Real-time site safety risk assessment and intervention method using the RFID-based multi-sensor intelligent system.

RFID multi-sensors Real-time assessment concurrent safety risks fuzzy fault tree analysis linguistic values risk rose static dynamic risks

Journal

Work (Reading, Mass.)
ISSN: 1875-9270
Titre abrégé: Work
Pays: Netherlands
ID NLM: 9204382

Informations de publication

Date de publication:
2023
Historique:
pubmed: 25 10 2022
medline: 3 3 2023
entrez: 24 10 2022
Statut: ppublish

Résumé

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. 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. 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. 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). 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.

Sections du résumé

BACKGROUND 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 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 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 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 CONCLUSIONS
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.

Identifiants

pubmed: 36278369
pii: WOR210011
doi: 10.3233/WOR-210011
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

743-760

Auteurs

Nabeel Mahmood (N)

Department of Civil, Environmental and Geodetic Engineering, The Ohio State University, Columbus, OH, USA.

Rongjun Qin (R)

Department of Civil, Environmental and Geodetic Engineering, The Ohio State University, Columbus, OH, USA.
Department of Electrical and Computer Engineering, Translational Data Analytics Institute, The Ohio State University, Columbus, OH, USA.

Tarunjit Butalia (T)

Department of Civil, Environmental and Geodetic Engineering, The Ohio State University, Columbus, OH, USA.

Maram Manasrah (M)

College of Engineering and Applied Science, University of Cincinnati, Cincinnati, OH, USA.

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Classifications MeSH