title: Real-time safety risk assessment based on a real-time location system for hydropower construction sites.
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.
authors.affiliation: State Key Laboratory of Hydroscience and Engineering, Tsinghua University, Haidian, Beijing 100084, China.
authors.forename: Hanchen
authors.identifier: 0000-0003-2884-3790
authors.initials: H
authors.lastname: Jiang
authors.affiliation: State Key Laboratory of Hydroscience and Engineering, Tsinghua University, Haidian, Beijing 100084, China.
authors.forename: Peng
authors.identifier: 0000-0003-1338-2514
authors.initials: P
authors.lastname: Lin
authors.affiliation: China Yangtze Three Gorges Group Corporation, Beijing 100038, China.
authors.forename: Qixiang
authors.initials: Q
authors.lastname: Fan
authors.affiliation: State Key Laboratory of Hydroscience and Engineering, Tsinghua University, Haidian, Beijing 100084, China.
authors.forename: Maoshan
authors.initials: M
authors.lastname: Qiang
mesh_terms: D060389:Construction Industry; D011211:Electric Power Supplies; D006801:Humans; D008962:Models, Theoretical; D018570:Risk Assessment