@inproceedings{034cb38447a0445e823b536523d0b430,
title = "Threshold-based approach to detect near-miss falls of iron workers using inertial measurement units",
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.",
author = "K. Yang and H. Jebelli and Changbum Ahn and Vuran, {M. C.}",
year = "2015",
doi = "10.1061/9780784479247.019",
language = "English (US)",
series = "Congress on Computing in Civil Engineering, Proceedings",
publisher = "American Society of Civil Engineers (ASCE)",
number = "January",
pages = "148--155",
editor = "O'Brien, {William J.} and Simone Ponticelli",
booktitle = "Computing in Civil Engineering 2015 - Proceedings of the 2015 International Workshop on Computing in Civil Engineering",
edition = "January",
note = "2015 ASCE International Workshop on Computing in Civil Engineering, IWCCE 2015 ; Conference date: 21-06-2015 Through 23-06-2015",
}