AI Technology-Driven Transformation of Sustainable Urban Planning: Technical Paths, Application Mechanisms and System Optimization Strategies

Chun Yik Jenny Li （ School of Architecture, Chongqing University, Chongqing 400044, China ）

Abstract

With the intensification of global urbanization and extreme climate events, traditional urban planning faces bottlenecks in data management, decision-making and responsive governance. This paper sorts out the applications of AI technologies such as machine learning and digital twin in sustainable urban planning, verifying their effectiveness in optimizing ecological, energy and transportation scenarios, improving planning efficiency and regulating carbon emissions. Combined with typical foreign cases, the paper identifies problems including regional imbalance, data barriers and talent shortage, and proposes optimization paths covering data infrastructure construction, standard system development, talent cultivation and public participation. The research provides a reference for the integration of AI and urban planning.

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