Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Describing Construction Hazard Images Identified from Site Safety Surveillance Video
Construction accidents are a major cause of occupational fatalities globally. On-site hazard identification is crucial to prevent such accidents. CCTV is commonly used for safety surveillance on construction sites, and can be utilized for machine learning-based automatic hazard identification. A Construction Hazard Description System (CHDS) was developed in this study to systematically label site objects and describe hazard scenarios. CHDS builds on the ontology of Taiwan Occupational Safety and Health Administration (TOSHA) for hazard classification and construction accident risk scenarios. The system produces site images and associated hazard descriptions that can be used to train automated construction accident risk identification systems through machine learning. According to domain experts, CHDS is effective in assisting construction safety personnel in describing hazard images collected on site, achieving high accuracy rates in both attribute description and hazard classification. It is concluded the system has great potential in improving the task of captioning construction hazard images.
Describing Construction Hazard Images Identified from Site Safety Surveillance Video
Construction accidents are a major cause of occupational fatalities globally. On-site hazard identification is crucial to prevent such accidents. CCTV is commonly used for safety surveillance on construction sites, and can be utilized for machine learning-based automatic hazard identification. A Construction Hazard Description System (CHDS) was developed in this study to systematically label site objects and describe hazard scenarios. CHDS builds on the ontology of Taiwan Occupational Safety and Health Administration (TOSHA) for hazard classification and construction accident risk scenarios. The system produces site images and associated hazard descriptions that can be used to train automated construction accident risk identification systems through machine learning. According to domain experts, CHDS is effective in assisting construction safety personnel in describing hazard images collected on site, achieving high accuracy rates in both attribute description and hazard classification. It is concluded the system has great potential in improving the task of captioning construction hazard images.
Describing Construction Hazard Images Identified from Site Safety Surveillance Video
Lecture Notes in Civil Engineering
Casini, Marco (Herausgeber:in) / Yu, Wen-Der (Autor:in) / Hsiao, Wen-Ta (Autor:in) / Cheng, Tao-Ming (Autor:in) / Chiang, Hung-Sheng (Autor:in) / Chang, Chia-Yu (Autor:in)
International Civil Engineering and Architecture Conference ; 2023 ; Kyoto, Japan
Proceedings of the 3rd International Civil Engineering and Architecture Conference ; Kapitel: 76 ; 937-948
06.02.2024
12 pages
Aufsatz/Kapitel (Buch)
Elektronische Ressource
Englisch
Hazard surveillance in new residential construction
| British Library Conference Proceedings | 1999
Construction hazard and safety handbook
| TIBKAT | 1985
Safety Hazard Identification on Construction Projects
| Online Contents | 2006