Visualizing what's missing: Using deep learning and Bow-Tie diagrams to identify and visualize missing leading indicators in industrial construction.

Journal: Journal of safety research
Published Date: Jul 1, 2025

Abstract

INTRODUCTION: In the construction industry, where safety is paramount, the frequency and severity of workplace incidents remain critical concerns. Therefore, site safety inspections have become essential for health and safety programs. While incident data is frequently used to identify gaps in the safety management system, inspection reports are rarely analyzed to identify unsafe patterns on site and reveal measures for safety enhancement. This limitation can reduce the effectiveness of safety inspections, and therefore, this study aims to identify what safety leading indicators do not capture hazards during inspections.

Authors

  • Rose Marie Charuvil Elizabeth
    Department of Chemical and Materials Engineering, School of Engineering Safety and Risk Management, University of Alberta, Edmonton, Alberta T6G 1H9, Canada.
  • Fereshteh Sattari
    Department of Chemical and Materials Engineering, School of Engineering Safety and Risk Management, University of Alberta, Edmonton, Alberta T6G 1H9, Canada. Electronic address: sattari@ualberta.ca.
  • Lianne Lefsrud
    Department of Chemical and Materials Engineering, School of Engineering Safety and Risk Management, University of Alberta, Edmonton, Alberta T6G 1H9, Canada.
  • Brian Gue
    Data Science, PCL Industrial Management Inc, Edmonton, Alberta T6E 3P4, Canada.

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