Predicting movements of onsite workers and mobile equipment for enhancing construction site safety
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...
| Main Authors: | , , , , , |
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| Format: | Article |
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Elsevier
2016
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| Online Access: | https://eprints.nottingham.ac.uk/33604/ |
| _version_ | 1848794665806987264 |
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| author | Zhu, Zhenhua Park, Man-Woo Koch, Christian Soltani, Mohamad Hammad, Amin Davari, Khashayar |
| author_facet | Zhu, Zhenhua Park, Man-Woo Koch, Christian Soltani, Mohamad Hammad, Amin Davari, Khashayar |
| author_sort | Zhu, Zhenhua |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | 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. |
| first_indexed | 2025-11-14T19:19:49Z |
| format | Article |
| id | nottingham-33604 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| last_indexed | 2025-11-14T19:19:49Z |
| publishDate | 2016 |
| publisher | Elsevier |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-336042020-05-04T17:58:46Z https://eprints.nottingham.ac.uk/33604/ Predicting movements of onsite workers and mobile equipment for enhancing construction site safety Zhu, Zhenhua Park, Man-Woo Koch, Christian Soltani, Mohamad Hammad, Amin Davari, Khashayar 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. Elsevier 2016-08-01 Article PeerReviewed Zhu, Zhenhua, Park, Man-Woo, Koch, Christian, Soltani, Mohamad, Hammad, Amin and Davari, Khashayar (2016) Predicting movements of onsite workers and mobile equipment for enhancing construction site safety. Automation in Construction, 68 . pp. 95-101. ISSN 0926-5805 Movement prediction; Kalman filtering; construction safety http://dx.doi.org/10.1016/j.autcon.2016.04.009 doi:10.1016/j.autcon.2016.04.009 doi:10.1016/j.autcon.2016.04.009 |
| spellingShingle | Movement prediction; Kalman filtering; construction safety Zhu, Zhenhua Park, Man-Woo Koch, Christian Soltani, Mohamad Hammad, Amin Davari, Khashayar Predicting movements of onsite workers and mobile equipment for enhancing construction site safety |
| title | Predicting movements of onsite workers and mobile equipment for enhancing construction site safety |
| title_full | Predicting movements of onsite workers and mobile equipment for enhancing construction site safety |
| title_fullStr | Predicting movements of onsite workers and mobile equipment for enhancing construction site safety |
| title_full_unstemmed | Predicting movements of onsite workers and mobile equipment for enhancing construction site safety |
| title_short | Predicting movements of onsite workers and mobile equipment for enhancing construction site safety |
| title_sort | predicting movements of onsite workers and mobile equipment for enhancing construction site safety |
| topic | Movement prediction; Kalman filtering; construction safety |
| url | https://eprints.nottingham.ac.uk/33604/ https://eprints.nottingham.ac.uk/33604/ https://eprints.nottingham.ac.uk/33604/ |