| Description |
1 online resource (258 p.) |
| Contents |
Intro -- Implementing Data-Driven Strategies in Smart Cities: A Roadmap for Urban Transformation -- Copyright -- Contents -- Contributors -- About the editors -- Foreword -- Preface -- Acknowledgments -- Memoriam -- Chapter 1: From smart city to data-driven city -- 1. Urban challenges -- 1.1. Environment issue -- 1.2. Economic competitiveness -- 1.3. Quality of life -- 1.4. Sustainability -- 1.5. Resilience -- 2. Definition of a smart city -- 2.1. Taxonomy of smart city -- 2.2. Technology-oriented approach or top-down -- 2.3. People-oriented approach or social smart cities |
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3. Smart city as an opportunity for innovation and entrepreneurship -- 3.1. Social entrepreneur -- 3.2. Urban entrepreneur -- 4. Resilient city -- 5. Sustainable city -- 5.1. The risks of ICT to environmental and social sustainability -- 5.2. The contribution of ICT to environmental and social sustainability -- 6. Augmented city -- 6.1. From small data to big data -- 6.2. Big data applications for cities -- 6.3. Smart mobility -- 6.4. Smart school -- 6.5. Smart energy -- 6.6. Smart facility management -- 6.7. Smart hospital -- 6.8. Smart security -- 6.9. Smart public governance |
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6.10. Smart economy -- 7. Is a data-driven approach progress? -- 7.1. False promises of big data -- 7.2. Potential benefits of big data -- 8. Data-driven smart city architecture -- 8.1. Evolution of the smart city models -- 8.2. The architecture of the solution -- 8.3. Real-time urban platform -- 8.3.1. Collective intelligence -- 8.3.2. Improving accessibility -- 8.3.3. Service provided by modules -- Issue reporting -- Waste collection -- Parking management -- 8.3.4. Added value-ROI -- References -- Chapter 2: Governance, decision-making, and strategy for urban development |
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1. Data-driven approaches for smart city -- 1.1. A systematic literature review -- 1.2. Evolutionary path to data-driven resilience in a private sector network -- 2. Smart urban governance -- 2.1. Definition of a big data citizen-centered approach -- 3. Big data citizen-centered organization change -- 4. Architecture of a big data citizen-centered urban governance -- 4.1. Data life cycle management -- 4.2. Real-time urban platform -- 4.3. Master Data Model -- 4.4. Data quality management -- 4.5. Data security and privacy -- References -- Chapter 3: Data Science technologies |
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1. What is data science? -- 2. Organizing for data science -- 2.1. Managing data science teams -- 2.2. Managing data science departments and organizations -- 3. Managing data science projects to solve urban issues -- 3.1. Problem statement -- 3.2. Developing the solution -- 4. Interview with Miamis CIO -- 4.1. The backbone of data-driven cities -- 4.2. The shinning projects of data-driven cities -- 4.3. The team -- 4.4. Linking data teams with the whole organization -- 4.5. DTFT: Do the fucking thing -- 4.6. Do something useful -- 5. Indicators for urban retail |
| Notes |
Description based upon print version of record |
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5.1. The importance of indicators |
| Subject |
Smart cities.
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|
Smart cities
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| Form |
Electronic book
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| Author |
Carrasco-Farré, Carlos
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| ISBN |
9780128211236 |
|
0128211237 |
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