Author(s)

Yongjian Liang ¹, Xiaoliang Zhou ¹

Affiliation(s)

¹ Beijing Normal-Hong Kong Baptist University, Zhuhai, Guangdong, China

Corresponding Author

Yongjian Liang

ABSTRACT

With rapid urbanization, cities face growing challenges in resource allocation, public safety, and administrative efficiency. Traditional governance models struggle to keep pace with complex urban dynamics. This study explores the application of weak AI technologies—such as machine learning and computer vision—in urban governance. Focusing on four scenarios: smart government, public safety, traffic management, and community services, it conducts a systematic review of 158 English articles from the past five years. Using a four-dimensional framework (technology, application, bottlenecks, and trends), the study outlines how AI enhances governance efficiency and identifies key implementation challenges. Real-world cases from Hangzhou and Shenzhen demonstrate AI's potential to optimize urban operations. The research offers insights into building inclusive, adaptable, and tech-driven urban governance systems.

KEYWORDS

Urban Governance, Artificial Intelligence, Smart City, Machine Learning, Public Safety, Traffic Management

CITE THIS PAPER

Yongjian Liang, Xiaoliang Zhou, A Survey on the Application of Artificial Intelligence in Urban Governance. Journal of Artificial Intelligence Practice (2025) Vol. 8: 118-124. DOI: http://dx.doi.org/10.23977/jaip.2025.080216.

REFERENCES

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