Automated non-PPE detection on construction sites using YOLOv10 and transformer architectures for surveillance and body worn cameras with benchmark datasets

Automated non-PPE detection on construction sites using YOLOv10 and transformer architectures for surveillance and body worn cameras with benchmark datasets

Abstract Ensuring proper Personal Protective Equipment (PPE) compliance is crucial for maintaining worker safety and reducing accident risks on construction sites. Previous research has explored various object detection methodologies for automated monitoring of non-PPE compliance; however, achieving...

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Bibliographic Details
Main Author: Seunghyeon Wang
Format: Article
Language:English
Published: Nature Portfolio 2025-07-01
Series:Scientific Reports
Subjects:
Personal protective equipment monitoring
Construction management
Computer vision
Deep learning
YOLOv10
Transformer architectures
Online Access:https://doi.org/10.1038/s41598-025-12468-8
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https://doi.org/10.1038/s41598-025-12468-8

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