{"product_id":"artificial-intelligence-technologies-for-smart-and-sustainable-urban-transportation-integrated-platforms-and-use-cases-hardback-9781394346745","title":"Artificial Intelligence Technologies for Smart and Sustainable Urban Transportation; Integrated Platforms and Use Cases (Hardback) 9781394346745","description":"\u003cfont face=\"Georgia\"\u003e\r\n\u003cp\u003e\u003cfont size=\"6\"\u003eArtificial Intelligence Technologies for Smart and Sustainable Urban Transportation\u003c\/font\u003e\u003cbr\u003e\r\n\u003cfont size=\"5\"\u003eIntegrated Platforms and Use Cases\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\r\n\r\n\r\n\u003cp\u003e\u003cfont size=\"4\"\u003ePethuru Raj (Edited by), Raj (Author), Sudesh Yadav (Edited by), Manas Kumar Mishra (Edited by), Satya Prakash Yadav (Edited by), Victor Hugo C. de Albuquerque (Edited by)\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003e9781394346745, Wiley\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003eHardback, published 12 December 2025\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003e400 pages\u003cbr\u003e28 x 19 x 3 cm, 0.857 kg\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\r\n\r\n\r\n\r\n\u003cp align=\"justify\"\u003e\u003cstrong\u003e\u003cfont size=\"3\"\u003e\u003cp\u003e\u003cb\u003eExplores 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.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eAs 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.\u003c\/p\u003e \u003cul\u003e \u003cli\u003eUncovers the innovative features of artificial intelligence in urban transportation, illustrating how integrated platforms enhance operational efficiency and sustainability at both macro and micro levels;\u003c\/li\u003e \u003cli\u003eDelves into the most common AI techniques and algorithms used in modern urban mobility systems;\u003c\/li\u003e \u003cli\u003eFocuses on how the evolution of AI paradigms supports real-time decision-making, transforming urban transportation planning and management;\u003c\/li\u003e \u003cli\u003eExamines the integration of trust management and advanced cybersecurity measures within AI-powered transportation systems;\u003c\/li\u003e \u003cli\u003eProvides 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.\u003c\/li\u003e \u003c\/ul\u003e\u003c\/font\u003e\u003c\/strong\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003e\u003cp\u003ePreface xix\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart 1: Artificial Intelligence in Solving Urban Planning and Designing Challenges 1\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e1 Illustrating the Sustainability, Challenges, and Concerns of Urban Mobility and Smart Cities 3\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eNilesh Bhosle, Amandeep Kaur, Raman Kumar, Yashwant Singh Bisht and Laith H. Alzubaidi\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e1.1 Introduction 4\u003c\/p\u003e \u003cp\u003e1.1.1 Characteristics of a Smart City 5\u003c\/p\u003e \u003cp\u003e1.2 Smart City 6\u003c\/p\u003e \u003cp\u003e1.2.1 An Overview of Smart Cities 6\u003c\/p\u003e \u003cp\u003e1.2.2 Role of Digitalisation in Smart Cities 6\u003c\/p\u003e \u003cp\u003e1.2.3 Infrastructural Impacts of Digitalisation in Smart Cities 9\u003c\/p\u003e \u003cp\u003e1.3 Smart Mobility in Smart Cities 10\u003c\/p\u003e \u003cp\u003e1.4 Analysis of Security Threats 13\u003c\/p\u003e \u003cp\u003e1.4.1 Mobility Trends in Smart Cities in the Future 14\u003c\/p\u003e \u003cp\u003e1.5 Issues and Opportunities Related to Smart Cities 15\u003c\/p\u003e \u003cp\u003e1.5.1 Challenges for Smart Cities 15\u003c\/p\u003e \u003cp\u003e1.5.2 Trends and Opportunities for the Future 17\u003c\/p\u003e \u003cp\u003e1.6 Conclusions 17\u003c\/p\u003e \u003cp\u003eReferences 18\u003c\/p\u003e \u003cp\u003e\u003cb\u003e2 Accentuating Climate Change Adaptation and Vulnerability (CCAV) Challenges 23\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eAdil Abbas Alwan, Amandeep Kaur, Nilesh Bhosle, Sanjeev Kumar Shah and Mohemmed Hussien\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e2.1 Introduction 24\u003c\/p\u003e \u003cp\u003e2.1.1 Adapting to Climate Change Vulnerabilities 25\u003c\/p\u003e \u003cp\u003e2.2 Related Work 26\u003c\/p\u003e \u003cp\u003e2.2.1 Spatial Violence 26\u003c\/p\u003e \u003cp\u003e2.2.2 Response to Climate Change 27\u003c\/p\u003e \u003cp\u003e2.3 Key Challenges in Climate Change Adaptation and Vulnerability (CCAV) 28\u003c\/p\u003e \u003cp\u003e2.3.1 Technical Challenges 28\u003c\/p\u003e \u003cp\u003e2.3.2 Financial Constraints 28\u003c\/p\u003e \u003cp\u003e2.3.3 Social and Cultural Barriers 28\u003c\/p\u003e \u003cp\u003e2.3.4 Institutional and Governance Challenges 29\u003c\/p\u003e \u003cp\u003e2.3.5 Multi-Level Governance (MLG) of Climate Change 29\u003c\/p\u003e \u003cp\u003e2.4 Case Studies Highlighting Vulnerability and Adaptation Challenges 30\u003c\/p\u003e \u003cp\u003e2.4.1 Small Island Developing States (SIDS) 30\u003c\/p\u003e \u003cp\u003e2.4.2 Rural Farming Communities in Sub-Saharan Africa 30\u003c\/p\u003e \u003cp\u003e2.4.3 Urban Slums in South Asia 31\u003c\/p\u003e \u003cp\u003e2.5 Strategic Frameworks for Addressing CCAV Challenges 31\u003c\/p\u003e \u003cp\u003e2.5.1 Through Community-Based Approaches 31\u003c\/p\u003e \u003cp\u003e2.5.2 Mobilising Climate Finance and Reducing Funding Barriers 31\u003c\/p\u003e \u003cp\u003e2.5.3 Strengthening Institutional Capacity and Governance Frameworks 32\u003c\/p\u003e \u003cp\u003e2.5.4 Innovating and Leveraging Technology 32\u003c\/p\u003e \u003cp\u003e2.5.5 Insufficient Funding and Resources 32\u003c\/p\u003e \u003cp\u003e2.5.6 Data Gaps and Uncertainty 32\u003c\/p\u003e \u003cp\u003e2.5.7 Insufficient Localised Solutions 33\u003c\/p\u003e \u003cp\u003e2.5.8 Institutional and Policy Challenges 33\u003c\/p\u003e \u003cp\u003e2.5.9 Social and Economic Inequities 33\u003c\/p\u003e \u003cp\u003e2.5.10 Awareness and Engagement of the Public Lacking 33\u003c\/p\u003e \u003cp\u003e2.5.11 Using Fossil Fuels as a Source of Energy 33\u003c\/p\u003e \u003cp\u003e2.5.12 Limitations 34\u003c\/p\u003e \u003cp\u003e2.5.13 Maintaining a Balance Between Short-Term and Long-Term Needs 34\u003c\/p\u003e \u003cp\u003e2.5.14 Adaptation Challenges Based on Ecosystems 34\u003c\/p\u003e \u003cp\u003e2.5.15 Efforts to Monitor and Evaluate Adaptation 34\u003c\/p\u003e \u003cp\u003e2.5.16 Global Coordination and Climate Justice 34\u003c\/p\u003e \u003cp\u003e2.6 Conclusion 35\u003c\/p\u003e \u003cp\u003eReferences 35\u003c\/p\u003e \u003cp\u003e\u003cb\u003e3 Delineating the Solution Approaches for Sustainable Urban Mobility 39\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eAdil Abbas Alwan, Amandeep Kaur, Nilesh Bhosle, Rajesh Singh and Mohammed Al-Farouni\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e3.1 Introduction 40\u003c\/p\u003e \u003cp\u003e3.2 Related Work 42\u003c\/p\u003e \u003cp\u003e3.3 Materials and Methods 44\u003c\/p\u003e \u003cp\u003e3.3.1 Travel Demand Generation 45\u003c\/p\u003e \u003cp\u003e3.3.2 Traffic Simulation Process 46\u003c\/p\u003e \u003cp\u003e3.4 Results Analysis and Discussion 47\u003c\/p\u003e \u003cp\u003e3.4.1 Amsterdam 47\u003c\/p\u003e \u003cp\u003e3.4.2 Helsinki 49\u003c\/p\u003e \u003cp\u003e3.5 Conclusion 51\u003c\/p\u003e \u003cp\u003eReferences 51\u003c\/p\u003e \u003cp\u003e\u003cb\u003e4 About the Growing Power of Artificial Intelligence (AI) and Blockchain for Fleet Management and Sustainable Societies 55\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eJayant Jagtap, Raman Kumar, Kunal Gagneja, Anita Gehlot and M. Muhsen Hassan\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e4.1 Introduction 56\u003c\/p\u003e \u003cp\u003e4.1.1 Artificial Intelligence and Blockchain 57\u003c\/p\u003e \u003cp\u003e4.1.2 Sustainable Smart City Society 59\u003c\/p\u003e \u003cp\u003e4.2 Literature Survey and Contribution 60\u003c\/p\u003e \u003cp\u003e4.2.1 Privacy and Security Concerns 60\u003c\/p\u003e \u003cp\u003e4.3 Blockchain to Support Smart Cities’ Operations 62\u003c\/p\u003e \u003cp\u003e4.4 Blockchain Benefits 63\u003c\/p\u003e \u003cp\u003e4.5 Types of Blockchain Networks 64\u003c\/p\u003e \u003cp\u003e4.6 Blockchain Suitability 65\u003c\/p\u003e \u003cp\u003e4.7 Conclusion 66\u003c\/p\u003e \u003cp\u003eReferences 67\u003c\/p\u003e \u003cp\u003e\u003cb\u003e5 Testifying the Criticality of the Internet of Things (IoT), 5G and AI: A Perfect Combination for Battery Management 71\u003cbr\u003e \u003c\/b\u003e\u003ci\u003ePreeti Rani, Raman Kumar, Amrita Singh, Jayant Jagtap and Muntather Almusawi\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e5.1 Introduction 72\u003c\/p\u003e \u003cp\u003e5.1.1 Energy Management Strategy Description 74\u003c\/p\u003e \u003cp\u003e5.2 Literature Review 74\u003c\/p\u003e \u003cp\u003e5.2.1 Managing an EV Battery Pack 75\u003c\/p\u003e \u003cp\u003e5.2.2 IoT in Battery Management 75\u003c\/p\u003e \u003cp\u003e5.2.3 Wireless BMS Incentive Program 75\u003c\/p\u003e \u003cp\u003e5.2.4 5G as a Catalyst for Rapid Data Transmission 76\u003c\/p\u003e \u003cp\u003e5.2.5 AI and Predictive Analytics in Battery Optimization 76\u003c\/p\u003e \u003cp\u003e5.2.6 Synergy of IoT, 5G, and AI in Battery Management 76\u003c\/p\u003e \u003cp\u003e5.3 The Internet of Things (IoT) in Battery Management 77\u003c\/p\u003e \u003cp\u003e5.3.1 Real-Time Monitoring and Predictive Maintenance 77\u003c\/p\u003e \u003cp\u003e5.3.2 Data Collection and Data-Driven Insights 77\u003c\/p\u003e \u003cp\u003e5.4 5G Connectivity: Enabling High-Speed, Low-Latency Data Exchange 77\u003c\/p\u003e \u003cp\u003e5.4.1 Enhancing Real-Time Decision Making 78\u003c\/p\u003e \u003cp\u003e5.4.2 Scalability of IoT Networks 78\u003c\/p\u003e \u003cp\u003e5.5 Artificial Intelligence (AI): The Brain Behind Smart Battery Management 78\u003c\/p\u003e \u003cp\u003e5.6 BMS’s Goals and Challenges 81\u003c\/p\u003e \u003cp\u003e5.6.1 Optimal Charging 82\u003c\/p\u003e \u003cp\u003e5.6.2 Fast Characterization 83\u003c\/p\u003e \u003cp\u003e5.7 Conclusion 83\u003c\/p\u003e \u003cp\u003eReferences 84\u003c\/p\u003e \u003cp\u003e\u003cb\u003e6 Using Local Knowledge and Sustainable Transport for Greener Mobility 89\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eJayant Jagtap, Amrita Singh, Sandeep Singh, Shivani Pant and Haider Mohammed Abbas\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e6.1 Introduction 90\u003c\/p\u003e \u003cp\u003e6.2 Related Work 92\u003c\/p\u003e \u003cp\u003e6.3 Greening Mobility Necessities 94\u003c\/p\u003e \u003cp\u003e6.3.1 Green Transport Standards 94\u003c\/p\u003e \u003cp\u003e6.4 Principles of the Sustainable Mobility Paradigm 97\u003c\/p\u003e \u003cp\u003e6.5 Conclusion 100\u003c\/p\u003e \u003cp\u003eReferences 100\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart 2: Green Revolution in IoV 105\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e7 Expounding the Importance of Explainable AI for Greener Transportations 107\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eAbhilasha Jadhav, Amrita Singh, Adil Abbas Alwan, Ruby Pant and Haider Alabdeli\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e7.1 Introduction 108\u003c\/p\u003e \u003cp\u003e7.2 Related Work 110\u003c\/p\u003e \u003cp\u003e7.2.1 Why Explainable AI is Needed? 111\u003c\/p\u003e \u003cp\u003e7.2.2 Evaluation of Explainable-AI (XAI) Frameworks and Results 113\u003c\/p\u003e \u003cp\u003e7.3 The Need for Explainable AI in Transportation 115\u003c\/p\u003e \u003cp\u003e7.4 AI’s Potential for Transforming Smart Cities and its Limitations 116\u003c\/p\u003e \u003cp\u003e7.5 Explainable AI Supports Greener Transportation 117\u003c\/p\u003e \u003cp\u003e7.5.1 Optimizing Traffic Flow and Reducing Emissions 117\u003c\/p\u003e \u003cp\u003e7.5.2 Managing and Reducing Fleet Emissions 117\u003c\/p\u003e \u003cp\u003e7.5.3 Enhancing Predictive Maintenance 118\u003c\/p\u003e \u003cp\u003e7.5.4 Supporting Autonomous Vehicles and Green Routing 118\u003c\/p\u003e \u003cp\u003e7.5.5 Facilitating Transparent Data Sharing 118\u003c\/p\u003e \u003cp\u003e7.6 Benefits of Explainable AI in Greener Transportation 118\u003c\/p\u003e \u003cp\u003e7.7 Challenges of Implementing Explainable AI in Greener Transportation 119\u003c\/p\u003e \u003cp\u003e7.8 Conclusion 120\u003c\/p\u003e \u003cp\u003eReferences 120\u003c\/p\u003e \u003cp\u003e\u003cb\u003e8 Demystifying the Aspects of Edge Computing and Edge AI for Real-Time Insights 127\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eAbhilasha Jadhav, Heena Madan, Mohammed Y. Al-khuzaie, Ruby Pant, Nidhi Singh and Hassan M. Al-Jawahry\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e8.1 Introduction 128\u003c\/p\u003e \u003cp\u003e8.1.1 Importance of Real-Time Processing in AI 129\u003c\/p\u003e \u003cp\u003e8.1.2 A Paradigm for Edge Computing 131\u003c\/p\u003e \u003cp\u003e8.1.3 Mobile Edge Computing (MEC) 132\u003c\/p\u003e \u003cp\u003e8.1.3.1 Understanding Edge Computing 132\u003c\/p\u003e \u003cp\u003e8.1.3.2 The Architecture of Edge Computing 132\u003c\/p\u003e \u003cp\u003e8.1.4 Advantages of Edge Computing 133\u003c\/p\u003e \u003cp\u003e8.2 Edge AI 134\u003c\/p\u003e \u003cp\u003e8.2.1 Decision-Making in Real-Time: Why it’s Important 135\u003c\/p\u003e \u003cp\u003e8.2.2 Purpose and Scope of the Paper 135\u003c\/p\u003e \u003cp\u003e8.3 Application of Edge AI in a Variety of Industries 137\u003c\/p\u003e \u003cp\u003e8.3.1 Manufacturing 137\u003c\/p\u003e \u003cp\u003e8.4 Edge AI Challenges and Limitations 138\u003c\/p\u003e \u003cp\u003e8.4.1 Challenges in Technology 138\u003c\/p\u003e \u003cp\u003e8.5 Future Directions and Trends 140\u003c\/p\u003e \u003cp\u003e8.5.1 Federated Learning on the Edge 140\u003c\/p\u003e \u003cp\u003e8.5.2 5G and Edge Synergy 140\u003c\/p\u003e \u003cp\u003e8.5.3 TinyML for Edge AI 140\u003c\/p\u003e \u003cp\u003e8.5.4 Integration with Blockchain for Security 140\u003c\/p\u003e \u003cp\u003e8.6 Conclusion 140\u003c\/p\u003e \u003cp\u003eReferences 141\u003c\/p\u003e \u003cp\u003e\u003cb\u003e9 Elucidating the Strategic Significance of Smart Grids Towards Sustainable Cities 145\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eAbhilasha Jadhav, Heena Madan, Mohammed Y. Al-khuzaie, Sanjeev Kumar Shah and Mohammed I. Habelalmateen\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e9.1 Introduction 146\u003c\/p\u003e \u003cp\u003e9.2 Related Work 149\u003c\/p\u003e \u003cp\u003e9.3 Smart Grids as a Catalyst for Sustainability in Urban Environments 154\u003c\/p\u003e \u003cp\u003e9.4 Smart Grid Technologies: Enabling Real-Time Decision Making 155\u003c\/p\u003e \u003cp\u003e9.5 Challenges in Implementing Smart Grids for Sustainable Cities 156\u003c\/p\u003e \u003cp\u003e9.6 Case Studies: Smart Grid Implementation in Sustainable Cities 156\u003c\/p\u003e \u003cp\u003e9.7 Conclusion 157\u003c\/p\u003e \u003cp\u003eReferences 157\u003c\/p\u003e \u003cp\u003e\u003cb\u003e10 Describing the Needs for Connected Electric Vehicles for Better Air Quality 161\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eShivakrishna Dasi, Jasgurpreet Singh Chohan, Saroj Kumar Gupta, Rajesh Singh and Myasar Mundher Adnan\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e10.1 Introduction 162\u003c\/p\u003e \u003cp\u003e10.2 Related Work 164\u003c\/p\u003e \u003cp\u003e10.2.1 Battery Electric Vehicles 165\u003c\/p\u003e \u003cp\u003e10.3 Performance Aspects of CAEVs 166\u003c\/p\u003e \u003cp\u003e10.3.1 Autonomous Vehicles 167\u003c\/p\u003e \u003cp\u003e10.3.2 Connected Vehicles 168\u003c\/p\u003e \u003cp\u003e10.3.3 Electric Vehicles 169\u003c\/p\u003e \u003cp\u003e10.4 The Impact of Air Quality on Environmental Justice (EJ) 170\u003c\/p\u003e \u003cp\u003e10.4.1 Data Collection and Setup of Air Quality Modeling Systems 170\u003c\/p\u003e \u003cp\u003e10.5 CAV Taxonomy Based on Performance 170\u003c\/p\u003e \u003cp\u003e10.5.1 Connected and Autonomous Electric Vehicles (CAEVs) 171\u003c\/p\u003e \u003cp\u003e10.5.2 The Quality of Experience Framework for CAEVs 172\u003c\/p\u003e \u003cp\u003e10.6 Conclusion 173\u003c\/p\u003e \u003cp\u003eReferences 173\u003c\/p\u003e \u003cp\u003e\u003cb\u003e11 Distilling the Convergence of AI and EVs Towards Self-Driving EVs 177\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eShivakrishna Dasi, Heena Madan, Mohammed Y. Al-khuzaie, Anita Gehlot and Ramy Riad Al-Fatlawy\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e11.1 Introduction 178\u003c\/p\u003e \u003cp\u003e11.1.1 The State of Electric Vehicles (EVs) Today 181\u003c\/p\u003e \u003cp\u003e11.2 Related Work 181\u003c\/p\u003e \u003cp\u003e11.2.1 AI as the Backbone of Self-Driving Technology 182\u003c\/p\u003e \u003cp\u003e11.2.2 Machine Learning and Computer Vision 182\u003c\/p\u003e \u003cp\u003e11.2.3 Deep Reinforcement Learning 182\u003c\/p\u003e \u003cp\u003e11.3 The Convergence of AI and EVs: Key Enablers for Self-Driving EVs 184\u003c\/p\u003e \u003cp\u003e11.3.1 Technical Challenges in the Path Towards Self-Driving EVs 185\u003c\/p\u003e \u003cp\u003e11.4 The Impact of Self-Driving EVs on Society and the Environment 186\u003c\/p\u003e \u003cp\u003e11.5 The Impact of Self-Driving Vehicles on the Environment 189\u003c\/p\u003e \u003cp\u003e11.6 Conclusion 190\u003c\/p\u003e \u003cp\u003eReferences 191\u003c\/p\u003e \u003cp\u003e\u003cb\u003e12 Explaining the Distinct Functionalities of Battery Management Systems (BMS) 197\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eHawraa Ali Sabah, Shivakrishna Dasi, Jaspreet Kaur, Devendra Singh and Ahmad Radee Alawadi\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e12.1 Introduction 198\u003c\/p\u003e \u003cp\u003e12.2 Battery Management System (BMS) 199\u003c\/p\u003e \u003cp\u003e12.3 An Overview of Components and Topologies 202\u003c\/p\u003e \u003cp\u003e12.3.1 Software Architecture 203\u003c\/p\u003e \u003cp\u003e12.3.2 Functionalities 204\u003c\/p\u003e \u003cp\u003e12.4 Battery Models 205\u003c\/p\u003e \u003cp\u003e12.4.1 Thermal Modeling 205\u003c\/p\u003e \u003cp\u003e12.4.2 Electrical Modeling 207\u003c\/p\u003e \u003cp\u003e12.5 Monitoring the Stack 208\u003c\/p\u003e \u003cp\u003e12.5.1 Batteries for Grid Storage 209\u003c\/p\u003e \u003cp\u003e12.5.2 A Modeling Approach to Lithium-Ion Batteries 209\u003c\/p\u003e \u003cp\u003e12.5.3 Advanced Model-Based BMSs 210\u003c\/p\u003e \u003cp\u003e12.6 State of Charge Estimation 210\u003c\/p\u003e \u003cp\u003e12.6.1 The Need for BMS in Smart Grids and EVs 211\u003c\/p\u003e \u003cp\u003e12.6.2 Challenges of BMS and Possible Solutions 211\u003c\/p\u003e \u003cp\u003e12.7 Conclusion 211\u003c\/p\u003e \u003cp\u003eReferences 212\u003c\/p\u003e \u003cp\u003e\u003cb\u003e13 Detailing How AI Empowers Battery Management Systems 215\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eUmesh Chandra Garjola, Ashish Singh, Hawraa Ali Sabah, Jaspreet Kaur and Zaid Alsalami\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e13.1 Introduction 216\u003c\/p\u003e \u003cp\u003e13.2 Systems for Managing Batteries 218\u003c\/p\u003e \u003cp\u003e13.2.1 Structure of Elements and Arrangements 219\u003c\/p\u003e \u003cp\u003e13.2.2 Structure of Battery-Management System 221\u003c\/p\u003e \u003cp\u003e13.2.3 System Functions to Manage Batteries 221\u003c\/p\u003e \u003cp\u003e13.2.4 Impacts of Battery-Management Systems 222\u003c\/p\u003e \u003cp\u003e13.2.5 A Study of How AI Can Be Applied to Smart Grids and Renewable Energy 222\u003c\/p\u003e \u003cp\u003e13.3 Traditionally, BMS Has Faced Many Challenges 224\u003c\/p\u003e \u003cp\u003e13.4 AI in Business Management Systems 225\u003c\/p\u003e \u003cp\u003e13.4.1 Calculation of State of Charge (SoC) and State of Health (SoH) 225\u003c\/p\u003e \u003cp\u003e13.4.2 Balancing and Controlling the Temperature of Cells 225\u003c\/p\u003e \u003cp\u003e13.4.3 Predicting and Diagnosing Faults 225\u003c\/p\u003e \u003cp\u003e13.4.4 Optimizing Energy Efficiency and Extending the Range 226\u003c\/p\u003e \u003cp\u003e13.5 BMS Powered by Artificial Intelligence 226\u003c\/p\u003e \u003cp\u003e13.5.1 Machine Learning (ML) and Deep Learning (DL) 226\u003c\/p\u003e \u003cp\u003e13.5.2 Reinforcement Learning (RL) 226\u003c\/p\u003e \u003cp\u003e13.5.3 An Algorithm for Detecting Anomalies 227\u003c\/p\u003e \u003cp\u003e13.5.4 Digital Twins 227\u003c\/p\u003e \u003cp\u003e13.6 BMS with AI Enhancements: Benefits 227\u003c\/p\u003e \u003cp\u003e13.6.1 BMS Integration with AI Offers Numerous Benefits 227\u003c\/p\u003e \u003cp\u003e13.6.2 Future Trends and Challenges 227\u003c\/p\u003e \u003cp\u003e13.6.3 Future Prospects 228\u003c\/p\u003e \u003cp\u003e13.7 Conclusion 228\u003c\/p\u003e \u003cp\u003eReferences 228\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart 3: Infrastructure Optimization in EV 233\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e14 Insisting for Electric Vehicle (EV) Charging Infrastructure Management Systems 235\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eJasgurpreet Singh Chohan, Ashish Singh, Jaspreet Kaur, Ruby Pant and Kassem AL-Attabi\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e14.1 Introduction 236\u003c\/p\u003e \u003cp\u003e14.2 The Need for EV Charging Infrastructure Management Systems 238\u003c\/p\u003e \u003cp\u003e14.2.1 User Demand for Convenience 239\u003c\/p\u003e \u003cp\u003e14.2.2 Utility and Energy Load Management 239\u003c\/p\u003e \u003cp\u003e14.2.3 Integration with Renewable Energy Sources 239\u003c\/p\u003e \u003cp\u003e14.3 Overview of the Charging Infrastructure for Electric Vehicles 239\u003c\/p\u003e \u003cp\u003e14.3.1 Equipment Specifications for Electric Vehicles 239\u003c\/p\u003e \u003cp\u003e14.3.2 Standards for Interoperable EV Charging 241\u003c\/p\u003e \u003cp\u003e14.4 Model Overview 242\u003c\/p\u003e \u003cp\u003e14.4.1 Vehicle Fleet 243\u003c\/p\u003e \u003cp\u003e14.4.2 Deployment of Electric Vehicle Charging Infrastructure 244\u003c\/p\u003e \u003cp\u003e14.5 Hotspot-Based EVCS 246\u003c\/p\u003e \u003cp\u003e14.6 Key Features of EV Charging Infrastructure Management Systems 246\u003c\/p\u003e \u003cp\u003e14.6.1 Smart Charging and Load Balancing 246\u003c\/p\u003e \u003cp\u003e14.6.2 Data Collection and Predictive Maintenance 247\u003c\/p\u003e \u003cp\u003e14.6.3 Dynamic Pricing and User Management 247\u003c\/p\u003e \u003cp\u003e14.6.4 Integration with Mobile Applications 247\u003c\/p\u003e \u003cp\u003e14.6.5 Grid Interaction and Energy Storage 247\u003c\/p\u003e \u003cp\u003e14.6.6 Scalability and Flexibility 247\u003c\/p\u003e \u003cp\u003e14.7 Challenges in Implementing EV Charging Infrastructure Management Systems 248\u003c\/p\u003e \u003cp\u003e14.7.1 High Initial Investment Costs 248\u003c\/p\u003e \u003cp\u003e14.7.2 Data Security and Privacy 248\u003c\/p\u003e \u003cp\u003e14.7.3 Interoperability and Standardization 248\u003c\/p\u003e \u003cp\u003e14.7.4 Grid Reliability and Capacity 248\u003c\/p\u003e \u003cp\u003e14.8 Future Directions and Innovations in EV Charging Infrastructure Management 248\u003c\/p\u003e \u003cp\u003e14.8.1 AI and Machine Learning for Predictive Optimization 249\u003c\/p\u003e \u003cp\u003e14.8.2 Blockchain for Secure Transactions 249\u003c\/p\u003e \u003cp\u003e14.8.3 Ultra-Fast and Wireless Charging 249\u003c\/p\u003e \u003cp\u003e14.9 Conclusion 249\u003c\/p\u003e \u003cp\u003eReferences 250\u003c\/p\u003e \u003cp\u003e\u003cb\u003e15 Illuminating the AIs Role in Shaping Up EV Charging Infrastructures 253\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eJatinder Kumar, Ashish Singh, Hawraa Ali Sabah, Yashwant Singh Bisht and Laith H. Jasim\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e15.1 Electro Mobility Charging Systems 254\u003c\/p\u003e \u003cp\u003e15.2 Literature Review 256\u003c\/p\u003e \u003cp\u003e15.3 Electric Vehicle Charging Infrastructure 257\u003c\/p\u003e \u003cp\u003e15.3.1 Infrastructural Types of Charging 258\u003c\/p\u003e \u003cp\u003e15.4 Optimizing the Charging Infrastructure Using Artificial Intelligence 259\u003c\/p\u003e \u003cp\u003e15.4.1 Predicting Charging Demand with Data Analytics 260\u003c\/p\u003e \u003cp\u003e15.4.2 Managing Dynamic Charges with AI 260\u003c\/p\u003e \u003cp\u003e15.4.3 Planned Infrastructure Optimization Algorithms 261\u003c\/p\u003e \u003cp\u003e15.5 Charging Intelligent Infrastructures 262\u003c\/p\u003e \u003cp\u003e15.5.1 The Challenges of Developing EV Charging Infrastructure 262\u003c\/p\u003e \u003cp\u003e15.5.2 Predicting Demand and Selecting Sites with AI 262\u003c\/p\u003e \u003cp\u003e15.5.3 Managing and Balancing Loads in Real Time 263\u003c\/p\u003e \u003cp\u003e15.5.4 The Integration of Renewable Energy Sources with AI 263\u003c\/p\u003e \u003cp\u003e15.5.5 Infrastructural Challenges and Considerations in AI-Driven Charging 264\u003c\/p\u003e \u003cp\u003e15.5.6 The Future of AI in EV Charging Infrastructure 264\u003c\/p\u003e \u003cp\u003e15.6 Conclusion 265\u003c\/p\u003e \u003cp\u003eReferences 265\u003c\/p\u003e \u003cp\u003e\u003cb\u003e16 Deciphering Smart Grid Integration and Energy Management 269\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eJatinder Kumar, Protyay Dey, Jasgurpreet Singh Chohan, Sanjeev Kumar Shah and Laith Jasim\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e16.1 Introduction 270\u003c\/p\u003e \u003cp\u003e16.1.1 Smart Grid Systems 271\u003c\/p\u003e \u003cp\u003e16.1.2 Energy Management System 272\u003c\/p\u003e \u003cp\u003e16.1.3 System for Managing Transmission Energy 273\u003c\/p\u003e \u003cp\u003e16.2 A Smart Grid EMS Based on Communication Technologies 275\u003c\/p\u003e \u003cp\u003e16.2.1 Gprs 275\u003c\/p\u003e \u003cp\u003e16.2.2 WiMAX (IEEE 802.16) 276\u003c\/p\u003e \u003cp\u003e16.2.3 Bluetooth (IEEE 802.15) 276\u003c\/p\u003e \u003cp\u003e16.2.4 Power Line Communication (PLC) 276\u003c\/p\u003e \u003cp\u003e16.3 Smart Grids: An Overview 277\u003c\/p\u003e \u003cp\u003e16.3.1 An Overview of Smart Grid Components 277\u003c\/p\u003e \u003cp\u003e16.3.2 Goals of a Smart Grid 278\u003c\/p\u003e \u003cp\u003e16.4 Integrating Smart Grids with Existing Infrastructure 278\u003c\/p\u003e \u003cp\u003e16.4.1 Upgrading Infrastructure 278\u003c\/p\u003e \u003cp\u003e16.4.2 Synchronizing with Renewable Sources 279\u003c\/p\u003e \u003cp\u003e16.4.3 Digitalizing the Grid 279\u003c\/p\u003e \u003cp\u003e16.4.4 Cybersecurity Measures 279\u003c\/p\u003e \u003cp\u003e16.5 Energy Management in the Smart Grid 279\u003c\/p\u003e \u003cp\u003e16.5.1 Demand Response 279\u003c\/p\u003e \u003cp\u003e16.5.2 Distributed Energy Resources Management (derm) 280\u003c\/p\u003e \u003cp\u003e16.5.3 Energy Storage Solutions 280\u003c\/p\u003e \u003cp\u003e16.5.4 Rates and Pricing for Real-Time Usage 280\u003c\/p\u003e \u003cp\u003e16.5.5 Electric Vehicle (EV) Integration 280\u003c\/p\u003e \u003cp\u003e16.6 Managing Energy and Integrating Smart Grids 280\u003c\/p\u003e \u003cp\u003e16.7 Conclusion 281\u003c\/p\u003e \u003cp\u003eReferences 282\u003c\/p\u003e \u003cp\u003e\u003cb\u003e17 Decoding the Aspects of Intelligent Traffic Management 287\u003cbr\u003e \u003c\/b\u003e\u003ci\u003ePreeti Rani, Jatinder Kumar, Sandeep Singh, Protyay Dey and Laith H. Jasim\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e17.1 Introduction 288\u003c\/p\u003e \u003cp\u003e17.2 Related Work 290\u003c\/p\u003e \u003cp\u003e17.3 Proposed Methodology 292\u003c\/p\u003e \u003cp\u003e17.3.1 Design Objectives 292\u003c\/p\u003e \u003cp\u003e17.3.2 Method and Materials 293\u003c\/p\u003e \u003cp\u003e17.4 ITS Applications in Various Transport Sectors 295\u003c\/p\u003e \u003cp\u003e17.4.1 Transportation Industry 296\u003c\/p\u003e \u003cp\u003e17.4.2 Low CE of Urban Transportation 296\u003c\/p\u003e \u003cp\u003e17.4.3 Road Traffic Transportation Infrastructure 296\u003c\/p\u003e \u003cp\u003e17.5 Result and Discussion 297\u003c\/p\u003e \u003cp\u003e17.6 Conclusion 298\u003c\/p\u003e \u003cp\u003eReferences 299\u003c\/p\u003e \u003cp\u003e\u003cb\u003e18 Exploring the Impact of Computer Vision in Smart Transportation 301\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eUmesh Chandra Garjola, Sandeep Singh, Kamaljeet Kaur, Protyay Dey and Laith Hussein\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e18.1 Introduction 302\u003c\/p\u003e \u003cp\u003e18.1.1 Surveillance Systems Along Roadsides: An Overview 302\u003c\/p\u003e \u003cp\u003e18.2 Related Work 303\u003c\/p\u003e \u003cp\u003e18.2.1 Computer Vision Functions 303\u003c\/p\u003e \u003cp\u003e18.3 Proposed Methodology 308\u003c\/p\u003e \u003cp\u003e18.3.1 ACF Object Detection System 309\u003c\/p\u003e \u003cp\u003e18.3.2 Point Tracker Algorithm 309\u003c\/p\u003e \u003cp\u003e18.3.3 Intelligent Transportation Systems: Computer Vision Applications 309\u003c\/p\u003e \u003cp\u003e18.3.4 Intelligent Transportation Systems and Machine Learning (ML) 310\u003c\/p\u003e \u003cp\u003e18.3.4.1 Machine Learning: The Evolution 311\u003c\/p\u003e \u003cp\u003e18.3.4.2 Challenges 313\u003c\/p\u003e \u003cp\u003e18.4 Result and Discussion 314\u003c\/p\u003e \u003cp\u003e18.5 Conclusion 317\u003c\/p\u003e \u003cp\u003eReferences 317\u003c\/p\u003e \u003cp\u003e\u003cb\u003e19 Exposing the Importance of Connected Lighting for Urban Sustainability 323\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eZainab. R. Abdulsada, Kamaljeet Kaur, Sapna Singh, Devendra Singh and Mohammed H. Al-Farouni\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e19.1 Introduction 324\u003c\/p\u003e \u003cp\u003e19.2 Sustainability 326\u003c\/p\u003e \u003cp\u003e19.3 Transdisciplinary Framework for Urban Lighting Research: Actors, Framework, and Four Steps 327\u003c\/p\u003e \u003cp\u003e19.4 Understanding Connected Lighting Systems 330\u003c\/p\u003e \u003cp\u003e19.5 Energy Efficiency and Reduced Carbon Emissions 330\u003c\/p\u003e \u003cp\u003e19.6 Conclusion 332\u003c\/p\u003e \u003cp\u003eReferences 333\u003c\/p\u003e \u003cp\u003e\u003cb\u003e20 Responsible and Green AI for Environment Sustainability 337\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eKunal Gagneja, Sapna Singh, Zainab. R. Abdulsada, Shivani Pant and Rami Riad Hussien\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e20.1 Introduction 338\u003c\/p\u003e \u003cp\u003e20.2 AI and the Environment 339\u003c\/p\u003e \u003cp\u003e20.2.1 Green-by AI 340\u003c\/p\u003e \u003cp\u003e20.2.2 Green-in AI 342\u003c\/p\u003e \u003cp\u003e20.3 Principles of Responsible AI 344\u003c\/p\u003e \u003cp\u003e20.4 Sustainable AI for Human and Planetary Flourishing 345\u003c\/p\u003e \u003cp\u003e20.5 AI for Environmental Sustainability 348\u003c\/p\u003e \u003cp\u003e20.5.1 Climate Prediction and Disaster Management 348\u003c\/p\u003e \u003cp\u003e20.5.2 Precision Agriculture 348\u003c\/p\u003e \u003cp\u003e20.5.3 Wildlife Conservation and Biodiversity 348\u003c\/p\u003e \u003cp\u003e20.5.4 Renewable Energy Optimisation 348\u003c\/p\u003e \u003cp\u003e20.6 Challenges and Future Directions 349\u003c\/p\u003e \u003cp\u003e20.7 Conclusion 349\u003c\/p\u003e \u003cp\u003eReferences 349\u003c\/p\u003e \u003cp\u003e\u003cb\u003e21 Integrating AI into Mobility as a Service (MaaS): The Future of Urban Transportation 355\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eKunal Gagneja, Zainab. R. Abdulsada, Sapna Singh, Ruby Pant and Ramy Al-Fatlawy\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e21.1 Introduction 356\u003c\/p\u003e \u003cp\u003e21.1.1 The MaaS Concept 356\u003c\/p\u003e \u003cp\u003e21.2 Mobility in Rural Areas is a Problem 359\u003c\/p\u003e \u003cp\u003e21.3 Transportation Systems and Artificial Intelligence: A Critical Review 360\u003c\/p\u003e \u003cp\u003e21.3.1 Artificial Intelligence-Assisted Smart Cities 360\u003c\/p\u003e \u003cp\u003e21.3.2 AI Applications Currently in Use 363\u003c\/p\u003e \u003cp\u003e21.3.3 Identifying Research Gaps 365\u003c\/p\u003e \u003cp\u003e21.3.4 Sustainability Implications of Apps 365\u003c\/p\u003e \u003cp\u003e21.3.5 The Impact of Urban Development on the Environment 366\u003c\/p\u003e \u003cp\u003e21.4 Encounters 367\u003c\/p\u003e \u003cp\u003e21.4.1 Challenges in Knowledge 367\u003c\/p\u003e \u003cp\u003e21.5 Expected Early Adopter and Users 368\u003c\/p\u003e \u003cp\u003e21.6 Conclusion 371\u003c\/p\u003e \u003cp\u003eReferences 371\u003c\/p\u003e \u003cp\u003eIndex 375\u003c\/p\u003e\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003eSubject Areas: Computer science [\u003ca title=\"See our other books on Computer science\" href=\"https:\/\/freshlyprintedbooks.co.uk\/search?q=%22Computer%20science%20%5BUY%5D%22\"\u003eUY\u003c\/a\u003e]\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\r\n\u003c\/font\u003e","brand":"Wiley-Scrivener","offers":[{"title":"Brand New","offer_id":52433819369752,"sku":"9781394346745","price":145.99,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0730\/2037\/5320\/files\/9781394346745.jpg?v=1784853954","url":"https:\/\/freshlyprintedbooks.co.uk\/products\/artificial-intelligence-technologies-for-smart-and-sustainable-urban-transportation-integrated-platforms-and-use-cases-hardback-9781394346745","provider":"Freshly Printed Books","version":"1.0","type":"link"}