Autorentext

Ashu Taneja is Associate Professor at the Centre for Research Impact and Outcome (CRIO), Chitkara University, India.

Abhishek Kumar is a Senior Member of IEEE and works as Assistant Director and Professor in the Computer Science & Engineering Department at Chandigarh University, India.

Suresh Vishnudas Limkar is Assistant Professor at the Department of Computer Science and Engineering at the Central University of Jammu, India.

Mariya Ouaissa is Professor of Cybersecurity and Networks at the Faculty of Sciences Semlalia, Cadi Ayyad University, Morocco.

Mariyam Ouaissa is Assistant Professor of Networks and Systems at ENSA, Chouaib Doukkali University, Morocco.

Klappentext

This book presents the 6G powered integration of Artificial Intelligence (AI) and Digital Twin (DT) technology for sustainable smart cities. In the context of smart cities, 6G, AI and DT hold enormous potential for transformation by boosting city infrastructure and planning, streamlining healthcare facilities, and improving transportation. 6G offers high speed and low latency seamless transfer of vast amounts of data which, when analysed with sophisticated AI models, enhance the decision-making capabilities for smart city infrastructure and urban planning. DT technology, through continuous monitoring and virtual modeling of urban ecosystems, enables predictive maintenance for energy distribution, water management and waste management in a smart city landscape for environmental sustainability.

Driving Innovation through AI and Digital Twin for 6G Powered Sustainable Ultra Smart Cities covers the 6G technological innovations, trends and concerns, as well as practical challenges encountered in the implementation of AI and DT for transforming smart cities for a sustainable future.

Inhalt

Preface xv
Ashu TANEJA, Abhishek KUMAR, Suresh Vishnudas LIMKAR, Mariya OUAISSA and Mariyam OUAISSA

Chapter 1 Navigating Artificial Intelligence and Digital Twin for Smart Cities 1
Wasswa SHAFIK

1.1 Introduction 2

1.2 Artificial intelligence in smart cities 4

1.2.1 Applications of AI in smart cities 6

1.2.2 Benefits and challenges of AI implementation 6

1.2.3 Definitions and components of smart cities 7

1.3 Digital twin technology 8

1.3.1 Concept and definition of digital twin 9

1.3.2 Key components and functionality 10

1.4 Understanding the role of artificial intelligence in smart cities 11

1.4.1 AI-driven decision-making 12

1.4.2 AI-enabled infrastructure management 13

1.5 The role of digital twin technologies in smart cities 14

1.5.1 Digital twins for urban planning 15

1.5.2 Digital twins for smart infrastructure 16

1.6 Integration of AI and digital twin in smart cities 17

1.6.1 Synergies and benefits of combining AI and digital twin technologies 18

1.6.2 Case studies and examples of successful implementations 19

1.7 Challenges and future directions 19

1.7.1 Ethical and privacy concerns 21

1.7.2 Potential innovations and advancements 22

1.8 Conclusion 22

1.9 Reference 23

Chapter 2 Smart City Development in 6G Era: Synergizing AI and Digital Twin Technology 27
Raj Kishor VERMA and Ahmed A. ELNGAR

2.1 Introduction 28

2.1.1 Smart cities 29

2.1.2 6G technology 32

2.1.3 Artificial intelligence 34

2.1.4 Digital twin 36

2.1.5 Urban development 38

2.1.6 Sustainability 41

2.2 Literature review/related work 43

2.3 Proposed diagram 45

2.3.1 Results 46

2.3.2 Seamless connectivity with 6G 47

2.3.3 Sustainability and environmental benefits 47

2.3.4 Improved public services and citizen engagement 47

2.3.5 Challenges and future directions 48

2.4 Conclusion 50

2.5 Future and scope 51

2.6 Challenges 52

2.7 References 53

Chapter 3 AI and Digital Twin for Smart Cities 55
Latha P, Geetha S, M. VAIDHEHI, Nalina Keerthana G and Muthu Selvi c

3.1 Introduction 56

3.2 Digital twin security 58

3.3 Advancing AI-driven digital twins 59

3.3.1 Factors advancing AI-driven digital twins 59

3.4 Systematic review of the research foundations 60

3.5 Understanding digital twins in a smart city context 61

3.6 The role of AI in enhancing digital twins 62

3.7 Understanding AI and digital twin technologies 63

3.7.1 Artificial intelligence (AI) 63

3.7.2 Digital twin (DT) 63

3.8 AI-driven energy management in smart cities 63

3.9 AI and digital twins in smart cities 65

3.10 Foundations of AI and digital twin technologies 65

3.10.1 Artificial intelligence (AI) 65

3.10.2 Machine learning (ML) 66

3.10.3 Deep learning (DL) 66

3.10.4 Strengthening learning (RL) 66

3.11 Technology for digital twins 66

3.12 Personalizing city services through AI 66

3.13 Interplay between AI and digital twins in urban environments 67

3.14 AI for urban planning and policy decisions 67

3.15 Ethical considerations and data privacy in smart cities 68

3.16 Understanding artificial intelligence in urban contexts 68

3.16.1 Machine learning (ML) 68

3.16.2 Advanced neural learning 69

3.16.3 Language processing technology 69

3.17 Urban landscape virtual models 70

3.18 Improving public safety and emergency response 70

3.19 AI for waste management 70

3.19.1 AI for water resource management 71

3.20 AI for urban planning and policy decisions 71

3.21 The societal impact of artificial intelligence and digital twins in urban environments 71

3.22 Applications in smart city domains 72

3.22.1 Urban planning and development 72

3.22.2 Traffic management and transportation 73

3.22.3 Energy and sustainability management 73

3.22.4 Disaster management and emergency response 73

3.22.5 Water, waste and environmental monitoring 74

3.22.6 Healthcare and public safety 74

3.22.7 Governance and citizen engagement 74

3.23 AI and digital twin 75

3.23.1 Smart home 75

3.24 Smart medical 76

3.24.1 AI in smart medical care 76

3.24.2 Digital twin in healthcare 76

3.24.3 AI and digital twin integration in smart healthcare 77

3.24.4 Impact on healthcare 77

3.25 Smart agriculture 77

3.25.1 AI in smart agriculture 77

3.25.2 Applications of digital twin in agriculture 78

3.26 Case studies 79

3.26.1 Singapore: integrating AI with digital twins for urban efficiency 79

3.26.2 Helsinki: enhancing urban planning and sustainability 79

3.26.3 Barcelona: revolutionizing energy management with smart grids 79

3.26.4 Rotterdam: building resilience through disaster management 80

3.27 Applications and benefits 80

3.28 Benefits and challenges 81

3.28.1 Benefits 81

3.28.2 Challenges 81

3.29 Case study: how the public views and accepts AI in smart cities 81

3.30 The future of AI in smart cities emerging trends and opportunities 82

3.31 Future prospects and research directions 83

3.32 Conclusion 83

3.33 References 83

Chapter 4 Security Solutions for Smart Cities Using Digital Twin 89
Shubham GUPTA and Ferdinand M. MAGTIBAY

4.1 Overview of smart cities 89

4.1.1 Importance of digital transformation in urban areas 91

4.1.2 Security challenges in smart cities 92

4.1.3 Role of digital twin in smart cities 95

4.1.4 Purpose and scope of the chapter 96

4.2 Understanding digital twin technology 96

4.2.1 Concept of digital twin 97

4.2.2 Types of digital twins in smart cities 97

4.2.3 Integration with emerging technologies 100

4.3 Security threats in smart cities and digital twins 101

4.3.1 Cybersecurity threats 101

4.3.2 Physical security threats 103

4.3.3 Privacy and ethical concerns 104

4.4 Digital twin-based security solutions for smart cities 105

4.4.1 Real-time threat detection and response 107

4.4.2 Cybersecurity solutions using digital twins 108

4.4.3 Physical security enhancements 109

4.4.4 Privacy-preserving mechanisms 110

4.5 Case studies and real-world implementations 110

4.5.1 Smart city security: case study of Singapore 111

4.5.2 Digital twin for critica…