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Urban Computing and Artificial Intelligence
A Data-Driven Tool for Urban Heat Mitigation
- 1st Edition - December 1, 2024
- Editors: Ansar Khan, Mattheos Santamouris, Dev Niyogi
- Language: English
- Paperback ISBN:9 7 8 - 0 - 4 4 3 - 1 4 1 6 8 - 3
- eBook ISBN:9 7 8 - 0 - 4 4 3 - 1 4 1 6 9 - 0
Urban Computing and Artificial Intelligence: A Data-Driven Tool for Urban Heat Mitigation is the first full synthesis of modern scientific and applied research on climate change, u… Read more
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Request a sales quoteUrban Computing and Artificial Intelligence: A Data-Driven Tool for Urban Heat Mitigation is the first full synthesis of modern scientific and applied research on climate change, urban warming, and the future of resilient cities. The book helps city governments better understand how to plan for the effects of climate change and impending natural disasters. It compiles the concepts, strategies, and technologies associated with resilient cities, and provides an outline of what constitutes climate change and its behavior relating to urban systems. Finally, the book develops a comprehensive concept for the future resiliency of cities related to hydro-climatology and extreme events.
Next, it explains the physical principles governing the formation of distinct hydro-climatology and resilient cities, and then illustrates how this knowledge can be applied to moderate the undesirable consequences of swift and haphazard urban development (energy, peak electricity demand, health, comfort, economy, and environment) and help to create more sustainable and resilient cities for the future. With urban climate science now a fully-fledged growing field, this timely book fulfils the need to bring together the disparate parts of urban climate research in global cities into a coherent framework. It is an ideal resource for students, researchers, and policymakers in the fields of urban climate, urban architecture and planning, environmental engineering, urban design, and redevelopment.
- Instructs on the incorporation of urban data, urban climate, and meteorological data into the design, planning, and operation of urban areas in order to make them safer, healthier, and more sustainable cities
- Discusses solutions for a broad range of problems such as spatial and temporal variations in peak electricity demand, the impact of extreme urban heat on public health, the societal and economic costs of urban extreme urban heat, the impact of urbanization on diurnal rainfall and the environment, the impacts of adaptation measures on urban climate, and more
- Facilitates communications with policymakers and end-users of urban data and urban meteorological and climatological data
Urban climatologists, meteorologists, data scientists, urban governing authorities, architects and urban planners, environmental engineers, energy scientists, and policymakers, Architecture and planning science, strategic city planning and urban development, land use planning, climatology and meteorology, earth and environmental sciences, economics, urban geography, atmospheric sciences, natural resource and environmental economics, public policy, technology and engineering
1. Weather extremes and urban warming: Are urban digital twins approaches emerging as the ultimate tool for resilient cities
2. The use of urban digital twins through machine learning and artificial intelligence in the design, planning, and making resilient cities
3. Urban warming and global energy crisis: how to achieve sustainable energy for future cities through machine learning and artificial intelligence
4. Seasonal variations in peak electricity demand in response to urban warming: Application of Google earth engine and artificial intelligence
5. Urban climate change and public health risk: deploying artificial intelligence for human health adaptation to urban warming in cities
6. Urban heat and human thermal comfort: developing health data, impacts, and indices through machine learning and artificial intelligence
7. Economic and societal costs of urban warming: understanding compound economic impact of climate change through machine learning algorithms
8. Urbanization and urban warming: deployment of urban digital twins to study the impacts on diurnal rainfall modification
9. Urban warming, energy balance and thermal management: the case studies for cost-effective and operative in urban heat mitigation through artificial intelligence
10. The impact of urban pollution in cities: an ensemble machine learning model for accurate air pollution detection
11. Major outcomes and limitations in future research and innovation agenda for using machine learning and artificial intelligence in urban digital twins for urban climate research
2. The use of urban digital twins through machine learning and artificial intelligence in the design, planning, and making resilient cities
3. Urban warming and global energy crisis: how to achieve sustainable energy for future cities through machine learning and artificial intelligence
4. Seasonal variations in peak electricity demand in response to urban warming: Application of Google earth engine and artificial intelligence
5. Urban climate change and public health risk: deploying artificial intelligence for human health adaptation to urban warming in cities
6. Urban heat and human thermal comfort: developing health data, impacts, and indices through machine learning and artificial intelligence
7. Economic and societal costs of urban warming: understanding compound economic impact of climate change through machine learning algorithms
8. Urbanization and urban warming: deployment of urban digital twins to study the impacts on diurnal rainfall modification
9. Urban warming, energy balance and thermal management: the case studies for cost-effective and operative in urban heat mitigation through artificial intelligence
10. The impact of urban pollution in cities: an ensemble machine learning model for accurate air pollution detection
11. Major outcomes and limitations in future research and innovation agenda for using machine learning and artificial intelligence in urban digital twins for urban climate research
- No. of pages: 225
- Language: English
- Edition: 1
- Published: December 1, 2024
- Imprint: Elsevier
- Paperback ISBN: 9780443141683
- eBook ISBN: 9780443141690
AK
Ansar Khan
Dr. Khan is an Assistant Professor of Geography at Lalbaba College, Howrah, India. His research incorporates simulation and numerical modeling of global climatic events including urban climate and microclimatic variation using the state-of-the-art Weather Research and Forecasting (WRF) model and Regional Climate Model (RegCM). A key focus of his research is searching for appropriate mitigation strategies and technologies to decrease the overheating of tropical urban areas while also decreasing energy consumption and protecting health. He has commendable expertise in handling data and implementing models in many software platforms. His research contribution has been recognized by some leading researchers in the domain of urban climate research.
Affiliations and expertise
Department of Geography, Lalbaba College, University of Calcutta, Kolkata, IndiaMS
Mattheos Santamouris
Prof. Mattheos Santamouris is the Anita Lawrence Professor of high-performance architecture at the University of New South Wales
in Australia. He is a former professor at the University of Athens, Greece; visiting professor at the Cyprus Institute, London Metropolitan
University, Tokyo Polytechnic University, Free University of Bozen-Bolzano, Brunel University London, and the National University of Singapore;
and a former president of the National Center of Renewable and Energy Savings of Greece. Through high-performance architecture, he
creates innovative methods, techniques, and technologies that improve indoor and outdoor environments while reducing energy
consumption. Indoor and outdoor comforts are vital human needs that contribute significantly to a good quality of life. He has been
involved in designing and implementing mitigation technologies in more than 60 cities, and energy conservation and renewable
technologies in hundreds of buildings and settlements of zero energy consumption.
Affiliations and expertise
Anita Lawrence Professor of High Performance Architecture, School of Built Environment, University of New South Wales, AustraliaDN
Dev Niyogi
Dev Niyogi is Dave P. Carelton Centennial Professor in the Department of Geological Sciences at Jackson School of Geosciences, and Department of Civil, Architectural, and Environmental Engineering in the University of Texas at Austin, USA. He was the most recent chair of the American Meteorological Society (AMS) Board of Urban Environment and elected advisory board member of the International Association of Urban Climate. He is currently serving on the AMS Committee on Applied Climatology, and has previously served on AMS Committee on Agriculture and Forest Meteorology, invited member FGDC Spatial Climate Working Group, Member of the Weather Research and Forecast (WRF) model WG-14 (land surface models), and Member of the AGU Biogeochemistry meetings group/spring meeting student awards chair. He has provided invited testimonies to the National Academy study group, planning summer meetings, and Senate Working groups.
Affiliations and expertise
Dave P. Carelton Centennial Professor, Department of Geological Sciences, Jackson School of Geosciences, and Department of Civil, Architectural, and Environmental Engineering, The University of Texas at Austin, Texas, USA