AR-Facilitated Safety Inspection and Fall Hazard Detection on Construction Sites
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arXiv
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| Auteurs principaux: | , , , , , |
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| Format: | Preprint |
| Publié: |
2024
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| _version_ | 1866916502763995136 |
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| author | Liu, Jiazhou Rao, Aravinda S. Ke, Fucai Dwyer, Tim Tag, Benjamin Haghighi, Pari Delir |
| author_facet | Liu, Jiazhou Rao, Aravinda S. Ke, Fucai Dwyer, Tim Tag, Benjamin Haghighi, Pari Delir |
| contents | Together with industry experts, we are exploring the potential of head-mounted augmented reality to facilitate safety inspections on high-rise construction sites. A particular concern in the industry is inspecting perimeter safety screens on higher levels of construction sites, intended to prevent falls of people and objects. We aim to support workers performing this inspection task by tracking which parts of the safety screens have been inspected. We use machine learning to automatically detect gaps in the perimeter screens that require closer inspection and remediation and to automate reporting. This work-in-progress paper describes the problem, our early progress, concerns around worker privacy, and the possibilities to mitigate these. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2412_01273 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | AR-Facilitated Safety Inspection and Fall Hazard Detection on Construction Sites Liu, Jiazhou Rao, Aravinda S. Ke, Fucai Dwyer, Tim Tag, Benjamin Haghighi, Pari Delir Human-Computer Interaction Computer Vision and Pattern Recognition Together with industry experts, we are exploring the potential of head-mounted augmented reality to facilitate safety inspections on high-rise construction sites. A particular concern in the industry is inspecting perimeter safety screens on higher levels of construction sites, intended to prevent falls of people and objects. We aim to support workers performing this inspection task by tracking which parts of the safety screens have been inspected. We use machine learning to automatically detect gaps in the perimeter screens that require closer inspection and remediation and to automate reporting. This work-in-progress paper describes the problem, our early progress, concerns around worker privacy, and the possibilities to mitigate these. |
| title | AR-Facilitated Safety Inspection and Fall Hazard Detection on Construction Sites |
| topic | Human-Computer Interaction Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2412.01273 |