Artificial Intelligence in Urban Planning and Design

Artificial Intelligence in Urban Planning and Design

Technologies, Implementation, and Impacts

1st Edition - May 14, 2022

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  • Editors: Imdat As, Prithwish Basu
  • Paperback ISBN: 9780128239414
  • eBook ISBN: 9780128239421

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Description

Artificial Intelligence in Urban Planning and Design: Technologies, Implementation, and Impacts is the most comprehensive resource available on the state of Artificial Intelligence (AI) as it relates to smart city planning and urban design. The book explains nascent applications of AI technologies in urban design and city planning, providing a thorough overview of AI-based solutions. It offers a framework for discussion of theoretical foundations of AI, AI applications in the urban design, AI-based research and information systems, and AI-based generative design systems. The concept of AI generates unprecedented city planning solutions without defined rules in advance, a development raising important questions issues for urban design and city planning. This book articulates current theoretical and practical methods, offering critical views on tools and techniques and suggests future directions for the meaningful use of AI technology.

Key Features

  • Includes a cutting-edge catalogue of AI tools applied to smart city design and planning
  • Provides case studies from around the globe at various scales
  • Includes diagrams and graphics for course instruction

Readership

Future city, smart city, AI, urban design technologies, city planning, civil engineers, city planners, and urban designers

Table of Contents

  • Cover image
  • Title page
  • Table of Contents
  • Copyright
  • Contributors
  • Preface
  • Content
  • Acknowledgments
  • Part 1: Theoretical foundations
  • Chapter 1: A new agenda for AI-based urban design and planning
  • Abstract
  • Acknowledgment
  • Embracing AI to recalibrate the master plan
  • The future of work: AI and the disruption of planning and urban design practice
  • Unpacking artificial intelligence for planners and urban designers
  • Fundamental AI components for disrupting planning and urban design practice
  • AI enhancing traditional planning and urban design services workflow
  • AI and the challenges to expertise
  • References
  • Chapter 2: AI and the limits of human creativity in urban planning and design
  • Abstract
  • Introduction
  • Architectural lessons
  • The limits of human creativity
  • References
  • Chapter 3: Complexity science for urban solutions
  • Abstract
  • Acknowledgments
  • Introduction
  • Artificial intelligence (AI) in the built environment
  • Complexity science and urban systems
  • Key aspects of spatial network analysis
  • Computational social science and its AI applications
  • Summary
  • References
  • Part 2: AI tools and techniques
  • Chapter 4: Classes of AI tools, techniques, and methods
  • Abstract
  • Acknowledgments
  • Introduction
  • A working definition of AI in urban planning and design
  • Tools: Algorithmic clades in urban planning and design
  • Techniques: A machine’s-eye view of the city
  • Methods: A snapshot from the practitioner's desktop
  • Conclusions
  • References
  • Chapter 5: Urban form analysis through morphometry and machine learning
  • Abstract
  • Urban form—A basic definition
  • Urban morphometry
  • Context-rich urban analysis and generation using machine learning
  • Urban morphometry with advanced statistics
  • References
  • Chapter 6: AI-driven BIM on the cloud
  • Abstract
  • Introduction
  • Background
  • AI-driven building information model on the cloud
  • Case studies
  • Conclusions
  • References
  • Part 3: AI in urban scale research
  • Chapter 7: Deep learning in urban analysis for health
  • Abstract
  • Introduction
  • Urban morphology and health
  • Deep learning in urban analysis for health
  • Applications of discriminative deep learning in urban health analysis
  • Applications of generative deep learning for urban health analysis
  • Challenges, opportunities, and next steps
  • References
  • Chapter 8: Spatial design of energy self-sufficient communities
  • Abstract
  • Acknowledgments
  • Cities and energy resiliency
  • Designing for energy self-sufficient urban settlements
  • Urban form and energy consumption in communities
  • Interpreting the black box
  • Closure
  • References
  • Further reading
  • Chapter 9: The image of the city through the eyes of machine reasoning
  • Abstract
  • Acknowledgment
  • Introduction
  • Background
  • Methods, tools, and techniques
  • Case study
  • Conclusions
  • References
  • Chapter 10: Optimizing urban grid layouts using proximity metrics
  • Abstract
  • Acknowledgments
  • Introduction
  • Materials and methods
  • Case study
  • Results
  • Discussion
  • References
  • Part 4: Case studies in urban design and planning
  • Chapter 11: Image analytics for urban planning: The case of the Barcelona Superblock
  • Abstract
  • Acknowledgment
  • The urgency for a new urbanism
  • Novel methods for image analytics
  • Conclusions
  • References
  • Chapter 12: Complexity science-based spatial performance analyses of UNStudio/DP Architects’ SUTD Campus and WOHA's Kampung Admiralty
  • Abstract
  • Acknowledgment
  • Introduction
  • Analyses of two vertically integrated spatial networks
  • Methodology and research phases
  • Conclusions
  • References
  • Chapter 13: Understanding urban leisure walking behavior: Correlations between neighborhood features and fitness tracking data
  • Abstract
  • Introduction
  • Leisure walk
  • Methodology and data
  • Results
  • Destinations
  • Conclusion and future work
  • References
  • Chapter 14: Spacemaker.Ai: Using AI in developing urban block variations
  • Abstract
  • Generative design
  • Tools at Spacemaker
  • Case study
  • Conclusion
  • Chapter 15: Möbius evolver: Competitive exploration of urban massing strategies
  • Abstract
  • Acknowledgment
  • Introduction
  • Competitive evolutionary design exploration
  • Demonstration
  • Discussion
  • Conclusions
  • References
  • Chapter 16: Adaptive master plans: Flexible modular design strategies
  • Abstract
  • Introduction
  • Background
  • Methods
  • Applications
  • Conclusions
  • Notes
  • References
  • Chapter 17: SASAKI: Filling the design gap—Urban impressions with AI
  • Abstract
  • Introduction
  • Background
  • Identifying a “good enough” tool
  • Using GANs to generate urban impressions
  • Key takeaways
  • Toward a sketch tool prototype
  • Conclusions
  • References
  • Chapter 18: KPF: A retrospective view on urban planning AI for 2020
  • Abstract
  • Preamble
  • Crises and inventions
  • Evolution of tools
  • Conclusions
  • References
  • Index

Product details

  • No. of pages: 408
  • Language: English
  • Copyright: © Elsevier 2022
  • Published: May 14, 2022
  • Imprint: Elsevier
  • Paperback ISBN: 9780128239414
  • eBook ISBN: 9780128239421

About the Editors

Imdat As

Imdat As is Assistant Professor in the College of Engineering, Technology, and Architecture at University of Hartford. His research and teaching interests include Artificial Intelligence and Deep Learning in Design, Augmented and Virtual Technologies, and Digital Fabrication He is on the Editorial Board of International Journal of Architecture and Planning and his work has been cited in popular and professional media, news coverage, and interviews.

Affiliations and Expertise

Assistant Professor, College of Engineering, Technology, and Architecture, University of Hartford, CT, USA

Prithwish Basu

Prithwish Basu is Principal Scientist in Network & Cyber Technologies at Raytheon BBN Technologies. He has a Ph.D. in Computer Engineering from Boston University.

Affiliations and Expertise

Principal Scientist, Network and Cyber Technologies, Raytheon BBN Technologies, USA

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