AR-Facilitated Safety Inspection and Fall Hazard Detection on Construction Sites

• URL: http://arxiv.org/abs/2412.01273v1
• Date: Mon, 02 Dec 2024 08:38:43 GMT
• Title: AR-Facilitated Safety Inspection and Fall Hazard Detection on Construction Sites
• Authors: Jiazhou Liu, Aravinda S. Rao, Fucai Ke, Tim Dwyer, Benjamin Tag, Pari Delir Haghighi,
• Abstract summary: 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.
• Score: 17.943278018516416
• License:
• Abstract: 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.

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