Abstract

The concern for workers' safety in construction industry is reflected in many studies focusing on static safety risk identification and assessment. However, studies on real-time safety risk assessment aimed at reducing uncertainty and supporting quick response are rare. A method for real-time safety risk assessment (RTSRA) to implement a dynamic evaluation of worker safety states on construction site has been proposed in this paper. The method provides construction managers who are in charge of safety with more abundant information to reduce the uncertainty of the site. A quantitative calculation formula, integrating the influence of static and dynamic hazards and that of safety supervisors, is established to link the safety risk of workers with the locations of on-site assets. By employing the hidden Markov model (HMM), the RTSRA provides a mechanism for processing location data provided by the real-time location system (RTLS) and analyzing the probability distributions of different states in terms of false positives and negatives. Simulation analysis demonstrated the logic of the proposed method and how it works. Application case shows that the proposed RTSRA is both feasible and effective in managing construction project safety concerns.

Highlights

  • The construction industry is one of the most dangerous industrial sectors worldwide [1, 2]

  • The safety risk associated with the dynamic hazard was first calculated, based on an observation symbol sequence representing the relative positions of workers and the crane. 20 samples were collected using the real-time location system (RTLS) and processed by the server

  • The hidden Markov model (HMM) parameters λDY, λST, and λRF used in this calculation were the same as those of the simulation in Section 3 as well as the safety state sets and the observation symbol sets

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Summary

Introduction

The construction industry is one of the most dangerous industrial sectors worldwide [1, 2]. Azadeh et al [25] developed a fuzzy expert system for performance assessment of health, safety, environment, and ergonomic system factors in a gas refinery with the objectives of the reduction of human error, creation of expert knowledge, and interpretation of large amounts of vague data These quantitative methods based on probability and fuzzy sets theory offer relatively accurate evaluation results compared to those of the traditional methods and have been implemented in practical projects. None of the above methods have been able to adapt to the dynamic context of construction projects, those complex activities which contribute greatly to the safety risk of on-site workers Such methods cannot provide real-time information about safety states, which is a necessity to enable timely response and rescue.

Risk Assessment Framework of RTSRA
Simulation Analysis
On-Site Application
Conclusions
Full Text
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