| Title |
Predictive Analytics for Municipal Public Security: A Comprehensive Scheme Integrating Big Data and Regression Models |
| Authors |
(Models Moonsik Kang) ; (Yonggyu Jung) |
| DOI |
https://doi.org/10.5573/IEIESPC.2024.13.1.81 |
| Keywords |
Municipal police system; Security demand prediction; Big data analysis; Correlation analysis; Regression model |
| Abstract |
As the operation of the municipal police system has started, people's attention has been focused on whether the demand for security personnel is appropriate. Municipal police is an executive organization of local government with autonomous administrative authority and autonomously provides municipal police service for residents in the jurisdiction. In other words, it is an organization that conducts police activities under the responsibility of the local government. This study designed a self-policing demand prediction system using big data analysis and a regression model based on regional characteristics, and the performance was evaluated by analyzing the correlations. The model proposed in this paper is a big data analysis model that extracts major variables using correlation analysis between the collected variables and the current demand for municipal police personnel. The performance of the proposed scheme was evaluated by generating and analyzing the appropriate number of people in need of security in a specific G area. The results confirmed that the prediction was accurate. |