Urban Computing and Artificial Intelligence: A Data-Driven Tool for Urban Heat Mitigation
Editat de Ansar Khan, Mattheos Santamouris, Dev Niyogien Limba Engleză Paperback – iun 2025
- 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
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Specificații
ISBN-13: 9780443141683
ISBN-10: 0443141681
Pagini: 225
Dimensiuni: 152 x 229 mm
Editura: ELSEVIER SCIENCE
ISBN-10: 0443141681
Pagini: 225
Dimensiuni: 152 x 229 mm
Editura: ELSEVIER SCIENCE
Cuprins
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