Construction safety is one of the significant problems on the world. Deep learning is an emerging term that acquires, processes and analyses image or video data to help computers have a high-level visual understanding of the world. In recent years, it has been introduced into the construction industry for improvements of occupational health and safety. This research contributes in solving this problem by using deep learning only RGB images that output detects the hazard zone on construction sites. The main goal of this study is to use different computer vision and deep learning to develop for different cases concerning fall related hazards.

Abstract
 1. Introduction
 2. Framework of the Deep learning–based construction site hazards zone detection
 3. Conclusion

• 김세훈(세종대학교 건설환경공학과) | Kim Sehoon
• Zarifjon Nakhalov(세종대학교 건설환경공학과)
• 이종재(세종대학교 건설환경공학과) | Lee Jong-Jae