Wearable Sensing Technology Applications in Construction Safety and Health
Publication: Journal of Construction Engineering and Management
Volume 145, Issue 11
Abstract
The advent of wearable sensing technologies has produced unprecedented opportunities for the near real-time collection and analysis of workers’ safety and health data. To encourage the proactive safety management these opportunities present, extensive research efforts have explored using various wearable sensing technologies—including motion sensors (e.g., inertial measurement units) and physiological sensors (e.g., heart-rate sensors, electrodermal-activity sensors, skin-temperature sensors, eye trackers, and brainwave monitors)—to detect potential safety hazards and to continuously monitor a worker’s health on a construction jobsite. However, these efforts tend to be piecemeal or fragmented, which presents a challenge for both the practitioners and the researchers who wish to fully understand the current developments in this area. In this context, this paper provides a critical review of the state of the art of wearable applications in construction safety and health. The review first identifies five general applications within the literature: preventing musculoskeletal disorders, preventing falls, assessing physical workload and fatigue, evaluating hazard-recognition abilities, and monitoring workers’ mental status. Second, this study identifies the challenges impeding further development and deployment of wearable applications, specifically, signal artifacts and noise in wearable-sensors’ field measurements, variable standards for personal safety and health risks in construction, users’ resistance to technology adoption, and uncertainty regarding the return on investment. Lastly, this paper recommends future research opportunities for advancing the field, especially in terms of conducting sensor fusion for wearable applications, developing a business case, and engaging wearables in risk assessment and post-injury compensability assessment.
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Data Availability Statement
All data generated or analyzed during the study are included in the published paper. Information about the Journal’s data-sharing policy can be found here: http://ascelibrary.org/doi/10.1061/(ASCE)CO.1943-7862.0001263.
Acknowledgments
This study was partially supported by the National Science Foundation (CMMI #1538029). Any opinions, findings, conclusions, or recommendations expressed in this article are those of the authors and do not necessarily reflect the views of the National Science Foundation.
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Journal of Construction Engineering and Management
Volume 145 • Issue 11 • November 2019
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