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Article type: Research Article
Authors: Mahmood, Nabeela; * | Qin, Rongjuna; b | Butalia, Tarunjita | Manasrah, Maramc
Affiliations: [a] Department of Civil, Environmental and Geodetic Engineering, The Ohio State University, Columbus, OH, USA | [b] Department of Electrical and Computer Engineering, Translational Data Analytics Institute, The Ohio State University, Columbus, OH, USA | [c] College of Engineering and Applied Science, University of Cincinnati, Cincinnati, OH, USA
Correspondence: [*] Address for correspondence: Nabeel Mahmood, P.E., Ph.D., PMP, LEED GA, CXLT, Department of Civil, Environmental and Geodetic Engineering, The Ohio State University, 409 Hitchcock Hall, 2070 Neil Avenue, Columbus, OH 43210, USA. E-mail: [email protected].
Abstract: BACKGROUND:One of the main problems that may put people’s safety in danger is the lack of real-time detection, evaluation, and recognition of predictable safety risks. Current real-time risk identification solutions are limited to proximity sensing, which lack providing the exposed person with risk-specific information in real-time. Combined values of concurrently presented risks are either unrecognized or underestimated. OBJECTIVE:This study goes beyond the proximity sensing state-of-the-art by envisioning, planning, designing, developing, assembling, and examining an automated intelligent real-time risk (AIR) assessment system. METHODS:A holistic safety assessment approach is followed to include identification, prioritization, detection, evaluation, and control at risk exposure time. Multi-sensor technologies based on RFID are integrated with a risk assessment intelligent system. System prototype is developed and examined to prove the concept for on-foot building construction workers. RESULTS:The evaluation of AIR assessment system’s performance proved its validity, significance, simplicity, representation, accuracy, precision, and timeliness. The reliability of providing quantitative proximity values of risk can be limited due to the signal attenuation; however, it can be reliable in providing risk proximity in a subjective linguistic fashion (Near/Far). CONCLUSION:The main contributions of the AIR assessment system are that the mobile wearable device can provide a linguistic meaningful risk assessment resultant value, the value represents the combined evaluation of concurrently presented risks, and can be sound delivered to the exposed person in real-time of exposure. Therefore, AIR system can be used as an effective prognostic risk assessment tool that can empower workers with real-time recognition and measurability of risk exposure.
Keywords: Real-time assessment, concurrent safety risks, RFID multi-sensors, static dynamic risks, linguistic values, risk rose, fuzzy fault tree analysis
DOI: 10.3233/WOR-210011
Journal: Work, vol. 74, no. 2, pp. 743-760, 2023
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