Internet of Energy for Smart Cities : Machine Learning Models and Techniques / Anish Jindal, Neeraj Kumar & Gagangeet Singh Aujla

By:

Jindal, Anish

Contributor(s):

Material type:

TextLanguage: English Publication details: London : Taylor & Francis Ltd, 2022.Edition: 1st edDescription: XX, 302 Seiten : ill.; 15.6 x 2.34 x 23.39 cmISBN:

9780367497750

Subject(s):

DDC classification:

23 621.310 JIN

Contents:

1. Smart City: The Verticals of Energy Demand and Challenges. 2. Conventional Power Grid to Smart Grid. 3. Smart Grids: An Integrated Perspective. 4. Internet of Energy: Solution for Smart Cities. 5. IoE Applications for Smart Cities. 6. IoE Design Principles and Architecture. 7. Machine Learning Models for Smart Cities. 8. Machine Learning Models in Smart Cities Data-Driven Perspective. 9. Case Study 1: Machine Learning Techniques for Monitoring of PV Panel. 10. Case Study 2: Intelligent Control System for Smart Environment. 11. Pathway and Future of the IoE in Smart Cities

Summary: 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 helps build the technical understanding for the reader

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Cover image	Item type	Current library	Home library	Collection	Shelving location	Call number	Materials specified	Vol info	URL	Copy number	Status	Notes	Date due	Barcode	Item holds	Item hold queue priority	Course reserves
	General Books	CUTN Central Library Medicine, Technology & Management		Non-fiction		621.310 JIN (Browse shelf(Opens below))					Available			51246

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1. Smart City: The Verticals of Energy Demand and Challenges.
2. Conventional Power Grid to Smart Grid.
3. Smart Grids: An Integrated Perspective.
4. Internet of Energy: Solution for Smart Cities.
5. IoE Applications for Smart Cities.
6. IoE Design Principles and Architecture.
7. Machine Learning Models for Smart Cities.
8. Machine Learning Models in Smart Cities
Data-Driven Perspective.
9. Case Study
1: Machine Learning Techniques for Monitoring of PV Panel.
10. Case Study
2: Intelligent Control System for Smart Environment.
11. Pathway and Future of the IoE in Smart Cities

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 helps build the technical understanding for the reader

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