Convergence of Cloud with AI for Big Data Analytics : Foundations and Innovation 9781119905219
This book was written to discuss the milestones in the development of three recent domains in Computer Science engineeri
334 106 6MB
English Pages 610 Year 2023
Table of contents :
A chapter-wise breakdown of the contents of the book follows:
• Chapter 1 discusses the integration of Artificial Intelligence, big data and cloud computing with the internet of things (IoT).
• Chapter 2 discusses cloud computing and virtualization.
• Chapter 3 presents a time and cost-effective multi-objective scheduling technique for cloud computing environment.
• Chapter 4 discusses cloud-based architecture for effective surveillance and diagnosis.
• Chapter 5 presents smart agriculture applications using cloud and the IoT.
• Chapter 6 presents applications of Federated Learning in computing technologies.
• Chapter 7 analyzes the application of edge computing in smart healthcare.
• Chapter 8 discusses a smart agriculture application using Fog-IoT.
• Chapter 9 presents a systematic study of the global impact of COVID-19 on the IoT.
• Chapter 10 discusses efficient solar energy management using IoT-enabled Arduino-based MPPT techniques.
• Chapter 11 presents an axiomatic analysis of pre-processing methodologies using Machine Learning in text mining from the perspective of social media in the IoT.
• Chapter 12 presents an app-based agriculture information system for rural farmers.
• Chapter 13 provides a systematic survey on AI-enabled cyber-physical systems in healthcare.
• Chapter 14 discusses an artificial neural network (ANN) aware methanol detection approach with CuO-doped SnO2 in gas sensor.
• Chapter 15 describes how to detect heart arrhythmias using Deep Learning algorithms.
• Chapter 16 presents an Artificial Intelligence approach for signature detection.
• Chapter 17 compares various classification models using Machine Learning to predict the price range of mobile phones.
A chapter-wise breakdown of the contents of the book follows:
• Chapter 1 discusses the integration of Artificial Intelligence, big data and cloud computing with the internet of things (IoT).
• Chapter 2 discusses cloud computing and virtualization.
• Chapter 3 presents a time and cost-effective multi-objective scheduling technique for cloud computing environment.
• Chapter 4 discusses cloud-based architecture for effective surveillance and diagnosis.
• Chapter 5 presents smart agriculture applications using cloud and the IoT.
• Chapter 6 presents applications of Federated Learning in computing technologies.
• Chapter 7 analyzes the application of edge computing in smart healthcare.
• Chapter 8 discusses a smart agriculture application using Fog-IoT.
• Chapter 9 presents a systematic study of the global impact of COVID-19 on the IoT.
• Chapter 10 discusses efficient solar energy management using IoT-enabled Arduino-based MPPT techniques.
• Chapter 11 presents an axiomatic analysis of pre-processing methodologies using Machine Learning in text mining from the perspective of social media in the IoT.
• Chapter 12 presents an app-based agriculture information system for rural farmers.
• Chapter 13 provides a systematic survey on AI-enabled cyber-physical systems in healthcare.
• Chapter 14 discusses an artificial neural network (ANN) aware methanol detection approach with CuO-doped SnO2 in gas sensor.
• Chapter 15 describes how to detect heart arrhythmias using Deep Learning algorithms.
• Chapter 16 presents an Artificial Intelligence approach for signature detection.
• Chapter 17 compares various classification models using Machine Learning to predict the price range of mobile phones.
- Author / Uploaded
- Danda B. Rawat
- Lalit K Awasthi
- Valentina Emilia Balas
- Mohit Kumar
- Jitendra Kumar Samriya
- Similar Topics
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