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Submit a ProposalArtificial Intelligence Technologies for Smart and Sustainable Urban Transportation
 | Integrated Platforms and Use Cases Edited by Pethuru Raj, Sudesh Yadav, Manas Kumar Mishra, Satya Prakash Yadav and Victor Hugo C. de Albuquerque Copyright: 2025/07/30 | Expected Pub Date:2025/07/30 ISBN: 9781394346745 | Hardcover | 396 pages |
One Line Description
Explores the future of transportation and provides a comprehensive guide to
leveraging cutting-edge digital technologies and AI-powered platforms for creating
smart, energy-efficient, and sustainable urban transportation systems.
Description
As urbanization accelerates globally, transportation has become a major contributor to environmental degradation and climate change. Rising greenhouse gas (GHG) emissions—including carbon dioxide (CO₂), methane, ozone, nitrous oxide, and chlorofluorocarbons—pose a serious threat to air quality and environmental sustainability. To counteract these challenges, nations advocate smart, eco-friendly urban mobility solutions. This book presents the latest advancements and transformative trends in urban transportation, emphasizing emerging digital technologies that foster sustainability. The integration of artificial intelligence, 5G and 6G, cybersecurity, the Internet of Things, blockchain, edge computing, and cloud-native infrastructures enhances intelligent and energy-efficient transportation systems. Experts and environmental advocates champion innovative software platforms and solutions essential for modernizing mobility. This book examines the foundational technologies driving this transformation and explores AI-powered platforms and management solutions shaping the future of urban transportation, making it an essential resource for beginners and seasoned professionals alike.
• Uncovers the innovative features of artificial intelligence in urban transportation, illustrating how integrated platforms enhance operational efficiency and sustainability at both macro and micro levels;
• Delves into the most common AI techniques and algorithms used in modern urban mobility systems;
• Focuses on how the evolution of AI paradigms supports real-time decision-making, transforming urban transportation planning and management;
• Examines the integration of trust management and advanced cybersecurity measures within AI-powered transportation systems;
• Provides a collection of case studies and detailed analyses of AI-based integrated platforms, offering theoretical perspectives and practical examples of technological advancements and their challenges.
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As urbanization accelerates globally, transportation has become a major contributor to environmental degradation and climate change. Rising greenhouse gas (GHG) emissions—including carbon dioxide (CO₂), methane, ozone, nitrous oxide, and chlorofluorocarbons—pose a serious threat to air quality and environmental sustainability. To counteract these challenges, nations advocate smart, eco-friendly urban mobility solutions. This book presents the latest advancements and transformative trends in urban transportation, emphasizing emerging digital technologies that foster sustainability. The integration of artificial intelligence, 5G and 6G, cybersecurity, the Internet of Things, blockchain, edge computing, and cloud-native infrastructures enhances intelligent and energy-efficient transportation systems. Experts and environmental advocates champion innovative software platforms and solutions essential for modernizing mobility. This book examines the foundational technologies driving this transformation and explores AI-powered platforms and management solutions shaping the future of urban transportation, making it an essential resource for beginners and seasoned professionals alike.
• Uncovers the innovative features of artificial intelligence in urban transportation, illustrating how integrated platforms enhance operational efficiency and sustainability at both macro and micro levels;
• Delves into the most common AI techniques and algorithms used in modern urban mobility systems;
• Focuses on how the evolution of AI paradigms supports real-time decision-making, transforming urban transportation planning and management;
• Examines the integration of trust management and advanced cybersecurity measures within AI-powered transportation systems;
• Provides a collection of case studies and detailed analyses of AI-based integrated platforms, offering theoretical perspectives and practical examples of technological advancements and their challenges.
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Author / Editor Details
Pethuru Raj, PhD is the Chief Architect in the Edge AI division of Reliance Jio Platforms Ltd. He has published more than thirty research papers in peer-reviewed journals, authored and edited forty-two books, and contributed fifty-four book chapters. He focuses on emerging technologies such as the Internet of Things, artificial intelligence model optimization, big and streaming data analytics, and blockchain.
Pethuru Raj, PhD is the Chief Architect in the Edge AI division of Reliance Jio Platforms Ltd. He has published more than thirty research papers in peer-reviewed journals, authored and edited forty-two books, and contributed fifty-four book chapters. He focuses on emerging technologies such as the Internet of Things, artificial intelligence model optimization, big and streaming data analytics, and blockchain.
Sudesh Yadav, PhD is an Assistant Professor in the Govt. College, Ateli, Distt-Mahendergarh, Haryana, India. She has published and reviewed many research papers in refereed international journals and conferences. Her areas of interest include artificial intelligence, IoT, digital image processing, soft computing and pattern recognition, and natural language processing.
Manas Kumar Mishra, PhD is a Professor at the IMS Engineering College, Ghaziabad, Uttar Pradesh, India. He has published more than 80 book chapters and research articles in international journals of repute. His research interests include distributed systems, mobile computing, artificial intelligence, and wireless sensor networks.
Satya Prakash Yadav, PhD is an Associate Professor in the Department of Computer Science and Engineering at the Madan Mohan Malaviya University of Technology, Gorakhpur, U.P., India with more than 17 years of experience. He has published four books, two patents, and many research papers in international journals. His research focuses on image processing, inf
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Table of Contents
Preface
Part 1: Artificial Intelligence in Solving Urban Planning and Designing Challenges
1. Illustrating the Sustainability, Challenges, and Concerns of Urban Mobility and Smart Cities
Nilesh Bhosle, Amandeep Kaur, Raman Kumar, Yashwant Singh Bisht and Laith H. Alzubaidi
1.1 Introduction
1.1.1 Characteristics of a Smart City
1.2 Smart City
1.2.1 An Overview of Smart Cities
1.2.2 Role of Digitalisation in Smart Cities
1.2.3 Infrastructural Impacts of Digitalisation in Smart Cities
1.3 Smart Mobility in Smart Cities
1.4 Analysis of Security Threats
1.4.1 Mobility Trends in Smart Cities in the Future
1.5 Issues and Opportunities Related to Smart Cities
1.5.1 Challenges for Smart Cities
1.5.2 Trends and Opportunities for the Future
1.6 Conclusions
References
2. Accentuating Climate Change Adaptation and Vulnerability (CCAV) Challenges
Adil Abbas Alwan, Amandeep Kaur, Nilesh Bhosle, Sanjeev Kumar Shah and Mohemmed Hussien
2.1 Introduction
2.1.1 Adapting to Climate Change Vulnerabilities
2.2 Related Work
2.2.1 Spatial Violence
2.2.2 Response to Climate Change
2.3 Key Challenges in Climate Change Adaptation and Vulnerability (CCAV)
2.3.1 Technical Challenges
2.3.2 Financial Constraints
2.3.3 Social and Cultural Barriers
2.3.4 Institutional and Governance Challenges
2.3.5 Multi-Level Governance (MLG) of Climate Change
2.4 Case Studies Highlighting Vulnerability and Adaptation Challenges
2.4.1 Small Island Developing States (SIDS)
2.4.2 Rural Farming Communities in Sub-Saharan Africa
2.4.3 Urban Slums in South Asia
2.5 Strategic Frameworks for Addressing CCAV Challenges
2.5.1 Through Community-Based Approaches
2.5.2 Mobilising Climate Finance and Reducing Funding Barriers
2.5.3 Strengthening Institutional Capacity and Governance Frameworks
2.5.4 Innovating and Leveraging Technology
2.5.5 Insufficient Funding and Resources
2.5.6 Data Gaps and Uncertainty
2.5.7 Insufficient Localised Solutions
2.5.8 Institutional and Policy Challenges
2.5.9 Social and Economic Inequities
2.5.10 Awareness and Engagement of the Public Lacking
2.5.11 Using Fossil Fuels as a Source of Energy
2.5.12 Limitations
2.5.13 Maintaining a Balance Between Short-Term and Long-Term Needs
2.5.14 Adaptation Challenges Based on Ecosystems
2.5.15 Efforts to Monitor and Evaluate Adaptation
2.5.16 Global Coordination and Climate Justice
2.6 Conclusion
References
3. Delineating the Solution Approaches for Sustainable Urban Mobility
Adil Abbas Alwan, Amandeep Kaur, Nilesh Bhosle, Rajesh Singh and Mohammed Al-Farouni
3.1 Introduction
3.2 Related Work
3.3 Materials and Methods
3.3.1 Travel Demand Generation
3.3.2 Traffic Simulation Process
3.4 Results Analysis and Discussion
3.4.1 Amsterdam
3.4.2 Helsinki
3.5 Conclusion
References
4. About the Growing Power of Artificial Intelligence (AI) and Blockchain for Fleet Management and Sustainable Societies
Jayant Jagtap, Raman Kumar, Kunal Gagneja, Anita Gehlot and M. Muhsen Hassan
4.1 Introduction
4.1.1 Artificial Intelligence and Blockchain
4.1.2 Sustainable Smart City Society
4.2 Literature Survey and Contribution
4.2.1 Privacy and Security Concerns
4.3 Blockchain to Support Smart Cities’ Operations
4.4 Blockchain Benefits
4.5 Types of Blockchain Networks
4.6 Blockchain Suitability
4.7 Conclusion
References
5. Testifying the Criticality of the Internet of Things (IoT), 5G and AI: A Perfect Combination for Battery Management
Preeti Rani, Raman Kumar, Amrita Singh, Jayant Jagtap and Muntather Almusawi
5.1 Introduction
5.1.1 Energy Management Strategy Description
5.2 Literature Review
5.2.1 Managing an EV Battery Pack
5.2.2 IoT in Battery Management
5.2.3 Wireless BMS Incentive Program
5.2.4 5G as a Catalyst for Rapid Data Transmission
5.2.5 AI and Predictive Analytics in Battery Optimization
5.2.6 Synergy of IoT, 5G, and AI in Battery Management
5.3 The Internet of Things (IoT) in Battery Management
5.3.1 Real-Time Monitoring and Predictive Maintenance
5.3.2 Data Collection and Data-Driven Insights
5.4 5G Connectivity: Enabling High-Speed, Low-Latency Data Exchange
5.4.1 Enhancing Real-Time Decision Making
5.4.2 Scalability of IoT Networks
5.5 Artificial Intelligence (AI): The Brain Behind Smart Battery Management
5.6 BMS’s Goals and Challenges
5.6.1 Optimal Charging
5.6.2 Fast Characterization
5.7 Conclusion
References
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Preface
Part 1: Artificial Intelligence in Solving Urban Planning and Designing Challenges
1. Illustrating the Sustainability, Challenges, and Concerns of Urban Mobility and Smart Cities
Nilesh Bhosle, Amandeep Kaur, Raman Kumar, Yashwant Singh Bisht and Laith H. Alzubaidi
1.1 Introduction
1.1.1 Characteristics of a Smart City
1.2 Smart City
1.2.1 An Overview of Smart Cities
1.2.2 Role of Digitalisation in Smart Cities
1.2.3 Infrastructural Impacts of Digitalisation in Smart Cities
1.3 Smart Mobility in Smart Cities
1.4 Analysis of Security Threats
1.4.1 Mobility Trends in Smart Cities in the Future
1.5 Issues and Opportunities Related to Smart Cities
1.5.1 Challenges for Smart Cities
1.5.2 Trends and Opportunities for the Future
1.6 Conclusions
References
2. Accentuating Climate Change Adaptation and Vulnerability (CCAV) Challenges
Adil Abbas Alwan, Amandeep Kaur, Nilesh Bhosle, Sanjeev Kumar Shah and Mohemmed Hussien
2.1 Introduction
2.1.1 Adapting to Climate Change Vulnerabilities
2.2 Related Work
2.2.1 Spatial Violence
2.2.2 Response to Climate Change
2.3 Key Challenges in Climate Change Adaptation and Vulnerability (CCAV)
2.3.1 Technical Challenges
2.3.2 Financial Constraints
2.3.3 Social and Cultural Barriers
2.3.4 Institutional and Governance Challenges
2.3.5 Multi-Level Governance (MLG) of Climate Change
2.4 Case Studies Highlighting Vulnerability and Adaptation Challenges
2.4.1 Small Island Developing States (SIDS)
2.4.2 Rural Farming Communities in Sub-Saharan Africa
2.4.3 Urban Slums in South Asia
2.5 Strategic Frameworks for Addressing CCAV Challenges
2.5.1 Through Community-Based Approaches
2.5.2 Mobilising Climate Finance and Reducing Funding Barriers
2.5.3 Strengthening Institutional Capacity and Governance Frameworks
2.5.4 Innovating and Leveraging Technology
2.5.5 Insufficient Funding and Resources
2.5.6 Data Gaps and Uncertainty
2.5.7 Insufficient Localised Solutions
2.5.8 Institutional and Policy Challenges
2.5.9 Social and Economic Inequities
2.5.10 Awareness and Engagement of the Public Lacking
2.5.11 Using Fossil Fuels as a Source of Energy
2.5.12 Limitations
2.5.13 Maintaining a Balance Between Short-Term and Long-Term Needs
2.5.14 Adaptation Challenges Based on Ecosystems
2.5.15 Efforts to Monitor and Evaluate Adaptation
2.5.16 Global Coordination and Climate Justice
2.6 Conclusion
References
3. Delineating the Solution Approaches for Sustainable Urban Mobility
Adil Abbas Alwan, Amandeep Kaur, Nilesh Bhosle, Rajesh Singh and Mohammed Al-Farouni
3.1 Introduction
3.2 Related Work
3.3 Materials and Methods
3.3.1 Travel Demand Generation
3.3.2 Traffic Simulation Process
3.4 Results Analysis and Discussion
3.4.1 Amsterdam
3.4.2 Helsinki
3.5 Conclusion
References
4. About the Growing Power of Artificial Intelligence (AI) and Blockchain for Fleet Management and Sustainable Societies
Jayant Jagtap, Raman Kumar, Kunal Gagneja, Anita Gehlot and M. Muhsen Hassan
4.1 Introduction
4.1.1 Artificial Intelligence and Blockchain
4.1.2 Sustainable Smart City Society
4.2 Literature Survey and Contribution
4.2.1 Privacy and Security Concerns
4.3 Blockchain to Support Smart Cities’ Operations
4.4 Blockchain Benefits
4.5 Types of Blockchain Networks
4.6 Blockchain Suitability
4.7 Conclusion
References
5. Testifying the Criticality of the Internet of Things (IoT), 5G and AI: A Perfect Combination for Battery Management
Preeti Rani, Raman Kumar, Amrita Singh, Jayant Jagtap and Muntather Almusawi
5.1 Introduction
5.1.1 Energy Management Strategy Description
5.2 Literature Review
5.2.1 Managing an EV Battery Pack
5.2.2 IoT in Battery Management
5.2.3 Wireless BMS Incentive Program
5.2.4 5G as a Catalyst for Rapid Data Transmission
5.2.5 AI and Predictive Analytics in Battery Optimization
5.2.6 Synergy of IoT, 5G, and AI in Battery Management
5.3 The Internet of Things (IoT) in Battery Management
5.3.1 Real-Time Monitoring and Predictive Maintenance
5.3.2 Data Collection and Data-Driven Insights
5.4 5G Connectivity: Enabling High-Speed, Low-Latency Data Exchange
5.4.1 Enhancing Real-Time Decision Making
5.4.2 Scalability of IoT Networks
5.5 Artificial Intelligence (AI): The Brain Behind Smart Battery Management
5.6 BMS’s Goals and Challenges
5.6.1 Optimal Charging
5.6.2 Fast Characterization
5.7 Conclusion
References
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