'Customized Regional Security' Police Data Analysis On-site Meeting

[Asia Economy Reporter Jeong Dong-hoon] The Police University Institute of Police Policy Research held an on-site meeting on the 10th at the Police Agency Cultural Plaza under the theme of 'Police Data Analysis for Region-Specific Customized Policing.'

This meeting was held to seek solutions using police data to enhance citizens' perceived safety ahead of the autonomous police era. On-site police officers, related departments of the Police Agency, and researchers attended.

The Institute of Police Policy Research presented research results including ▲ Predictive analysis of changes in the policing environment due to the COVID-19 economic crisis ▲ Analysis of factors affecting perceived safety in the Seoul Police Agency and suggestions for improvement ▲ Classification of 112 call types and hotspot analysis.

Researcher Park Se-yeon of the Smart Policing Intelligence Center presented changes in crime occurrence according to economic indicator changes using machine learning techniques. Statistically significant crimes were analyzed, showing that compared to June 2017, in June 2020, ▲ gambling (127%↑), ▲ special economic crimes (44%↑), and ▲ robbery (25%↑) surged sharply, while ▲ assault (12%↓) and ▲ injury (7%↓) decreased.

Researcher Min Hwi-kyung presented on the topic 'Analysis of Factors Affecting Perceived Safety in the Seoul Police Agency and Suggestions for Improvement,' discussing factors influencing the evaluation of police policing services.

As a result of analyzing various factors affecting citizens' perceived safety, it was found that influencing factors differ by police station. For example, the factor most affecting residents' perceived safety in Police Station A was ‘high incidence of crimes against women,’ whereas in Police Station B, it was ‘high proportion of economically vulnerable population,’ showing different influencing factors.

Researcher Kim Hye-jin presented 'Classification of 112 Call Types and Hotspot Analysis.' This program automatically classifies ‘other types of 112 calls’ through natural language processing techniques, improving the accuracy of crime statistics required by the respective police stations.

Accordingly, compared to existing statistics, about 38% of other types can be automatically reclassified into specific types such as phishing scams, intoxicated persons, and violence. Additionally, it is possible to geographically identify occurrence patterns of special theme crime types.

Professor Kim Jung-gon of Keimyung University presented 'Performance of Daegu Metropolitan Police Agency’s 112 Call Response Using Floating Population Analysis.' Professor Kim has been researching the reallocation of patrol routes and efficiency improvement of 112 call responses based on floating population in collaboration with the Daegu Metropolitan Police Agency. Through this research, the Daegu Metropolitan Police Agency operated a patrol route algorithm targeting five areas of Daegu City, reducing 112 calls and particularly achieving effects in preventing theft.

Jang Kwang-ho, head of the Smart Policing Intelligence Center (Police Superintendent), stated, "Ahead of the autonomous police era, it is important for the police to utilize customized data," adding, "More urgent than technology is the attitude within police organizations where each department is willing to share the data they manage with other departments. Our center will play a role in supporting departments within the police organization to share data with each other and develop technology."

This content was produced with the assistance of AI translation services.