Abstract
This study addresses construction safety by deploying computer vision techniques, specifically a YOLOv8 model by Ultralytics, to monitor PPE compliance. Targeting helmets, vests, and safety shoes, it aims to mitigate accident risks. The model was trained with 2934 images and validated with 816, achieved a 95% mAP. Emphasizing AI's potential in safety management and occupational health in the construction industry. This research lays groundwork for future AI-based safety enhancements in construction sector, highlighting the industry's pressing need for innovative approaches to reduce occupational hazards and improve compliance standards.
| Originalsprog | Engelsk |
|---|---|
| Titel | Proceedings of the 2024 European Conference on Computing in Construction |
| Redaktører | Marijana Srećković, Mohamad Kassem, Ranjith Soman, Athanasios Chassiakos |
| Antal sider | 8 |
| Forlag | European Council on Computing in Construction |
| Publikationsdato | 2024 |
| Sider | 577-584 |
| ISBN (Elektronisk) | 978-9-083451-30-5 |
| DOI | |
| Status | Udgivet - 2024 |
| Begivenhed | 2024 European Conference on Computing in Construction - Chania, Grækenland Varighed: 14 jul. 2024 → 17 jul. 2024 https://ec-3.org/conference2024/ |
Konference
| Konference | 2024 European Conference on Computing in Construction |
|---|---|
| Land/Område | Grækenland |
| By | Chania |
| Periode | 14/07/2024 → 17/07/2024 |
| Internetadresse |
| Navn | European Conference on Computing in Construction |
|---|---|
| ISSN | 2684-1150 |