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Produktbild: Artificial Intelligence (AI) for Smart and Sustainable Urban Transportation

Artificial Intelligence (AI) for Smart and Sustainable Urban Transportation

159,99 €

inkl. gesetzl. MwSt., Versandkostenfrei


Beschreibung

Produktdetails

Einband

Gebundene Ausgabe

Erscheinungsdatum

02.06.2026

Herausgeber

Sathyan Munirathinam + weitere

Verlag

Wiley

Seitenzahl

464

Maße (L/B/H)

16,2/23,7/3,3 cm

Gewicht

778 g

Sprache

Englisch

ISBN

978-1-394-35106-0

Beschreibung

Produktdetails

Einband

Gebundene Ausgabe

Erscheinungsdatum

02.06.2026

Herausgeber

Verlag

Wiley

Seitenzahl

464

Maße (L/B/H)

16,2/23,7/3,3 cm

Gewicht

778 g

Sprache

Englisch

ISBN

978-1-394-35106-0

Herstelleradresse

Libri GmbH
Europaallee 1
36244 Bad Hersfeld
DE

Email: gpsr@libri.de

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  • Produktbild: Artificial Intelligence (AI) for Smart and Sustainable Urban Transportation
  • List of Contributors xxi
    About the Editors xxvii

    1 Recent Trends in Intelligent Transportation Systems 1
    Kathi Durgesh, Siddharth Garia, and Vishal Kumar Narnoli

    1.1 Introduction 1
    1.2 Methodology 3
    1.3 Results 9
    1.4 Discussion 10

    2 Artificial Intelligence and IoT Applications Transforming the Automotive Industry 15
    Raviprakash R Salagame

    2.1 Introduction 15
    2.2 Automotive AI Applications and Urban Use Cases 23
    2.3 Connected Vehicles 30
    2.4 Electric Vehicles (EV) 32
    2.5 Shared Mobility 35
    2.6 Future Trends Toward Smart Transportation 35
    2.7 Conclusion 36

    3 Artificial Intelligence in Transportation Using Automated Grading, Adaptive Learning, and Predictive Maintenance to Increase Efficiency 41
    S. Cyciliya Pearline Christy, K. Merriliance, and Mary Immaculate Sheela Lourdusamy

    3.1 Introduction 41
    3.2 Overview of Artificial Intelligence in Transportation 42
    3.3 Automated Grading Systems in Transportation 44
    3.4 Adaptive Learning in Traffic Management and Logistics 46
    3.5 Predictive Maintenance in Transportation Systems 48
    3.6 Ethical, Regulatory, and Security Considerations 50
    3.7 Future Outlook and Emerging Technologies 51
    3.8 Conclusion 53

    4 Autonomous Vehicles and Smart Mobility 57
    P. Sudheer, S. Ashmad, M. Saravanan, and A. Immanuel

    4.1 Introduction 57
    4.2 Challenges in Smart Mobility and Autonomous Vehicles 62
    4.3 Case Studies and Practical Applications of Smart Mobility and Self-driving Cars 64
    4.4 Policies, Ethics, and Governance in the Autonomous Vehicle Ecosystem 66

    5 Artificial Intelligence (AI) for Smart and Sustainable Urban Transportation 73
    Ishika Gupta, Hriday Gupta, Siddharth Gupta, and Prerna Ajmani

    5.1 Introduction 73
    5.2 Background 74
    5.3 Enabling Technologies 78
    5.4 Components 84
    5.5 AI-driven Sustainable Solutions 92
    5.6 Security and Privacy in AI and IoT for Smart Cities and Electric Vehicles 95
    5.7 Case Studies and Real-world Implementations 100
    5.8 Challenges for 6G 105
    5.9 Future Directions 106
    5.10 Conclusion 110

    6 Smart Mobility: Integrating AI for Sustainable Urban Transportation Solutions 113
    A. Jothi Kumar

    6.1 Introduction 113
    6.2 AI in Traffic Management Systems 114
    6.3 Virtual Architecture for AI-based Traffic Management Systems 117
    6.4 AI Applications in Sustainable Urban Mobility 119
    6.5 Data-driven Mobility Solution 121
    6.6 Case Studies of AI Implementation in Smart Cities 121
    6.7 Moral and Political Views 121
    6.8 Future Trends and Innovations 122
    6.9 Conclusion 123

    7 Reinforcement Learning for Energy-efficient Urban Freight Transportation 125
    Nancy Jasmine Goldena and R. Rashia Subashree

    7.1 Introduction 125
    7.2 Fundamentals of RL 126
    7.3 RL Applications in Energy-efficient Urban Freight Transportation 127
    7.4 Integration of RL Applications with Smart Logistics and IoT 131
    7.5 Challenges and Limitations 136
    7.6 Future Directions 137
    7.7 Conclusion 138

    8 Advancements and Challenges in Autonomous Vehicles and Smart Mobility: The Role of AI in Transforming Transportation 141
    A. Jane, Dr. K. Merriliance, and Dr. Mary Immaculate Sheela Lourdusamy

    8.1 Introduction 141
    8.2 Advancements in Autonomous Vehicles and Smart Mobility 144
    8.3 Artificial Intelligence in Autonomous Vehicles 145
    8.4 Perception and Fusion of Sensors for AI-powered Automobiles 148
    8.5 Advantages of AI in Autonomous Vehicles 150
    8.6 Challenges in Autonomous Vehicles and Smart Mobility 151
    8.7 Future Directions and Conclusion 152

    9 Enhancing Urban Traffic Management with Multi-scale Hierarchical GANs 159
    Ashik Shah Jahangeer and P Shanmugavadivu

    9.1 A System Stuck in Time 159
    9.2 When GANs Hit the Road: The Gaps in Current AI Models 162
    9.3 Reimagining Intelligence: The Architecture of MSH-GAN 164
    9.4 The City in Layers: Micro and Macro-level Generators 167
    9.5 Listening to the City: Real-time IoT Data Integration 169
    9.6 Understanding the Why: Hierarchical Modeling and Contextual Awareness 172
    9.7 Thinking at the Edge: Decentralized Computation for Faster Response 174
    9.8 Measuring Intelligence: Evaluating the Performance of MSH-GAN 176
    9.9 From Control to Care: MSH-GAN and the Future of Smart Cities 179
    9.10 Looking Ahead: The Road Beyond MSH-GAN 182

    10 IoT and AI Integration in Traffic Management 187
    J. Steffi, K. Merriliance, and Mary Immaculate Sheela Lourdusamy

    10.1 Introduction 187
    10.2 Role of IoT in Traffic Management 188
    10.3 AI Applications in Traffic Optimization 191
    10.4 Smart Traffic Signals and AI-driven Control Systems 193
    10.5 Incident Detection and Emergency Response 195
    10.6 Public Transport Enhancement with IoT and AI 196
    10.7 Environmental and Sustainability Benefits 198
    10.8 Challenges and Future Trends 200

    11 Intelligent Urbanism: AI and Big Data-driven Approaches to Planning, Design, and Transportation 205
    R. Saradha

    11.1 Introduction 205
    11.2 Literature Background 207
    11.3 Methodology 210
    11.4 Results and Discussion 221
    11.5 Conclusion 223

    12 AI-driven Public Transport Solutions 231
    Shantanu Bindewari, Prakhar Consul, Hilal Ahmed Shah, Basab Nath, and Mansi Trivedi

    12.1 Introduction 231
    12.2 AI Applications in Transportation 234
    12.3 Introduction to AI in Automation and Ticketing 237
    12.4 AI for Safety and Security 241
    12.5 Dynamic Route Optimization Systems 243
    12.6 AI in Public vs. Private Transportation 245
    12.7 Challenges and Ethical Considerations 249
    12.8 Future Trends and Innovations 250
    12.9 Conclusion 251

    13 AI-driven Data Analytics for Smart Urban Transport: Innovations, Challenges, and Future Trends 255
    A. Jasmine Sugil, K. Merriliance, and Mary Immaculate Sheela Lourdusamy

    13.1 Introduction 255
    13.2 AI-powered Data Sources in Urban Transport 260
    13.3 AI Techniques for Urban Transport Analytics 266
    13.4 Key Applications of AI in Urban Transport 270
    13.5 Case Studies and Real-world Implementations 272
    13.6 Challenges and Ethical Considerations 275
    13.7 Future Trends in AI for Urban Transport 277
    13.8 Conclusion 280

    14 Transforming Smart Mobility: L4S and NaaS APIs for Real-time Traffic Management and Autonomous Transport 283
    L. Ameer Shohail

    14.1 Introduction 283
    14.2 Architectural Foundation for Real-time and Autonomous Mobility 284
    14.3 Current Directions in Programmable Transport Networks and LatencyControl 288
    14.4 System Design and Implementation Strategy for Real-time Mobility Control 291
    14.5 Results from Real-time Policy and Queue Enforcement 293
    14.6 Reflections on Programmable Responsiveness in Urban Mobility 296
    14.7 Conclusion 298

    15 AI-driven Public Transportation: Enhancing Efficiency, Sustainability, and User Experience 301
    M. Robinson Joel

    15.1 Introduction 301
    15.2 Existing AI Uses in Public Transportation 304
    15.3 Recognizing AI's Significance in Transportation 305
    15.4 AI Applications in Transportation: Exemplary Instances 307
    15.5 Traffic Management Systems Using AI 309
    15.6 Top AI Resources for Public Transportation 310
    15.7 AI Improve Public Transportation Efficiency 318
    15.8 Safety Benefits of AI in Public Transportation 319
    15.9 Flowchart for GPS-based Vehicle Tracking 321
    15.10 Build Your Own ESP32 GPS Tracker with Live Tracking 324
    15.11 Market Share of AI in Transportation by Different Elements 326
    15.12 Related Work 331
    15.13 Conclusion 336

    16 Cognitive AI for Adaptive and Resilient Urban Transportation: A Data-driven Approach to Sustainable Mobility 343
    Vishal Jain, Archan Mitra, and Sanchita Paul

    16.1 Introduction 343
    16.2 Conceptual Framework and Literature Review 346
    16.3 Methodology 350
    16.4 Integrated Cognitive AI Framework for Urban Transportation 352
    16.5 Data Analysis and Empirical Findings 355
    16.6 Discussion 358
    16.7 Conclusion 361

    17 Optimizing Urban Traffic with Graph Analytics: A Case Study of a Metropolitan Transportation Network 367
    S. Rakshika and Sudeepa Roy Dey

    17.1 Introduction 367
    17.2 Related Work 370
    17.3 Types of Routing Algorithm 372
    17.4 Work 375

    18 Urban Mobility Reimagined: AMRUT Interventions and the 2041 Outlook 387
    S. Thangapriya, Nancy Jasmine Goldena, T. S. Vasughi, M. Kannan, and Barath Ramesh

    18.1 Introduction 387
    18.2 Geospatial Mapping of Tirunelveli Using Advanced Technologies 388
    18.3 Identifying Research Gaps in Tirunelveli for Sustainable Regional Development 389
    18.4 Climate and Rainfall 391
    18.5 Precipitation 392
    18.6 Soil Type Analysis and Resource-efficient Agricultural Planning in Tirunelveli Region 393
    18.7 Geomorphology 394
    18.8 A Road map for Tirunelveli's Future Economy 397
    18.9 AI-based Urban Housing Analytics and Slum Rehabilitation Forecasting for Tirunelveli LPA 398
    18.10 Tirunelveli 2041 as a Sustainable Growth Use Case 399
    18.11 Conclusion 403

    19 GIS-based Analysis of Road Accidents: A Case Study on Hotspot Identification and Safety Improvement 407
    Kirti Goyal, Siddharth Garia, Anoop Bhardwaj, Amol Sharma, Sneha Das, and Animesh Nayak

    19.1 Introduction 407
    19.2 Methodology 408
    19.3 Results and Discussion 408
    19.4 Data Collection and Preparation 408
    19.5 Analysis 412
    19.6 Identifying Blackspots Using GIS 414
    19.7 Key Insights 416
    19.8 Conclusion 417
    19.9 Recommendations 417
    19.10 Way Forward 417

    References 418
    Index 421