Real-time site safety risk assessment and intervention method using the RFID-based multi-sensor intelligent system.
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...
| Published in: | Work Vol. 74; no. 2; pp. 743 - 761 |
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| Main Authors: | , , , |
| Format: | algorithm pictorial research tables/charts Journal Article |
| Published: |
Sage Publications Inc.
2023
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| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=162119900&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 162119900 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 10519815 3RC jtl: Work issn: 10519815 maglogo: N pubinfo: dt: 2023 vid: 74 iid: 2 pid: 344 pub: Sage Publications Inc. place: Thousand Oaks, California artinfo: ui: 162119900 159734240 162119900 162119900 10.3233/WOR-210011 162119900 ppf: 743 ppct: 18 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Real-time site safety risk assessment and intervention method using the RFID-based multi-sensor intelligent system. aug: au: Mahmood, Nabeel Qin, Rongjun Butalia, Tarunjit Manasrah, Maram affil: Department of Civil, Environmental and Geodetic Engineering, The Ohio State University, Columbus, OH, USA sug: subj: Risk Assessment Methods Occupational Safety Radio Frequency Identification Methods Artificial Intelligence Technology Reliability Decision Making Validity Human Algorithms ab: 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. pubtype: Academic Journal doctype: algorithm pictorial research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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