Year: 2025
Type: article
Study design: Systematic Review
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.
Authors: Yongjian Liang, Xiaoliang Zhou
Institution: Beijing Normal-Hong Kong Baptist University
Language: English
Subfield: Media Technology
Field: Engineering
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4411248999