Open Daily: 10am - 10pm | Alley door pickup 10am - 7pm 3038 Hennepin Ave Minneapolis, MN
612-822-4611

  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
The Future of Sustainable Smart Cities: Using Machine Learning to Enhance Residents' Well-Being, Optimize Mobility, and Support Commercial Success

The Future of Sustainable Smart Cities: Using Machine Learning to Enhance Residents' Well-Being, Optimize Mobility, and Support Commercial Success

Walker, Thomas
Goubran, Sherif
Leon Wang, Liangzhu

Hardcover

Series: Palgrave Studies in Emerging Risk Management and Sustainable Finance

Business GeneralInvesting & FinanceGeneral Architecture

ISBN10: 3032170540
ISBN13: 9783032170545
Publisher: Palgrave MacMillan
Published: Aug 3 2026
Pages: 356
Language: English
Cities are engines of economic growth and innovation. To sustain growth in urban agglomerations, local governments need strategies to address disruptions caused by climate change, resource scarcity, and social inequity. Machine learning (ML) offers a powerful way for city planners to manage, predict, and mitigate these complex challenges. While urban planning has traditionally relied on techniques based on historical data and deterministic models, the dynamic and interconnected nature of contemporary challenges demands more sophisticated and AI-augmented approaches. ML algorithms today can ingest large-scale, multisource data to generate real-time predictions and identify vulnerabilities across infrastructure, mobility, and social systems.

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