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Threshold-based approach to detect near-miss falls of iron workers using inertial measurement units
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Web of Science
Cited 33 time in Scopus
- Authors
- Issue Date
- 2015
- Citation
- Congress on Computing in Civil Engineering, Proceedings, Vol.2015-January No.January, pp.148-155
- Abstract
- Falls are the single most dangerous safety accident within the construction industry, representing 33% of all fatalities in construction. Numerous unrecognized near-miss falls exist behind every major fall accident. The detection of near-miss fall occurrence therefore helps the identification of fall-prone workers/tasks and invisible jobsite hazards and thereby can prevent fall accidents. This paper presents and evaluates the feasibility of a threshold-based approach for detecting the near-miss falls of construction iron-worker. Kinematic data of subjects are collected through an IMU sensor attached to the subjects' sacrum; the subjects then perform walking on a steel beam structure. Fall-related features - sum vector magnitude (SVM), and normalized signal magnitude area (SMA) - are used to detect near-miss falls. Threshold values of these features are defined to achieve the best accuracy in near-miss fall detection based upon experiment data. According to selected threshold values, iron-workers' near-miss falls were detected. The result of this research demonstrate the opportunity of utilizing SVM and SMA in documenting workers' near-miss fall incidents in real-time.
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Related Researcher
- College of Engineering
- Department of Architecture & Architectural Engineering
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