Electronics and Communications Technology

Frontiers of Mechanical and Industrial Engineering

Artificial Intelligence for Next-Gen Green Vehicles
Driving Toward a Sustainable Future

Editors: Hari Murthy, PhD
Kukatlapalli Pradeep Kumar, PhD
Joseph P. Mani, PhD
Kyoungseok Han, PhD
Prasenjit Chatterjee, PhD

Artificial Intelligence for Next-Gen Green Vehicles

In Production
Pub Date: Forthcoming October 2027
Hardback Price: $190 US | £150 UK
Hard ISBN: 9781779649539
E-Book ISBN: 978-1-77964-954-6
Pages: Est 376 pp w index
Binding Type: Hardback / ebook
Series: Frontiers of Mechanical and Industrial Engineering
Notes: 13 color and 72 b/w illustrations

As the automotive industry undergoes a profound transformation, artificial intelligence is redefining how next-generation transportation systems are designed, manufactured, operated, and integrated into increasingly connected cities. This new volume, Artificial Intelligence for Next-Gen Green Vehicles: Driving Toward a Sustainable Future, explores the convergence of AI and sustainable transportation and its potential to create a cleaner, safer, more efficient, and more connected mobility ecosystem.

Drawing on interdisciplinary perspectives, the volume examines how intelligent algorithms, machine learning, real-time data analytics, and emerging digital technologies are advancing electric and autonomous vehicles. Chapters address AI-driven autonomous electric vehicles and zero-emission smart cities, automotive manufacturing, environmental challenges in transportation, electric and hybrid vehicle technologies, cybersecurity, vehicle behavior prediction, communications security and privacy, and traffic congestion prediction. Additional topics include smart parking, electric vehicle adoption, and applications of virtual and augmented reality in green electric vehicles.

Balancing technological innovation with broader sustainability considerations, the chapters consider environmental impacts, infrastructure, policy, urban mobility, and practical implementation. Data-driven analyses and case studies demonstrate how advanced technologies can improve vehicle performance and efficiency while supporting more sustainable transportation systems.

Key Features
• Explores AI applications in electric, autonomous, and next-generation green vehicles.
• Examines cybersecurity, communications, traffic prediction, smart parking, and sustainable mobility.
• Presents data-driven analyses and practical case studies of emerging vehicle technologies.
• Addresses environmental impacts, infrastructure, adoption challenges, and future opportunities.

CONTENTS:
Preface

1. AI-Driven Autonomous Electric Vehicles (AEVs): Paving the Way for Zero-Emission Smart Cities
Md. Afroz, Emmanuel Nyakwende, and Birendra Goswami

2. Revolutionizing Green Vehicles: The Role of Artificial Intelligence in Achieving Zero Emissions
Babu Kumar S., Anoop G. L., Chaitra P. C., Kukatlapalli Pradeep Kumar, and Shruti Jalapur

3. AI in the Automotive Industry: Transforming Mobility and Manufacturing
Bhairavi Rewatkar, Ashish Tiwari, and Meera Dhabu

4. Greening Mobility: Addressing Environmental Challenges in Transportation
Jaspreet Kaur, Divya Gupta, Amrinder Singh, and Simarjeet Kaur

5. Green Future: The Convergence of Technology and Sustainability
Prachi Sasankar, Pranika Walokar, Sejal Sharma, Rashmi Thakre, and Dinanshi Waghmare

6. Emerging Technologies and Environmental Impact of Electric and Hybrid Electric Vehicles: A Comprehensive Data Analysis
Melwin Robinson, Esha Bobby, Swathi Madhavan, Jacquline Shigu, and Kukatlapalli Pradeep Kumar

7. Cybersecurity Threats in Electric Autonomous Vehicles
Ashwini K. B., Navasmeet Manav Nayak, Ravikiran N. S., Darshith V., and Sushil Kumar

8. End-to-End Learning for Real-Time Vehicle Behavior Prediction
T. Allwin Kingstan, Nandana Suresh, Nirupama R. Pillai, Sooraj Santhosh, and Benjamin A. Jacob

9. AI-Enabled Communications Security and Privacy of Autonomous Vehicles: A Comprehensive Review of Novel Approaches
Niranjan W. Meegammana and Harinda Fernando

10. A Real-Time Traffic Arrival Time and Congestion Prediction System Using Rainfall Data
Tulsi Pawan Fowdur, Navish Kumar Ragoo, and Saeid Eslamian

11. Statistical Data Analysis of AI in Autonomous Technologies: Unveiling Insights from Performance and Trends
Manisha N., Chinnapalli Neha Angel, Kukatlapalli Pradeep Kumar, and Mani Joseph

12. Smart Parking Solutions for Urban Mobility and Sustainability: A Case Study of Pune
Chandani Tiwari, Ashvini Shende, Vijaya Kumbhar, and Thomson Varghese

13. Steering Toward Sustainability: A Comprehensive Data Analysis on Electric Vehicle Adoption and Challenges
Libena Igi J., Kongara Akhila, Kasine R. S., Kukatlapalli Pradeep Kumar, and Hari Murthy

14. Case Study on the Use of Virtual and Augmented Reality in Green Electric Vehicles
Kukatlapalli Pradeep Kumar, Ryan Netto, Darin Davis Johnson, and P. Joel Thomas

Index


About the Authors / Editors:
Editors: Hari Murthy, PhD
Faculty Member, Department of Electronics and Communication Engineering, CHRIST (Deemed to be University), Bengaluru, India

Hari Murthy, PhD, is a faculty member in the Department of Electronics and Communication Engineering at CHRIST (Deemed to be University), Bengaluru, India. His research interests include additive manufacturing and the printing of functional materials for sensing and healthcare applications. Dr. Murthy has published several articles in international journals and conference proceedings and co-edited the book Novel Anti-Corrosion and Anti-Fouling Coatings and Thin Films, published by Wiley-Scrivener in 2024. His doctoral research focused on novel anticorrosion materials. He earned his PhD from the University of Canterbury, New Zealand.

Kukatlapalli Pradeep Kumar, PhD
Associate Professor and Data Science Program Coordinator, CHRIST (Deemed to be University), Bengaluru, India

Kukatlapalli Pradeep Kumar, PhD, is an Associate Professor and Data Science Program Coordinator at CHRIST (Deemed to be University), Bengaluru, India. His academic and research interests span data science, information security, data provenance, and multiparty secret sharing. Dr. Kumar has contributed multiple research publications to scholarly journals and conference proceedings, with his work addressing emerging issues at the intersection of data management, security, and computational technologies.

Joseph P. Mani, PhD
Professor and Head, Department of Mathematics and Computer Science, Modern College of Business and Science (MCBS), Oman

Mani P. Joseph, PhD, is Professor and Head of the Department of Mathematics and Computer Science at the Modern College of Business and Science (MCBS), Oman. With more than 30 years of experience in higher education, he has served as Associate Dean for Quality Assurance and Accreditation and Assistant Dean for Academic Affairs at MCBS. He has also held academic and administrative positions at Sharjah College, UAE, and MG University, Karunya University, and Cochin University of Science & Technology, India. His expertise encompasses curriculum development, institutional and program review, institutional research, accreditation documentation, and teaching. His research interests include cybersecurity, machine learning, and information technology education, and he has published several articles in these areas.

Kyoungseok Han, PhD
Associate Professor, Department of Automotive Engineering at Hanyang University, Seoul, South Korea

Kyoungseok Han, PhD, is an Associate Professor in the Department of Automotive Engineering at Hanyang University, Seoul, South Korea. He was formerly affiliated with the School of Mechanical Engineering at Kyungpook National University (KNU) in South Korea. His research focuses on smart manufacturing systems, intelligent robotics, human-machine interfaces, and innovation in engineering education. His work encompasses adaptive mechanical systems, data-driven intelligent system design, AI-driven system optimization, and cyber-physical systems. He has authored and co-authored numerous publications in international journals and conference proceedings. Dr. Han also works to integrate next-generation educational tools into engineering curricula, promote interdisciplinary collaboration, and mentor young researchers. He serves on editorial boards and technical committees of scholarly journals and professional societies, contributing to advances in intelligent mechanical systems.

Prasenjit Chatterjee, PhD
Professor, Department of Mechanical Engineering; Dean, Research and Consultancy, MCKV Institute of Engineering, West Bengal, India

Prasenjit Chatterjee, PhD, is Professor of Mechanical Engineering and Dean of Research and Consultancy at the MCKV Institute of Engineering, West Bengal, India. He has published more than 155 research papers in international journals and peer-reviewed conference proceedings and has authored or edited more than 55 books. His areas of expertise include intelligent decision-making, fuzzy computing, supply chain management, optimization techniques, risk management, and sustainability modeling. Dr. Chatterjee is also one of the developers of two multiple-criteria decision-making methods: Measurement of Alternatives and Ranking according to COmpromise Solution (MARCOS) and Ranking of Alternatives through Functional Mapping of Criterion Sub-Intervals into a Single Interval (RAFSI). His research broadly addresses decision-making and optimization methodologies for complex engineering and management problems.




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