지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 발행연도
- 2024.3
- 수록면
- 265 - 272 (8page)
이용수
초록· 키워드
오류제보하기
In the construction industry, there is a gradual increase in the application of computer vision for field management and safety analysis of workers. Computer vision is employed for tasks like monitoring the use of safety helmets, verifying the fastening of safety rings, and automatically recognizing the behavior of heavy equipment. However, research specifically addressing the postures leading to musculoskeletal disorders is relatively limited. The construction site, being labor-intensive and involving various professionals and equipment in each process, requires continuous management and monitoring to minimize musculoskeletal diseases among workers and ensure their safety. Managing such a large construction site with diverse tasks for each process poses challenges for effective oversight. In this study, risk postures were defined based on REBA, and key joint points were identified using Posenet. Using this data, a model was developed to classify workers" postures using Teachable Machine, demonstrating high accuracy in recognizing different risk postures.
목차
Abstract
1. 서론
2. 문헌고찰
3. 데이터 수집
4. 근로자 인식 모델
5. 결론
REFERENCES
참고문헌 (13)
참고문헌 신청
Cheon, W. h. (2022). A study for evaluators and assessment tools to improve the effectiveness of musculoskeletal risk assessment, School of Industrial Engineering, Graduate School University of Ulsan.
Health and safety statistics (2020). Health and safety at work, Summary statistics for Great Britain 2020, 5, Retrieved January 28, 2023, from https://www.gov.uk/government/statistics/health-and-safety-statistics-2019-to-2020-annual-release
Jeong, I. S., Kim, J. W., Chi, S. H., Roh, Myungil, Biggs, Herbert. (2021). Solitary work detection of heavy equipment using computer vision. Journal of Civil and Environmental Engineering Research, 41(4), 441-447.
Kang, K. S., Cho, Y. W., & Ryu, H. G. (2020). A basic study on the instance segmentation with surveillance cameras at construction sties using deep learning based computer vision. Journal of the Korea Institute of Building Construction, 20(2), 55-56.
Lee, D. K., & Kim, J. H. (2010). A study on the prevention system of musculoskeletal disorders in korea and other countries. Journal of the ergonomics society of Korea, 29(4), 423-433.
Health and safety statistics (2020). Health and safety at work, Summary statistics for Great Britain 2020, 5, Retrieved January 28, 2023, from https://www.gov.uk/government/statistics/health-and-safety-statistics-2019-to-2020-annual-release
Jeong, I. S., Kim, J. W., Chi, S. H., Roh, Myungil, Biggs, Herbert. (2021). Solitary work detection of heavy equipment using computer vision. Journal of Civil and Environmental Engineering Research, 41(4), 441-447.
Kang, K. S., Cho, Y. W., & Ryu, H. G. (2020). A basic study on the instance segmentation with surveillance cameras at construction sties using deep learning based computer vision. Journal of the Korea Institute of Building Construction, 20(2), 55-56.
Lee, D. K., & Kim, J. H. (2010). A study on the prevention system of musculoskeletal disorders in korea and other countries. Journal of the ergonomics society of Korea, 29(4), 423-433.
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