Abstract
In various parts of the world, big data related methods is being utilized to predict criminal activities and facilitate prompt arrests. Advancements in big data and technology have made it possible to analyze and forecast crime patterns effectively. This research aims to analyze the effectiveness of Crime Prevention Through Environmental Design (CPTED) elements and predict crime rates using machine learning techniques based on data from 2016 to 2021 in Seoul. This study utilizes diverse data in CPTED elements obtained from the Smart Public Safety Big Data Platform. The significance of this study lies in demonstrating the effectiveness of CPTED and leveraging big data for crime prediction. The findings can serve as a reference for the policy-making and the establishment of crime prevention systems based on predictive insights.
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