Quantifying Hazard Exposure Using Real-Time Location Data of Construction Workforce and Equipment
Publication: Journal of Construction Engineering and Management
Volume 142, Issue 8
Abstract
Traditional risk-assessment methods typically evaluate accident probability, exposure frequency or duration, and consequence severity, respectively, and finally determine a quantitative risk score or a qualitative risk level. The assessment process is prospective and subjective. Changing and complex construction situations impede their practical and efficient application. To assess safety risk with regard to changing site conditions in an objective and efficient way, this study proposes a quantitative model for hazard exposure assessment based on real-time location data of construction workforce and equipment, collected by a location-based proximity warning system. In contrast with traditional risk-assessment methods, the model proposed in this study combines accident probability and hazard exposure duration into a single quantitative concept—hazard exposure amount. This concept takes into account the space factor as well as the time factor of construction activities. For ease of understanding, a hazard is analogized as a radiation source and the hazard exposure is then referred to as the radiation quantity received. The longer duration and closer proximity in which a person is exposed to a radiation (hazard), the more radiation the person receives (the higher risk to which the person is exposed). A trial study is described in which a proximity warning system was developed and used to demonstrate and test the model’s capability of hazard exposure assessment. This shows that the system can provide safety officers with an ongoing and immediate means of comparing safety risk trends from worker, hazard, and project perspectives.
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Acknowledgments
Many thanks go to Bo Ye, Wei Lu, and Xintao Yang for their indispensable efforts in the system development and trial studies. The work was supported by the Innovation and Technology Commission of Hong Kong, under the public sector trial scheme of a project “Location-Based Technologies for Asset Tracking and Risk Management” (ITT/004/15LP), and the Research Grants Council of Hong Kong with the grant titled “Proactively Monitoring Construction Progress by Integrating 3D Laser-Scanning and BIM” (PolyU 152093/14E).
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Information & Authors
Information
Published In
Journal of Construction Engineering and Management
Volume 142 • Issue 8 • August 2016
Copyright
© 2016 American Society of Civil Engineers.
History
Received: May 12, 2015
Accepted: Dec 8, 2015
Published online: Feb 26, 2016
Discussion open until: Jul 26, 2016
Published in print: Aug 1, 2016
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