ETRI-Knowledge Sharing Plaform

ENGLISH

성과물

논문 검색
구분 SCI
연도 ~ 키워드

상세정보

학술대회 An Approach to Automatic Classification of Construction Workers by Degree of Risk
Cited 0 time in scopus Download 1 time Share share facebook twitter linkedin kakaostory
저자
최유희, 김도현
발행일
202010
출처
International Conference on Information and Communication Technology Convergence (ICTC) 2020, pp.1653-1656
DOI
https://dx.doi.org/10.1109/ICTC49870.2020.9289519
협약과제
20ZS1200, 인간중심의 자율지능시스템 원천기술연구, 김도현
초록
Most of construction accidents are caused by the unsafe behavior of construction workers. To reduce the risk of accidents, safety manages should be assigned to manage safety. However, it is difficult for safety manages to manage risks of all worksites. To address this issue, it is necessary to continuously monitor worksites in a timely manner. However, since it is difficult that a safety manager identify hazard areas in many worksites where various tasks are carried out simultaneously, it is necessary to be able to monitor safety of high-risk worksites and identify worksites with high risk of accidents. Therefore, we propose a method to detect and classify workers by degree of risk for the worksites where hazard area has been identified.
키워드
deep learning, risk, safety, workers
KSP 제안 키워드
Automatic classification, Construction workers, High risk, Risk of accidents, Unsafe behavior, construction accidents, deep learning(DL)