Artificial Intelligence and Machine Learning in Smart City Planning
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Artificial Intelligence and Machine Learning in Smart City Planning shows the reader practical applications of AIML techniques and describes recent advancements in this area in various sectors. Owing to the multidisciplinary nature, this book primarily focuses on the concepts of AIML and its methodologies such as evolutionary techniques, neural networks, machine learning, deep learning, block chain technology, big data analytics, and image processing in the context of smart cities. The text also discusses possible solutions to different challenges posed by smart cities by presenting cutting edge AIML techniques using different methodologies, as well as future directions for those same techniques.
Key Features
- Reviews the smart city concept and teaches how it can contribute to achieving urban development priorities
- Explains soft computing techniques for smart city applications
- Describes how to model problems for effective analysis, intelligent decision making, and optimal operation and control in the smart city paradigm
- Teaches how to carry out independent projects using soft computing techniques in a vast range of areas in diverse fields like engineering, management, and sciences
Readership
Researchers and grad students; Practitioners in smart city planning/design
Table of Contents
- 1. Smart City Framework
2. Smart City Finance
3. Smart Water Management
4. Smart Education
5. Smart Garbage Management Systems
6. Smart Environment
7. Smart Transportation
8. Tackling Cyber Attacks
9. Smart Parking Systems
10. Smart Health Care
11. Smart Communications
Product details
- No. of pages: 325
- Language: English
- Copyright: © Elsevier 2023
- Published: January 2, 2023
- Imprint: Elsevier
- Paperback ISBN: 9780323995030
About the Editors
Vedik Basetti
Associate Professor Vedik Basetti Ph.D. works at the National Institute of Technology in Hamirpur, India.
Affiliations and Expertise
Associate Professor, NIT-Hamirpur, National Institute of Technology, Hamirpur, India
Chandan Shiva
Affiliations and Expertise
Assistant Professor, Department of Electrical and Electronics Engineering, SR University, Warangal Urban, India
Mohan Ungarala
PhD from the National Institute of Technology (NIT), Hamirpur, India, 2017. At present, he is a lecturer in the Department of Applied Sciences (DSA) at Université du Québec à Chicoutimi (UQAC), Québec, Canada. Since 2018, he is also a postdoctoral researcher at UQAC with the Research Chair on the Aging of Power Network Infrastructure (ViAHT). Dr. Mohan is a senior member of IEEE and member of the IEEE DEIS His main research interests include aging phenomena of high-voltage insulation, condition monitoring of electrical apparatus, alternative dielectric materials, transformer insulation in cold countries, and AIML applications.
Affiliations and Expertise
Department of Applied Sciences (DSA), Universite du Quebec a Chicoutimi (UQAC), Quebec, Canada
Shriram Rangarajan
Dr. Shriram’s industrial and R&D experience includes working as a Test Engineer at M.S. Kennedy Corporation, Syracuse, New York, USA, Research Associate and Planning Engineer at London Hydro Inc., London, Ontario, Canada, Global Research Consultant, General Electric, Bangalore, Karnataka, India, Research Assistant at Duke Energy eGrid - Clemson University Restoration Institute, Charleston, SC, USA.
research areas of interests include Smart Grid, Flexible AC Transmission System (FACTS), Power system stability, Renewable Energy - PV Solar (Smart inverters) & Wind, Power quality, Distribution Systems and Distributed Generation.
Affiliations and Expertise
Associate Professor, SR University, Warangal and Clemson University, Clemson University, USA
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