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.
- 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
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
Vedik Basetti earned his PhD degree from the National Institute of Technology, Hamirpur, India, in 2016. Dr. B. Vedik joined the Department of Electrical and Electronics Engineering, SR University, Warangal, T.S., India, as faculty in 2016, where presently he is working as Associate Professor. His research work has been published in various reputed international journals and international conferences. His research interest includes soft computing techniques, smart grid, smart transmission system, and power system state estimation. Dr. B. Vedik is an IEEE member and a professional member of ACM. Chandan Kumar Shiva has completed his BTech in electrical and electronics engineering from Ran Vijay Singh College of Engineering & Technology, Jamshedpur, India. He holds a PhD from the Indian Institute of Technology (Indian School of Mines), Dhanbad, Jharkhand, India. At present, he is Assistant Professor in the Department of Electrical and Electronics Engineering at SR University, Warangal, India. His field of interest comprises artificial intelligent techniques, smart grid, automatic generation control, and power system optimization. Mohan Rao Ungarala is a lecturer in the Department of Applied Sciences 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. Dr. Mohan is a senior member of the IEEE and a member of the IEEE DEIS. Since 2019, he is an active member of the IEEE DEIS Technical Committee on Liquid Dielectrics”, and led an IEEE International Study Group on Pre-breakdown in Ester Liquids”. 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. Shriram S. Rangarajan is Associate Professor at SR University, Warangal, India. His industrial and R&D experience includes working as Test Engineer at M.S. Kennedy Corporation in New York, Research Associate and Planning Engineer at London Hydro Inc. in Canada, Global Research Consultant at General Electric in Bangalore, and Research Assistant at Duke Energy eGridClemson University Restoration Institute in United States.
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