Implementing Data-Driven Strategies in Smart Cities : A Roadmap for Urban Transformation
Language: English
Published by Elsevier Inc, 2021
- Softcover
- New
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
AbeBooks seller since August 14, 2006
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Add to basketItem description from seller
nach der Bestellung gedruckt Neuware - Printed after ordering - Implementing Data-Driven Strategies in Smart Cities is a guidebook and roadmap for practitioners seeking to operationalize data-driven urban interventions. The book opens by exploring the revolution that big data, data science, and the Internet of Things are making feasible for the city. It explores alternate topologies, typologies, and approaches to operationalize data science in cities, drawn from global examples including top-down, bottom-up, greenfield, brownfield, issue-based, and data-driven. It channels and expands on the classic data science model for data-driven urban interventions - data capture, data quality, cleansing and curation, data analysis, visualization and modeling, and data governance, privacy, and confidentiality. Throughout, illustrative case studies demonstrate successes realized in such diverse cities as Barcelona, Cologne, Manila, Miami, New York, Nancy, Nice, São Paulo, Seoul, Singapore, Stockholm, and Zurich. Given the heavy emphasis on global case studies, this work is particularly suitable for any urban manager, policymaker, or practitioner responsible for delivering technological services for the public sector from sectors as diverse as energy, transportation, pollution, and waste management. …
Seller Inventory # 9780128211229
- Title
- Implementing Data-Driven Strategies in Smart Cities : A Roadmap for Urban Transformation
- Author
- Didier Grimaldi
- Publisher
- Elsevier Inc
- Publication year
- 2021
- Condition
- Neu
- Binding
- Taschenbuch
- Language
- English
- ISBN 10
- 0128211229
- ISBN 13
- 9780128211229
- Item weight
- 351 grams
- Dimensions
- 229x152x14 mm
Implementing Data-Driven Strategies in Smart Cities is a guidebook and roadmap for practitioners seeking to operationalize data-driven urban interventions. The book opens by exploring the revolution that big data, data science, and the Internet of Things are making feasible for the city. It explores alternate topologies, typologies, and approaches to operationalize data science in cities, drawn from global examples including top-down, bottom-up, greenfield, brownfield, issue-based, and data-driven. It channels and expands on the classic data science model for data-driven urban interventions – data capture, data quality, cleansing and curation, data analysis, visualization and modeling, and data governance, privacy, and confidentiality. Throughout, illustrative case studies demonstrate successes realized in such diverse cities as Barcelona, Cologne, Manila, Miami, New York, Nancy, Nice, São Paulo, Seoul, Singapore, Stockholm, and Zurich. Given the heavy emphasis on global case studies, this work is particularly suitable for any urban manager, policymaker, or practitioner responsible for delivering technological services for the public sector from sectors as diverse as energy, transportation, pollution, and waste management.
- Explores numerous specific urban interventions drawn from global case studies, helping readers understand real urban challenges and create data-driven solutions
- Provides a step-by-step and applied holistic guide and methodology for immediate application in the reader’s own business agenda
- Presents cutting edge technology presentation with coverage of innovations such as the Internet of Things, robotics, 5G, edge/fog computing, blockchain, intelligent transport systems, and connected-automated mobility
"Synopsis" may belong to another edition of this title.
About the Author
Carlos Carrasco-Farré in the Department of Operations, Innovation and Data Science at ESADE Business School, Barcelona, Spain. His research interest is in human-machine interactions and decision-making. More specifically, his research focuses in computational social science, the intersection of technology (artificial intelligence, machine learning, data science) and society (management, decision-making and strategy). He has contributed to various academic and nonacademic publications and books on economics, management, and urban strategy.
"About the title" may belong to another edition of this title.
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