| Title |
The Quantification of the Safety Accident of Foreign Workers in the Construction Sites |
| DOI |
https://dx.doi.org/10.6106/KJCEM.2024.25.5.025 |
| Keywords |
Deep Learning Algorithm; Safety Accidents; Safety Management; Foreign Workers |
| Abstract |
The purpose of this study is to propose a model development framework to predict the risk of safety accidents for foreign workers based on a deep learning algorithm for systematic safety management of foreign workers in the construction industry. Many past studies have shown that foreign workers working at construction sites are relatively more vulnerable to safety accidents than non-foreign workers, but quantitative research on the risk of safety accidents among foreign workers working at construction sites is lacking. Furthermore, due to a lack of predictive research on safety accidents, realistic and systematic safety management for foreign workers is not possible. Therefore, in order to complement this, this study proposes a deep learning algorithm-based model that collects, analyzes, and predicts safety accident data occurring at construction sites for systematic safety management of foreign workers at construction sites. The results and framework of this study can be used to analyze and predict various safety accident risks that occur at construction sites, and ultimately can serve as an important guideline for safety management of foreign workers at construction sites. |