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Urban safety is becoming an increasingly crucial issue due to rising crime rates and urbanization. The concept of a “Safe City” aims to ensure citizen safety through effective crime prevention and rapid response strategies. Volunteer security teams play a vital role in supplementing police efforts to maintain community safety. However, current patrol routes are often set unsystematically, relying on experience, leading to inefficient resource use and reduced effectiveness in crime prevention. This study optimized patrol routes for volunteer security teams using advanced data analysis techniques and route optimization algorithms. By integrating various data sources and applying advanced algorithms, the study systematically improved patrol efficiency and effectiveness. By analyzing security facility locations, crime data, and weak areas in Gangseo-gu, this study identified gaps between infrastructure and vulnerable areas. The novelty of this research lies in its comprehensive approach to deriving a security vulnerability index and designing optimal patrol routes based on integrated BIM-GIS data. This optimized approach ensures effective coverage of critical zones, significantly enhancing the operational efficiency of volunteer security teams.
Lee et al. (Thu,) studied this question.