Predicting movements of onsite workers and mobile equipment for enhancing construction site safety

被引：97

作者：

Zhu, Zhenhua ^{[1
]}

Park, Man-Woo ^{[2
]}

Koch, Christian ^{[3
]}

Soltani, Mohamad ^{[1
]}

Hammad, Amin ^{[4
]}

Davari, Khashayar ^{[1
]}

机构：

[1] Concordia Univ, Dept Bldg Civil & Environm Engn, Montreal, PQ H3G 1M8, Canada

[2] Myongii Univ, Dept Civil & Environm Engn, Yongin 449728, Gyeonggi Do, South Korea

[3] Univ Nottingham, Dept Civil Engn, Room B27 Coates Bldg,Univ Pk, Nottingham NG7 2RD, England

[4] Concordia Univ, CIISE, Montreal, PQ H3G 1M8, Canada

来源：

AUTOMATION IN CONSTRUCTION | 2016年 / 68卷

关键词：

Movement prediction; Kalman filtering; Construction safety; DATA-COLLECTION; TECHNOLOGY; MANAGEMENT; SYSTEM;

D O I：

10.1016/j.autcon.2016.04.009

中图分类号：

TU [建筑科学];

学科分类号：

0813 ;

摘要：

Tens of thousands of time-loss injuries and deaths are annually reported from the construction sector, and a high percentage of them are due to the workers being struck by mobile equipment on sites. In order to address this site safety issue, it is necessary to provide proactive warning systems. One critical part in such systems is to locate the current positions of onsite workers and mobile equipment and also predict their future positions to prevent immediate collisions. This paper proposes novel Kalman filters for predicting the movements of the workers and mobile equipment on the construction sites. The filters take the positions of the equipment and workers estimated from multiple video cameras as input and output the corresponding predictions on their future positions. Moreover, the filters could adjust their predictions based on the worker or equipment's previous movements. The effectiveness of the filters has-been tested with real site videos and the results show the high prediction accuracy of the filters. (C) 2016 Elsevier B.V. All rights reserved.

引用

页码：95 / 101

页数：7