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.

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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

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article

An Improvement Safety Management Method for Welding Operations Based on Gaze Estimation and Object Detection

Dong Jia, Ying Liang, Yi Tan
Kalpa publications in computing
Occupational Health and Safety Research
article

An Improvement Safety Management Method for Welding Operations Based on Gaze Estimation and Object Detection

Dong Jia, Ying Liang, Yi Tan
article en

Abstract

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.

Kalpa publications in computingVol. 22
National Natural Science Foundation of China
Openalex Percentile: Top 68%
Occupational Health and Safety Research
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