An Improvement Safety Management Method for Welding Operations Based on Gaze Estimation and Object Detection
In the field of construction engineering, particularly in steel structure construction, welding operations are of great importance. However, this activity carries significant safety risks, such as severe accidents like eye burns. Therefore, safety management and protective measures for these high-risk activities are especially crucial. Although computer vision-based object detection algorithms have already been applied in the construction sector, these algorithms generally lack the capability to process high-level semantic information. They can only detect objects, but cannot understand the state of the objects. To address this issue, this paper proposes an improved welding safety inspection method based on gaze estimation and object detection. First, from a human-machine interaction perspective, the method combines gaze estimation and object detection to determine the worker's operational status. Second, it performs real-time checks on the personal protective equipment (PPE) used by the welders. Experiments demonstrate the feasibility of this approach, enhancing its ability to respond to complex scenarios and contributing to improved safety levels in construction projects.
Authors
- Dong Jia
- Ying Liang (ORCID: https://orcid.org/0009-0008-4713-0773)
- Yi Tan (ORCID: https://orcid.org/0009-0006-3472-5028)
Publication Details
- Journal
- Kalpa publications in computing
- Published
- 2025-08-28
- DOI
- https://doi.org/10.29007/k9k5
- Primary Topic
- Occupational Health and Safety Research
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China