigation, air purifying plants etc. all have generated awareness within patrons across India. Indian Scientists and researchers have consequently formulated a ‘solar tree’, that is a structure similar to a tree. These branches are fitted with adjustable solar panels at various levels, which charge during daytime and turn on the LED lights automatically after it becomes dark [8]. The main benefit of this product is that for building a solar park 400 m2 of land is required while it needs only about 4 square feet of land. In addition, the solar tree can potentially illuminate five homes and can be used in street-lighting, systems for industrial power supply and within the forests.

2 Necessity of the Solar Energy for Sustainable Development of Smart City Small sized solar parks can be integrated as component of smart cities such that additional requirements can be satisfied. Apart from rooftop solar, solar energy such as solar water heaters, solar street lighting, solar traffic signals, solar pumps, solar concentrators based cooking can be used in other forms. India has been witnessing an unmatched change from rural to mostly urban life in the last three decades. It is expected that smart cities will include a large number of infrastructure services and smart solutions. Carefully, elements that form part of a smart city have some power supply [9], with at least 10% of the energy required for a smart city that comes from solar and smart metering. Renewable energy technologies will contribute greatly in achieving the objectives of the Smart Cities Mission to make them a zero-polluting and self-sustaining city. Renewable energy like solar energy contributes a lot to it. Rooftop Solar Energy will make smart cities’ homes self-sufficient in their energy needs. Solar energy is also zero polluting energy. Effective and efficient use of available roofs with pure metering facilities can feed additional generation to the grid which will surely serve the basic mission of self-sufficiency in green energy needs. The efficiency of solar generation and smart storage solutions needs to be further improved to better achieve these objectives. In addition, other renewable energy technologies that have to contribute more to this mission are waste-to-energy. The

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solid waste produced can be converted into energy and other bio-products that will make these smart cities self-sufficient in their energy and bio-fertilizers requirements and also remove zero waste from these homes [10, 11]. Sewage treatment plants with biogas and electricity generation should be in the plan for smart cities. Promoting and planning green buildings in smart cities with integrated renewable energy and energy conservation systems can save about 30– 40% of the traditional energy used in buildings. There is a need to promote energy efficient green buildings over solar passive designs in solar cities. It has been made mandatory that almost 10% of energy requirement of smart cities will be derived from solar energy. In addition, it is proposed that 80% of the buildings must be power efficient, green buildings. Globally, solar energy has been one of the promising solutions as green fuel for boosting the increasing energy requirements. Solar applications in the form of solar rooftops, solar heaters, solar street lights, and solar traffic lights etc. that sprint on solar energy would ensure a clean and green environment within these smart cities. Solar energy will play a major role in developing a smart city. The key benefits from the application of this energy are: 1. Renewable resources: Solar is a renewable resource of energy because it is capable of producing power till the sun is available [12]. Also, it is an inexhaustible resource so the energy can be utilized by installing solar panels which can reduce our dependence over the non-conventional sources of energy. 2. Eco-friendly: as a renewable resource of energy it is an alternate to fossil fuels since it is clean, non-polluting, and stable. Solar energy is not associated with the emissions of harmful gases such as the carbon dioxide, nitrogen dioxide or sulphur oxide. Hence, the adverse impacts on the environment are few. As the energy is generated from the sun; so, there is no requirement for the transport of radioactive waste to fuel or the storage space. 3. Condensed electricity bills: Solar energy, interestingly, reduces utility bills. By installing solar panels in homes, electricity prices are reduced. It can also be utilized for purposes similar to heating water and space heating in homes. This can save up to 20% in energy expenditure. 4. Ease of maintenance: The expenses in installing a solar panel are high, but once it is undertaken the benefits would accrue for years with minimum protection [9]. At will, panels can be attached forever, which will not require too much semantics. These panels are silent and release no toxins. 5. Solar Panel Installation: is done without difficulty as these do not need any wires, or power sources. Since the panels are mainly installed on roofs there is no need for additional space for them. 6. Remote locations: Solar energy may be generated within even the most remote locations in the region, meaning these might be installed in sites without access to grid power. Therefore, solar would provide access to power even in the farthest areas of India. Clearly with the numerous benefits of solar energy, it can be rightly said that though the smart cities would lay the foundation for a new India, the utilization of solar energy in these cities would be instrumental in the creation of a new India.

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3 Connectivity and Structure of the Solar Energy in Smart Cities It is of importance to first understand the basics and the principles of energy conversion and management, only then insights can be developed for integrating these concepts within the smart cities [5, 13]. Energy management is referred to as the discipline to plan, direct, control the supply and consumption of energy by minimizing energy costs and pollution through the efficient use of energy to maximize productivity and comfort. In simple words, energy management concerns with saving energy. In the terms of savings of energy, energy management necessitates monitoring, regulating and conserving energy [14]. It includes optimized energy use, managing energy resources and focusing on energy efficiency. With the rapid expansion of urban areas in the cities a challenging task is to manage the energy footprint. As the existing cities develop and there is transition to smart cities, managing energy is an important part of this urban transformation. A smart city as an urban centre optimizes resources for providing a high quality of life for its residents. It is expected that the smart cities by being more autonomous would manage their energy needs more effectively by keeping in mind the resources and needs of various stakeholders at the local level. In this context, SEM attempts to understand energy management like a basic unit for the smart cities. SEM is briefly defined as a constituent of smart city development which acts as a place for sustainable, self-sufficient and resilient energy systems thereby ensuring energy access to all with key attributes of affordability as well as sustainability. Conservation of energy, energy efficiency and the optimized integration of local sources of renewable energy is aimed. Adequacy of energy services through the medium is ensured. It is described by combination of technologies with ICT (Information Communication Technologies) which allow the incorporation of several domains and allow the cooperation of varied stakeholders while ascertaining the sustainability of the measures. Figure 2 defines SEM by including all of its dimensions. SEM largely involves the integration of technology along with the energy systems, enables policies, formulation of strategies, allows institutional changes, and enhances awareness through organizing programs on training as well as capacity building, energy audits, measures on energy conservation and so on.

3.1 Solar Rooftop Panels: Advantages, Costs and Smart Policies There is not a single account of rooftop solar, which is economical for residence owners, firm owners and the communities. The transition towards clean, inexpensive and reliable power in USA is observed in the rapid propagation of the solar panels on rooftops of most of the households as well as the businesses. During the period

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between 2009 and 2015 the residential, solar rooftop showed growth greater than 50–55% annually, on an average. Each state in USA is endowed with sufficient solar energy to enable solar as an appealing alternative. A 5 KW solar PV (photovoltaic) plant can produce power equivalent to two-thirds of energy usage of a typical house. Individuals and the organizations are not just involved within the environmental expenses of solar power, but also for their capability for generating their own power as well as the decided and competitive prices of electricity.

3.2 Economics of Solar Rooftop Solar rooftop occasionally comes out to be more economical for house owners, corporate and even communities. Declines in the cost of technology, easy finance options and a expanding network of solar startup firms and the financial agencies has been responsible in driving down the prices for solar home systems in USA between 2011 and 2015. Additionally, a solar investment tax reimburses 30% of the cost price and with state and other local tax rebates within the leading states may further reduce the total costs resulting in greater price declines. The advances in technology and economies of scale have resulted in a decrease in the prices of solar rooftop PV systems. On the global scale manufacture of solar panel (for solar roofing and the other markets) grew from 24,000 MW during 2010 to almost 40,000 MW in the year 2014. The price of solar PV within USA is also impacted by market conditions world over, particularly the presence of lower priced Chinese products. Solar PV prices within USA have also profited from the “soft” reductions in the cost, such as which are related to the sales, inspections, permits, power grid connections and earning margins of retailers as well as the installers. These declines are owing to the large scale and presence of solar system installations and the dedicated efforts led by community for streamlining the permit processes and for pooling in the local homeowners.

3.3 Proprietorship Options Solar power also has been successful in creating numerous ownership structures. Several household owners and firms have taken benefit of the third-party ownership alternatives. Solar roof top customers utilize solar leases and or agreements for the purchase of power while they end up paying very little or nothing for these systems and also receive power in the long term at very attractive rates. The responsibilities for maintaining these systems lay with the project developers which may include private firms, corporate or power utilities. As per an estimate during 2015 third parties owned greater than 75% of these innovative solar residential systems.

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Solar roof top is leaving the conventional stream. Drop in the prices and novel financing arrangements have ensured that the solar rooftop systems are available more widely and also that the customers come from diverse financial backgrounds. Further some states such as California have designed specific policies for supporting their low income groups or disadvantaged populations [15]. Firms have installed solar rooftop for not only improving their environmental profiles but also for reducing their operating expenses. By the year 2022, Indian firms installed capacity of over 9000 MW of solar rooftop over the country. These firms include Adani, Tata, Kohl, Wal-Mart, Apple and Costco along with several malls, departmental stores, manufacturers of consumer goods and car firms.

3.4 Employment and Solar Power Solar power which includes solar rooftop, has been a strongly driving the economic growth. In the previous year the solar industry in US provided employment to more than 190,000 people, with a massive job growth rate which has enhanced the entire economy growth. Since 2018, US is home to over 6000 solar firms, distributed within all 50 states and making investments of around $15 billion annually within the economy. Since solar rooftops can also be installed within the smaller cities and towns, in addition to the remote locations, it provides job prospects for the local employees. Under the mandate of Skill Development of the GoI, job training programs for training the local youth in installing solar have been initiated by local colleges, NGOs and other organizations over the country [15].

3.5 Environmental Concerns with Rooftop Solar In contrast to the conventional fossil fuels which even today meet the major component of our power supply to India, solar PV panels generate power with no energy input; do not cause air pollution, do not generate smoke or ash or any other waste products. While the manufacture of solar panels similar to other energy equipment leads to emissions, PV power generation by itself: • Does not generate GHGs which contribute towards climate change • Unlike Coal does not generate emissions of any harmful gases or hazardous wastes that are associated with the generation of power, such as mercury, lead and arsenic. • Unlike nuclear power does generate any form of hazardous long-term waste or result in significant environmental risks • Avoids environmental risks such as water pollution caused during natural gas, extraction • Further, there is no water in the PV power generation on the roof. Solar is in complete contrast to most of the power plants generating electricity with the use

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of steam. These forms of renewable power include coal-based power, nuclear, natural gas plants and few other facilities of renewable energy, that are dependent on water as a coolant. This dependence may lead to problems at which time cold water gets either too little or extremely hot. Solar PV systems, in contrast, do not need water for generation of electricity. • Mostly, there is no impact on wildlife other than solar panels as these are usually installed within the built environments. Solar PV panels include materials which have to be handled carefully during the manufacturing of panels and their disassembling once their useful lives are over. The production of solar panels alongside the computer chips, entails a wide range of unsafe materials such as hydrochloric acid, nitric acid, sulphuric acid and even hydrogen fluoride. The non-silica solar cells, which include cadmium telluride, gallium arsenide and copper-indiumgallium-desalanide, usually comprise of greater hazardous materials as compared to those present within conventional silicon cells. • Recycling at the end of life is a perspective to keep solar panel materials away from landfills. PV manufacturers from Europe and even few from India have initiated field wide programs for it.

3.6 Smart Policies for Growth of Rooftop Solar Govt, state and local policies are crucial for ensuring the success of solar rooftop and those systems which provide clean power. Effective policies which are being used presently include: • Net metering: is power billing mechanism which enables customers generating power through renewable means to use that power anytime irrespective of when it gets generated. • Feed-in tariffs: are fixed prices for power which are generally paid to solar energy producers for every unit of energy they generate and feed into the main electricity grid. In some parts of USA these tariffs are available. Similar tariffs have driven the development of renewable energy within Europe. • Price of solar-tariff: Owners of solar system may be remunerated based on the designed value of total paybacks given by the system [9]. These solar rates indicate not just the advantages of provision of power, but the significance of putting power within the grid, reduction in fossil fuel usage and other environmental benefits. • Solar carving-exterior: Few states focus on small scale solar as a component of their major efforts for increasing investment within the renewable energy sector, mandating utilities for using solar energy and/or dispersed generation. Such forms of “carving-outs” offer additional revenue for the owners of solar systems. • Tax incentives and subsidies: Most of the states provide tax incentives to households and firms for the purchase of renewable energy, these incentives are given over the federal tax credit of 30%. Few local governments provide rebates in property tax. Urban Local Bodies with PACE (property-assessed clean energy)

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schemes offer finance for acquiring solar systems over rooftops of homes or businesses then these schemes recover the expenses via property taxes over a period of time. In several jurisdictions, innovative policies imply that the solar on the roof is not just limited to homeowners with roofs that are sunken. Residents on rent, those with shaded roofs, owners of condominium may be unable to utilize solar PV on their roofs, however, “shared solar” solutions expand the prospects for all the users of power. The solutions in these cases include virtual net metering, that enables houses to use the benefits of solar power generation which is not directly linked with their power meters. These policies enable consumers within multi-storey buildings to utilize solar power from one-meter present over the building. Power consumers can also subscribe to solar power generated from a mega off the site solar system.

4 Significance of the Proposed Solar Energy System for Smart City Recent reports have shown that Diu will be 100% powered by solar and it will be India’s first union territory to do so. Within just three years, solar power capacity of 13 MW was installed which was almost twice of the peak power demand in the region. This development is very useful for the 22,000 residents of this region who are reaping the economic benefits of this progress. It is also expected that with this achievement they will be considered as suitable for India’s Smart Cities Mission. India’s Urban Renewal Project is selecting 100 cities across India to redevelop its entire urban ecosystem, leading to improvements in institutional, physical, social and economic infrastructure. An integral part of this initiative is the opportunity to change and change the way India operates its cities. Therefore, the development and deployment of renewable energy capacity in India’s urban cities is of critical importance.

4.1 Solar Power and India’s Smart Cities Mission In smart cities for managing and optimizing the infrastructure consistent power supply will be needed for the provision of various ICT (information and communication technology) and IoT (Internet of Things) solutions. The major aim of smart cities is to improve the quality of life for its urban residents through the provision of services with the use of IT and it would be incomplete without adequate focus on renewable sources of energy. The most accessible form of solar power across India, more than 300 sunny days every year. The potential of solar power generation, particularly India’s favourable

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geographical location, is incredible. For comparison, California—1/8th the size of India—consumes about 3 quadrillion BTUs annually, and netted 49.95% of this demand through solar power in the early part of March this year. California is geographically less suited for the production of solar energy than India, due to India’s favourable latitudes that forcefully pull the Tropic of Cancer. At the recent inauguration of the ISA, Prime Minister Narendra Modi has set a target towards achieving 100 GW of solar energy from a total power requirement of 175 GW that would be generated from renewable energy sources. In India rapidly growing population creates huge demand for electricity and there is a significant proportion waiting for consistent access to energy. There is need to formulate a strategy for efficient power generation in efficient and more liveable cities.

4.2 The Sunny Future of India’s Smart Cities and Solar Power As per guidelines of the Government of India regarding the smart cities at least 10% of the city’s power demands must be satisfied by solar energy. With the development of Indian smart cities, energy will be required therefore; solar power capacity will also be needed to develop. Development of this new urban landscape will be driven by solar energy. As the govt. sets and manages to maintain its guidelines with the support of private and public players it is hoped that other Indian smart cities will all follow the example of Diu. After the twenty-first Conference of Parties (COP21) held in Paris in 2015, it has a nationally determined contribution (INDC) to the United Nations Framework Convention (UNFCCC); India declared a voluntary target of reducing the emission intensity of its GDP by 33–35% at the 2005 level by 2030, despite having no binding mitigation obligation as per the Convention. To achieve this goal, a series of policy measures were introduced. The National Solar Mission (NSM) has achieved the target of increasing the installed solar capacity from 20 to 100 GW by the year 2022. The goal is to complete 40 GW rooftop solar projects and 60 GW and medium level grid-connected projects. In addition, a list of 60 more Ministry of Solar Energy (MNRE), to reduce greenhouse gas (GHG) emissions and motivate the country to ‘energy sufficiency’, was released. India’s ‘Solar Cities Development’ program designed to encourage/encourage urban local bodies to prepare roadmap to guide their cities in creation of ‘renewable energy cities’ or ‘solar cities’. With the main objective of promoting cities which offer ‘smart’ solutions based infrastructure facilities along with a sustainable environment as well as a wholesome quality of life to their residents, Government of India initiated the Smart Cities Mission in the year 2015. Under this scheme, the MoUD (Ministry of Urban Development) selected a total of 100 smart cities located in different states of the country. As per the Smart City guiding principles given by the Government of India, solar energy must satisfy at least 10% of the total city’s energy needs. Surat

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city, in the state of Gujarat, is one of the few cities in India to have achieved the coveted position in both listed lists of model Indian cities issued by MNRE and MOUD. As a result, Surat Municipal Corporation (SMC) is actively taking steps to meet expectations in the field of renewable energy. Surat Municipal Corporation is a local self-governing body which came into existence under the Bombay Provincial Municipal Act, 1949. It performs all the mandatory functions and discretionary functions assigned by the BPMC Act, 1949. Gujarat lies in the success story of Surat city. A firm and systematic plan to achieve the Government’s strong will for development and the goals and expectations related to solar energy of Surat city. Initially, SMC signed a MoU with the Solar Energy Corporation (SECI) to facilitate the implementation of the solar rooftop scheme in Surat city. SMC planned its roadmap for success with various stakeholders such as DISCOMs, state nodal agencies, chief electrical inspectors, project developers, banks, etc. In addition, SMC sought the project management consulting services of The Energy and Resources Institute (TERI), New Delhi, to carry out feasibility studies and monitoring for the implementation of various solar and energy efficiency projects in the city. As estimated by TERI, a ceiling capacity of 11,924 MW is distributed among various smart cities in the country; the city has about 418 MW (~3.5%).

5 Smart Solutions by Integrating Innovative Concepts and Technology In the last five years there has been a phenomenal growth in the US solar market as a result the total number of solar PV installations run in several thousands. It is remarkable, but it is still in a nascent stage as compared to the several millions of solar roof top systems as well as ground based solar systems which will be installed within the coming decades. The effect of such greater percolation of dispersed; sporadic renewable power production makes it vital that the infrastructure of grid is greatly flexible as well as smarter so as to allow for steady and coherent flow of electricity (Fig. 3). A vital component which will enable a profitable transition is the PV inverter.

5.1 Smart Roof Top Solar Microinverter Smart inverter has become a hot topic for discussion within the industry. A smart inverter should have digital structural design, capability to communicate bidirectionally and tough software infrastructure that is installed on the roof top (Fig. 4). These systems begin with reliable, strong and effective hardware with silicon centre that can be regulated by means of a scalable software platform which includes complex

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capabilities for monitoring. An intelligent inverter should be compatible and capable of sending and receiving messages, along with the sharing of granular data with the proprietor, utility and the other stakeholders. With these systems the installers and the service technicians are able to identify the issues in operation and maintenance such as estimating probable troubles within inverter or module and even allowing the upgradation of specific parameters remotely, in just a few seconds. Such smart power electronic equipments should include in addition a powerful API functionality i.e. application programming interface which enables the owners of fleet and other associates in a way to secure within their software the creation of powerful enterprise rank tools (an API is referred to a collection of programming commands for gaining access to web based software or tools. When a firm issues customers it’s API, customers are able to work with the firm’s software.)

5.2 Benefits of Utilizing Smart Microinverters Several manufacturers are almost ready to meet the smart inverter challenge. However, the topology and software control packages of all inverter are not equally created. Particularly, microelectronics technology offers few benefits to the commercial, residential, and solar utility scale. An integrated micro internet package can help reduce energy (LCoE) levels, facilitate greater energy output throughout the system’s lifetime, system’s reliability and its uptime. There is reduction in system’s costs due to decreased expenses incurred during installation in the labour and materials. Microinverters provide a host of AGFs (advanced grid functions) mandated by few regulatory standards for supporting the stability of grid like the power curtailment, ramp rate control, fault diagnosis and voltage support. The latest microinverters are highly adaptive and may be actually called a completely networked and a software defined inverter. The advantages of this software regulated system comprise the capability of providing grid supported services in a regular manner for over two decades of inverter platforms with help of software updates and with no substitute hardware. Though the quantity of solar power over several parts of grid within the USA is growing rapidly, it is still considerably lower as a proportion of the total generation mix. However, one state is offering valuable insight into the future of high level solar PV penetration, it is Hawaii. The following case study has illustrated, the advantages of having a completely networked, software described microinverter architecture (at the 50th stage) which have already been experienced both by the customers as well as the utilities. The main aerial utility communicated Enpez and informed that greater voltage fluctuations were being experienced as compared to the past and the utility must expand the voltage window for compensating for the variation because of increasing number of solar PV installations that took place in its service area. The utility stated that the inverters should decrease the range of frequency from 59.6 to 57 Hz, and

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asserted that such modifications were installed in the previous years on the PV systems. It was important to highlight that even by working from a network operations center which was over thousands of miles away within the Bay Area of San Francisco, the technicians were capable of satisfying the utility’s newer requirements. They also remotely upgraded the software to over 400 PV through indirect communication links [16].

6 Intelligent Solar System Management for Smart Cities With the rapidly growing requirements of energy and a steady depletion of conventional sources, solar energy is gaining prominence. Earth receives almost 160,000 TW of solar energy; whereas the present demand globally is over 16 TW. Solar energy received from sun is unlimited however; its transformation into a functional form is still not very economical. Further a reliable solar system needs to be enhanced by proper energy storage systems for dealing with diurnal and seasonal variations within solar radiation. With this background various nations have formulated their long term roadmap for solar energy utilization. For this event Japan would expand its solar PV by the year 2025 at a reasonable price. Large scale (~MW) demonstration projects are in progress in USA, Europe, and Australia. Such projects have high utility. Firstly, projects cut down the cost of energy technology since an operation of technology at a large scale lowers the price of that particular expertise. This has also motivated businesses/startups for spending in technologies associated with solar energy. Secondly, such projects support in being as trials for solar energy operation at a large scale. Thirdly, demonstration projects appeal to academic institutions for undertaking research and development in the long run. Fourthly such projects have enhanced public awareness regarding green technologies. All of these projects comprise of only a single element of a nation’s long-term vision for energy with in which solar energy aims to satisfy conventional energy technologies. Currently there is no technology or govt. intervention that can substitute the conventional fossil fuel-based systems. However, India being a developing nation with huge burden of petroleum imports there is dire need for expansion in solar based R&D [17]. For widespread implementation of solar energy India’s geographical location is very favourable. But a rapidly growing population, erratic power market, poses numerous challenges to scientists as well as business owners. The situation of India’s power sector is unique and it is not possible to compare it with other nations. Similar to USA or Japan several villages as well as islands are connected to the major grid and face spatial and seasonal variations within demand. It is hence, necessary that India ramps up development in solar energy at different scales ranging from small to large scale and standalone systems. It is also significant to consider hybrids of solar energy with other renewable energy resources. The present socio-economic scenario of the nation is clearly not sufficient however, more initiatives have been planned and the situation is expected to be better in the

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future. The Government of India has launched the National Solar Mission that is expected to significantly enhance the share of solar energy within the total energy along with the other sources of renewable energy such as wind, nuclear, tidal etc. The necessity for expansion has also been recognized. DST (Department of Science and Technology) and MNRE (Ministry of New and Renewable Energy) are leading the initiative for promotion of the consortia of main research institutions for projects related to solar energy cooperation. A notable scheme in this regard is DST’s PSI— Pan-IIT Solar Energy Initiative that is aimed at delivering 1 MW of solar base energy grid within 5Ms. Multi-specialization teams from different institutes are active participants within the initiative. For further strengthening the involvement in the National Solar Mission as well as the PSI, it is believed that the objective might be to formulate an inclusive inter-disciplinary group at the institutional level. It is decided to place a PEMFC (polymer electrolyte membrane fuel cell) system within the technology demonstration unit. A hydrogen production unit would also be put for supporting the fuel cell system. The selection of PEMFC is on account of the fact that PEMFC technology is currently very well developed. While high temperature fuel cell technologies like SOFCs (solid oxide fuel cells) need significant fundamental research. In contrast with PEMFCs, that need pure hydrogen, SOFC systems may utilize various fuels and might be combined with the present heat engine technologies. Hence, SOFC systems are very much attractive for steady power generation. However, owing to lack of storage the power generated needs to be consumed in the grid itself. For being able to achieve this recipients of power need to be connected to either GPN or operate on the day solar energy gets generated. A standalone power system needs significant energy storage. It could serve as an additional source of power on the campus of a public institution such as a school, PHC, panchayat or an anganwadi. As these establishments usually function during the day hours the solar power generated is properly used.

References 1. Chourabi, H., Nam, T., Walker, S., Gil-Garcia, J.R., Mellouli, S., Nahon, K., Pardo, T.A., Scholl, H.J.: Understanding smart cities: an integrative framework. In: Proceedings of 45th Hawaii international conference on system science (HICSS), 2289–2297 (2012) 2. IBM.: The Smarter City—Energy and Utilities, https://www-03.ibm.com/innovation/us/the smartercity/energy/index.html 3. Chicco, G., Mancarella, P.: CO2 emission reduction from sustainable energy systems: benefits and limits of distributed multi-generation. In: Proceedings of Second International Conference on Bioenvironment, Biodiversity and Renewable Energies. Venice, 22–27 May 2011 4. Morvaj, B., Lugaric, L., Krajcar, S.: Demonstrating smart buildings and smart grid features in a smart energy city. In: Proceedings of 3rd International Youth Conference on Energetics (IYCE), 1–8 (2011) 5. Forecasting energy consumption from smart home sensor network by deep learning. In: International Conference on Smart Trends for Information Technology and Computer Communications, pp. 255–265. Springer, Singapore (2017) 6. Cossent, R., Gómez, T., Frías, P.: Towards a future with large penetration of distributed generation: is the current regulation of electricity distribution

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6. Méndez, V.H., Rivier, J., de la Fuente, J.I., Gómez, T., Arceluz, J., Marín, J., Madurga, A.: Impact of distributed generation on distribution investment deferral. Int. J. Electr. Power Energy Syst. 28(4):244–52 (2006). https://dx.doi.org/10.1016/j.ijepes.2005.11.016 8. EPA, US. CHP Technologies, https://www.epa.gov/chp/technologies.html [24.07.19] 9. “Biofuels Legislation in Europe.” European Biofuels Technology Platform. https://www.bio fuelstp.eu/legislation.html Accessed 30.09.19 10. Big Data Analytics for Smart and Connected Cities. IGI Global 11. Sarkar, M., Banerjee, S., Badr, Y., Sangaiah, A.K.: Configuring a trusted cloud service model for smart city exploration using hybrid intelligence. Int. J. Ambient Comput. Intell. 8(3), 1–21 (2017) 12. Usaola, J.: Operation of concentrating solar power plants with storage in spot electricity markets. IET Renew Power Gener. 6(1), 59–66 (2012) 13. Erdinc, O., Uzunoglu, M.: Optimum design of hybrid renewable energy systems: overview of different approaches. Renew. Sustain. Energy Rev. 16(3), 1412–1425 (2012). https://dx.doi. org/10.1016/j.rser.2011.11.011 14. Hammons, T.J.: Geothermal power generation worldwide. In: Proceedings of the Power Tech Conference 1, pp. 1–8. IEEE Bologna (2003) 15. Cossent, R., Gómez, T., Olmos, L.: Large-scale integration of renewable and distributed generation of electricity in Spain: current situation and future needs. Energy Policy 39, 8078–87 (2011). https://dx.doi.org/10.1016/j.enpol.2011.09.069 16. Poland, M.P., Nugent, C.D., Wang, H., Chen, L.: Smart home research: projects and issues. Int. J. Amb. Comput. Intell. 1(4), 32–45 (2009) 17. KalogirouSoteris, A.: Solar thermal collectors and applications. Prog. Energy Combust Sci. 30(3), 231–295 (2004)

Intelligent Transport System for a Smart City Samir Telang, Arvind Chel, Anant Nemade, and Geetanjali Kaushik

Abstract The term smart city was coined in the early 1990s. This term includes urban development with new improved developments in the technology, innovation, and globalization. The major contribution is towards adapting the smart growth movement of the late 1990s. This has advocated improved urban planning and utilization of improved Wi-Fi enabled gadgets. It is needed for growth in new global knowledge economy. It also integrates the operation of urban infrastructure and services used in the buildings, transportation, electrical and water distribution and public safety. The smart city is part of urban development which has information and communication technology (ICT) to facilitate improved insight into as well as control over the various systems that affect the lives of residents. Keywords Smart city · Intelligent transport system · Information and communication technology · Smart solutions

S. Telang · A. Nemade Research Centre, Jawaharlal Nehru Engineering College, MGM University, CIDCO, N-6, Aurangabad, Maharashtra 431003, India e-mail: [email protected] A. Nemade e-mail: [email protected] A. Chel (B) Department of Mechanical Engineering, MGM’s Jawaharlal Nehru Engineering College, Aurangabad, Maharashtra 431003, India e-mail: [email protected] G. Kaushik Department of Civil Engineering, Hi Tech Institute of Technology, Waluj, Aurangabad, Maharashtra 431136, India © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 S. C. Tamane et al. (eds.), Security and Privacy Applications for Smart City Development, Studies in Systems, Decision and Control 308, https://doi.org/10.1007/978-3-030-53149-2_9

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1 Introduction Recent times have seen significant developments in the field of technology and world over it is being tried to undertake their implementation effectively. Concept of smart cities is gaining importance across the world. Smart cities make best use of information communication technology for managing different systems which affect the life of residents. In these smart cities it is necessary to upgrade existing infrastructure as cities face issues of insufficient public transport, road congestion and transport related GHG emissions. Therefore, it is necessary to focus on the provision of smart automobiles, intelligent transport systems, multi-level parking, electronic toll collection, clean fuel based public transport. Electric vehicles and Hybrids will reduce the dependence on fossil fuels. However, there is urgent need for progress in batteries, inverters, motors and other charging infrastructure. Hence, it is important to discuss various aspects involved in intelligent transport systems for smart cities in the following sections.

1.1 Defining a Smart City The term “smart city” has been in use ever since the early 1990s, to describe the manner in which urban development is focusing towards globalization, technology and innovation for creating a better urban base. Information expertise has been applied for meeting the various urban challenges such as resolving complex systems for integrating functions of urban transport, provision of services in the buildings, distribution of electricity and water supply and ensuring public safety. Basically, a smart city makes best use of information communication technology (ICT) for managing different systems that affect the life of the resident. There is no universally accepted definition of a ‘smart city’. Therefore, the concept of a smart metropolis differs from city to city and from one country to the other, contingent upon the levels of development, availability of resources and aspirations of the city residents of the city [1]. A smart city is basically described by four important pillars of developmentphysical, social, institutional and the financial infrastructure. This might become the long-term aim and cities can initiate work for such an infrastructure by adding successive layers of ‘smartness’. With such a vision of city administration it is imperative to examine these parameters and develop our own perception of a smart city. Spatial planning models are based on factors such as physical-social networks, diversity and human impact on city vehicles, city’s resilience, etc. [2, 3].

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1.2 Advance Vehicle Safety Automobile researchers have in depth knowledge within advanced vehicle safety research and development consequently they enable us in improving the manner we are able to interact with smart, autonomous as well as semi-autonomous automobiles. The Center for Intelligent Transportation Research Engineers (CITRE) focuses on designing better safety and assistance systems for driver, areas such as automatic parking; lane departure warning, lane assistance, rollover warning, warning from collision, night sight, assistance in overtaking, unsafe pedestrian detection and warning among others are researched for improving the experience [4]. In addition automobile researchers investigate the relation between mechanical and behavioral factors towards their contribution to human injuries; so the researchers can develop solutions which avoids these risks from turning into reality. Centre in association with its collaborators develops, builds and tests such systems [5] involving loop software and hardware.

1.3 Intelligent Transportation Systems Researchers particularly from the 1990s have focused efforts on improving safety measures to protect an average driver for urban use vehicles. Solutions tackling a range of smart or intelligent transportation issues have been developed which include smart cities, shared mobility, vehicular to infrastructure communication, inter vehicular communication, automatic driving and parking, systems for traffic management, cooperative and adaptive control over traffic. Further there is on-going debate over driverless cars within the society; despite the intervention being life enhancing it is changing societal perception about personalized transport [6]. With societal perceptions being at core of research these days automotive researchers take these perceptions into account along with industry experienced technical manpower for finding innovative solutions to deal with fuel economy, public good and liability [7].

1.4 Fuel Economy The major drivers directly impacting the automobile industry include fuel economy, emissions and safety. CAFE (Corporate Average Fuel Economy) regulations mandate continuously improving the fuel economy of the fleet, whilst the Environmental Protection Agency (EPA) regulates the tailpipe emissions for vehicular sources. Automotive researchers and experts aim at optimizing all associated systems covering all aspects of fuel economy (engine efficiency, friction reduction, power train hybridization, aerodynamics) as well as the emissions [8].

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1.5 Role of Automobile Industries in Smart Cities In order to reduce the dependence on fossil fuels technologies for electrification of vehicles have advanced in the past decade and there has been significant progress in basic performance (driving, stopping, cornering etc.). The technology for EVs and hybrids has been taken from those of Metro, Railways i.e. fields in which significant progress has been made in batteries, inverters and motors. Advances in ICT have resulted in its increasing application within vehicles [9]. With collection of huge amounts of operational data from a wide variety of sensors there are services which use these data. Consequently the development of technologies for integrating vehicles within social infrastructure is globally progressing [10]. Such trends in India are being recognized by MNCs, Hitachi is setting up demonstration experiments which use vehicles as energy as well as social infrastructure. EVs, Hybrids and other electric vehicles with their low levels of carbon dioxide (CO2 ) emissions help in reducing the dependence on fossil fuels. For the smart cities to be able to make automobile technologies and allow for their deployment globally, it is necessary to provide [11], with the charging infrastructure [12].

2 Need of Intelligent Transport System in a Smart City While it is needed to boost the transportation sector in the country, few intrinsic challenges and concerns exist: 1. 2. 3. 4.

Insufficient public transport Congestion on roads Transport related GHG emissions Engine Technology up gradation- India has recently started implementation of BS VI norms which is equivalent to EURO 6 implemented in European countries. No new vehicles BSIV are being registered after 31st March, 2020. 5. India is rapidly upgrading setups for Electronic toll collection (ETC) as well as traffic monitoring which were previously inadequate leading to jams at highway tolls. 6. Indian smart cities are establishing Intelligent Transportation Systems (ITS) and multi-level parking systems however; it will be few years till these systems are in place within the country. It is needed to emphasize on improved infrastructure, legal provisions for sustainable fuels, clean fuel based public transport and successful implementation of the expansion plans towards cities to usher in an age of smart transportation within India.

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2.1 Smart Automobiles Smart transportation categories include Smart Automobiles, Smart Infrastructure, Sustainable fuels, and Intelligent Transport system. Presently the focus is on fuel efficiency, higher performance, safer design, advanced engines with latest emission norms/green fuel, connected cars/IoT, driverless vehicles, wearable devices etc. [12]. Auto technology currently enables cars to “see” around, collect data about probable concerns on the road thereby giving “eyes” behind their heads to drivers. Majority of crashes involve driver error therefore automobile manufacturers build a sequence of safety features that assist for brief periods in avoiding accidents. Such assistance systems for driver include automatic braking, blind spot warning, lane departure, telematics control and adaptive cruise control among others. Few technological advancements that have been made in India include anti-lock braking system and the electronic stability program (ESP). An important study reveals that the ESP may be able to save the lives of 10,000 Indian people. Further firms such as ABS and other electronic giants in India might cut down accidents. These safety systems may be in stated on Indian passenger cars as mandatory tools. A major automobile giant in India has concluded that almost 70% of accidents which include vehicle skidding may be avoided with ESP saving 10,000 lives each year in the country. This study has highlighted that currently, about 40% new cars manufactured in India are provided with ABS while ESP is installed in only 4–5% of all new cars. It is expected that these safety features will be installed in more cars in the coming years. Since September, 2015, ABS has been made mandatory in commercial vehicles. Automated Manual Transmission helps in untangling and disintegrating the clutch and gear through the electronic actuator. Indian government has made crash test criteria obligatory for all newly manufactured cars while the deadline for the upgradation of existing cars was October 2018. The new basic safety criteria (which include crash tests from front and side) will apply to all models of cars. As per recent government order, cars are to be tested at 56 kmph for frontal crash norms, while the speed for testing of side crash is 50 kmph. Automation and Traceability—Various security components have come up for the automotive industry which includes automation, security components, auto sensors and more. Automation has been optimized selectively and detects the source of error. Further, the vision system identifies acceptable image quality is and also stores the image for analysis in the future. Soft-Feel Interiors—Create a subtle, yet powerful emotional connect right from the console, to door handle, to arm rests and others, it is the way a surface feels it gives a sense of quality to the vehicle interiors. Such improved comfort in driving and safety features help to achieve a range of toughness, flexibility, strength and fatigue properties.

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2.2 Electric Vehicles As per a study conducted in 2012 by the Automotive Research Center at University of Duisburg-Essen, Germany, worldwide there has been a shift in manufacturing trend for light vehicle production from combustion engines towards hybrid and electric vehicles. It is expected that by 2030, combustion engines will be used only in 56% of vehicles massive decline from 98% in 2013. Hybrid technologies will comprise of 35% vehicles and electric vehicles will make up only 9%. This will significantly reduce GHG emissions and such vehicles will also be more fuel efficient. It is aimed that in the next 15–20 years electric vehicles will comprise 100% of the fleet. The future of vehicle technology therefore lies into hybrid electric vehicles (dual fuel), electric vehicles and fuel cell vehicles. In India dual fuel vehicles which run on diesel/petrol and CNG are increasingly becoming popular. In Indian market within the electric vehicle segment, brands like Toyota, Mahindra and BMW have a strong presence. Government of India has adopted a National Electric Mobility Mission Plan 2020 that encourages green vehicles adoption and aims to enhance domestic manufacturing capability within the automotive sector. Even to encourage greater foreign trade the government has provided subsidies on green vehicles parts. In India the electric vehicles market is still at a budding stage and the challenge is to right away enhance the charging infrastructure within the mega cities. According to an estimate in 2017 electric vehicles accounted for almost 5% (175,000 cars) of the Indian car market while by 2020 the global market may reach about 20 million cars. Therefore, in India a long way has to be traversed before global technologies are captured [13].

2.3 Smart Fuel and Better Emission Standards Rapid rate of urbanization has led to an increase in GHG emissions highlighting the need for adopting sustainable technologies. For controlling these emissions particularly in Delhi and NCR, the Supreme Court has prohibited the sale of large SUV vehicles with diesel engines of 2000 cubic capacity and above. As presented to the EPCA (Environmental Protection and Protection Authority) report almost 7000– 30,000 vehicles during this period were towed away from the city it led to a 19–20% reduction in pollution levels.

2.3.1

Alternative Fuels

Use of biofuels (ethanol, biodiesel), CNG, hydrogen-powered vehicles, fuel cell technology, electric and solar powered vehicles are advocated as clean fuels. In India owing to its low cost CNG has become a popular fuel. However, more number of fueling stations as well as infrastructure support is needed for enhancing access.

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Biodiesel is a clean fuel with properties similar to diesel. Using Jatropha and Karanjia seeds it is manufactured through a simple chemical reaction involving alcohol and vegetable oils. State-owned firm Indian Oil has conducted extensive field studies along with Haryana Roadways, Indian Railways and the Tata Group. Preliminary experiments have shown a major reduction within smoke density (10–15%) when biodiesel blend is used as fuel.

2.3.2

Emission Standards

Bharat Stage (BS) emission standards are followed in India. These emission standards regulate the generation of air pollutants from IC engine equipment which include motor vehicles [11]. BS standards are established on the basis on European standards and are frequently upgraded. BS IV standard was implemented in 13 metro cities during April, 2010 while the rest of India moved to BS III. Since October, 2014 BS IV has been extended to another 20 cities. In the IInd Auto Fuel Vision and Policy 2025 notified in May, 2014 by GoI (Government of India) provides a roadmap 2025 for fuel emission standards. For the adoption of these latest standards Govt. has decided to leave BS V standards altogether and leapfrog to implement BS VI norms from April 2020. As compared to the other countries, Euro 6 (an equivalent of BS VI) has already been implemented effectively in Europe.

2.4 OEMS to Benefit from the Challenges With further tightening of Carbon dioxide emissions not only in Europe; other nations such as China, USA and Japan the Original Equipment Manufacturers (OEMs) have been pushed to invest greater in e-mobility. It implies electric vehicles, electrical/hybrid powertrains; advanced IC engines, lightweight batteries etc. In addition OEMs need to also invest in the alternative technologies to be able to meet emissions targets in the future (beyond 2025). As per a report by Mckinsey on automobile industry it is expected that networked cars will increase by 30% each year in the next few years; an estimate says that by 2020 one in five cars would be Internet connected. Such cars would mainly be part of the premium segment. Further services would be delivered services via car—Smartphone capabilities, internet radio, tourism information, entertainment services, driver-assistance etc. OEMs would have to deal with shorter product and service cycles concerned with updates in software and technology. Further it will be necessary to build relationships with firms which build apps customized to the car. According to AT Kearney research the auto firms spend third most amounts on undertaking research so that OEMs are able to meet consumer demands and update with technological advances in the field. In India National Automotive Testing and R&D Infrastructure Project (NATRiP) is the largest and most important initiative taken within the automotive

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sector representing a unique conglomerate of the Government, various state governments as well as the industry. It aims to create a top-class facility for testing and R&D infrastructure for automotive industry within the country [14].

2.5 Necessity of Intelligent Transport System for Smart City City transport plays an important role in ensuring a quality in the life of citizens within a city. Presently, public and the private roads in most of the cities form important means of transport and logistics. Few mega cities possess strong back bone transport mode in the form of local train network and metro. Insufficient capacity of public transport, lack of safety, poor road safety issues, crowded road network, lack of traffic management, absence of proper parking and the lack of modal preferences are the major issues facing Indian transport. Most of our cities lack integrated transport systems facing a huge gap between demand–supply. A World Bank research study projects that by year 2031, almost 600 million people would reside in Indian cities. However, only about 20 of these cities having population over half a million (>500,000) have any type of organized public transport system. Further it is very disappointing to note that within mega Indian cities the share of public transport has actually declined from almost 70% during 1994 to just about 40% during 2007. Moreover, accident and the death rate among Indians are among the highest within the world, majorly impacting the poor as well as vulnerable sections of the society. Some of the major issues in public transport in India are highlighted, which are mapped as a part of Accenture——NASSCOM Technology can play an important role in transportation planning by forecast of demand and supply of data feed. It can also assist in improving the reliability of public transport systems through the provision of information on arrival/departure/route for passengers to enable comfortable travel. Intelligent traffic management system can support in effective traffic flow Integrated Multi modal fare helps citizens in utilizing multiple modal alternatives without the trouble of purchasing tickets [15]. This Accenture NASSCOM report plan provides guidelines for leveraging smart technology solutions for improving public transport.

3 Connectivity and Structure of the Transport System There are various systems that can be adopted to improve the connectivity in the smart city as follows: 1.

Bicycle sharing System A bicycle/bike sharing system for public, is a scheme in which bicycles are available to individuals for shared use on a short-term basis. With the help of

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smartphone apps nearby stations are shown on the map along with the bikes and open docks available at every station. 2. Geospatial-enabled efficient Transportation System On the basis of real time data geospatial enabled services are able to provide regular traffic forecast, mobile applications for journey planning and real time tracking from mobiles increasing the reliability of public transport. 3. Dynamic Carpooling/Car sharing Carpooling apps connect drivers and passengers within real time, thereby enabling dynamic carpooling. It is mutually beneficial as drivers are able to find people moving towards same destination and even passengers are able to directly debit fare to the app, totally avoiding the requirement for any sort of money exchange. 4. Integrated Transportation Hubs These are able to connect multi modes of transport such as metro, bus, BRTS, etc. 5. Public transport surveillance It is important to have a surveillance system in place on the public transport for the safety and security of passengers. System administrators are able to remotely monitor the public transport and take action in case of serious accidents/incidents. 6. Road user charging These are direct charges that are levied for the use of roads, include road tolls, time-based/distance-based fees, congestion charges and any other category of charges to prohibit the use of certain vehicle classes or polluting vehicles. Such charges reduce peak traffic, road congestion, air and noise pollution levels, GHG emissions and road accidents. 7. Smart Parking It allows for effective management of parking spaces (both on and off street) with the help of cameras, sensors, smart parking solutions etc. 8. Smart Toll Smart toll utilizes RFID, number plate detection, etc. for charging toll charges to user’s account so that there are no vehicles lines at toll gates on local, state and national highways. 9. Smart Traffic Lights It senses traffic conditions and tune traffic lights to allow for smooth traffic flow. 10. Freight ICT Services This improve the efficiency in freight vehicle operations and help in saving time and energy. ICT enables greater data collection, enhances predictive abilities, in realtime and allow for dynamic decision making along with its implementation which result in an effective freight system. Cities must support electric and renewable energy powered vehicles with required infrastructure. Transport is an important pillar for any city. India requires a balanced approach in expanding public transport infrastructure along with utilization of smart technology solutions. With this aim Government of India is investing in numerous

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initiatives at local, state and national level for improving public transport with the use of smart technology solutions. There is also a dire need to improve the efficiency, quality and safety of public transport. Recently several words have been made use of for describing our cities and for making them more accessible with the use of technology. IBM suggests steps taken towards “Smart Cities”, while Cisco describes them as “Smart + Connected Cities” and “Internet of Everything”. Editor of Wired magazine has termed the changes as the upcoming “programmable world”.

3.1 Connected Cities In contrast to a “smart city” a “connected city” focuses more on physical, electronic and the human infrastructure which help a city to function. While a smart city typically involves both ICT and other enabling approaches, a connected city is greatly focused on those networks which collect exchange and utilize that information. A connected city has all related city systems such as health care, waste management, transportation, utilities, employment, and education among others which are able to communicate and coordinate with each other [16]. Within a smart city the administration as well as the citizens utilizes the best ICT means for attaining common goals which include economic development, sustainable environmental development and ensuring improvement in the quality of life for its residents. • For being “smart”, a city “should be connected.” • It should be able to align with its conventional mission for Intelligent Transportation System • Businesses and governments which aim at sale of products and services use the term “smart cities” for being able to add to larger dialogue.

3.2 Smart/Connected City Examples Worldwide there exist numerous examples of smart cities. Few cities may not be completely “smart”, but with their best practices they serve as role models for other cities across the world. Four international cities below present a picture of the immense potential held by the smart city approach [16]. Rio de Janeiro city of Brazil possesses world’s largest “smart” operational centre that gather information from 30 different agencies under a single roof. This centre was planned after the devastating landslides experienced by Rio in April, 2010. This disaster has impelled the Mayor to understand from IBM the manner in which big data would be helpful in predicting and responding to disasters in the future. This project in Rio city rapidly expanded from being a landslide forecast at the operations centre to become the pioneer in the analysis of historical as well as real time data

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for efficiently managing the services along with improving the management of its usual data streams. Rio is also the first city in collecting data from the drivers by associating with mobile app for road navigation, Waze. It has also partnered with transit navigation mobile app for data on pedestrians and also collaborated with mobile application for accessing the data on cyclists. Santander city at Spain has almost 10,000 sensors which are located around the city. These sensors are fixed on street lamps, poles, walls of buildings and placed under the parking spaces collecting data related to environmental factors, traffic, weather and residents among others. With the help of a smart phone app citizens are provided with real time information on cultural programs, retail offers, sightseeing information etc. In the future it is planned to include more information such as on demographics, real estate, villages and so on. With this innovation there has been a positive effect on the local economy and also an increase in tourism. Singapore has promptly become world’s top-class cities and this success has been attributed to its efforts in becoming the smartest city world over. This has been done by tapping data across the island nation for a variety of applications. Singapore’s land transport authority in collaboration with IBM and MIT (Massachusetts Institute of Technology) is improving usage of public transport. Infocom Development Authority of Singapore has set upon office of the Smart Cities Programme under which cameras, sensors, GPS devices installed across the city provide useful information on traffic, predict congestion and recommend alternative routes. Singapore was among the first few cities in the world to execute congestion pricing that utilizes traffic data for adjusting toll prices in real-time. The city of Songdo in South Korea has a powerful information network underneath the city, energy usage and other necessary city services are monitored and efficiently controlled by the city officials. With the help of this network citizens are provided with a smartcard which acts as an access pass, integrated credit card, and house key. Almost every device, road, building or vehicle is equipped with wireless microchips or sensors. Entire data is collected, analysed and monitored within real-time by a central monitoring hub [5, 17, 18]. Los Angeles in a manner similar to Rio had tried to utilize computer algorithms for forecasting the location, effects of earthquakes and the aftershocks [13]. This assisted in effective evacuations from affected areas. Researchers also observed that this algorithm for predicting aftershocks may also be used for predicting criminal activity this resulted into PredPol (Predictive Policing) which determines probable crime areas. With the use of these tools within a test neighbourhood, officials saw a percent decline in the crime [4, 19]. New Urban Mechanics office has been set up by the City of Boston for finding innovative solutions to city problems by involving information technology [5]. In addition, to official purpose several Boston agencies are promptly making use of new ICT tools: 1. Smart Parking application helps to decrease vehicle idle time during parking. 2. Shot Spotter determines gun shots location.

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3. Smart Rapid Transit closely monitors subway stations through video cameras and sensors which detect movements and the presence of biological weapons. 4. GHG Emission Tracking utilizes sensors placed on the top of high buildings to detect and estimate GHG emissions. 5. Street Bump is a mobile application which makes use of cellular phones for determining the location of road potholes. In the last few decades, a novel system based on data has come into prominence. Internet is the main channel for data it transmits large quantities of sensor data almost near light speed. Wireless technologies of communication like mobile phones, remotely programmable machines, wi-fi and bluetooth generate a field of connectivity around most of the developed world. With the advent of data network, there has been a change in the perception of society which has accelerated data usage. Individuals who have used computers and Internet since childhood are usually termed as “digital natives” this generation makes up an increasing fraction of the technical workforce and the society at large. With their being more comfortable with ICT, they usually accept and, in most instances, even demand technology integration into their lives. According to U.S. Department of Transportation Intelligent Transportation Systems Joint Program Office a smart/connected city is one where in residents and systems interact and coordinate with each other more frequently as compared to the rural areas.

4 Significance of the Proposed Transport System Out of India’s 1.35 billion population almost 30% resides in cities. This number is equivalent to the population of USA. Going by estimates by 2031 the urban population is expected to grow close to 600 million. The number of metro cities (>one million population) has already increased from 35 (in 2001) to 50 (in 2011). By 2031 this number would increase to 87. Increasing population in cities would require greater urban infrastructure which will be needing investment. Presently almost 75% transport in Indian cities is via motorized two wheelers, public transport, and bicycle and on foot despite growing numbers of cars (over past 2 decades). Smaller and medium sized cities have lesser incomes compared to mega cities and therefore the dependence on private vehicles is relatively less. WHO has included mortality, morbidity and loss of years due to sickness related to road injuries as health impact from motor vehicles. In 2012 close to 500,000 road accidents occurred as per data from Union Ministry of Road Transport and Highways. Almost 11% of road accidents occurring globally take place in India. Urban transport reforms have been initiated in India with focussed national policies and state government programs. Few years ago, Central Govt. launched a new mission across the country termed as “Smart Cities”, within which 100 smart cities are to be developed with a funding of around Rs. 1 lakh crore within a period of five years. A new urban renewal mission

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was also initiated named after former Prime Minister Atal Bihari Vajpayee. It is expected that the move will rejuvenate nation’s urban landscape by improving the urban infrastructure. Even in 2006 Jawaharlal Nehru National Urban Renewal Mission (JNNURM) was launched to improve urban infrastructure and to enable prompt but planned development of 65 selected cities in India. It was a reform-driven assistance program from the centre. Financial support was related to a set of compulsory reforms targeted at governance and reforms in the region. A total investment close to US$20 billion over a period of seven years was envisaged. Though the JNNURM reforms focussed on all sectors within urban infrastructure almost a quarter of overall JNNURM funding was allocated to transport sector. While 30 states and union territories were selected for JNNURM funds, the funding from transport sector was mainly allocated to Delhi. The project guidelines for obtaining funding for these transportation projects suggested that the transport infrastructure improvement plan should be in accordance with the NUTP (National Urban Transport Policy) highlighting sustainable mobility with focus on public transport, nonmotorized transport (NMT) and the transit-oriented development (TOD). However, analysis of selected projects revealed that the screened and accepted projects did not conform to the spirit of NUTP and the actual expenditure was majorly focused on car-centric infrastructure. Under JNNURM’s transport reforms, 15% of the total projects belonged to the category of mass transit projects while almost a whopping 70% projects within the category of roads and flyover. Cities formulated newer public transportation systems like BRT (bus rapid transit), rail-based systems such as metro and the monorail for the promotion of public transport. In several cities, centre approved BRT and bicycle schemes with little emphasis on the space for pedestrians. Despite of the fact that 50% of trips in India cities are on foot, bicycle or by means of intermediate public transport systems. In 2005, under JNNURM city development plans were to be formulated and few mandatory reforms had been stated but no reforms were mentioned for urban transport. In 2008 the second package for economic stimulus was particularly linked with various reforms associated with the transport sector like the Parking Policy, formulation of the Urban Transport Fund, Advertising Policy and the Unified Metropolitan Transport Authority (UMTA) which were duly notified by the state. Transport projects at the state and city level were to be funded in two phases: first instalment was released to only those selected cities which had initiated purchase of buses from central government. However, there was a compulsory clause for second instalment release to provide a detailed report of the reforms started both at the city as well as the state level. The record available with the government revealed that from a total of 65 cities, just five to ten cities had actually implemented few reforms. JNNURM program’s monitoring and the evaluation framework was the major aim of this government supported program by tracking the utilization of the associated monetary funds. The major focus of the JNNURM mission and focus of the present smart cities mission is initiating newer technologies with the rationale of solving traffic issues and satisfying the high density demands of busy corridors in Indian cities. It is for this reason a well-integrated transport system is in high

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demand. But mega cities which have well developed metro systems have neglected the holistic approach in planning which fails the public transport system within a city and compels residents to depend on their private transport. The second issue facing Indian cities is their poor governance. As per recent McKinsey’s report 2030 onwards, several Indian cities will grow rapidly both in terms of population and GDP therefore, it is significant that India addresses these questions. Further, it is necessary to enhance the coordination between different agencies involved in urban planning and development.

5 Smart Solutions by Integrating Innovative Concepts and Technology in Parking In London, it is difficult to find car parking easily. UK has over 27 million cars which are used for making trips numbering over 25 billion in a year. Almost 57% of such trips (39 million) each day need provision of parking spaces which is far from their homes. A multi-storey parking hub makes it worthy to identify innovative parking solutions as well as innovations. It also facilitates varied perspectives regarding the future of parking. 1. Recent innovations in smart parking Smart city planning, smart parking solutions to sensor-based technologies will be the future of smart cities and would define the manner in which major cities would develop world over. IoT (Internet of Things) would facilitate these smart cities. Parking spaces with recent advances in software innovations including wireless technology based on sensor, presently worldwide more than 10,000 such devices have been installed. In order to improve city design and to aid in city planning such parking sensors are used for viewing data on parking across a district by the administration. Such innovations within parking provides citizens real time parking data and also speedily regulates the parking areas. This technology may assist the visitors in accessing parking spaces in firm’s car park and at the local supermarkets 2. Innovations in parking for mega cities Smart parking means selective, with significant innovation in transportation and technology. What latest innovations should be adopted by cities? Strangely, innovation has lesser relation to parking but more with the provision of information to administration involved in planning the cities and the residents utilizing the city facilities. The ‘Internet of Things’ smart camera, wireless transfer of sensors and the application of real smart data is useful for better planning in the future. This data is used for sending real-time information to drivers for informing them about parking spaces. Senors Feedback System to different vehicles.

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3. Valet parking system for Airports In the latest trend world over robots are being utilized for wallet parking. Such as the city of Düsseldorf has Ray while there is robot Stan in Lyon. These wallet parking robots pick up the vehicles and leave them within an outdoor car parking area. 4. Innovative concepts in parking It is also possible that one may wish to earn a fortune through the sale of parking solutions to the major car manufacturers.

6 Intelligent Transport System Management Intelligent Transportation Systems (ITS) include various ICT (Information and Communication Technology) solutions for efficient management. The main thematic areas within ITS are: 1. Commuter Information System These systems offer information in real time to those passengers who use the public transport. ETA or the estimated time of arrival of buses/trains is generally displayed on bus stands, MRT platforms or electronic sign boards at railway stations and airports. These systems sometimes are also able to provide important information on individual mobiles particularly within Indian Railways and the aviation industry. With information about ETA there is reduction in uncertainty there by leading to a decline in congestion within the waiting areas. 2. Parking Management in Real Time Multi-level car parking offers information regarding available parking spaces to public via electronic sign board display. This feature is helpful for the parking staff and the customers. Such multi-level parking is beneficial with requirement of minimal land, ease of entry and exit, multiple sensors along with the security devices result in lower expenses in the operating and maintenance [20]. 3. Smart Cards Among the above technologies, smart cards have been extensively used within the Delhi and other metro networks. Smart integrated cards (can be used in any form of public transport) are being considered by state governments of Delhi and other states. Such integrated cards enable citizens in paying for any form of public transportation systems through a single card, introducing multiple modal transportation systems within the mega cities. Electronic collection systems for toll and automatic systems for managing parking have been instated in Delhi at few locations and also within few other cities. There is a dire need for adoption of such smart technologies for improving the public transport within India. It will create massive prospects for the semiconductor businesses. Electronic collection systems for toll involve systems based on RFID (Radio Frequency Identification) at each point of entry these read remotely resulting in the automatic deduction of tolls. With the use of this technology there are considerable savings in the queuing

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time, fuel costs and the air pollutants at the toll gates. Such facility is present in the Mumbai-Pune highway within India. Even in SEZ Gujarat similar electronic centers for toll collection are being established. It is hoped that this technology would encourage industries manufacturing semiconductor chips, RFID devices and related IT systems. The latest development in smart parking assistants and vehicle technology is utilizing the sensors. Even the chassis as well as the driveline are equipped with such sensors and cameras which offer assistance in parking. Therefore, it is a valuable technology for new learners and inexperienced drivers as the technology enhances safety and comfort in driving as well as parking. 4. Automatic Speed Enforcement The recent automated speed enforcement program has been executed well in the other countries. It needs to be implemented effectively within India. On account of heavy traffic and congestion on the roads, it is greatly important to gain from features like auto traffic management, automatic red light, multiple car tailgating among others. 5. Airport Surveillance and Safety Equipment Improved airport security not just avoids possibility of any terrorist attack or any other such tragedy, but also reaffirms public faith within the safety of flight travel, which received a massive blow after the 9/11 tragedy. In view of this, several steps have been undertaken at Indian airports which include the deployment of CISF for managing airport security, the installation of CCTV surveillance systems, modern and advanced systems for X-ray baggage inspection and the up gradation of security and surveillance systems. Smart cards have also been made use for managing critical installations for supporting the efforts of security personnel at sensitive airports. 6. Application of RFID with in Transportation of Freight Despite RFID not being a latest technology, India has been sluggish in its adoption and usage. With an emerging Indian economy, there has been a drastic growth in manufacturing and exports. However, the Indian sector of logistics still lags behind the worldwide standards in several ways. With the use of RFID in transport of freight, India may be able to improve the shortcomings in this sector resulting in improved rankings of the country at the global scale.

References 1. MoUD.: Draft concept note on smart cities, National conclave of Ministers and principal Secretaries/Secretaries of States and Union Territories Government of India, New Delhi (2014) 2. Gupta, V., Ag‘arwal, P.K., Gurjar, J.: Some basic issues for development of efficient public transport system in smart cities. In: National Conference on Sustainable & Smart Cities 2015, 10–11 April 2015 3. Gurjar, J., Agarwal, P.K., Gupta, V.: Applications of innovative technologies for development of sustainable transport system. J. Adv. Res. Automot. Technol. Transp. Syst. 1(4), 6–10 (2014)

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4. Behera, J.: Towards development of intelligent transport system for control of traffic management in Indian Cities. Indian Highw. J. Rev. Road Road Transp. Dev. 42(6), 66–77 (2014) 5. Krishnamoorthy, C.S., Rajeev, S.: Artificial Intelligence and Expert Systems for Engineers. CRC Press Publication (1996) 6. Vanjakshi, L., Ramadurai, L., Anand, A.: Intelligent transportation systems. Synthesis report on ITS including issues and challenges in India. Intell. Transp. Syst. Traffic Manag. Dehradun City. IJSR. 3(4): 1–10 (2014) 7. Dinakaran, M.: Intelligent transport systems. Indian Highw. J. Rev. Road Road Transp. Dev. 42(5), 51–60 (2014) 8. Gifford, J.: Information technology and transportation. ITIF event. Digit. Qual. Life 78. Transportation May 14 (2009) 9. Zhou, X., Gifford„ J.: Institutional challenges in the development of intelligent transportation systems: 79. Route 1 Corridor and the national capitol region. In: Presentation at Transportation Research Board 89th Annual Meeting, 12 Jan. 2010. Washington, DC (2010) 10. Schlingensiepen, J.: Korporative IT-Systemarchitektur zur Unterstuetzung unternehmensuebergreifender kooperativer Produktentwicklung. Integrierte Produktentwicklung, Teil Bd. 14. Otto-von-Guericke-Univ., Lehrstuhl fuer Maschinenbauinformatik, Magdeburg (2008) 11. Smart Cities: Smart Cities—Ranking of European Medium-Sized Cities (2007) 12. United Nations Conference on Road Traffic: United Nations Conference on Road Traffic, Vienna, 7 October-8 November 1968. Final Act, Convention on Road Traffic, Convention on Road Signs and Signals. United Nations, New York (1969) 13. Williams, B. Proof of Ownership. Thinking Highways, vol. 9, January 2014, No 1 14. Accenture: Building and Managing an Intelligent City 44 (2011) 15. Public Policy Ex: Smart Cities, Smart Europe. April 2014. 6. My way: multi-modal journey planning made easy to encourage the use of sustainable modes of transport 16. Forecasting energy consumption from smart home sensor network by deep learning. In: International Conference on Smart Trends for Information Technology and Computer Communications, pp. 255–265. Springer, Singapore (2017) 17. Big Data Analytics for Smart and Connected Cities. IGI Global 18. Sarkar, M., Banerjee, S., Badr, Y., Sangaiah, A.K.: Configuring a trusted cloud service model for smart city exploration using hybrid intelligence. Int. J. Ambient Comput. Intell. 8(3), 1–21 (2017) 19. Poland, M.P., Nugent, C.D., Wang, H., Chen, L.: Smart home research: projects and issues. Int. J. Ambient Comput. Intell. 1(4), 32–45 (2009) 20. Litman, T. Ready or Waiting? Traffic Technology International. ROW14 (2014)

Application of Internet of Things in Mishap Avoidance Due to Swamping: A Novel Approach Neil Patel and Ramchandra Mangrulkar

Abstract Swamping is one of the most dangerous natural disasters that affect the affected part of the world, causing human deaths, destruction of places, lessening economic growth and affecting health of human beings. According to economics times published dated 14th Oct. 2019, 1900 deaths occurs in overall monsoon in India, including 382 in Mumbai. 46 people were reported as missing and overall 25 lacks people in 22 states got affected due to swamping mishap been reported causing human deaths. The work presented here is to address swamping issue by flood prevention system which reports the symptoms of danger in advance so that the chances of survival will be more in affected areas. The system provides alarm in advance by giving them the knowledge of affected places and helps to point out the location of victim places, sometimes also to protect valuable properties. Usually in urban areas, when the level of water raises above a certain marked level called threshold level, the regulatory authorities issues an order to open the gutters so as to allow flow of excessive water into it. As a result, the level of the water decreases but on the contrary, people are unaware about the opened gutter. When a person inadvertently walks on the gutter, there is a possibility of a person stumbling into it. Therefore, there is a crucial need for building a system that warns the nearby person to prevent him/her from causing an accident. The major goal of this chapter is to give warning signals to the person through proposed system. It also proposes an IoT system based on Wireless Sensor Network (WSN) in which water level sensors are distributed over a region that monitors the level of the water. As soon as the regulatory authority opens the gutters, the sensor detects the change and sends the response to the base station. The base station will send a notification or an alert to the people present nearby that area. This will led the people to avoid the affected route and follow different route or walk-aside the gutter. The system consists of water level N. Patel (B) · R. Mangrulkar Department of Computer Engineering, Dwarkadas J. Sanghvi College of Engineering, Mumbai, Maharashtra, India e-mail: [email protected] R. Mangrulkar e-mail: [email protected] © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 S. C. Tamane et al. (eds.), Security and Privacy Applications for Smart City Development, Studies in Systems, Decision and Control 308, https://doi.org/10.1007/978-3-030-53149-2_10

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sensors and base station which includes Node MCU and battery for giving power. The level sensor is used to monitor the level of water from the ground which will respond when there will be an abrupt change in the level of water. The proposed system claims to be beneficial in avoiding swamping related mishaps. Keywords WSN · IoT · Swamping · Node MCU · Mishaps · Urban · Stumbling

1 Introduction A natural disaster are natural events such as earthquakes, volcanoes, swamping, hurricane, etc. Lakhs of people have lost their lives, became homeless and seriously injured. Among all the natural disasters mentioned above, swamping are the one which usually occurs every year. Around 1900 people have lost their lives and 46 people have been stated missing in New Delhi. The next state is Maharashtra where major people have lost their lives due to heavy swamping. The above mentioned figures are given by Economic Times. Swamping not only affects human beings but also disturbs animals, birds, environment, economic instability and many more. As a result, there is high need of precaution systems, rescue systems and avoidance systems. With the current trends and technologies in the domain of computers and electronics, there are several ways through which people can be notified or warned by some medium of communication. There are several research organizations, governments and private companies which are working on the issues faced during natural calamities. The proposed system is based on the domain called Internet of Things (IoT). Internet of Things (IoT) is a wide domain used for connecting several physical smart devices through internet for gathering, sharing and taking decisions on certain conditions [1]. IoT has a massive variety of applications in the field of embedded systems, Robotics, automations, etc. IoT applications bring massive worth into our lives. With increasing demands of wireless networks, sensors and advanced computing capacities, the Internet of Things might be the next frontier in the competition for its share of the wallet. Few applications using IoT [2, 3] are listed as follows, also summarize in Fig. 1. 1. 2. 3. 4.

Smart Cities Agriculture Smart Healthcare Systems Industrial Automation

Water availability is one of the key factors controlling living conditions and economic development in towns and cities. Disaster management for urban areas is one of the growing priorities of factors such as people migrating to cities, unplanned development and operational and maintenance costs [4]. Today, many people from the society have periodically raised issues regarding the security and prevention from natural disasters such as flood, earthquake, hurricane, etc. Swamping/floods are one of the dangerous natural disaster where immoderate amount of water is gathered into

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Fig. 1 Applications of internet of things

a specific location or region. The resulting consequences can give rise to damage and loss to human life [2]. During swamping, several cases have been noticed where due to the lack of safety and security many people have lost their lives, or suffered due to damage. Swamping have an effect on individuals, communities, organizations and have huge consequences on social, lucrative, and environment. The consequences of these floods can be negative and positive which varies depending upon the area and the effect of expansion in that area, and amenability and cost of the natural and developed environments they affect. Swamping are those cases where immoderate water flows into an area. As a result, it will led to a major damage to human life. Spotting of inundation and proceeding by having remedies to avoid them will often cost big sum of finance. The conventional schemes also add to the level difficulty by usage of complex readings, measurements and expensive utilities. The inundation avoidance models brought up in other developed nations are fantastically expensive and high expertise is needed to monitor and maintain the system to collect information real time and analyses [1]. Major motivation for the work presented is the damage caused by floods due to which people have lost their lives and suffered from damage. The work explores the system that can be used to avoid mishap during swamping. The model presented makes use of IoT system based on Wireless Sensor Network (WSN) in which water level sensors are distributed over a region that monitors the level of the water. When the regulatory authority opens the gutters, the sensor detects the change and sends the response to the base station. The base station will send a notification or an alert to the people present in that area. There are two things which make the proposed system different from the existing system: first, the existing systems are based on wired networks, instead the proposed system is based on Wireless Sensor Network (WSN). Second, the existing systems refers to the general prevention from swamping whereas, proposed model suggest a dedicated system developed for an avoidance of mishaps. Wireless Sensor Network (WSN) consists of sensors which are distributed in an adhoc manner. It is used for monitoring various environmental conditions, healthcare systems, smart

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homes, smart cities, traffic control, etc. WSN includes sensors nodes which are low power devices, limited memory and have energy constraints. It can be deployed in extreme environmental conditions and may be prone to enemy attacks [5]. The rest of the chapter is organized as Sect. 2 gives the detailed study of various work found in the literature, Sect. 3 talks about the smart technologies and how it related to this chapter, Sect. 4 addresses the recent issues and challenges, Sect. 5 summarizes the advantages and disadvantages based on various models found in the literature. Section 6 presents the detail idea about the proposed model. Section 7 concludes the work presented with few guidelines for further extension.

2 Literature Review In many urban areas where the level of the water rises above a marked level, the regulatory authorities issue an order to open the gutters. As a result, the level of water decreases but on the contrary side, people are unaware about the opened gutters. When a person inadvertently walks on the gutter, there is a possibility of a person stumbling into it. Another important factor to be noticed is water related problems in cities are ubiquitous but especially important and crucial in cities located in developing countries. On the contrary, there is a lack of water or poor water quality that can damage development or deteriorate the conditions and health, further threats such as increasing flooding and ecosystem deterioration due to land use changes and human pressure are spreading [6]. At present, various systems are developed for detection of the inundation and apprise people [1] and thus they are cautious for immediate reposition themselves from the current position to a safer area. The differentiating factor for the above described models lie in the technology they apply for making predictions about floods, and the medium of factor used for communication to warn the people and also the cycle used to transmit the alert message for avoidance from mishap has to cross prior to it reaches the destination. Yupin Suppakhun et.al. presented the research based on proposing an IoT model for mishap messages. Authors suggested the work about the user tools inducted in the inundation danger zone comprise of to estimate rainfall amount, level of water, and water flow rate. The predicted data gathered from all gadgets will be transmitted to cloud server via a wireless network. Authors also explained an implemented of model which was used for alerting people [7]. The inundation monitoring and warning product is programmed and interfaced so that it will be capable of showing the data values obtained from the user device by a blink light applications Ms. Jayashree S et al. presented the work based on early flood detection through an Iot system. Authors also expressed their views about the practical feasibility for the deployment of the system in rural areas. The major objective behind the development of the system is to get an early intimation of the floods so that the people can be made aware in advance [8]. Narayandas Suresh et al. presented their work to estimate the level of the flood. Authors also presented an idea with a sensor to assess the level of water in waterways.

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For the above mentioned purpose and to get clearance of the idea, they developed a simulated experimental proceeded through a demo explanation. System is developed with a prediction of the level sensor of water in vision to a simple circuit that is kept open which closes when level of water matches with the water level and substantially made an attempt to keep the water case under a supervised system [9]. J. A. Hernández-Nolasco.et al. came up with a sensor to measure water level from the sources of water. In this case, the reason mentioned and the proof of the concept, for designing the research through a small module that is developed using the level reading water sensor based on a straightforward open circuit that encloses when comes in touch with water and provisional testing into the water cast in a governed and sophisticated region as the one mentioned above. The system is executed using the Netduino plus 2 which is an electronic circuit interfaced to electrical oppositions which are situated at a certain amount of height, in a water cast [10]. O. Amale et al. proposed uniqueness of an adaptable and systematic WSN for finding out the landslides. It offers a better standard rain keeping track of low amount in context of manual investment. The research inculcates the WSN-enabled architecture for keeping a watch on the system to send, gather and share dynamic data using GPRS via a cellular network. The content is transmitted from remote stations to the server. Executing deep analysis using machine learning topic called Support Vector Machine classifier for predicting rain [11]. K. Vinothini et al. develops a system for detecting the level of water during floods to avoid accidents to human beings. The system uses Wi-Fi module for transmitting data which is interfaced with PIC microcontroller that is responsible for taking decision. The circuit is trained and tested using Decision Tree Algorithm with a high accuracy. The system achieves a high accuracy as output but the practical feasibility and the cost of system seems to be difficult and costly [12]. Dola Sheeba Rani et al. proposes a system for flood detection and alerting system. The system uses a Machine Learning model which is trained for monitoring the normal and abnormal behavioral characteristics of the external environment. The model is trained using the historical weather data for understanding the salient features for training model. The system considers two ML model i.e. Linear Regression and Support Vector Machine (SVM) for checking the performance. The hardware circuit consists of water level sensor interfaced with the warning based system. Due to the lack of results from ML models, the proposed system integrated Convolution Neural Network. The main drawback of the proposed system is processing of the data will be slow due to neural networks [13].

3 Smart Technologies During the 19th century, the definition of a normal city was an ideal city and in the coming 21st century the normal city was transformed into smart city. The development in the fields of technologies from the 18th century took a boost in urban and industrial areas [14]. Smart Technologies can be defined as technologies that are part

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of not only sending and receiving information but based on this information, it can take decisions so as to make human life more comfortable and easier. It can handle unpredicted situations in unexpected changes of the environment [6]. There has been a huge growth in domain of smart technologies such as Smart TVs, Smart Watches, Smart Phones, Smart ACs, etc. Currently, there are various issues in countries that can be resolved using the applications of Smart Technologies. However there are few dedicated organizations which provides solutions for the issues in the external environment; a smart technology using a software and hardware components can adapt to the changes internally and externally by making minor edits in the database and code [7]. Real time applications to these Smart Technologies and Systems needs a detailed study and analysis regarding the practical feasibility, cost and its associated complications [15]. In this chapter, a real time solution is proposed to one of the issues that can be resolved using Smart Technologies. The chapter discusses an issue regarding swamping in detail and proposes a smart system for the precautionary measure of the people. Although the proposed system is a system with intercommunicating devices, intelligence is added by giving the system the decision making power by processing and analyzing the data.

4 Recent Issues and Challenges The majority of models found in the literature can be categorized into Four Major categories viz. Early Flood Warning, Flood Surveillance Alert System and Flood Alarming System. The implementation, advantages, drawbacks and methods how to overcome the drawbacks will be discussed.

4.1 Early Flood Warning Elizabeth was the first to address this issue with the objective to warn people about early detection of flood so that people can get cautious so that they can rescue or avoid from getting damaged [8]. The approach is stated in the aforementioned image Fig. 2 in which it is followed by the architecture and attributes of the proposed system. The system architecture is meant to avoid various damages involving society as a whole by predicting flood. The system wants some of the nodes to be deployed across river bank and use a novel communication system which is heterogeneous in nature. This system senses and collects data in real-time and its specialty is that it possesses self-monitoring for failure detection. The system takes into consideration a number of linear regression models for the forecasting of swamping. This offers fast and accurate calculation. This is one of the advantage features of the proposed system. Floods that are caused by rainfall are the utmost consideration of the model. This model requires information of the amount of rainfall and the time dependent

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Fig. 2 Working of early flood warning system

response of soil to the rainfall, for predicting the existence of swamping. It also utilizes details of topography, composition of soil, land cover, weather conditions and other quantitative measures like the moisture of soil. Hence, the sensors must take into consideration several parameters. Since considering a lot of parameters, there might be a requirement for a several sensors, making the system more expensive. This is the drawback of this model.

4.2 Flood Surveillance Alert System The research was based on proposing an IoT model for alerts on disasters. Figure3 shows the basic working and the flow of the above mentioned system.

Fig. 3 Flowchart for flood surveillance alert system

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The system’s functions are segregated into two parts: The first part is about the equipment of the client that is fitted in the risk areas. There are modules used for the estimation of the rate of rainfall, water’s level and rate of flow. The estimated data generated from these devices will be uploaded to a cloud server via a wireless network. The latter part is based on notification and display. The flood monitoring and warning system is developed to showcase the values of data that are received from the client side through the blink and line applications [7]. The main drawback of this system is that every request is uploaded to a cloud for its processing. As a result, the time for the system to give the response increases. Instead, similar kind of requests should be filtered so that the time for the system to response decreases. This can be one of the drawbacks for the system [7]. The above mentioned Figures 2 and 3 are the existing models for the avoidance and preventive measures from flood damage. In the next part we discuss about the technologies and the proposed model to overcome the above mentioned drawbacks.

4.3 Flood Alarming System Seal et al. [8] proposes wireless sensor network based system, which implements by encircling of an alarm to warn the people about the arrival of flood by using computations and measurements to provide results in real-time. Figure 4 described the flow for the Flood Alarming System. The system utilizes multiple variable linear regressions which is simple to comprehend and inculcate. The usage of it lessens resource usage and provides high degree of accuracy for the results. The model does not impose any constraints with respect to the number of parameters. The rise in the level of water is expressed using a polynomial from which the threshold’s exceeding can detect the probability of the flood’s occurrence. The authors have also employed a time multiplier function to determine the gap in time for any two consecutive readings taken. A central node described in the model is not used in the working. The model only predicts the flood and lets out warning to the people by triggering the alarm. However, the alarm frequency and the distance the alarm’s voice covers is not mentioned clearly. Efficient energy consumption is left as a future work (Table 1). Figure 5 shows working of model. The working of system can be is divided into three parts: 1. Sensors stretched out in an area. 2. Base Station. 3. Alerting the user. 1. Sensors stretched out in an area: In this chapter, we are focusing upon a specific area. The model starts with the first phase i.e. Sensors stretched-out in an area. In this phase, a region is targeted and the sensors are placed near the gutters. The sensors are placed in a manner such that when the there is an abrupt change in

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Fig. 4 Process diagram for flood alarming system

the level of the water, the sensor will identify the change and report it to the base station. 2. Base Station: The next phase of the model consists of Base station. The base station is a complete circuit of Node MCU, battery and sending signals for communication. When the base station gets an alert from the sensor, it will check the credentials of the sensor so as to know from which sensor the message has arrived. On the basis of credential, base station will report to the next phase. The credentials will help the system to know the location of the sensor in that specific region. 3. Alerting the user: The final phase of the model is to alert the people by communicating with them. This phase of the model will send an alert message so as to make the people aware about the danger situation.

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Table. 1 Drawbacks of the existing systems Sr. No

System name

Drawbacks

1

Early flood warning

• Sensors must take several parameters into picture • Since considering a lot of parameters, there might be a requirement for a several sensors, making the system more expensive

2

Flood surveillance alert system

• Every request is sent to the cloud for processing. As a result, the time for the system to give the response increases

3

Flood alarming system

• The model only predicts the flood and lets out warning to the people by triggering the alarm. However, the alarm frequency and the distance the alarm’s voice covers is not mentioned clearly

Fig. 5 Flowchart flood alarming system

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5 Advantages and Limitations The models under study were presented in Sect. 3. The categories of models are specified accordingly. However, these models have their own advantages and disadvantages. These are described in this section. 1. Connections are less complex. (a) In the existing system, since they are based on wired networks the complexity for the connection increases. (b) Handling the system with more number of connections is difficult. 2. Installation is easy as compared to the existing systems. (a) The major task is to only place the sensor in the area. (b) The connections of the sensor and the base station is wireless, therefore making it less time consuming for installation of the whole system. (c) Since the number of wired connections is less, the circuit becomes less complex. 3. Dedicated for a single problem which is usually not highlighted. (a) The solutions given by all the existing systems are very general to the avoidance towards flood damage. (b) This system focuses on the point where due to avoidance of certain accidents, the lives of the people can be saved.

6 Proposed Model for Avoiding Mishaps Due to Swamping The models studied so far found to be depended on the internet, the delay caused by the information flow from first to the regulatory authority, followed the chain for delay to the public, electricity power-cut, complex calculations and inefficient consumption of energy and power by the alerting model are main factors which bring to a chance disadvantages [1]. The dependency on internet and continuous power supply, delay get generated during communication [1]. The proposed mishap avoidance system mainly focuses on above issues and presented the model which will surely saves life of human, by giving alarm to the people residing in nearby areas. The internal system based on alert or sound gets activated as soon as gutters are open. This alarm will used to signal people to avoid the route. Certainly, this will also help to provide substitute path to follow. The proposed system makes use of sensor network and battery assisted components connected to the gutters. The water level sensor gives the observations according to the thresholds parameters. The water level sensor basically determines the level of the water from the ground [16]. The major components in the proposed system are described as follows:

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1. Water Level Sensor Level of solidity which can flow is detected by the level sensors. The substances include liquids, powder, etc. The measurement of the level of water can be carried out within cylindrical shaped containers or it can be the level of any water-body such as river, wells, Lake Etc. [17, 18]. 2. Node MCU Node MCU is a low-cost IoT platform. It is also open source. It is basically a kind of development kit used for the developing of IoT platforms. It is simple, interactive and programmable. Mainly it consists of Arduino type hardware IO, Node JS style network API and the lowest cost Wi-Fi. This development kit is based on ESP8266and hence integrates PWM, GPIO, I2C, ADC and 1-Wire, all in a single board [14, 19].

6.1 System Architecture Figure 6 shows the detailed system architecture of proposed model. As mentioned, the complete system is divided into three phases. These are as follows: Sensors stretched out in an area. Base Station. Alerting the user. Phase 1 represents a region which is spread out with sensors near gutters. The sensors continuously monitor the level of water from the ground. When the level of water abruptly changes, the sensor will detect the change and send a report of change to the next phase. Along with the information of water, it also carries its credentials so that it the location of the sensor can be identified. Phase 2 represents a Node MCU. Node MCU is used for gathering real-time information from the sensors so to visualize and take appropriate decisions. When it receives the sign of from sensor, it also identifies its location from the details of the sensor so as to know where the gutters are opened. Once the processing is done, it sends the location details of the gutter to the Phase 3. Phase 3 represents a GSM Module. The GSM Module is used for sending SMS messages to the people present in that the area. It will send an alert saying the area and location of the gutter, inform the people that to avoid going from that route. The generalized steps are described as: 1. Monitor water level continuously. 2. If an abrupt change found in the level of the water then, a. Sensor transmits the signals to the base station. b. Base Station receives the signals from the sensor which detected change.

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Fig. 6 System architecture of proposed system

c. Node MCU identifies the location of sensor and respective gut ter on the basis of credentials of the sensor. d. Node MCU transmits the data to the GSM Module. e. GSM Module sends a broadcast message to the people present in that specific region. 3. if not, continue to sense the water level.

6.2 Implementation Model As mentioned in the above system architecture, the whole system is divided into three phases. Figure 7 shows the implementation model for the proposed system. The first block shows a water level sensor that monitors the level of water constantly. The two blocks associated with it shows the parameters and credentials for the sensor. When there is an abrupt change detected, the sensor sends an message to the next phase i.e. Base Station. When a message is sent to the base station, the message is packed with credentials and paramters. The parameters and credentials used are shown in Figure 7. When the base station receives the message from sensor, it extracts the credentials and parameters. Processing is done mainly on parameters and credentials are used for identifying the sensor and its respective location. On the basis of the parameters and credentials, a message is generated by the NODE MCU. The message is transmitted to the GSM Module which is the third phase of the system. When GSM receives the generated message, it sends the alert message to public present or residing in that affected area.

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Fig. 7 Implementation model

6.3 Case Study This section gives the detailed interpretation of the proposed model as case study. There are six scenarios describing each and every step and phase of the system. Figure 8 shows a normal scenario where rainfall is taking place. A water level sensor is placed near the gutter. The sensor will be installed in such a way that it is not damaged. It is assumed that heavy rainfall has occurred and the level of the water from the ground has increased. Figure 9 shows a case in which the level of the water has crossed the threshold value. As a result, the regulatory authority issues an order to open the gutters.

Fig. 8 Scenario-1 showing normal rainfall

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Fig. 9 Scenario-2 showing heavy rainfall and water level raised from ground level

On opening of the gutter, the water starts to flow inside the gutter, the level sensor detects this abrupt change in the level of water and responds to the base station. Figure 10 shows the regulatory authorities have raised an order for opening of the gutters. As a result, due to the abrupt change in the level of the water, the sensor sends an alert message to the base station as shown in Fig. 11.

Fig. 10 Scenario-3 regulatory authorities opened the gutter

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Fig. 11 Scenario-4 sensor transmitting signals to base station

When the base station receives the message from the sensor, it verifies the credentials and extracts the id and location of the sensor from the credentials as shown in Fig. 12. The extraction of id and location is done so as to know in which area or place the sensor is placed. A message is generated from the base station and is transmitted to the GSM Module as shown in Fig. 13. The GSM Module sends an alert message to the people present in that area.

Fig. 12 Scenario-5 data trasmitted to base staion from sensor

Fig. 13 Scenario-6 alert message transmitted to the people in effected area

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7 Conclusion Swamping is caused due to natural calamities which do not have any human control and its natural disaster. The unavoidable swamping due to natural disaster has major impact on human life. The mishaps during these situations automatically get increased. As a result of management of swamping by the regulatory authorities, few immediate actions are taken including opening of gutters. To cope up with such disaster, the proposed system presented in this chapter surely helps a lot. The proposed system bestows the best of it in above situations. So if the water level rises above the threshold level, it raises an alarm. This alarm sends message to nearby people, awakening the citizens to avoid any mishaps. Thus the system aids the regulatory authorities and helps the citizens to come out of this life threatening situation. It tries to relinquish the capabilities that would help the nation. The model proposed surely has proven advantages such as simple and cost effective solution, acting as a guard bands and as an alert mechanism. The system drop-ships all the functionalities for has a prototype working for gutters. The idea is that if the flood occurs then our system will determine all the water-prone regions where the water could be accumulated at a surplus amount. Extension of this work can be considered for providing safeguards not only during swamping, but also during regular maintains by regulatory authorities.

References 1. Jayashree, S., Sarika, S., Solai, A.L., Prathibha, S.: A novel approach for early flood warning using android and IoT. In: proceedings of 2nd International Conference on Computing and Communications Technologies (ICCCT), Chennai, pp. 339–343 (2017) 2. Chaurasia V.K., Yunus A., Singh M.: An overview of smart city: observation, technologies, challenges and blockchain applications. In: Singh D., Rajput N. (eds.), Blockchain Technology for Smart Cities. Blockchain Technologies. Springer, Singapore (2020) 3. Adu-Manu, K., Tapparello, C., Heinzelman, W., Katsriku, F., Abdulai, J.D.: Water quality monitoring using wireless sensor networks: current trends and future research directions. ACM Trans. Sens. Netw. 13, 1–41 (2017). https://doi.org/10.1145/3005719 4. Price, R., Vojinovic, Z.: Urban Flood Disaster Management. Urban Water J. 5, 259–276 (2008). https://doi.org/10.1080/15730620802099721 5. Chatterjee, S., et al.: Rainfall prediction using hybrid neural network approach. In: 2018 2nd International Conference on Recent Advances in Signal Processing, Telecommunications & Computing (SigTelCom), 67–72 (2018). 6. Biˇcevska Z.: Applying of smart technologies: evaluation of effectiveness. In: Szmuc T., Szpyrka M., Zendulka J. (eds.), Advances in Software Engineering Techniques. CEE-SET 2009. Lecture Notes in Computer Science, vol 7054. Springer, Berlin, Heidelberg (2012) 7. Suppakhun, Y.: Flood surveillance and alert system an advance the IoT. In: Proceedings of IEEE Asia Pacific Conference on Circuits and Systems (APCCAS), Bangkok, Thailand, pp. 325–328 (2019) 8. Basha, E.A., Ravela, S., Rus, D.: Model-based monitoring for early warning flood detection. In: Proceedings of 6th ACM Conference on Embedded Network Sensor Systems, ACM, (2008)

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9. Suresh, N., Babu, K.H., Prasad, S. V.S.: Flood level estimating system. In: Proceedings of International Conference on Intelligent Sustainable Systems (ICISS), Palladam, pp. 1173–1177 (2017) 10. Hernández-Nolasco, J.A., Ovando, M.A.W., Acosta, F.D., Pancardo, P.: Water Level Meter for Alerting Population about Floods. In: Proceedings of IEEE 30th International Conference on Advanced Information Networking and Applications (AINA), Crans-Montana, pp. 879–884 (2016) 11. Amale, O., Patil, R.: IOT based rainfall monitoring system using WSN enabled architecture. In: Proceedings of 3rd International Conference on Computing Methodologies and Communication (ICCMC), Erode, India, pp. 789–791 (2019) 12. Vinothini and Jayanthy, S.: IoT based flood detection and notification system using decision tree algorithm. In: 2019 International Conference on Intelligent Computing and Control Systems (ICCS), Madurai, India, pp. 1481–1486 (2019). https://doi.org/10.1109/ICCS45141.2019.906 5799 13. Rani, D.S., Jayalakshmi, G.N., Baligar, V.P.: Low cost IoT based flood monitoring system using machine learning and neural networks: flood alerting and rainfall prediction. In: 2020 2nd International Conference on Innovative Mechanisms for Industry Applications (ICIMIA), Bangalore, India, pp. 261–267 (2020). https://doi.org/10.1109/ICIMIA48430.2020.9074928 14. Mardacany, E.: Smart cities characteristics: importance of built environments components. In: IET Conference on Future Intelligent Cities, London, pp. 1–6 (2014), https://doi.org/10.1049/ ic.2014.0045 15. Priyadarshinee, I., Sahoo, K., Mallick, C.: Flood prediction and prevention through wireless sensor networking (WSN): a survey. Int. J. Comput. Appl. 113, 30–36 (2015). https://doi.org/ 10.5120/19855-1795 16. Wang, Y., Chen, X., Wang, L., Min, G.: Effective IoT-facilitated storm surge flood modeling based on deep reinforcement learning. IEEE Internet of Things J. 7(7), 6338–6347 (July 2020). https://doi.org/10.1109/JIOT.2020.2969959 17. Bajrami, X., Murturi, I.: An efficient approach to monitoring environmental conditions using a wireless sensor network and NodeMCU. Elektrotech. Inftech. 135, 294–301 (2018). https:// doi.org/10.1007/s00502-018-0612-9 18. Web link: https://www.intermap.com/risks-of-hazard-blog/threecommon-types-of-flood-exp lained 19. Web Link: https://insights.diligent.com/cyber-risk/why-board-members-need-to-take-iot-cyb ersecurity-more-seriously

Blockchain Technology and Emerging Communications Applications R. Teeluck, S. Durjan, and V. Bassoo

Abstract Blockchain is a distributed ledger technology (DLT) which facilitates peer-to-peer transaction, operating on a consensus mechanism. Each data entry is thoroughly verified and is calculated through a hash algorithm by all nodes in the networks to attain a consensus before being inserted in the corresponding block. It can be visualized as a chain of blocks holding permanent, reliable, authenticated, distributed and tamper-proof data. Often misled with the term Bitcoin, blockchain is the foundation on which crypto currencies are built. Having paved the way for crypto currencies which have boomed exponentially over the past years, the blockchain technology has way more to offer. From its creation in 2008 till recent days, this technology has evolved, introducing new possibilities such as smart contracts and smart property. Blockchain promises a massive disruption on how traditional transactions occur in diverse fields including financial technology (FinTech), Smart Cities, Internet of Things (IoT), healthcare, governance, global trade and the telecommunication sector including the upcoming 5G technology. In this chapter, we provide a clear overview on the principle behind blockchain technology followed by the state-of-the-art applications of blockchain in various sectors while laying emphasis on new emerging blockchain applications. Keywords Blockchain · Distributed ledger technology · Mining · Cryptocurrency · Smart contracts · Internet of things · Healthcare · Logistics · Governance · 5G

R. Teeluck · S. Durjan · V. Bassoo (B) Department of Electrical and Electronic Engineering, Faculty of Engineering, University of Mauritius, Moka, Mauritius e-mail: [email protected] R. Teeluck e-mail: [email protected] S. Durjan e-mail: [email protected] © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 S. C. Tamane et al. (eds.), Security and Privacy Applications for Smart City Development, Studies in Systems, Decision and Control 308, https://doi.org/10.1007/978-3-030-53149-2_11

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1 Introduction Blockchain is a distributed ledger, built over the Internet that keeps track of the ownership of assets and records transactions into immutable blocks. Hitherto, blockchain has gone through three maturity states namely starting from cryptocurrencies where it was limited to financial transactions [1]. The idea behind cryptocurrencies was to use the immutable and traceable characteristics of blockchain to provide a secure peer to peer transaction without the need of a third party such as a bank. The convenience of cryptocurrencies led to the second generation of blockchain which deals mainly with smart assets [1]. This new way of perceiving blockchain led to the development of several application prototypes which promised the disruption of many legacy systems in diverse sectors. Finally, the third generation of blockchain allows the creation of contracts [1] which allows agreements to be stored in a decentralized peer to peer manner. Figure 1 illustrates the chronology of blockchain from its ideation to its expected full maturity state in 2025. Blockchain was figured in the Hype Cycle for Emerging Technologies, 2017 published by Gartner [2], where all the promising technology having a high degree of competitive advantage are showcased. As for the technology enthusiasts, blockchain is referred to as the greatest invention since the Internet [3].

1.1 History of Blockchain The concept of distributed ledger technology (DLT) dates back to the nineteenth century [4]. The first blockchain emerged in October 31st 2008 and was created by Satoshi Nakamoto. His work was published in his paper Bitcoin: A Peer-toPeer Electronic Cash System [5]. From this stepping-stone, the genesis block was produced and the first bitcoin purchase was done in January 2009 [6]. By 2011, bitcoin reached equity with the dollar [7]. From then, there has been a mercurial increase in the value of bitcoin. Gradually, other cryptocurrencies such as Ripple surfaced in 2012, enabling instantaneous and direct transfers between two parties [8]. In December 2013, Ethereum released a white paper on the blockchain platform, enabling decentralised applications such as smart contracts [9]. In February 2014, Lightning Networks produced a white paper proposing scaling solution for blockchain, allowing Visa-like volumes by reducing transaction time for crypto payments [10]. The year 2014 proved to be ground-breaking for the demarcation of blockchain with the rise of private blockchain, which was mainly achieved by

Fig. 1 Maturity of Blockchain Technology

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extending blockchain beyond the public domain. Later R3, a DLT company was founded and led to the creation of a consortium of over 40 financial groups dedicated to the implementation of blockchain [11]. Around the same year, the Ethereum Project was able to raise crowdfunding due to its potential to create new applications. In 2015, the Linux foundation launched another consortium for the implementation of blockchain. Both consortiums aim at developing prototypes for the application of blockchain in various fields including the healthcare, IoT, governance, food sector, financial institutes and the telecommunication sectors. Some prototype projects went viral, attracting attention of big firms towards blockchain solutions. As a matter of fact, according to a survey conducted by Accenture in 2019, 19% of telecommunications industries believe that implementing blockchain can be impactful to their respective firms [12]. In the telecommunication industry, blockchain has proved to step out of its proof-of-concept and pilot stage through different platforms developed by consortiums of telecommunications giants. However, blockchain can still be considered as an emerging technology that has more to offer before attaining its fruition. Figure 2 depicts the stages of blockchain from its conception up to the present-day hype.

Fig. 2 History of Blockchain Technology

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1.2 Motivation In literature, most of the reviews cover mainly the use of blockchain as smart contracts and crypto-currencies. However, the implementation of blockchain expands beyond FinTech applications and is the foundation of many next generation technologies. The unique tamperproof audit that blockchain introduces gives a new dimension to security in diverse sectors such as IoT, healthcare, governance, global trade and the telecommunication sector. This chapter provides an in-depth review of the current application of blockchain in the industry and provides a clear understanding on the use of blockchain applied to communications beyond cryptocurrencies. We have gathered information through diverse whitepapers, patents, forums, industry press releases and articles in order to paint a clear picture of how blockchain is being implemented in diverse fields. Furthermore, towards the end of the chapter, we provide a holistic discussion on the limitations of blockchain.

1.3 Chapter Outline This chapter is organised as follows. Section 2 introduces the blockchain technology, illustrating all the major components, its different architectures and the different blockchain platforms available. Section 3 is solely focused on blockchain applications revolving around IoT, healthcare, traceability, logistics, smart ownerships, and governance. In Sect. 4, the limitations of blockchain is discussed and Sect. 5 assesses the applicability of blockchain technology of diverse applications. Finally, Sect. 6 concludes the chapter.

2 Blockchain Technology 2.1 Components A blockchain can be compared to a log in which records are batched into timestamped blocks. Each block contains a hash, the hash of the previous block, an index, a timestamp, the data and the hash of the data as shown in Fig. 3. For a block to be considered valid, each block should perfectly reference the previous block’s hash [13] hence creating the link between the blocks and giving rise to the term blockchain.

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Fig. 3 Blockchain representation

2.1.1

Hash

A hash function produces a string of alphanumeric characters of fixed length based on the input data. The concept of hashing dates back to the 1990s when NIST (National Institute of Standards and Technology) in collaboration with the NSA (National Security Agency) published the first secure Hash algorithm, ‘SHA1’ in May 1994 [14]. A hash can be easily calculated from a given message but impossible to build the message given a hash value. A hash is unique to the message and even the slightest modification made to the message will completely change the hash value. Blockchain makes use of this unique property of hash to ensure security and data integrity. As illustrated in the Fig. 4, the hash of a block is calculated by taking as argument the previous block’s hash, index, timestamp, and a hash representing the data.

2.1.2

Mining of a Block

The process of adding a new block to the chain is known as mining. Since blockchain networks are decentralised P2P networks with no central authority, all nodes need to abide to a consensus mechanism for decision making. Consensus mechanisms vary depending on the type of the blockchain network. Some consensus mechanisms are reward based and some are not. For example, in a public blockchain architecture such as the bitcoin blockchain, nodes compete against each other to solve a crypto-puzzle in exchange for reward. As soon as a node finds a valid hash for a block (by solving the proof-of-work), it appends the block to its local blockchain and broadcasts the solution. Upon receiving the solution, all the other nodes of the network check for the authenticity of the block. If the solution is correct, the block is updated on all local blockchains of the decentralised network, consensus is met and the reward is

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Fig. 4 Hash computation in Blockchain

auto generated for the solving miner. If the solution is incorrect, consensus is not met and the block is simply rejected.

2.1.3

Consensus Mechanisms

• Proof-of-work: In proof-of-work (PoW), miners attempt to solve a complex cryptographic math puzzle which is based on Adam Back’s Hashcash. PoW scans for a 32-bit value, called a nonce, which is specific to a message, showing that the miner has put in enough effort and resources in mining the block. The first miner to find the solution to the PoW is rewarded. PoW can also be considered as the main pillar of security in public blockchains like bitcoin, as it acts as a protection shield from denial-of-service attacks and hackers from sneaking in the network. • Proof-of-stake: Unlike proof-of-work, the creator of the new block, referred to as a validator, is determined on the wealth known as the stake [15]. Only selected validators are allowed to mine new blocks to the chain thus reducing the power consumption involved in mining. Conversely, no reward is given, so, validators take a transaction fee as reward. Validators are bound to mine honestly, else they lose their stake. • Delegated proof-of-stake: All participants have the right to be included in decisionmaking, thus known for acting as a digital democracy. Real-time voting is used in combination with a social system of reputation to attain consensus [16], hence considered as the least centralized consensus protocol. Every node has a fair share of judgement and opinion with this particular consensus protocol. In simpler terms, each node votes for a validator which will be responsible for mining new blocks and collecting rewards.

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• Proof-of-resonance: This requires a coordinated system of 50% + 1 nodes to achieve consensus, that is, nearly one half of the entire network [17]. It eases the validation of other shards. All participants in this network are rewarded equally. • Proof-of-importance: Several participants are elected as miners, based on the number of coin they own, through a process known as harvesting. This is done by choosing nodes with higher importance score and this score is calculated by the NEM (New Economic Movement) protocol [18]. • Proof-of-activity: It is an amalgamation of both proof-of-work and proof-of-stake. The mining process starts with a standard proof-of-work and once the miner is determined, the system switches to proof-of-stake [19]. The mined block, compared to traditional mining, does not contain any transaction but instead, a header and the miner’s reward. From the header information, a random set of validators will be chosen, based on the number of coin they own, to sign the block. The reward is then split between the miner and the validators. • Proof-of-burn: A consensus mechanism which contributes in the proper and ethical functioning of each transaction. It prevents chances of double spending whereby it follows the principle of ‘burning’ the coins held by miners which grant them mining rights [20]. Miners are rewarded according to the amount of coin burnt. • Proof-of-elapsed time: Often used in permissioned blockchain. It is mainly based on a principle of a fair lottery system where each participant has a fair chance of becoming the leader [21]. The leader is responsible for the mining of new blocks. Each node is allocated with a duration of a specific time period during which that node will have to enter a hibernation state and the first one to wake up after that allocated time completion will be declared as the leader. In other words, the one with the shortest waiting time will be the winner provided that the particular participant succeeds in fulfilling the task during the given time. • Proof-of-authority: It is a form of proof-of-stake whereby the validator’s identity is mostly used to perform the role of stake rather than with the monetary value [22]. In other means, the authenticity of the validator is checked to make sure that it is the exact same person. A person can only have one specific identity, thus there is no possibility of forging it. • Proof-of-storage: it is similar to proof-of-work but the only difference is that it uses storage instead of computational power. A lower energy cost is required which is a beneficial factor. The miner should prove that an amount of space has been saved and allocated for data in the blockchain. It is prominent for malware detection, spam detection and denial of attacks. • Proof-of-solvency: It is particularly helpful for the integrity of customers’ savings. To ensure that customers do not lose all their savings permanently and have a smooth transaction, proof-of-solvency controls each customer’s account to verify that the correct amount is credited or debited [23]. • Proof-of-reputation: This consensus checks the ‘reputation’ of the participant before giving access to that participant. Somehow, it adds a layer of protection over the network, providing more security and more reliability [24]. It can be inferred

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that it is another way to prevent 51% attacks. Once the proof-of-reputation is checked, afterwards proof-of-authority comes in to prove the identity of the node. 2.1.4

Smart Contracts

Smart contract is an application that runs on the blockchain network and is composed of self-executing statements that consists of a set of if-else statements imposed by their issuer. Once all the conditions of the contract are met, they are automatically executed, speeding the transaction processing time. Since smart contracts are decentralised over the blockchain network, this improves transparency and clear communication among participant nodes. To ensure reliability of a smart contract, the use of asymmetric keys is implemented. Since the first smart contract platform, Ethereum, was released in 2013, this has led to a significant interest by blockchain innovators, paving the way to the new blockchain generation, Blockchain 2.0. Today, many blockchain applications (public or private) make use of smart contracts reducing paper works and enforcing trust between entities. Smart contracts are disrupting the way traditional business models function. In a traditional business model, any transaction between a buyer and a seller requires the intervention of a trusted third party to verify and approve the deal officially. A transaction may include one or more trusted parties to validate a deal (bank, notary, insurance company) making it a lengthy process. Furthermore, each middleman charges a fee for their services, making the deal more expensive. Smart contracts allow anonymous parties to carry out secure transactions and agreements without the intervention of a central authority or legal body. A smart contract is enough to track and trace a transaction in a transparent and irreversible manner. Let’s take the example where user A wants to send an item to an untrusted user B. User A generates a smart contract identified by A’s public key specifying the requirements that need to be met. Finally, A signs the contract using his private key and the contract is then sent to the blockchain network. If a user B matches the requirements imposed by the smart contract, user B signs the smart contract with his private key. This transaction is once more sent on the blockchain network for approval. If all the nodes agree that the requirements were met, the transfer of ownership is approved and B becomes the new owner of the item. To illustrate this process, Figs. 5 and 6 compare the sale of a car between Bob (the owner) and Alice (the buyer) without and with smart contracts respectively.

2.2 Blockchain Architecture Blockchain does not come up with a completely new paradigm but it extends the idea of the old typical ledger used in the 1990s. Typical ledgers are centralised in a way that they are owned and controlled by central entities normally known as an administrator. The administrator has jurisdiction upon implementing changes to the

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Fig. 5 Traditional business model

Fig. 6 Smart contract business model

ledger without seeking consensus of the ledger’s stakeholders. Blockchain, however, completely eradicated the concept of centralization by bringing forward the concept of decentralization and distributed networks. Instead of storing every transaction and data over a single server, like banks or governments, blockchain utilizes a decentralised database which is distributed over a network of nodes. Blockchain networks can be either public, consortium or private. Figure 7 portrays the three types of

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Fig. 7 Blockchain architectures

blockchain architectures. Public blockchains can also be termed as permissionless blockchains. Any host on the Internet can join the network and contribute to the computing power without any extra permission required for reading and sending a particular transaction over the network. Furthermore, cryptoeconomics [25] secure public blockchains, due to the amalgamation of economic rewards and cryptographic verification such as proofof-work. In simpler terms, nodes are incited to contribute to the computing power of solving the proof-of-work as well as participate to the consensus process in exchange of a reward. Since public blockchains are open to everyone, their networks are highly distributed making it suitable for applications such as cryptocurrencies. However, this makes the network vulnerable to some threats such as the ‘51% attack’ [26]. Popular public blockchain networks are Bitcoin blockchain and Ethereum blockchain. In Consortium blockchains, only a preselected set of nodes have control upon the consensus process. The right to read the blockchain may be public or restricted to participants [27]. As a result, they are referred as partially decentralized or federated networks. Consortium blockchains are typically implemented among financial institutions. Each new block needs to be digitally signed by a majority of the institutions being part of the consortia before being approved. Since consortium is restricted to some preselected, trusted nodes only, this eliminates threats such as the ‘51% attack’ on the network. Since all miners are known, if a particular miner is suspected of performing a malicious activity, the miner is subjected to an investigation and can even be removed from of the consortium. Some applications of consortium

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Table 1 Blockchain architecture properties Property

Public blockchain

Consortium

Private blockchain

Consensus approval

At least 50% of the network

At least 50% of selected nodes

At least 50% of the specific institution’s nodes

Read permission

Public

Might be public or private

Completely private

Efficiency

Low

High

High

Throughput

Low

High

High

Latency

Slow

Moderate

Moderate

Number of nodes

High

Moderate

Low

Number of trusted nodes

None

Low (consortium nodes only)

High

Centralized

Decentralized and distributed

Partial

Fully centralised

blockchain to this date are: (i) Quorum, an Ethereum-based enterprise distributed ledger platform, (ii) Hyperledger, a Linux Foundation project which aims to support cross-industry blockchain technologies, (iii) R3 s Corda, an open source blockchain project designed particularly for enterprise use, (iv) Digital Assets Holdings for the mutualisation of financial market data and finally (v) Ripple, a cryptocurrency allowing quick payments between two parties. In Private blockchains, write permissions are kept centralised to one organization known as the certificate authority. This authority reserves the right to change the rules of a blockchain (including the consensus mechanism), revert or modify transactions. Participants need to obtain an invitation or permission to join the network before accessing the blockchain network [28]. The access control mechanism could vary according to the central authority’s criterions. The level of involvement (including data request or data mining) will be decided based upon the certificate offered by the central authority. This kind of permissioned blockchains are commonly used by private businesses for applications such as database management and auditing. Table 1 shows a summary of the properties of the different blockchain architectures.

2.3 Blockchain Platforms 2.3.1

Hyperledger

Hyperledger is a hub hosted by the Linux foundation whereby communities of software developers and companies join hands to build blockchain frameworks [29].

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Table 2 Hyperledger projects Hyperledger project

Description

Fabric

Hyperledger fabric is a project led by IBM. The project was developed on Go [30] and was designed as a consortium blockchain with different degrees of permissions. Fabric mainly uses smart contracts, called Chaincode [31], which contains all the rules and business logics. Furthermore, it also provides modular implementation whereby different components of blockchains such as consensus and membership services can become plug-and-play. With such flexibilities, Fabric allows enterprises to setup their blockchain network based on their specific requirements. Commonly referred to as the IBM blockchain platform [32], Fabric is the backbone of many blockchain application platforms including TradeLens and FoodTrust

Sawtooth

Hyperledger Sawtooth is a project led by Intel. The project is developed on Python and is designed to support both permissioned and permissionless blockchain applications. It allows application developers to design contract logic, in any programming language, to suit their specific needs [33]. Furthermore, Sawtooth introduced. Proof-of-elapsed time (PoET) [34] as a new consensus mechanism enabling quicker consensus and lower computational power requirements for the mining process

Indy

Indy is a project that is still in the development phase. This permissioned blockchain is a collection of tools and libraries, designed to provide quick and affordable distributed identity management tool [35]

Burrow

The Burrow project is a concept that permits multiple chains to run in parallel without any interference [36]. Burrow makes use of smart contracts and Tendermint consensus mechanism [37]. Furthermore, it provides a smart contract interpreter that is developed to interpret the Ethereum Vitrual Machine [38]. It is customizable to the business needs ranging from logistics, supply chain, voting, up to Decentralized Autonomous Organisation (DAO)

Iroha

Iroha project is mainly tailored for the use of distributed ledgers and digital asset management systems [39]. It makes use of a consensus mechanism called YAC [40] (Yet Another Consensus). Iroha specifically deals with financial sector and provides fast services with high level of security and privacy. Furthermore, Iroha integrates easily with existing platforms such as SQL, thus facilitating implementation

Hyperledger consists of over 100 members originating from diverse sectors including technology firms, financial institutions and blockchain startups (Table 2).

2.3.2

Ethereum Blockchain

Ethereum is a protocol that adds an abstract foundation layer on top of blockchain whereby state machine concepts can be built [41]. It allows anyone to write smart contracts and define their arbitrary rules based on mathematical computations. As a result, Ethereum provides modularity and can be the building block of various

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applications. A typical Ethereum transaction contains the message recipient, the sender’s signature, the amount of ether transacted, a startGas value indicating the maximum allowable number of transactional steps and a gasPrice value indicating the price per computational steps [42].

2.3.3

Azure Platform

Microsoft Azure blockchain service provides a platform on which custom blockchain applications can be built within a few clicks. Azure blockchain service simplifies the creation, management and governance of consortium blockchain networks [43]. This blockchain-as-a-service platform is fully based on the Ethereum protocol which allows the user to define consortium policies suited for their needs. The first ledger available on the Azure blockchain, developed in partnership with JP Morgan [44], is Quorum [45]. Quorum is currently implemented by Starbucks, Louis Vuitton, and the Xbox Finance team [43].

2.3.4

Ant Blockchain

Ant financial is an e-commerce company under the control of Alibaba Group that launched a blockchain backend-as-a-service platform in 2018. The Ant blockchain platform is suitable for e-billing and offers five BASIC services (Blockchain, Artificial Intelligence, Security, Internet of Things, and Computing) [46]. E-billing ensures perfect security, keeping a ledger with clear.

2.3.5

Dragonchain

Dragonchain is a blockchain network which operates with a token called Dragon in order to perform several tasks and transactions. Dragonchain ensures the safety and security of transactions and even protects stored data. Moreover, Dragonchain provides the scope and possibility of easily creating and generating smart contracts through Dragonchain platform which supports many widely used existing coding languages [47]. The main services that Dragonchain offers are: identity management, data security and safety, ticketing management, decentralization, digitized voting system and other financial services.

2.3.6

Energy Web Foundation

The Energy Web is an open-source, scalable blockchain platform specifically designed for the energy sector’s regulatory, operational and market needs. It provides a shared digital infrastructure for the energy and blockchain community to build and

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run their solutions. Along with Affiliates and the Community the Energy Web Foundation is using blockchain’s potential to accelerate the transition to a decentralized, democratized, decarbonized, and resilient energy system [48].

2.3.7

VAKT Platform

VAKT is a digital platform built specially for crude oil trades [49]. This platform is designed to develop trust between two untrusted parties having to share information they need in order to take individualistic decisions. Being a universal trade platform, VAKT corroborates the relationship between three banks and nine leading oil and energy companies. VAKT gives a full-fledged update of post trade management and also ensures a secure trade in an integrated banking marketplace.

2.3.8

Ripple Payment Network

Ripple payment network is a payment network allowed to make payments using tokens such as I Owe You (IOUs) the native currency XRP, or any type of cryptocurrency [50]. There is no need of having a trusted relationship between gateways in a Ripple network. Transactions can be carried out smoothly since the network operates on a consensus basis rather than on mining. This is achieved by the participants in the network, who take snapshots of the transaction between gateways and publish them publicly to check for the authentication. Atleast 80% of the validators should agree upon the transaction using the Ripple Protocol Consensus Algorithm (RPCA).

2.3.9

Blockchain Mobility Consortium

Mobi is a consortium platform for blockchain innovations in the mobility sector. It was created by automaker giants including Ford, Renault, GM and BMW. The mobi consortium consists of blockchain start up organisations such as IBM, Accenture and Consensys [51]. The aim of this consortium is to develop blockchain applications enabling tracking of car parts, verification of car identity, path planning and obstacle mapping for autonomous driving cars and autonomous micropayments capabilities [52].

3 Blockchain Applications In order to paint a clear picture on how blockchain is implemented in various sectors, this section reviews its major applications in diverse fields including telecommunication, health care, real estate, global trade and governance. The applications are drawn from a variety of scenarios and attention is brought to specific blockchain platform.

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Some of them are built on top of the major blockchain platforms such as Ethereum or Hyperledger, while some are custom made to suit specific purposes.

3.1 Blockchain and IoT The need for decentralisation of data in IoT devices is widely achieved by using cloud platforms. It allows IoT data to be stored on different servers in a distributed manner, facilitating ease of access. However, the major downsides of this technology is the vulnerability to cyber-attacks such as account hijacks, malware delivery and data leaks [53]. Participants are not aware and cannot verify how and where their personal data is being used. The authors in [54], through their paper on IoT security, shed light upon most of the possible threats that the IoT system has faced, ranging from low to high-level security issues. The characteristics of blockchain has brought great interest to the IoT sector to leverage the lack of security problems. This has given rise to alliances between companies working towards implementing blockchain to improve IoT systems. The Trusted IoT Alliance [55] is one of the major consortiums which aims to create an IoT ecosystem with security, interoperability, scalability, and improved performance using blockchain systems.

3.1.1

Blockchain Solutions for the IoT Sector

While IoT data security and privacy challenges are well defined in [56], the improvements that blockchain may bring to the IoT sector are as follows: • Decentralisation: The shift from a centralised network to a decentralised P2P architecture will highly improve data sharing, eliminating central point of failures and bottlenecks. In addition, since the data will not be owned by one big company, this will reduce the number of cases whereby big companies sell the data of their users. • Identification: Using a common blockchain network, IoT devices will be able to uniquely identify themselves. A blockchain has 160 bits address space which generates a unique hash of the public key using ECDSA (Elliptic Curve Digital Signature Algorithm). With a 160-bit address space, in comparison to IPv6 which only has a 128-bit address space, blockchain address space can generate more than enough addresses to provide a secure GUID (Global Unique Identifier) which does not require any registration from a central authority such as Internet Assigned Numbers Authority (IANA). This blockchain solution is more scalable when it comes to IoT devices, since according to the authors in [54], IoT devices might be unfit to support the IPv6 protocol stack due to their memory capacity constraints. • Autonomy: Blockchain has allowed the development of smart autonomous assets. Using smart contracts, digital wallets and proper consensus mechanisms, devices

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are capable of interacting with each other without the involvement of a server or human interaction. The authosrs in [57] propose a new autonomous E-Business model integrating blockchain to IoT. They adopt distributed autonomous corporations (DACs) as the transaction entity to handle the sale of data and smart property. In their model, they shed light upon how a DAC can interact directly and autonomously with other DACs or human, by exchanging data for IoT coins, using smart contracts. • Reliability: The key aspect that blockchain brings to IoT is data reliability. Sensor data on the chain can be trusted since the sensor nodes have to identify themselves using their private keys before sending data to the chain. Furthermore, existing data on the chain cannot be modified or tampered with due to the decentralised nature of blockchain. • Security: It is computationally impossible to tamper sensor data found on the blockchain. However, main security breaches can occur while communicating data between sensors and servers on the network. The communication protocol (HTTP, CoAP, MQTT, and XMPP) and routing related protocols (RPL, 6LoWPAN) used in IoT are not secured by nature and they have to rely on complex security protocols such as DTLS, TLS or IPSec to ensure security [54]. Such security protocols are resource intensive requiring lots of memory space. In a blockchain approach however, a device could use its GUID and its pair of asymmetric keys to encrypt its communication. Therefore, the use of blockchain gives rise to a lightweight security protocol with low processing power suitable for sensors. 3.1.2

Blockchain Integration in the IoT Sector

The challenging part of blockchain and its integration to IoT is deciding upon the way interactions take place. According to the authors in [58] the interactions can be IoT-IoT, IoT-Blockchain or using a hybrid approach which encompasses IoT and blockchain as well as emerging technologies such as Fog computing. The three blockchain interactions, shown in Fig. 8 are explained below: • IoT-IoT: In this approach, discovery and routing mechanisms are used to set up communication between sensors. This leads to low latency interactions between sensors, allowing them to communicate without using the Internet [58]. In this approach, blockchain is only used for storing the sensor data in a reliable and secure way. • IoT-Blockchain: In IoT blockchain interaction, every single node interaction is done through the blockchain. Using the 160-bit address space found in the blockchain header, sensors are able to identify themselves uniquely through the blockchain network, increasing the autonomy of sensor nodes. Furthermore, all the sensor data and sensor transactions are traceable, immutable and transparent to every device found on the blockchain network. • Hybrid Approach: In a hybrid approach, part of the transactions take place through the blockchain and the rest of the transactions take place directly between

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Fig. 8 Blockchain interactions in IoT

IoT devices using discovery and routing protocols. This approach is more suitable for applications in a way that it provides both low latency transactions between sensors as well as the security aspect that blockchain provides. Furthermore, a hybrid approach could make use of technologies such as fog computing or cloud computing to compensate for the limitations of IoT and blockchain. Computationally expensive processes such as mining could be performed on the fog while complex data computations could be performed on the cloud. 3.1.3

Smart Cities

Advancement in IoT has allowed the introduction of smart cities, involving the interconnection of autonomous systems, distributed and control systems to support heterogeneous networks for intelligent information processing [59]. To overcome the security limitations of current smart cities, the authors in [59] propose a hybrid architecture combining blockchain and software defined networking. The hybrid network comprises of two main different nodes namely the core node and the edge node, each having its SDN controller, as illustrated in Fig. 9. The core nodes are the miner nodes responsible for the creation of new blocks and verify the PoW. These nodes possess high computational and storage resources. Edge nodes on the other hand are limited in resources and act as centralised servers for public infrastructures such as smart homes, smart buildings, smart traffic, smart parking, smart industries and smart hospitals. The distributed network in the core allow resiliency against attacks even when one of the nodes is compromised. However, there is a centralised trust between the edge node and the IoT devices. This allows the edge nodes to store access policies and credentials, leveraging traffic from the core, thus reducing latency and bottlenecks. The large amount of data generated by the IoT devices are sent to the edge nodes in real time. The edge routers filter, pre-process and encrypt the raw data before forwarding it to the core network. The miner nodes will then analyse, validate and

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Fig. 9 Hybrid Network Architecture for Smart City [59]

calculate the PoW of the data before generating the block that will be appended to the blockchain. The architecture of a smart city can be broken down into four security framework layers namely Physical, Communication, Database and Interface layer respectively [60]. At the physical layer, which comprises of sensors and actuators, there is no single standard defined for security and the standards are dependent on the manufacturer. However, security on the communication layer is bound to well defined standards such as IEEE 802.11, IEEE 802.15, Ethernet, 6LoWPAN among others. Blockchain is deployed on the database layer. Each record is assigned a timestamp and is identified by a unique digital signature. However, the two types of blockchain that can be implemented are permissioned or permissionless. It is not advisable to opt for a public ledger (permissionless) as it takes more time to reach consensus and may be subjected to unknown attacks. Finally, the interface layer is dedicated mainly for smart applications, which interoperate in effective decision-making. These applications are also exposed to attackers in the system hence, strong security mechanisms should be integrated.

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3.2 Blockchain and Healthcare Blockchain, being a nascent technology is invading the healthcare domain, reinforcing the privacy and security of patients’ data. Personal data of patients are sensitive and are prone to cyber-attacks, like in cases of the WannaCry ransomware attack [61], data breach in Orlando-based orthopaedic center [62] and the interception of a third party in Nuance healthcare company [63]. The book in [64] illustrates various models to strengthen data management and data security of medical data being communicated on private and private cloud platforms. In [54], a hybrid blockchain system was proposed. The prototype consists of a fully private blockchain and a consortium blockchain. Data in fully private blockchain is private and confidential to every node in the network and only authorised users have access to shared information of patients. On the other hand, consortium blockchain is mainly focused on building a trust among nodes, hence reaching on a mutual consensus. All visiting patients possess both a public and a private key. On a similar note, all nodes share a private and a public key to encrypt and decrypt sending and receiving data respectively. This is known as asymmetric cryptography and is mainly helpful for the ensuring the privacy and intergrity of patients’ data. As per a study carried out by IBM, 16% of healthcare executives are estimated to have implemented blockchain solutions, while around 56% are planning to opt for blockchain by 2020 [65]. Blockchain is being used and moulded into the following main functions: anonymising data, securing data, traceability of data, data management and data transparency. These attributes will enable security for Wireless Sensor Networks (WSN) in the healthcare industry allowing real-time monitoring of remote patients [66].

3.2.1

Anonymising Data

In processes such as population health data, where medical information of a particular demographic needs to be shared with full anonymity, blockchain technology will promote security, real-time data sharing, interoperability, and data integrity. This will incite people’s participation in health studies, exchanging their data against tokens. With more data sets across diverse populations, through Artificial Intelligence and machine learning algorithms, widespread risks of the population health will be discovered.

3.2.2

Securing Data

The healthcare sector has been vulnerable to several attacks as explained in the first part of Sect. 3.2, due to their highly centralised architecture, representing a single point of failure. Phillips Healthcare, considered as one of the healthcare giants, came up with blockchain technology as a solution extending the concept of a decentralised

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network that will prevent malicious parties from impinging into the network without authorisation. The architecture designed for such kind of blockchain is a hybrid health blockchain, with mainly two types of blockchain: namely consortium blockchain and private blockchain, to strengthen secure storage and secure share of medical data. In this way, the participants in the blockchain network are chosen upon trust, and the mining process is reserved to a predefined consortium among health institutions, thus preventing unknown parties from viewing or modifying patients’ data.

3.2.3

Traceability of Data

In the pharmaceutical industry, the dissemination of counterfeit drugs is a serious problem. According to the World Health Organisation, “10% of the worldwide medical products circulating in low- and middle-income countries are either substandard or falsified” [67]. Counterfeit drugs might contain the appropriate active ingredients, but usually, the dosage amount is either too high or too low, or might even be manufactured without respecting pharmaceutical standards. The consumption of such forged drugs can even lead to death, henceforth big pharmaceutical industries have applied a number of other technologies including the use of Radio Frequency Identification (RFID) tags [68] to demarcate genuine products from counterfeit ones. However, in the existing solutions, there is still a central authority which can be compromised or documents which can be faked. For this reason, Hyperledger came with a project to trace drugs using the blockchain technology. Every transaction that will be present on the chain will be immutable and timestamped. This will ensure that any drugs whose data are present on the chain can be easily traced and authentified. The mining of new blocks are reserved to a consortium of trusted pharmaceutical laboratories only, implying that counterfeiters are not allowed to insert transaction on the chain. However, for transparency the blockchain can be read publicly. This way, just by scanning a QR code, any consumer can view the blockchain and verify the provenance of the medicine.

3.2.4

Data Management

The healthcare system is a complex system with multiple entities and patients are required to share their personal data and health records across several platforms. In the US, the Health Insurance Portability, and Accountability Act (HIPAA) imposes strict regulations concerning the privacy of a patient’s data, urging that the patient’s health data should be secured from breaches and any kind of modifications [69]. The introduction of blockchain to this data-centric system resolves many issues. The authors of [70] propose a healthcare blockchain solution for Fast Healthcare Interoperability Resources (FHIR), which is an emerging standard that depicts data formats and elements, along with providing publicly accessible Application Programming Interfaces (APIs) for the purpose of exchanging Electronic Health Records. In their work, they shed light on a consensus protocol Proof of Interoperability. The

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Proof of Interoperability consensus verifies that incoming messages are interoperable with regard to a known set of structural and semantic constraints defined by the FHIR profile. For a secure sharing of data between entities, the healthcare blockchain uses smart contracts and SHA256 to validate transactions. This way, patients are able to share their personal health information in full anonymity and securely. Likewise, with the emergence of newer technologies such as mobile computing and wireless sensing, data management in the healthcare industry has become more complex. This has given rise to the concept of pervasive social network (PSN) based healthcare which involves sharing the collected data by medical sensors. Taking into consideration the computational limitation of sensor nodes for advanced cryptographic protocols, the authors in [71] propose a blockchain solution for PSN-based healthcare. In their system, the healthcare blockchain is stored on the most powerful nodes of the PSN-based healthcare system. The healthcare blockchain stores and shares network consensus that specifies the addresses, contributors and affiliations of health data. Only authentified PSN nodes are allowed to access health data of other nodes through the addresses. For the authentication of nodes, the authors propose an authenticated association protocol based on IEEE 802.15.6. Two types of nodes are illustrated in their model as shown in Fig. 9: (i) the user nodes that generate broadcast healthcare transactions, including addresses of the coordinator and medical sensors data, which is then hashed, from the Wireless Body Area Network (WBAN) area to the PSN area and (ii) the miner nodes which are more powerful user nodes, responsible for the generation of new blocks and transaction verification.

3.2.5

Data Transparency

When it comes to research of a new cure, clinical trials need to be conducted and the effectiveness of the given medicine should be tested within a predefined statistical range of acceptance. In order to prove the effectiveness of a medicine on a specific disease, tests and hypothesis testing are carried out respectively on a population sample. Upon a successful trial, the treatment can be extrapolated to a larger scale and this implies a huge amount of data sets. Moreover, in many cases, pharmaceutical companies acting in bad faith hide or modify the collected data in order to reach the required range of acceptance. In order to bring fairness and transparency into clinical trials, researchers can use blockchain technology for more secure, unbiased and clear clinical trials.

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3.3 Blockchain and Asset Traceability 3.3.1

Everledger

Everledger provides a digital and global ledger to keep track of provenance of high valued items [72]. Using the power of IBM’s blockchain (which implements the Hyperledger fabric), all information about the assets and their respective ownership is stored on the blockchain network. This information can be viewed by the owners or stakeholders, to track their assets. Everledger started with the diamond industry by ensuring that the authenticity of the asset is secured and stored among all industry participants. Everledger was able to create a digital thumbprint for individual diamonds by capturing over 40 metadata points which is then recorded on their blockchain as soon as they come out of the factory. For a better understanding of how the Everledger functions, let us take an example of a simple scenario as illustrated in Fig. 10. In this scenario, the diamond factory refines a diamond which is then registered on the Everledger network by creating a unique identity using +40 metadata points. Bob buys this newly refined diamond, registers it on the Everledger network. At this stage, a unique identity is created using the +40 metadata points and Bob’s credentials called the hash function, which is then saved in the Everledger blockchain. After buying it, Bob insures it in an insurance company which records the required data in the insurance company ledger and in doing so, it verifies its ownership from the Everledger blockchain to ensure its authenticity. Bob’s diamond gets stolen and he reports it to the insurance company, where a compensation is granted to Bob in return of the stolen diamond. The insurance

Fig. 10 PSN network implementing Blockchain

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Fig. 11 Everledger process of tracking valued items on Blockchain

company changes the ownership of the lost diamond and in addition, notifies the Everledger blockchain about the change. Charlie, the thief, attempts to sell the diamond to a jeweller, who in exchange, requests for an ownership verification in the Everledger blockchain. Upon verification, using the +40 metadata points, the Everledger blockchain recognises the stolen diamond. Charlie is identified as the thief and the Everledger notifies the insurance company, returning the diamond righteously (Fig. 11).

3.3.2

Provenance

Project Provenance Ltd developed a prototype on the Ethereum blockchain platform enabling the traceability and certification of goods across the supply chain. Provenance allows manufacturers, as well as end consumers to track the origin of products and confirm their authenticity through their immutable ledger of previous records. Provenance provides certification and audit of goods by tracking six major actors involved in the supply chain namely: producers, manufacturers, registrars, standard organisations, certifiers and auditors, and finally, customers [73]. Each of these actors are required to log every transaction the product undergoes on the blockchain, signing with their private key to authentify themselves. In this way, blockchain prevents any attempt of frauds or counterfeits products on the market, since all the product’s history is transparently available to all participants on the blockchain network.

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Power Ledger

Power Ledger [74, 75] is an Australian blockchain-based platform for energy trading. Conscious that the sheer control and manipulation of non-renewable energy has always been a difficult task to realize, with blockchain, energy is under tight and close supervision, and is also being regulated to avoid all means of energy wastage. The peer-to-peer architectural ledger offers the recording of all transactions of energy consumers in real-time. Power Ledger platform uses two coins: Power Ledger Token and Sparkz. The platform supports two types of blockchain such as the public Ethereum blockchain, and the private consortium blockchain, Ecochain. Power Ledger recently teamed up with Japan and is all set to incentivize energy consumption in Japan after 2011 Fukushima Nuclear disaster.

3.4 Blockchain and Logistics 3.4.1

Global Trade

Global trade is a complex process whereby goods have to transact between many intermediaries, including land transportation providers, freight forwarders, brokers, governments, ports and ocean carriers before reaching the desired destination. Point to point communication between these intermediates takes time and this slows down the trade process. A survey carried out by Maersk, the world’s largest shipping company, showed that a simple shipment transaction of refrigerated goods from East Africa to Europe transact through nearly 30 people and organizations giving rise to more than 200 different interactions and communications [76]. On the same wavelength, another survey by the Dutch Institute for Advanced Logistics showed that a simple trade from China to the Netherlands took 40 days at sea and an additional 14 days to process the paperwork. In order to ease transfer of paperwork and provide a transparent platform to all intermediaries, Maersk partnered with IBM to bring blockchain to global trade, providing end-to-end tracking of containers. The IBM-Maersk private blockchain, named the TradeLens platform, allows all transactions to be stored in an immutable manner, providing transparency to all intermediaries, based on their access level. In addition, participants of this supply chain can track the progress of goods, view their current status and inspect landing cost bills. With this level of transparency, the transit time of goods is highly reduced and any frauds or errors can be easily spotted. Furthermore, any amendments brought to a transaction has to be approved by all the nodes of the network, thus giving rise to a secure and tamperproof record system. Till now the TradeLens platform is still in the prototype phase and it is tested and implemented on specific trade routes. This innovation has caught the attention of 94 organisations [77] who are joining hands together in the testing phase. TradeLens platform makes use of smart contracts to validate transactions between the main entities of the supply chain which are: the producers, the export authorities, ports,

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customs and importers. Shipping from a specific port requires the digital signatures of a distinct number of export authorities to approve the export, along with precise documents describing the origin, chemical treatments, quality of products and custom duties. Once all these requirements are met, a smart contract is created and broadcast to the blockchain network to inform every entity about the transaction. Furthermore, all actions related to the physical goods are also captured and broadcasted to the blockchain. This includes: (1) which document was submitted, when and by who, (2) where the products are, (3) who is in procession of the products and (4) what is the next step in the transaction. According to a report by the World Economic Forum published in 2013 [78], it was predicted that “reducing supply chain barriers to trade could increase GDP by nearly 5% and trade by 15%”. Considering blockchain integration to the global chain, with IBM and Maersk paving the way with their TradeLens platform these numbers could be reached by 2020. Similarly, taking into consideration the advances and benefit that TradeLens platform has brought, other blockchain platforms are cropping up in the global trade such as the Shipchain platform [79] and the Maritime Executive Blockchain platform [80].

3.4.2

Food Sector

Food security is a major concern to the end consumers. In this new era, food undergoes a lot of processes from the farm up to the market shelves. Due to the high number of intermediaries, it is a complex task to track the origin of the product, especially when most of the transactions are hand written. Till now, RFID serves as a purpose for identifying multiple high-speed moving objects under poor environmental conditions and without any leveraged manual intervention [81]. In the logistics field, RFID has proved its efficiency due to its extensive use in productionprocessing, warehouse management, logistics tracing and counterfeit products, thus enhancing and improving supply chain management. However, RFID is a centralised traceability technique which is a monopolistic, asymmetric and has an opaque information system that invokes a high danger which results into potential trust, such as tampering of data, corruption, data misuse, falsifying and forging of data and frauds. Blockchain, increases transparency of the food industry supply chain by strengthening information credibility and enhances the safety and security assurance of agrifood supply chain by giving real-time tracking and monitoring of food. Moreover, blockchain emerges as a stringent ledger where blocks of data cannot be added or erased without a mutual agreement or authorisation. On the same wavelength, Walmart, JD.com, IBM and Tsinghua University launched a Blockchain Food Safety Alliance in China. These four companies have devised standards to collect data about the origin, safety and authenticity of food, using blockchain technology [82]. With artificial ingredients, additives, unhealthy and other harmful chemical substances being added in food regularly, blockchain excavates the reality of the origin of the food that come in the plates of all the consumers. With such a perspective in mind, the Walmart-IBM blockchain unveils

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the ingoing and outgoing procedures for the food processing of popular brands such as Nestle. Nine other companies, together with Walmart have collaborated with IBM to implement the Food Trust Blockchain in order to gain the trust of consumers [83]. As per IBM, Food Trust Blockchain stores data of about one million items and in future, hopes to prevent outbreaks in the food marketplace [83].

3.5 Blockchain and Smart Ownership Blockchain applications are heavily disrupting FinTech (Financial technology). From new means of digital payments to new means of tracking and verifying the provenance of goods, blockchain is now enabling the transfer of ownership in a quick, secure and transparent manner. Blockchain 2.0 provides a secure platform which protects the rights of the owner, resolves disputes, ensures that ownership is correctly transferred after sale and eliminates any acts of fraudulent sales.

3.5.1

Real Estate

Real estate has been a big market for years. The selling and ownership transfer of properties is a time-consuming process that involves a lot of paperwork and the participation of many intermediaries such as title agents, notaries, lawyers, land registries and banks. Due to this complexity, it is difficult to track fraudulent acts and surreptitious deals among intermediaries. To bring transparency to real estate transactions, blockchain solutions are sought. The aim is to reduce the number of intermediaries, keeping only the indispensable ones and providing a transparent and immutable ledger. Propy [84] is a company that launched a prototype implementing blockchain to real estate transactions. Based on the Ethereum platform, the Propy blockchain [85] validates transactions using smart contracts. Propy makes use of multiple distinct contracts interacting together. Each contract fulfils a specific function allowing the creation and modification of records, contract updates and other administrative functions [85]. The prototype require three types of contracts and they are: the title contract, allowing the permission to create and update new property metadata to the blockchain, the deed contract, for managing the relevant information required by third parties, and finally the identity contract, which stores and verifies the identity of all participants of the system. These three contracts all together will constitute the smart contract that validates the transaction. A transaction using Propy blockchain requires only five entities: the buyer, the seller, a government validator (land registry), a broker and a real estate inspector. A transaction using the Propy blockchain platform is as follows: 1. The seller’s broker generates a deal requesting for a title contract, a deed contract and an identity contract. The Propy website signs the title contract to create a new transaction and upon verification of the broker’s identity, signs the identity

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contract, using its private key. At the same time, the land registry will verify whether the seller owns the property being sold. Upon approval, the land registry signs the deed contract using its private key. Once the smart contract is created, it is sent to the blockchain network where participants can view the deeds. Since smart contracts are not legally recognised by government validators or real estate inspectors yet, Propy makes use of electronic signatures to sign the e-purchase agreement. Furthermore, the signed e-purchase agreement is saved to the blockchain. A deposit is then made in Propy coins to pay the transaction fees. Propy then converts the propy coins to fiat money to pay the intermediaries. All these transactions are once more broadcasted to the blockchain network to ensure transparency. All other required contracts such as title report disclosures and settlement statements are signed using electronic signatures and stored on the blockchain. Finally, the new deeds for the property are recorded on the blockchain.

The integration of blockchain to real estate promises transparency and security throughout the transfer of ownership, however, the legacy system of government validator and real estate inspector limit the true potential of blockchain.

3.5.2

Automotive Industry

Being the third-fastest-growing technological sector according to Intel, the automotive industry is now embracing blockchain. Vehicle to vehicle communication and the huge amount of data that car sensors generate promise better performance, efficiency and durability through data analytics. The purpose of implementing blockchain to this industry is to bring transparency and interconnectivity among owners, their cars and external institutions. ShiftMobility [86] launched their blockchain application on the Ethreum platform and is powered by a cryptocurrency called Blockcurr which allows decentralised payments among entities. ShiftMobility network tracks and records all the transactions that a car undergoes, including previous car parts transactions and repairs, list of previous owners, insurance contracts, the amount AutOns tokens on their blockchain. AutOns tokens are reward tokens that are owned for each mile of data added to the ShiftMobility network. These tokens can be redeemed for discounts on repairs and maintenance. When a change in the car ownership is initiated, the new owner inherits the complete service history of the previous owner [87]. This way, the resale value of a car is easily determined and this does not require the intervention of third parties to evaluate the resale price. Conversely, Porsche launched the Porsche-XAIN vehicle network allowing a more secure lock/unlock mechanism, grant temporary access to the car, and send notifications in real time to the car owner when the car is in use. This prototype is a combination of blockchain technology and machine learning and is referred to as blockchain intelligence [88]. XAIN makes use of an energy-enhanced consensus mechanism

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called Practical Proof of Kernel Work (PPoKW) allowing low computing power devices such as sensors [89], car’s engine control unit and smartphones to contribute to the consensus.

3.6 Blockchain and Governance 3.6.1

Voting System

The traditional ballot box voting mechanism has been ubiquitous since decades and recently with the advent of technology, e-voting allowed people to vote outside geographical borders. However, the disadvantage of this approach is the lack of security leading to expose back-end attacks and vote tampering. Blockchain reinforces the notion of e-voting. Moreover, the main aspect of introducing blockchain in the voting system is because of the secure architecture and to promote transparency and meritocracy during election. With blockchain, every data will be automated and saved in the chain of blocks. Authentication, transparency, data integrity, data security and prevention of data infringement are assured by the solid infrastructure that blockchain offers. Security of votes is ensured by the effective use of tokens and the regulatory amount stored in the candidate’s wallet. Usually, a vote is represented as the token and thereof, can be monitored under strict conditions imposed by the blockchain. Every vote given to a specific candidate will be stored and saved in the corresponding person’s wallet, hence eliminating any trace of voting manipulation, unbiased and unfair judgement. Some of the companies which adopt such voting policies are FollowMyVote [90] and BitCongress [90].

3.6.2

Birth Certificates

Blockchain is used to digitalize birth certificates in many states. The aim behind implementing blockchain technology is to reduce paperwork and eliminate the hassle of issuing legal documents [91]. Compared to the traditional system, this method is less time-consuming, less archaic and more secure [92]. Storing personal data as sensitive as birth certificates is a threat for identity theft in the era of hacks and leaks. Blockchain remedies the situation with the help of its distributed ledgers. The idea behind distributed ledgers applied to birth certificates is to deny unauthorized access to the documents by third parties. The permissioned blockchain can easily control access of whom can share a copy of the birth certificate, thus ensuring a secure, reliable and trustworthy transaction. States such as Illinois launched a pilot project regarding a blockchain-based birth certificate system [92]. At the birth of a child, data such as name, date of birth, gender will be logged on the blockchain in the presence of doctors and the parents [92].

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Passport and Identification

The idea behind digitizing passports is to eliminate manual checks in airports and make it a paperless travel. Modern techniques that are used by international airports involve the use of biometrics. These biometrics are verified with a centralized database and no assertion can be given that the data has not been tampered with. With a completely different approach, blockchain has enabled the implementation of self-sovereign identity for privacy protection [93]. Self-sovereign identity systems [94] use blockchain’s distributed nature so as to decentralize the identifiers and at the same time, provide an assertion that the data has not been tampered with. This regulates the arrival and departure process of travelers as a new block will be added to the blockchain as soon as the biometrics have been authentified. Blockchain is also advantageous from the traveler’s point of view as the access to the biometrics database is regulated and the traveler can choose what biometric information to share and when. In this way, the passenger can control the use of their personal data and can keep track on how their data is being used [95]. Likewise, Dubai implemented a blockchain-based passport system which makes use of a QR code on the passport to update the blockchain [93]. Similarly, the governments of Canada and the Netherlands launched a pilot program that uses a travelermanaged identity platform known as the Known Traveller Digital Identity (KTDI), which is based on Linux’s Hyperledger Indy [95]. Another promising blockchain prototype which aims at providing digital identity is the ID2020 developed in the collaboration of Accenture [96], Microsoft and Avanade. The major goal of this project is to provide a solution to the 1.1 billion people in the world that are unable to prove their identity [85].

3.6.4

Donations

Blockchain once again, annihilates all uncertainties and builds a trust between citizens and charity organization allowing them to donate without any suspicions. For more control over donations, blockchain demonstrates other potential uses of this underlying technology. The concept of a decentralized, peer-to-peer ledger renders blockchain beneficial in several social events and fundings. There are 5 top blockchain solutions, which contribute enormously in incentivizing charity works and donations to be done in a more transparent, authentified and ethical manner namely: Alice, Bithope, GiveTrack and Pinkcoin (Table 3).

3.7 Blockchain in Telecommunications Blockchain has the potential of creating new avenues in the telecommunication sector. Apart from bringing security and integrity to the IoT sector as illustrated in Sect. 2.1, blockchain will create new business models for Communications Service Providers

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Table 3 Blockchain donation platforms Blockchain donation platform Purpose Alice [97]

Alice caters for homeless people’s needs. It ensures versatility and transparency by verifying that donated money is being used appropriately and solely for the purpose they were being collected. Furthermore, donations are frozen as soon as the amount set by the organisation is met, preventing over-collection of funds. Alice makes use of smart contract to track and trace donations If an inappropriate usage of money is detected, the transaction is cancelled and the money is bounced back to the donor

Bithope [98]

Use crypto-currency which provides non-profit organizations the facility to acquire international donors Bithope eases this task by allowing donors to donate anonymously

GiveTrack [99]

Givetrack collects bitcoins for charity purposes The implementation of bitcoin blockchain provides real-time financial tracking and tracing of the digital money given by donors at each different stage and at any interval of the process Donors can have a follow up of where and how their donations are being used and if they are being used for the appropriate reason ethically from the time the money has been collected till the full implementation of the donated money

PinkCoin [100]

PinkCoin is a cryptocurrency developed to ease donation process and is based on a reward system. It is based on a hybrid consensus between proof-of-stake and proof-of-work Donors can preserve their coins in a wallet called Staking which allows them to receive an interest on their principal amount after holding the deposit for a period of time The profit made is usually given since the donors’ money is being used overnight to build the blockchain platform

(CSP). Big telecommunication companies such as Huawei and Deloitte are assessing the relevance of DLT to the telecommunication sector through proof-of-concept [101]. Likewise, global leading CSPs such as AT&T, Colt, Deutsche Telekom, Globe Telecom, Softbank, Telefónica and Vodafone have tested blockchain through pilot projects and are now moving towards proper deployments [12]. In this section we provide an overview of the proof-of-concepts and how it will affect data management of current mobile networks, the upcoming 5G technology and support new business models.

3.7.1

Data Management-Roaming

CSPs face many limitations when providing roaming services to their respective subscribers. The transition from one network to another foreign network (CSP-toCSP) requires proper data management since roaming frauds are most likely to occur.

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Roaming frauds have accounted for $1.8 billion to $10.76 billion losses to CSPs since 2013 [102]. When a roaming event is triggered, the Visitor Public Home Network (VPMN) needs to query the Home Public Mobile Network (HPMN) to access the subscriber’s credentials and resources for the billing procedure. However, two major vulnerabilities of roaming include longer detection time, that is time taken to detect the fraud and longer response time, that is the time taken to respond to that fraud due to lack of control features. To prevent the aforementioned roaming issue, a private blockchain can be implemented between CSPs that share a roaming agreement. The CSPs designate nodes that will act as miners to verity each transaction broadcasted on the blockchain network [101]. Roaming agreements between HPMN and VPMN are dealt by smart contracts as soon as Call Detail Records (CDR) data are shared. Furthermore, each time a subscriber triggers an event while being served by the VPMN, CDR data is broadcasted to the HPMN and billing is automatically calculated based on the services requested and it is communicated back to the VPMN. With a blockchain approach, CDR data can be verified and billing process can be initiated accordingly without any delay. Globe Telecom [103], Deutsche Telekom [104] and Vodafone [105] have already implemented their blockchain prototype to deal with roaming issues.

3.7.2

5G Technology

With the deployment of 5G networks, a massive number of devices will be connected, sharing and storing huge chunks of data. As per Cisco’s IBSG predictions, there might be 50 billion devices connected to the Internet by 2020 [106]. In the radio access network, 3GPP defines ANDSF (Access Network Discovery and Function) for discovering and selecting the best nearby access network [101]. However, an increase in the number of devices comes with challenges like delay and time sensitivity induced during the data transfer through the optical network connecting the core network to the RAN. In order to maintain QoS of users, and bringing data closer to the RAN, a blockchain-based network can be implemented to edge computing. The access points act as nodes participating in the blockchain network where rules and agreements between each node can be defined using smart contracts to ensure authenticity in real-time. Similarly, 5G will allow the seamless integration of IoT devices supporting extensive use of machine-to-machine communication. Nevertheless, one of the main concerns with sensor-driven applications, is the ability of securing, authenticating and privatizing the personal information which can be fulfilled by blockchain. Considering the additional computational power that edge computing can bring to IoT devices, blockchain will provide a trusted data sharing between cloud and sensor node.

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eSIM

The emergence of eSIM to replace the legacy chip-based SIM card, used by previous generations mobile phones, is a solution proposed for the upcoming 5G and uses cryptographic techniques to authenticate and identify a subscriber. A smart contractbased approach is adopted to generate automated identity verification. Each new subscriber is assigned a set of public and private key during his account creation. The public key is used to create the digital virtual identity with all the credentials of the subscriber stored, a digital signature is also added to the blockchain using the private key. Blockchain points to the data and provides a security mechanism with authentication and verification parameters to ensure the ethnicity and reliability of the data [101]. An eSIM approach will also allow mobile number portability [107], where the user will be allowed to use different devices without having to register with a new phone number for different devices. Furthermore, with all customers transaction logged onto a blockchain, transparency and auditability will be easier to the CSP. This will create new avenues such as mobile payments via eSIM [107] built on top of the CSP services.

3.7.4

Blockchain-as-a-Service

With the new avenue led by the implementation of eSIM as described earlier, new business models are cropping up to CSPs in the form of an identity-as-a-service (IaaS) [101] running on a private blockchain platform. The business model is to provide an easy access to blockchain as well as regulate and authentify each transaction. As CSPs already possess all the required infrastructure in terms of data management and storage services, blockchain-as-a-service is a very promising sector to diversify and expand their services. As an illustration to one of the many use cases of an IaaS, let us consider an application in an educational institution. As the students go through their academic course, all their certificates can be registered on their identity blockchain in an authentic and tamperproof way. This way, an employer or a foreign institution can easily verify the authenticity of the employee’s qualifications without having to execute lengthy procedures such as contacting the respective universities. Besides, any other crash course or online courses certificates can also be logged onto the blockchain in a sequential manner. Using a similar approach, through issuing smart contracts, CSPs can also regulate royalties for the music industry, thus regulating the sharing of content and ensuring that the artists are remunerated [108].

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4 Blockchain Limitations 4.1 Regulatory Issues 4.1.1

General Data Protection Regulation

While blockchain is expected to reach a mainstream implementation in 2025, a preeminent juncture needs to be addressed and this juncture is licencing. Blockchain, being a data software structure needs to conform to the existing laws regarding data privacy such as the General Data Protection Regulation (GDPR) [109]. GDPR strictly imposes that any user sharing their data on a public platform needs to have the right of rectification and the right to be forgotten. Since blockchain is an immutable and distributed ledger, it does not conform to this regulation. Due to its distributed architecture, in the case where a user wishes to leave a blockchain network, if the right to be forgotten has to be applied as per GDPR, this will cost a lot in computation power and will require all the previous blocks of the chain to be re-mined and this process is computationally impossible.

4.2 Legal Issues 4.2.1

Smart Contracts

Blockchain is disrupting the way traditional business works. The introduction of smart contracts has speeded up transaction rates and this has also given rise to Decentralized Autonomous Organizations (DAOs). DAOs can transact the same way traditional companies do, without the requirement of a human input. From a legal perspective, two major problems arise and they are: (1) in the case where a DAO is involved in a conflict who endorses the responsibility, and, (2) since smart contracts are just a series of line codes, in the case of a dispute between entities, how will a court decide upon the contract terms and conditions? Besides, it is infeasible to code the entire agreement between parties and embed it in the blockchain code. As a result, part of the agreement remains physically on paper [110]. During a dispute, the court will have to decide whether the smart contract genuinely relate to the alleged paper contracts. Such situations require new legislations and at the same time, lawyers will have to work in collaboration with blockchain developers to understand the principles of smart contract coding.

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4.3 Ethical Issues The massive adoption of blockchain in multiple fields have raised two prominent ethical issues which are its effect on the environment and its contribution to criminal activities.

4.3.1

Environmental Issues

Blockchain is a resource intensive process requiring lot of power consumption. In the Bitcoin blockchain, the proof-of-work consensus requires a lot of power for computing the crypto-puzzle. In addition, since miners compete for mining a new block, many miners waste power in unnecessary mining. It is estimated that bitcoin mining alone is responsible for 0.6% of the world’s entire electricity usage and such exuberant usage of power is a serious concern for the environment.

4.3.2

Criminal Activities Issues

Crypto-currency have vile antecedents with criminal activities on the dark web. The Silk Road, the largest platform for drugs and illicit goods made heavy use of bitcoin for anonymous purchases, before its shutdown in 2013. The use of bitcoin was favoured because it enabled pseudo-anonymity between drug dealers. Furthermore, dark web sites are hubs for money laundering through bitcoin and other immoral transactions such as human trafficking, child pornography and terrorism financing. Although blockchain can keep track of all the preceding transactions, the owners are pseudo-annonymous, that is, they are uniquely identified only by their public keys. Law enforcement authorities are still finding ways to combat cyber-crimes involving anonymity that blockchain brings to criminal enterprises [111]. Until now, the only country that has successfully regulated the use of blockchain is Malta. Considered as the ‘Blockchain Island’, the Maltase government has come with three regulatory frameworks for a legal implementation of blockchain including the Malta Digital Innovation Authority (MDIA) Act, the Innovative Technological Arrangement and Services (ITAS) Act, and the Virtual Financial Asset (VFA) Act [112]. The MDIA Act is a law that aims at certifying distributed ledger technology platforms. It describes the rules that an authority needs to abide to before setting up a DLT platform. The ITAS Act deals mainly with the certifications of DLT platforms. The VFA Act aims at regulating the creation of new ICOs, the exchange between crypto-currencies and the digital wallet providers [113].

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5 Blockchain Applicability Throughout this literature, the convenience of blockchain in various fields of application was depicted. Blockchain solutions are gaining tremendous popularity among large enterprises. As a matter of fact, a survey carried out by Deloitte on August 2018 demonstrated an increased interest towards blockchain solutions among huge enterprises, as compared to 2016 [114]. Companies are injecting huge amount of money on blockchain projects. The survey also reported that 40% of the responders are planning to invest $5 million or more on blockchain technology in 2019. Considering such huge amount of money invested for a blockchain start-up, this brings one question to the reader, ‘Is blockchain really a solution to all problems?’. Before adopting a blockchain solution approach, it is wise to evaluate the current organisation’s needs and requirements. Some other technologies, other than blockchain might be better suited. In order to answer the aforementioned question, Fig. 12 depicts the most fundamental questions that needs to be answered before implementing any form of blockchain architecture. If the organisation is not ready to embrace digital assets, at this early stage, the use of blockchain has no sense and traditional business records will be the only solution. Similarly, if the need of modifying the ledger is sought, the use of a centralised database is preferred, as blockchain provides an immutable ledger platform. Blockchain has enabled trusted transactions between multiple untrusted parties. If the organisation deals with a single party, a centralised database approach is of better convenience. Furthermore, blockchain makes use of consensus mechanisms in order to deal through trustless environments. If the organisation is dealing with trusted parties only, then managed databases will still be convenient. Consensus mechanisms are resource intensive processes as all nodes of the network need to process the data. A transaction on the bitcoin blockchain can take about 10 min to be accepted, in contrast to a transaction on the Ethereum blockchain which can take around 12 s. These consensus time will increase with the size of the blockchain network. If the need of high performance is required by the organisation, blockchain network will not be able to suit this purpose. Since databases do not require the consensus of the whole network, they are preferred if high performance is required. Furthermore,

Fig. 12 Decision tree for the implementation of a Blockchain architecture

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another important aspect to be considered is the amount of data pertained in the transactions. As blockchain is a decentralised P2P platform where all the nodes process a full copy of the chain, this will require huge storing capacity as the number of transactions increases. For this purpose, if huge amount of datasets are involved, a blockchain approach will not be efficient. One of the key features that blockchain brings after decentralisation and immutable transactions is transparency. While planning to implement a blockchain network, the organisation will promote transparency among its midst. For this reason, if sensitive information such as business secrets or passwords are to be handed, investing in blockchain solutions will be futile. Instead, for such applications, an encrypted database is favoured. Another aspect to take into consideration is the applicability of contractual solutions. Blockchain transactions can be established through smart contracts which facilitates the transactions between organisations. In a case that an organisation is not willing to implement smart contracts, a blockchain resort is not advised. Finally, blockchain has an immutable structure. If an organisation is prone to changing the transaction rules, that is favour some organisations by offering discounts, a blockchain approach will not permit such change in transaction rules. Having considered all the above questions, the organisation is now able to determine whether blockchain could be beneficial to the enterprise or not. However there exists different types of blockchain architectures and at this stage the organisation needs to decide whether they want their data to be publicly accessible or not. If the answer is yes, a public blockchain is the solution. Else, the last question to be tackled with is, determining who is eligible for the consensus mechanisms. If consensus is reserved to a set of trusted nodes only, a consortium blockchain approach is favoured else, a private blockchain will work just fine. Table 4 shows how blockchain was implemented by different well-known big organisations throughout diverse sectors.

6 Conclusion Blockchain is one of the biggest current technology trends easing regular transactions of many organisations. The decentralised and distributed architecture adds a new layer of security to authenticate data. Blockchain has the full potential to build a transformative distributed system increasing transparency, reinforcing automated trust among individuals and generating smart contracts for reliable, traceable, immutable and secure transactions. In this chapter we provided an extensive review of potential applications of blockchain beyond the crypto realm laying emphasis on emerging technologies such as 5G and IoT as well as innovative applications in various areas. However, blockchain is still in its infancy stage and as highlighted in Sect. 5, blockchain has its own limitations which is delaying its full-fledged adoption. To unleash its full potential, a set of standardized regulations needs to be developed and put in practice for the interoperability of blockchain technology. Once this legal

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Table 4 Blockchain implementation in big companies Company

Business orientation

Blockchain implemented

Purpose

Agricultural Bank of A banking company Hyperledger fabric China providing special and specific services related to the agricultural sector mainly

Ensures a smooth process for loan approvals to farmers and to businesses, eliminates risk of double spending, tampering of data [115]

Alibaba Group Holding Ltd

A cloud computing arm of Alibaba group, providing Blockchain as a service to businesses

Customers can generate their own consortium blockchain, using Blockchain As a Service (Baas). Security of Baas is assured with a more trusted and secure computing system [116]

Allianz SE

A multinational IBM’s Hyperledger financial services Fabric, Bitcoin company offering asset blockchain and Corda management and loan facilities

Allows for transacting catastrophe swap. Accelerates all processes involved while decreasing the need of human interventions while providing authentication, transparency and credibility [117]

Amazon.com ENG

A multinational Hyperledger Fabric & company providing Ethereum e-commerce facilities, teleshopping services, cloud computing and focuses on artificial intelligence, with a virtual assistant named Alexa

Uses blockchain as a digital medium to record payment and transactions and build a secure and trusted relationship between buyers and sellers online

American express company

Money transfer across borders

Secure money transfers, faster and secure transactions through proof-payment [118, 119]

Hyperledger Fabric and Ant Blockchain

Hyperledger Fabric

(continued)

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Table 4 (continued) Company

Business orientation

Blockchain implemented

Purpose

Apple Inc

A multinational technology company selling electronics

Ethereum

Use of iTokens for customers to make payment and purchases. Customers will be granted a certain amount of token for free, and they can purchase more from the Apple Store and it will be stored in a distributed ledger securely, and transactions can be done as per the amount they possess [120]

AT&T, Sprint, T-Mobile and Verizon

Giants telecommunications companies in the US

IBM’s Hyperledger, Microsoft Azure platform

Mainly involves in catering for the needs of customers providing blockchain solutions across verticals focusing towards healthcare, manufacturing and retail sector [105]. Using AT&T’s global network and its IoT capabilities, data is easily stored on the IBM blockchain platform to attain a global access [105]

AXA Group

A French multinational Ethereum insurance company, engaged in financial services

To enhance interaction and communication between partners and customers using smart contracts. Offers data security and encryption of valued customers. Stores data securely in clear manner. Automated payments and verification and access to any information on customers [121] (continued)

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Table 4 (continued) Company

Business orientation

Blockchain implemented

Purpose

Bank of America

A multinational investment banking company

Ethereum

To improve any sort of cash handling, involving cash deposits, cash withdrawal [122]. Easier to record, access and protect data with blockchain’s architecture. Chances of data corruption, stealth and tampering are low

Bank of China

A commercial bank maintaining cordial relationship in administration and management, also deals in reselling insurance and security services

IBM’s Hyperledger Fabric

Involves smart banking with actions of securing financial data and services which is shared with third parties. Also allows real time sharing of information and ensures that transactions contracts are fully met before proceeding [123]

China Construction Bank Corporation

A banking company providing financial services for constructions purposes

IBM’s Hyperledger Fabric

Faster transactions, an increase in transparency, streamline procedures, and enhance customer service [124]

Colt Technology Services

A company which provides global network services and voice services

Communications Blockchain Network (CBN) [125]

Provides blockchain services as a communication tool for a secure and proper interaction between organisations through smart contracts. Furthermore, Colt is planning to provide an automated way of inter-carrier settlements [126]. Besides it also facilitates software-defined networking (continued)

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Table 4 (continued) Company

Business orientation

Blockchain implemented

Purpose

Daimler AG

A German automotive Ethereum multinational company

A mobiCoin reward-based system, to reward risk-aware and environmentally safe drivers who consider speed limits and abide by the road safety rules [127]

Deutsche Telekom

An European International telecommunications company which partnered with T-Labs for implementing blockchain-based projects

Hyperledger fabric

Makes use of smart contracts to regulate roaming tariffs and protect subscribers against roaming frauds. On top, they are prototyping a blocking test procedure for stolen mobile phones whereby stolen phones are identified and blocked based on their IMEI number stored on a decentralised blocking list [104]

Ford Motor Company

American multinational automobile and commercial vehicles seller company

Mobility open Blockchain initiative

Allows payment facilities for rented vehicles, record transactions and give available information to insurance companies to ease procedures [128]

Globe Telecom

A mobile and broadband network provider based in Philippines

Ant blockchain

Works on a proof-of-concept which focuses on roaming services. In a partnership with other companies including Ant Financial, they came up with [103] a digital wallet-based money transfer (continued)

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Table 4 (continued) Company

Business orientation

Blockchain implemented

Purpose

IBM

A multinational Hyperledger Fabric company which sells and produces computers spare parts, and also provides other services such as hosting and consultations

Record any transaction securely by methods of encryption [129]

Intel Corporation

A multinational Hyperledger sawtooth company that deals with the manufacturing of semiconductor

Improve efficiency, clear and transaction transactions and reinforce customer-company relationship

Microsoft Corporation

A multinational technology company selling computer software, operation system, electronics

Microsoft Azure platform

A server-less blockchain, which comprises of striking features such data management, messaging purposes [130]

Mitsubishi UFJ Financial Group

A Japanese multinational and vehicle manufacturing company

Ripple payment network

Built upon a cloud platform along Akamai Technologies, it offers secure, clean, transparent and smooth transaction and payments. Handles and tackles latencies [131]

Nestle

Food and beverage company which produce food for all age-group

Food Trust

Mainly used for food traceability and keep track of the origin of all food ingredients to ensure health safety

Oracle

Development of database software, cloud engineering systems and enterprise software

Hyperledger Fabric

Automate operations and provide security to their services [132]

Royal Bank of Canada

A financial services Hyperledger company providing the fabric citizens with services such as loans

Secure and trusted cross-border payments between two countries. Attain a more efficient, transparent, clear and low-cost facilities (continued)

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Table 4 (continued) Company

Business orientation

Blockchain implemented

Royal Dutch Shell

A British-Dutch oil and VAKT platform gas company

A consortium blockchain for oil and gas trading. Facilitates all companies to keep track of real-time oil and gas pricings globally

Samsung Electronics Co

South-Korean multinational electronics company selling mobile phones and others

Used for smooth and faster shipping, tracking, accounting and logistics purposes

Siemens AG

The largest industrial Energy Web manufacturing Foundation platform company having a panoply of sectors such as health care branch, Energy and other branches

Improve efficiency and control of energy consumptions and energy systems and promote financial project funding. Enhance interoperability in the energy field [133]

Softbank

A fixed-line ISP service

Carrier Blockchain Study Group (CBSG) global consortium

Provides a real-time interoperability between CSPs eliminating latency and failures in any transaction [134]

Telefónica

An international telecommunications company based in Europe and Latin America

Wibson

Focuses on proof-of-concept which exploits on blockchain ability to bring trust between business partners. Compiling all Call Data Records (CDRs) on one blockchain platform will tackle billing issues [135]

Toyota Motor Corp

A Japanese automotive Blockchain mobility multinational company, consortium selling cars and high performing vehicles

Nexledger

Purpose

To develop an efficient mobility ecosystem, and for easier access of autonomous data and facilitate insurance-related information [136] (continued)

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Table 4 (continued) Company

Business orientation

Blockchain implemented

Purpose

Vodafone

A multinational telecommunications company present in over 25 countries

IBM blockchain platform

Has a vision of implementing private blockchain to bring a trustless environment, remove intermediaries, ensures integrity, facilitates auditing and maintain consistency in the telecommunications industry [105]

Walmart

A multination retail company owning multiple chain of grocery stores, hypermarkets and storage departments

Hyperledger fabric

Mainly used to guarantee food safety, food traceability and build a firm trust between customers and retailers

Walt Disney Company

An entertainment company which provides theme parks, kids shows

DragonChain

Help in tracking of financial transactions for verification purposes and management of its assets [137]

barrier is overcome, blockchain might become the solution to many data centric issues.

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