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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
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Title
Data-driven Multivalence in the Built Environment
Published by
Springer International Publishing, June 2019
DOI 10.1007/978-3-030-12180-8
ISBNs
978-3-03-012179-2, 978-3-03-012180-8
Editors

Biloria, Nimish

X Demographics

X Demographics

The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 32 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 32 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 8 25%
Student > Ph. D. Student 7 22%
Student > Doctoral Student 5 16%
Researcher 2 6%
Student > Bachelor 1 3%
Other 4 13%
Unknown 5 16%
Readers by discipline Count As %
Engineering 7 22%
Arts and Humanities 6 19%
Design 3 9%
Social Sciences 3 9%
Economics, Econometrics and Finance 2 6%
Other 4 13%
Unknown 7 22%