| Title |
AI-based Construction Site Prioritization for Safety Inspection Using Big Data |
| Authors |
황윤호(Hwang, Yun-Ho) ; 지석호(Chi, Seokho) ; 이현승(Lee, Hyeon-Seung) ; 정현준(Jung, Hyunjun) |
| DOI |
https://doi.org/10.12652/Ksce.2022.42.6.0843 |
| Keywords |
건설현장점검; 랜덤 포레스트; 인공지능; 분류; 예측 Construction site inspection; Random forest; AI; Classification analysis; Prediction |
| Abstract |
Despite continuous safety management, the death rate of construction workers is not decreasing every year. Accordingly, various studies are in progress to prevent construction site accidents. In this paper, we developed an AI-based priority inspection target selection model that preferentially selects sites are expected to cause construction accidents among construction sites with construction costs of less than 5 billion won (KRW). In particular, Random Forest (90.48 % of accident prediction AUC-ROC) showed the best performanceamong applied AI algorithms (Classification analysis). The main factors causing construction accidents were construction costs, total number of construction days and the number of construction performance evaluations. In this study an ROI (return of investment) of about 917.7 % can be predicted over 8 years as a result of better efficiency of manual inspections human resource and a preemptive response to construction accidents. |