The Future of Sustainable Smart Cities

Cities serve as engines of economic growth and innovation, yet sustaining them requires strategies to address climate change, resource scarcity, and social inequity. While urban planning traditionally relied on deterministic models, today’s interconnected challenges demand sophisticated, AI-augmented approaches. Machine learning (ML) empowers planners to manage and mitigate these complexities by leveraging massive datasets for real-time predictions across infrastructure, mobility, and social systems. This edited volume examines how ML supports sustainable smart cities and urban environments that prioritize resident quality of life while maintaining economic resilience. It explores ML-driven innovations in building design, optimized urban mobility, and critical resilience efforts like flood management and air quality monitoring. Furthermore, it highlights tools for social equity and community well-being. Featuring contributions from global experts in architecture, engineering, and computer science, this collection offers actionable insights for building sustainable urban futures by bridging theoretical advancements with practical case studies.