Real-time monitoring unsafe behaviors of portable multi-position ladder worker using deep learning based on vision data.

Journal: Journal of safety research
PMID: 38081718

Abstract

INTRODUCTION: Fatal fall from height accidents, especially on construction sites, persist, underscoring the importance of monitoring and managing worker behaviors to enhance safety. Deep learning showed the possibility of substituting the manual work of safety managers. However, applying detection results to determine compliance with safety regulations has limitations.

Authors

  • Minsoo Park
    School of Civil, Architectural Engineering and Landscape Architecture, Sungkyunkwan University, 2066, Seobu-ro, Jangan-gu, Suwon 16419, Gyeonggi-do, Republic of Korea.
  • Dai Quoc Tran
    School of Civil, Architectural Engineering and Landscape Architecture, Sungkyunkwan University, 2066, Seobu-ro, Jangan-gu, Suwon 16419, Gyeonggi-do, Republic of Korea.
  • Jinyeong Bak
    College of Computing and Informatics, Sungkyunkwan University, 2066, Seobu-ro, Jangan-gu, Suwon 16419, Gyeonggi-do, Republic of Korea.
  • Almo Senja Kulinan
    Department of Global Smart City, Sungkyunkwan University, 2066, Seobu-ro, Jangan-gu, Suwon 16419, Gyeonggi-do, Republic of Korea.
  • Seunghee Park
    School of Civil, Architectural Engineering and Landscape Architecture, Sungkyunkwan University, Suwon 16419, Korea.

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