Internet of energy for smart cities : machine learning models and techniques /

Machine learning approaches has the capability to learn and adapt to the constantly evolving demands of large Internet-of-energy (IoE) network. The focus of this book is on using the machine learning approaches to present various solutions for IoE network in smart cities to solve various research ga...

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Bibliographic Details
Corporate Author: Taylor & Francis
Other Authors: Jindal, Anish (Editor), Kumar, Neeraj (Computer scientist) (Editor), Aujla, Gagangeet Singh (Editor)
Format: eBook
Language:English
Published: Boca Raton, FL : CRC Press, 2022.
Edition:First edition.
Subjects:
Online Access:Connect to the full text of this electronic book
Description
Summary:Machine learning approaches has the capability to learn and adapt to the constantly evolving demands of large Internet-of-energy (IoE) network. The focus of this book is on using the machine learning approaches to present various solutions for IoE network in smart cities to solve various research gaps such as demand response management, resource management and effective utilization of the underlying ICT network. It provides in-depth knowledge to build the technical understanding for the reader to pursue various research problems in this field. Moreover, the example problems in smart cities and their solutions using machine learning are provided as relatable to the real-life scenarios. Aimed at Graduate Students, Researchers in Computer Science, Electrical Engineering, Telecommunication Engineering, Internet of Things, Machine Learning, Green computing, Smart Grid, this book: Covers all aspects of Internet of Energy (IoE) and smart cities including research problems and solutions. Points to the solutions provided by machine learning to optimize the grids within a smart city set-up. Discusses relevant IoE design principles and architecture. Helps to automate various services in smart cities for energy management. Includes case studies to show the effectiveness of the discussed schemes.
Physical Description:1 online resource (xx, 302 pages)
Bibliography:Includes bibliographical references.
ISBN:9781000411003
1000411001
9781000410983
1000410986
9781003047315
1003047319