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Smart Cities and Artificial Intelligence: Convergent Systems for Planning, Design, and Operations [Pehme köide]

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(Co-Director, Smart Cities Convergence Masters Program, London, UK), (Vice Dean, Department of Information Art & Design of the Academy Art & Design Masters Supervisor, Tsinghua University, Beijing, China)
  • Formaat: Paperback / softback, 284 pages, kõrgus x laius: 229x152 mm, kaal: 430 g
  • Sari: Smart Cities
  • Ilmumisaeg: 05-May-2020
  • Kirjastus: Elsevier Science Publishing Co Inc
  • ISBN-10: 0128170247
  • ISBN-13: 9780128170243
Teised raamatud teemal:
Smart Cities and Artificial Intelligence: Convergent Systems for Planning, Design, and OperationsSuurem pilt
  • Formaat: Paperback / softback, 284 pages, kõrgus x laius: 229x152 mm, kaal: 430 g
  • Sari: Smart Cities
  • Ilmumisaeg: 05-May-2020
  • Kirjastus: Elsevier Science Publishing Co Inc
  • ISBN-10: 0128170247
  • ISBN-13: 9780128170243
Teised raamatud teemal:
Püsilink: https://www.kriso.ee/db/9780128170243.html
Märksõnad:

Smart Cities and Artificial Intelligence offers a comprehensive view of how cities are evolving as smart ecosystems through the convergence of technologies incorporating machine learning and neural network capabilities, geospatial intelligence, data analytics & visualization, sensors, and smart connected objects to name a few. These recent advances in AI move us closer to developing operating systems that simulate human, machine, and environmental patterns from transportation infrastructure to communication networks. Understanding cities as real-time, living, dynamic systems coupled with new tools including generative design allows readers to plan, manage, and optimize city operations, making cities more efficient and sustainable with the ultimate goal of becoming self-regulating.

Smart Cities and Artificial Intelligence

provides a transdisciplinary, integrated approach, using theoretical and applied insights to examine how the digital and physical worlds are converging and how a new combination of human and machine intelligence is capable of transforming the experience of the urban environment. It provides a fresh holistic perspective on smart cities through an interconnect stream of theory, methodology, system architecture, and the application of Smart City Functions to define an integrated process of the design, planning, and implementation of smart cities.

  • Explores the latest concepts in smart city design and development and the transformation of cities through the convergence of human, machine, and natural systems enabled by Artificial Intelligence
  • Includes numerous diagrams to illustrate and explain complex smart city systems and solutions
  • Features diverse smart city examples and initiatives from around the globe
Preface xiii
Acknowledgments xv
Introduction xvii
Description of each section xxvii
Info system (Fig. 0.0) xxxi
1 Evolution of cities/technologies
1.1 Overview of smart city concept and context
2(2)
1.2 The evolution and integration of technology, AI, and cities
4(5)
1.2.1 Evolutionary strategies
7(2)
1.3 City DNA narratives
9(8)
1.3.1 Beijing---the radiating megacity
10(1)
1.3.2 London---the cosmopolitan hub
11(1)
1.3.3 New York---the media metropolis
12(1)
1.3.4 Dubai---the iconic branded city
13(1)
1.3.5 Songdo---the new digital city
14(1)
1.3.6 Masdar---the new sustainable city
15(1)
1.3.7 NEOM---the future city
16(1)
1.4 The dimensions of the city and potential for convergence
17(4)
1.4.1 Physical/environment dimension
18(1)
1.4.2 City systems, infrastructure dimension
19(1)
1.4.3 The human dimension
19(1)
1.4.4 Culture, society, and governance dimension
19(1)
1.4.5 Digital infrastructure dimension
20(1)
1.4.6 The ubiquitous dimension
20(1)
1.5 How convergence theory applies to smart cities
21(1)
1.6 Conclusion
22(3)
References
23(1)
Further reading
24(1)
2 City as living organism
2.1 The city as a living organism
25(8)
2.1.1 Concepts of space and representation
26(2)
2.1.2 Dynamic, self-regulating systems in nature
28(1)
2.1.3 Biomimicry
29(1)
2.1.4 Biomimicry applied to human anatomy
30(1)
2.1.5 City as extension of the human body
31(2)
2.2 Principles of collective intelligence
33(3)
2.3 City DNA
36(3)
2.3.1 Cities as global brands/destinations
37(2)
2.4 The role of data collection and mapping
39(4)
2.4.1 Mapping the system
39(2)
2.4.2 Mapping as the basis of smart cities
41(1)
2.4.3 Real-time behavioral data
42(1)
2.5 Conclusion
43(4)
References
44(1)
Further reading
45(2)
3 Strategies, planning, and design
3.1 Criteria for planning and design of smart cities
47(5)
3.1.1 Strategic goals
48(3)
3.1.2 Outcome-based modeling
51(1)
3.2 New approaches to innovation for planning and designing smart cities
52(8)
3.2.1 Cities as living labs
53(1)
3.2.2 City as hubs of innovation/innovation-driven cities
54(2)
3.2.3 Co-design
56(1)
3.2.4 Citizen centric cities
56(3)
3.2.5 Design thinking
59(1)
3.3 Convergence methodologies
60(6)
3.3.1 Human-machine collaboration
60(1)
3.3.2 Real-time visualization
61(1)
3.3.3 Information architecture and Philosophy of Information
62(1)
3.3.4 Real world/virtual simulation
62(1)
3.3.5 Generative design and metadesign
63(1)
3.3.6 Convergence Development Method: strategy, planning, design, and operations process
64(1)
3.3.7 Convergence design method: design thinking/machine learning
65(1)
3.3.8 Convergence application method: outcome-based AI scenario modeling
65(1)
3.4 Conclusion
66(3)
References
66(3)
4 City Operating Systems
4.1 Overview of operating systems
69(2)
4.2 The language and representation of systems architecture
71(7)
4.2.1 The role of meta-architecture, information architecture and technical architecture in the design of smart city operating systems
73(1)
4.2.2 Meta-architecture---principles and guidelines
74(1)
4.2.3 Operating systems planning considerations
74(2)
4.2.4 Operating systems design considerations
76(1)
4.2.5 Information architecture and technical architecture
77(1)
4.3 Representational hierarchy of cities as operating systems
78(7)
4.3.1 City ecosystem
78(2)
4.3.2 Smart city framework---the smart city mandala
80(1)
4.3.3 OS Behavioral Typologies
81(2)
4.3.4 Anatomy of operating systems
83(1)
4.3.5 Smart city operating system flow
84(1)
4.4 What is the correct OS?
85(2)
4.5 New constructs---convergence-based city OS
87(5)
4.5.1 Convergent OS
88(2)
4.5.2 Co-development/open source/open data
90(1)
4.5.3 Self-regulating systems
91(1)
4.6 Conclusion
92(3)
References
93(1)
Further reading
93(2)
5 Connectivity
5.1 Introduction
95(2)
5.1.1 Connectivity itself will become intelligent
96(1)
5.1.2 All living organisms are related within a frequency spectrum
97(1)
5.2 Evolution of connectivity
97(2)
5.3 The electromagnetic spectrum, frequencies, and bandwidth
99(2)
5.3.1 Electromagnetic patterns, frequencies, and human energy fields
99(2)
5.3.2 Electromagnetic spectrum
101(1)
5.4 The role of machine learning and deep learning in intelligent connectivity
101(2)
5.4.1 Radio Frequency Machine Learning Systems
101(1)
5.4.2 The role of evolutionary algorithms in connectivity
102(1)
5.5 Connectivity anatomy
103(5)
5.5.1 The human body and neural networks as models of connectivity
103(1)
5.5.2 The brain
104(1)
5.5.3 Other organic models of connectivity
105(1)
5.5.4 The backbone of connectivity---telecommunication networks
106(1)
5.5.5 The sensorial layer of connectivity
107(1)
5.5.6 Mobile connectivity
108(1)
5.6 Integrated networks and services
108(5)
5.6.1 Industry 4.0---the basis of connectivity
108(1)
5.6.2 Convergence connectivity
109(1)
5.6.3 Intelligent connectivity using combination of 5G AI and IoT
110(1)
5.6.4 Connectivity singularity
111(1)
5.6.5 Smart objects
111(2)
5.7 Conclusion
113(4)
References
114(1)
Further reading
114(3)
6 Interface
6.1 City-wide interface---the city is an interface
117(4)
6.1.1 City interface as an extension of the city OS
118(2)
6.1.2 The city as an ecosystem---scale, boundaries bridging global and hyperlocal
120(1)
6.1.3 Infrastructure as interface
121(1)
6.2 City interface functions
121(7)
6.2.1 Urban navigation
122(2)
6.2.2 Urban media
124(1)
6.2.3 Urban sensing
125(1)
6.2.4 Urban interaction
126(2)
6.3 City interface design practices
128(5)
6.3.1 Theory and method of city interface design
129(1)
6.3.2 Urban user experience
129(2)
6.3.3 Urban interaction design
131(1)
6.3.4 Urban simulation and gaming
131(2)
6.4 Collective intelligence interface
133(2)
6.4.1 Collective intelligence
133(1)
6.4.2 Collective intelligence participation/interaction
133(1)
6.4.3 Dynamic frames of reference
134(1)
6.4.4 Human to human, human to machine, machine to machine and machine to nature
134(1)
6.5 Convergence Urban Interface
135(2)
6.5.1 Total interface solution---AI/sensors/big data/pattern recognition
137(1)
6.6 Conclusion
137(4)
References
138(1)
Further reading
138(3)
7 Smart City Scenarios
7.1 Introduction
141(2)
7.2 Theory of systems change
143(3)
7.2.1 Multi-level perspective
143(2)
7.2.2 Convergence application
145(1)
7.3 Smart mobility
146(4)
7.3.1 Past---present---future
146(3)
7.3.2 Object---action-outcome
149(1)
7.4 Smart environment
150(2)
7.4.1 Past---present---future
150(1)
7.4.2 Object---action---outcome
151(1)
7.5 Smart people
152(3)
7.5.1 Past---present---future
152(2)
7.5.2 Object---action---outcome
154(1)
7.6 Smart governance
155(2)
7.6.1 Past---present---future
155(1)
7.6.2 Object---action---outcome
156(1)
7.7 Smart economy
157(2)
7.7.1 Past---present---future
157(1)
7.7.2 Object---action---outcome
158(1)
7.8 Smart living
159(2)
7.8.1 Past---present---future
159(1)
7.8.2 Object---action---outcome
160(1)
7.9 Conclusion
161(3)
References
161(1)
Further reading
162(2)
8 Smart city functions
8.1 Introduction
164(1)
8.2 Smart city enablers (hardware infrastructure)
165(3)
8.2.1 Collection: IoT and low energy consuming sensors
166(1)
8.2.2 Processing: scalable computing power and storage through edge and cloud computing
166(1)
8.2.3 Transmission: network infrastructure---5G
167(1)
8.2.4 OS: AI smart city operating systems
167(1)
8.3 Introduction to AI, AI applications and capabilities (software infrastructure)
168(4)
8.3.1 Capabilities-based AI
169(1)
8.3.2 Functionality-based AI
169(1)
8.3.3 Computer Vision
170(1)
8.3.4 Natural language processing
170(1)
8.3.5 Machine learning
171(1)
8.3.6 Predictive analytics
171(1)
8.3.7 Robotics
171(1)
8.4 The convergence of AI applications within smart cities
172(1)
8.4.1 Convergent applications
172(1)
8.4.2 Hierarchy framework for scale and scope of smart city functions
173(1)
8.5 Smart city functions
173(18)
8.5.1 Smart environment
174(3)
8.5.2 Smart government
177(2)
8.5.3 Smart mobility
179(3)
8.5.4 Smart economy
182(2)
8.5.5 Smart people
184(2)
8.5.6 Smart living
186(2)
8.5.7 Convergence of smart city functions
188(3)
8.6 Conclusion
191(2)
Further reading
192(1)
9 Smart city business models
9.1 Introduction
193(1)
9.2 The smart city/Artificial Intelligence market
194(4)
9.2.1 Business models and risk mitigation
194(1)
9.2.2 A Marxist analysis of smart cities
195(1)
9.2.3 Smart city movement marketing
196(2)
9.3 Innovation-led economics
198(7)
9.3.1 Innovation as the driver
198(1)
9.3.2 Intellectual property as the new asset
199(2)
9.3.3 China---USA race, India rising
201(2)
9.3.4 Cities as living labs
203(2)
9.4 The new economy
205(3)
9.4.1 Planetary accounting
205(1)
9.4.2 Strategy shift
206(1)
9.4.3 New forms of digital currency
207(1)
9.4.4 Blockchain
207(1)
9.4.5 Holochain
207(1)
9.5 New forms of business exchange
208(2)
9.5.1 Flow
208(1)
9.5.2 Channeling on demand
209(1)
9.6 Bringing it together
210(2)
9.6.1 Convergent economies
211(1)
9.6.2 Collaboration
211(1)
9.6.3 Self-regulating systems
212(1)
9.7 Conclusion
212(5)
References
213(1)
Further reading
214(3)
10 Conclusions
10.1 From theory to practice
217(2)
10.2 East-West Collaboration
219(3)
10.3 The human factor
222(1)
10.4 Wide-spread automation
223(1)
10.5 Consequences of embracing convergence
224(3)
Further reading
226(1)
Appendix 227(6)
Glossary of Terms 233(4)
Index 237
Christopher Grant Kirwan is a multidisciplinary professional and educator with more than 30 years experience spanning the fields of urban planning, architecture, new media, and branding. Living and working in international hubs of innovationMilan, New York, Dubai, Beijing, Bangkok, Rio de Janeiro, and Londonhe has been involved in all phases of project implementation including the research, planning, design, and business of technology integration, urban development, and smart cities. In addition to his role as co-director of the Smart Cities Convergence program launching in spring 2023, he is currently a Visiting Professor at both Henley Business School Informatics Research Centre, University of Reading, and Parsons School of Design in New York and has previously taught at Harvard Graduate School of Design and Tsinghua University where he co-founded the Design Beijing Lab with Dr. Zhiyong Fu. Zhiyong Fu has more than 20 years of teaching and research experience in the fields of information design, interaction design, service design, and social innovation related to humancomputer interface and smart cities. Dedicated to educational program development and cross-institutional collaboration, he has established workshops, innovation labs, and special joint research projects around the world. He is currently an Associate Dean of China-Italy Design Innovation Hub at Tsinghua University, Vice Director of China Innovation and Entrepreneurship Education Research Center and serves as the Secretary-General for China Information and Interaction Design Committee (IIDC) and Vice President of the International Chinese Association of Human Computer Interaction (ICACHI).