Buch, Englisch, 336 Seiten, Format (B × H): 156 mm x 234 mm, Gewicht: 626 g
Buch, Englisch, 336 Seiten, Format (B × H): 156 mm x 234 mm, Gewicht: 626 g
ISBN: 978-1-83669-040-5
Verlag: John Wiley & Sons
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.
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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 critical infrastructure protection: case study of London 112
4.5.3 AI-powered digital twins in US smart cities 113
4.6 Challenges and future directions 113
4.6.1 Technical and implementation challenges 114
4.6.2 Policy and regulatory challenges 115
4.6.3 Future trends and innovations 116
4.7 Conclusion 116
4.8 References 117
Chapter 5 Building Sustainable Urban Futures with AI and Digital Twins 119
Dhruv Kumar SONI and Ashu TANEJA
5.1 Introduction 119
5.1.1 Understanding AI and digital twins in urban systems 121
5.1.2 Artificial intelligence: transforming urban systems 122
5.1.3 Digital twins: bridging the physical and digital worlds 123
5.2 The synergy between AI and digital twins 124
5.2.1 Energy management and smart grids 125
5.3 Role of AI in sustainable smart cities 127
5.4 Case studies and real-world applications 128
5.4.1 Singapore: virtual city modeling and energy efficiency 128
5.4.2 Barcelona: smarter public services 128
5.4.3 Dubai: sustainable urban management 129
5.5 Integration with emerging technologies 129
5.6 Challenges and ethical considerations 131
5.7 Future directions 131
5.8 Conclusion 132
5.9 References 133
Chapter 6 Enhancing Urban Efficiency with AI and Digital Twin Technologies in Smart City Infrastructure 139
Sanjivani Hemant KULKARNI, Vipan KUMAR, Anupam KANWAR, Priya DASARWAR, Monali GULHANE, Nitin RAKESH and Utku KOSE
6.1 Introduction 140
6.1.1 Introduction to smart cities 140
6.1.2 Overview of digital twin technology 141
6.2 Theoretical background 142
6.2.1 Key concepts in AI relevant to urban applications 142
6.2.2 Introduction to digital twins: history, development and current status 142
6.2.3 Overview of the IoT and its integration with AI and digital twins 143
6.3 Framework and implementation 144
6.3.1 Designing an AI-enhanced digital twin model 144
6.3.2 Integration strategies for IoT data with digital twins 145
6.3.3 Technologies and tools used in the implementation 146
6.4 Applications of AI and digital twins in smart cities 147
6.4.1 Infrastructure management (water, power, waste management) 147
6.4.2 Traffic and transportation systems 148
6.4.3 Public safety and emergency response 148
6.5 Results and discussion 150
6.5.1 Presentation of results from real-world case studies or simulations 150
6.5.2 Analysis of the impact of AI and digital twins on urban system efficiency 153
6.6 Future trends and innovations 156
6.6.1 Emerging technologies in AI and digital twins 156
6.6.2 Predictive analysis for long-term urban planning 157
6.7 Conclusion 158
6.8 References 158
Chapter 7 Toward Smart Healthcare in Digital Twin Featuring AI for Innovation in Smart Cities and Sustainability 161
Bhupinder SINGH, Ashima JAIN and Christian KAUNERT
7.1 Introduction 161
7.1.1 Related work 165
7.2 DT in personalized medicine 169
7.3 DT in precision medicine 171
7.3.1 State-of-the-art models and techniques 172
7.3.2 Available platforms 174
7.3.3 Issues and challenges 175
7.4 Conclusion 178
7.5 Future scope 179
7.6 References 180
Chapter 8. Toward Smart Healthcare in Digital Twin for 6G-Powered Sustainable Ultra-Smart Cities 183
M. VAIDHEHI, C. MALATHY, Pradeep SUDHAKARAN, Aswathy K. CHERIAN, R. GEETHA and Guntupalli Manoj KUMAR
8.1 Introduction 183
8.1.1 Overview of 6G technology 184
8.1.2 DT in healthcare 184
8.1.3 Importance of sustainability in ultra-smart cities 185
8.2 DT in healthcare 186
8.2.1 Operational principles of DT technology for healthcare 187
8.2.2 Influence in patient monitoring, disease prediction and treatment planning by DT 188
8.2.3 Role of AI, IoT and big data in DT healthcare 189
8.3 Healthcare systems by 6G 190
8.3.1 Telemedicine and remote patient discussion 190
8.3.2 Haptic Internet and remote operations 191
8.3.3 Real-time patient monitoring and wearable technology 191
8.3.4 Edge computing and ultra-low latency in 6G healthcare applications 192
8.3.5 Melding of AI-assisted diagnostics with 6G networks 192
8.4 Sustainable ultra-smart cities and healthcare 193
8.4.1 The role of green energy and sustainable infrastructures in healthcare 193
8.4.2 Smart hospitals and intelligent patient care management 194
8.4.3 Renewable energy in healthcare 195
8.4.4 Smart hospitals and intelligent patient care management 196
8.4.5 Blockchain and cybersecurity for healthcare data privacy 197
8.5 Challenges and opportunities 199
8.5.1 Technical challenges in deploying DT healthcare systems 199
8.5.2 Regulatory and ethical considerations in smart healthcare 200
8.5.3 Case studies on regulatory and ethical considerations in smart healthcare 201
8.5.4 Opportunities for AI-driven precision medicine in ultra-smart cities 202
8.6 Future trends and research directions 203
8.6.1 Quantum computing influencing healthcare 204
8.6.2 The role of nanotechnology and biotech in 6G healthcare 205
8.6.3 Challenges in global 6G healthcare adoption 207
8.7 Conclusion 207
8.8 References 208
Chapter 9 Smart Patient Monitoring using Wearable Devices: Applications and Future Scope 211
Garima CHOPRA, Suhaib AHMED and Shubham GUPTA
9.1 Introduction 211
9.1.1 Overview 211
9.1.2 Evolution of wearable devices in healthcare 212
9.1.3 Significance of real-time monitoring 214
9.2 Wearable devices for healthcare monitoring 214
9.2.1 Types of wearable devices 215
9.2.2 Key features and components 216
9.2.3 Materials used in devices 218
9.3 Applications of wearable devices in healthcare sector 220
9.3.1 Remote patient monitoring 221
9.3.2 Early detection of diseases 221
9.3.3 Diabetes management 222
9.3.4 Wearables for neurological disorders 222
9.3.5 Sleep monitoring and mental health tracking 223
9.3.6 Rehabilitation and post-surgical recovery 223
9.3.7 Fitness and preventive healthcare 223
9.4 Case study on wearable devices for the healthcare industry 228
9.4.1 Mental health management using wearable devices 228
9.4.2 Challenges and future directions 229
9.5 Limitations and challenges 229
9.6 Future trends and scope of wearable healthcare monitoring 230
9.6.1 Advancements in wearable sensor technologies 230
9.6.2 Role of AI in smart monitoring 231
9.6.3 Personalized and precision medicine 231
9.6.4 Integration with AR and VR 231
9.6.5 Potential in remote rural and under-served areas 232
9.7 Conclusion 232
9.8 References 233
Chapter 10 Toward Smart Healthcare in the Digital Twin Ecosystem: Architecture, Challenges and Implementation 237
MAMTA and Shravya Reddy KARRI
10.1 Introduction 238
10.1.1 Overview of digital twin technology 238
10.1.2 Relevance of digital twin in healthcare 238
10.1.3 Objectives and scope of the chapter 239
10.2 Digital twin architecture for smart healthcare 240
10.2.1 Key components of digital twin systems 240
10.2.2 Integration of IoT, AI and Big Data in healthcare 241
10.2.3 Real-time data acquisition and processing 241
10.3 Applications of digital twin in healthcare 242
10.3.1 Personalized treatment and patient monitoring 243
10.3.2 Virtual testing and simulation for medical devices 243
10.3.3 Enhancing precision in surgical procedures 244
10.3.4 Hospital operations and workflow optimization 244
10.3.5 Drug development and clinical trials 245
10.3.6 Public health and epidemic management 245
10.3.7 Mental health and cognitive care 245
10.3.8 Personalized treatment and patient monitoring 246
10.3.9 Virtual testing and simulation for medical devices 247
10.3.10 Enhancing precision in surgical procedures 247
10.4 Challenges in implementing digital twin for healthcare 248
10.4.1 Data security and privacy concerns 248
10.4.2 High costs of deployment and maintenance 249
10.4.3 Interoperability issues between systems 250
10.4.4 Ethical and legal considerations 251
10.5 Conclusion 252
10.5.1 Future prospects 252
10.5.2 Case studies and real-world examples 253
10.5.3 Insights from research projects and pilot programs 253
10.6 Future directions and opportunities 254
10.6.1 Advances in AI and machine learning for digital twins 254
10.6.2 Expanding the scope to global healthcare systems 255
10.6.3 Potential for predictive and preventive healthcare 256
10.7 Conclusion of the chapter 257
10.7.1 Key takeaways from the chapter 257
10.7.2 Role of digital twins in transforming healthcare 257
10.7.3 Call to action for future research and collaboration 258
10.8 Final thoughts 258
10.9 References 259
Chapter 11 Revolutionizing Smart Healthcare: Implementing Digital Twin Technology for Personalized Medical Solutions 265
Prashant WAKHARE, Anagha SHINDE, Navnath B. POKALE and Akanksha GOEL
11.1 Introduction 266
11.1.1 Overview of smart healthcare 266
11.1.2 Digital twin technology in healthcare 268
11.2 Background and literature review 268
11.2.1 Smart healthcare systems 268
11.2.2 Earlier research on digital twin technology in healthcare 269
11.3 Architecture of smart healthcare in the digital twin ecosystem 271
11.3.1 Key components of the ecosystem 271
11.3.2 Data flow and interaction between components 273
11.3.3 Role of AI and machine learning in enhancing digital twin capabilities 274
11.4 Challenges in implementing digital twin in healthcare 275
11.4.1 Data privacy and security concerns 275
11.4.2 Scalability and interoperability issues 276
11.5 Implementation strategies for smart healthcare using digital twin 277
11.5.1 Building the digital twin model for healthcare applications 277
11.5.2 Integration with existing healthcare infrastructure 277
11.5.3 Real-world case studies and applications 278
11.6 Future directions and emerging trends 278
11.6.1 Integration of 6G and advanced IoT for enhanced connectivity 278
11.6.2 Personalized healthcare using digital twin technology 279
11.7 Results and discussion 280
11.8 Conclusion 284
11.9 References 284
List of Authors 287
Index 291
