A Prototype Risk Assessment Dashboard for the Construction Industry: Getting Experts in the Loop Thanks to Machine Learning

Construction work is fundamentally hazardous. Traditional risk assessment tools (e.g., checklists and audits) are static in essence and hard to make evolve. In this paper, we demonstrate how to get experts dynamically in the loop thanks to machine learning. Namely, we discussed the design of a prototype risk assessment dashboard dedicated to fall accidents. The interactive graphical user interface allows professionals to generate construction scenarios and compare their evaluation of risks with that of the dashboard. The latter continuously learns from expert feedback. The proof-of-concept we present here shows that it is possible to capitalize on expert knowledge in a dynamic and user-friendly way. Thanks to its neural network architecture, not only does the dashboard learn from the experts, but professionals also learn from the dashboard.

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Publication Details

Journal
Safety
Published
2025-12-01
DOI
https://doi.org/10.3390/safety11040118
Primary Topic
Occupational Health and Safety Research
Type
article
Field-Weighted Citation Impact
0.00

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article

A Prototype Risk Assessment Dashboard for the Construction Industry: Getting Experts in the Loop Thanks to Machine Learning

Mirza Muntasir Nishat, Nils O.E. Olsson, Antoine Rauzy
Safety
Occupational Health and Safety Research
article

A Prototype Risk Assessment Dashboard for the Construction Industry: Getting Experts in the Loop Thanks to Machine Learning

Mirza Muntasir Nishat, Nils O.E. Olsson, Antoine Rauzy
article en

Abstract

Construction work is fundamentally hazardous. Traditional risk assessment tools (e.g., checklists and audits) are static in essence and hard to make evolve. In this paper, we demonstrate how to get experts dynamically in the loop thanks to machine learning. Namely, we discussed the design of a prototype risk assessment dashboard dedicated to fall accidents. The interactive graphical user interface allows professionals to generate construction scenarios and compare their evaluation of risks with that of the dashboard. The latter continuously learns from expert feedback. The proof-of-concept we present here shows that it is possible to capitalize on expert knowledge in a dynamic and user-friendly way. Thanks to its neural network architecture, not only does the dashboard learn from the experts, but professionals also learn from the dashboard.

SafetyVol. 11(4)
Norwegian University of Science and Technology (NO)
Norges Forskningsråd
Openalex Percentile: Top 50%
Occupational Health and Safety Research
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A Prototype Risk Assessment Dashboard for the Construction Industry: Getting Experts in the Loop Thanks to Machine Learning — Mirza Muntasir Nishat, Nils O.E. Olsson, et al. · Safety (2025) | TGRS Research Map | TGRS