Image-and-Skeleton-Based Parameterized Approach to Real-Time Identification of Construction Workers' Unsafe Behaviors

Hongling Guo, Yantao Yu, Qinghua Ding, Martin Skitmore

Research output: Journal article publicationJournal articleAcademic researchpeer-review

21 Citations (Scopus)

Abstract

Workers' unsafe behaviors are one of the main causes for construction accidents. Fully understanding the causes of unsafe behaviors on site will help to prevent them, thus reducing construction accidents. The accurate and timely identification of site workers' unsafe behaviors can aid in the analysis of the causes of unsafe behaviors and prevention of construction accidents. However, the traditional methods (e.g., site observation) of behavior data collection on site is neither efficient nor comprehensive. This paper develops a skeleton-based real-time identification method by combining image-based technologies, construction safety knowledge, and ergonomic theory. The proposed method recognizes unsafe behaviors by simplifying dynamic motions into static postures, which can be described by a few parameters. Three basic modules are involved: an unsafe behavior database, real-time data collection module, and behavior judgement module. A laboratory test demonstrated the feasibility, efficiency, and accuracy of the method. The method has the potential to improve construction safety management by providing comprehensive data for the systematic identification of the causes to workers' unsafe behaviors, such as inappropriate management methods, measures or decisions, personal characteristics, work space and time, as well as warning workers identified as behaving unsafely, if necessary. Thus, this paper contributes to practice and the body of knowledge of construction safety management, as well as research and practice in image-based behavior recognition.

Original languageEnglish
Article number04018042
JournalJournal of Construction Engineering and Management
Volume144
Issue number6
DOIs
Publication statusPublished - 1 Jun 2018

Keywords

  • Behavior-based safety (BBS)
  • Construction worker
  • Image-based behavior recognition
  • Real time
  • Safety management

ASJC Scopus subject areas

  • Civil and Structural Engineering
  • Building and Construction
  • Industrial relations
  • Strategy and Management

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