The Future of Sustainable Smart Cities

Cities are engines of economic growth and innovation. Unfortunately, growth in urban agglomerations is at risk due to increasing abnormalities due to climate change, resource scarcity, and social inequity. Machine learning (ML) presents a powerful new way for city planners to manage, predict, and mitigate these complex urban challenges. And, while urban planning has relied on conventional techniques dependent on historical data and deterministic models, the dynamic and interconnected nature of contemporary urban challenges demands more sophisticated approaches. ML algorithms can ingest massive amounts of data to identify patterns and generate real-time predictions across multiple urban systems. ML models can predict future patterns and assess urban vulnerabilities across infrastructure, mobility, and social systems. This book examines how ML can be used to build and support resilient cities: cities that are prepared for multiple challenges while maintaining capacities to thrive economically and socially. The book explores new ways to use ML to support smarter infrastructure and building design, from system-level networks to specific applications in construction and operations. Chapters demonstrate how ML optimizes urban mobility through enhanced public transportation, fleet management, and urban flow prediction. The book examines ML applications in urban resilience, including flood risk management, air quality monitoring, and disaster response systems. Additionally, it explores innovative applications in social sustainability, such as affective computing for community well being and equity-focused planning tools. The book will feature contributions from leading experts in architecture, urban planning, engineering, computer science, and sustainability. It showcases real-world case studies of successful ML applications in cities around the globe, providing valuable insights for policymakers, urban planners, and researchers. The resulting volume bridges theoretical developments with practical implementations, offering both technical depth and actionable insights for creating sustainable urban futures.