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DALIAN UNIVERSITY OF TECHNOLOGY Login 中文
张明媛

Associate Professor
Supervisor of Doctorate Candidates
Supervisor of Master's Candidates


Title : 建设管理系 系主任
Gender:Female
Alma Mater:Dalian University of Technology
Degree:Doctoral Degree
School/Department:Department of Construction Management
Discipline:Project Management
Business Address:综合实验4号楼509室
E-Mail:myzhang@dlut.edu.cn
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Current position: Home >> Scientific Research >> Paper Publications

Utilizing Computer Vision and Fuzzy Inference to Evaluate Level of Collision Safety for Workers and Equipment in a Dynamic Environment

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Indexed by:Journal Papers

Date of Publication:2020-06-01

Journal:JOURNAL OF CONSTRUCTION ENGINEERING AND MANAGEMENT

Included Journals:SCIE、CPCI-S

Volume:146

Issue:6

ISSN No.:0733-9364

Key Words:Safety management; Collision accident; Construction worker; Computer vision; Fuzzy inference

Abstract:The construction industry is facing unique problems in accident prevention. The existing management method for detecting workers' unsafe behaviors and unsafe states of objects relies primarily on manual monitoring, which does not only consume large amounts of time and money but also cannot cover all workers in the entire construction site. Meanwhile, the workers' perception of being at risk of injury decreases when they are concentrated in a crowded and noisy environment. In this case, it is difficult for them to take essential measures to protect themselves in the face of danger. In view of the aforementioned issues, this study proposes a method of evaluating the collision safety level of construction workers based on computer vision and fuzzy inference. Specifically, the proposed model works via two modules: vision extraction and safety assessment. The vision extraction module identifies construction workers and equipment through computer vision; centroid pixel coordinates and crowdedness are then extracted from a detection box. Afterward, the spatial relationship between moving devices and workers is calculated by a pixel calibration process. In the safety assessment module, the collected status information is analyzed by evaluating the safety level of each worker and conducting accident prevention through a fuzzy inference system. The safety level, which indicates the comprehensive risk of collision between workers and equipment in a particular dynamic environment, will be displayed numerically, breaking through the limitations of conventional qualitative evaluation. Field experiments validate the feasibility of the proposed method of informing workers about potential danger situations in an objective way. Moreover, by setting a safety-level threshold, the onsite safety management personnel can take corresponding measures to avoid collision accidents when the worker's safety level is lower than the threshold.