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Data-driven Multivalence in the Built Environment

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Cover of 'Data-driven Multivalence in the Built Environment'

Table of Contents

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    Book Overview
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    Chapter 1 Smart Equity: An Australian Lens on the Need to Measure Distributive Justice
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    Chapter 2 The Convenient City: Smart Urbanism for a Resilient City
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    Chapter 3 Conceptualization of Smart City: A Methodological Framework for Smart Infrastructure, Smart Solutions and Smart Governance
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    Chapter 4 Development Challenges for Big Data Command and Control Centres for Smart Cities in India
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    Chapter 5 Understanding Consumer Demand for New Transport Technologies and Services, and Implications for the Future of Mobility
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    Chapter 6 Smart Interactive Cities [SICs]: The Use of Computational Tools and Technologies [CTTs] as a Systemic Approach to Reduce Water and Energy Consumption in Urban Areas
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    Chapter 7 Centenarian Transhumanism Aging in Place
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    Chapter 8 Grey Smart Societies: Supporting the Social Inclusion of Older Adults by Smart Spatial Design
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    Chapter 9 Real-Time Interactive Multimodal Systems for Physiological and Emotional Wellbeing
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    Chapter 10 Design Labs for Data-Driven Multivalence
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    Chapter 11 The Role of Living Labs in Developing Smart Cities in Indonesia
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    Chapter 12 Algae Building: Is This the New Smart Sustainable Technology?
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    Chapter 13 The Qualitative Image: Urban Analytics, Hybridity and Digital Representation
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    Chapter 14 Multimodal Accommodations for the Nomadic International Citizen [MANIC]
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    Chapter 15 Understanding the Relationship Between Smart Cities and Entrepreneurial Ecosystems: The Case of Sydney
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    Chapter 16 Urban Wellbeing in the Contemporary City
Attention for Chapter 2: The Convenient City: Smart Urbanism for a Resilient City
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Chapter title
The Convenient City: Smart Urbanism for a Resilient City
Chapter number 2
Book title
Data-driven Multivalence in the Built Environment
Published by
Springer, Cham, January 2020
DOI 10.1007/978-3-030-12180-8_2
Book ISBNs
978-3-03-012179-2, 978-3-03-012180-8
Authors

Rob Roggema, Roggema, Rob

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 8 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 8 100%

Demographic breakdown

Readers by professional status Count As %
Lecturer 2 25%
Professor 1 13%
Researcher 1 13%
Student > Doctoral Student 1 13%
Unknown 3 38%
Readers by discipline Count As %
Engineering 3 38%
Unspecified 1 13%
Economics, Econometrics and Finance 1 13%
Computer Science 1 13%
Unknown 2 25%