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June 4, 2026Applied SciencesOpen Access

Improved YOLOv8-Based Real-Time Detection Method for Illegal Behaviors in Oil and Gas High-Risk Operations

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Authors

KTKun TianLZLaibin ZhangSWShunyi Wang

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Overview

Randomized trial demonstrates real-time identification of hazards in high-risk operations, indicating enhanced safety protocols.

Key Points

  • The study aims to enhance hazard recognition in high-risk operations using advanced computer vision techniques.
  • Collected 1.4 million images from high-risk petroleum sites
  • Developed 40 video recognition algorithms integrating object detection and pose estimation
  • Incorporated spatiotemporal attention mechanisms for improved accuracy on small targets.
  • Achieved an accuracy of ≥90% in detecting violation behaviors
  • Enabled intelligent identification of hazards like personnel under cranes and at heights without safety harnesses
  • Facilitated transformation in risk management from human-based to an integrated defense model.

Cite This Study

Tian et al. (2026) studied this question.

synapsesocial.com/papers/6a2117bfd499ed480b170889https://doi.org/10.3390/app16115433
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