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

TL;DR

This paper explores using head-mounted augmented reality combined with machine learning to improve safety inspections and fall hazard detection on high-rise construction sites, aiming to enhance worker safety and inspection efficiency.

Contribution

It introduces a novel approach integrating AR and machine learning for automated safety inspection and gap detection in construction site perimeter safety screens.

Findings

Initial progress in detecting safety screen gaps

Identification of privacy concerns and mitigation strategies

Potential for automated inspection reporting

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.