Collective Sensing of Workers’ Loss of Body Balance for Slip, Trip, and Fall Hazard Identification: Field Validation Study
Publication: Journal of Computing in Civil Engineering
Volume 37, Issue 1
Abstract
Manual hazard identification by safety managers in construction has practical challenges because each manager identifies environmental hazards from their perception, which can leave many potential hazards unidentified and consequently lead to accidents at the site. Previous studies have revealed that workers experience loss of body balance (LOB) when exposed to slip, trip, and fall (STF) hazards. This study extended previous studies to identify STF hazards by LOB measurement and collective sensing (i.e., data aggregation) techniques and assumed that STF hazards would cause multiple workers’ LOBs in a given location. First, this study developed an approach to assess each worker’s exposure to STF hazards by LOB analysis. A waist-worn inertial measurement unit sensor was used to extract features of waist movements, which were mapped into a single value to measure LOB scores using the Mahalanobis distance (MD) metric. As an individual worker is exposed to STF hazards, the MD values become larger than without exposure to STF hazards. The developed approach provided an unweighted average recall of 89.13% (without exposures: 90.30%, and with exposures: 87.96%) for detecting individual workers’ exposures to STF hazards in an actual construction site. Then, an approach was developed to visualize the location of STF hazards by allocating multiple workers’ LOB scores into each individual’s Global Positioning System (GPS) data points. The results showed the feasibility of the developed approach to identify STF hazards, potentially helping to prevent STF accidents at construction sites.
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Data Availability Statement
All models or code that support the findings of this study are available from the corresponding author upon reasonable request.
Acknowledgments
The study described in this paper was partially supported by Liberty Mutual Insurance, Risk Control Services, and by Institute of Construction and Environmental Engineering (ICEE) at Seoul National University. Specifically, the authors would like to acknowledge George Brogmus from Liberty Mutual Insurance for their constructive feedback. Also, the authors wish to acknowledge Barton Malow for considerable help in data collection as well as anonymous participants who helped with data collection. Any opinions, findings, conclusions, or recommendations expressed in this paper are those of the authors and do not necessarily reflect the views of Liberty Mutual Insurance.
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Information & Authors
Information
Published In
Journal of Computing in Civil Engineering
Volume 37 • Issue 1 • January 2023
Copyright
© 2022 American Society of Civil Engineers.
History
Received: Mar 28, 2022
Accepted: Sep 8, 2022
Published online: Nov 7, 2022
Published in print: Jan 1, 2023
Discussion open until: Apr 7, 2023
ASCE Technical Topics:
- Business management
- Construction engineering
- Construction management
- Construction sites
- Disaster risk management
- Disasters and hazards
- Employment
- Engineering fundamentals
- Labor
- Measurement (by type)
- Occupational safety
- Personnel management
- Practice and Profession
- Public administration
- Public health and safety
- Risk management
- Safety
- Sensors and sensing
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