Advancing Oilfield Safety: A Computer Vision Approach to Line of Fire Risk Detection

Abstract In industrial environments, the movement of heavy equipment poses significant risks to personnel. This paper presents a Line of Fire (LoF) Detection system that leverages real-time video feeds, object detection, and motion tracking to identify and alert when individuals are in the path of moving equipment, specifically pipes. The system utilizes advanced machine learning models for person detection and pipe segmentation, combined with a robust alert mechanism, to enhance safety measures.

Authors

Publication Details

Journal
SPE Annual Technical Conference and Exhibition
Published
2024-09-20
DOI
https://doi.org/10.2118/221066-ms
Primary Topic
Fire Detection and Safety Systems
Type
article
Field-Weighted Citation Impact
0.00
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article

Advancing Oilfield Safety: A Computer Vision Approach to Line of Fire Risk Detection

D. Radha Krishna, Vignesh Santhalingam, Antonio Abinader, T.J.G.M. Lam et al.
SPE Annual Technical Conference and Exhibition
Fire Detection and Safety Systems
article

Advancing Oilfield Safety: A Computer Vision Approach to Line of Fire Risk Detection

D. Radha Krishna, Vignesh Santhalingam, Antonio Abinader, T.J.G.M. Lam, Velizar Vesselinov
article en

Abstract

Abstract In industrial environments, the movement of heavy equipment poses significant risks to personnel. This paper presents a Line of Fire (LoF) Detection system that leverages real-time video feeds, object detection, and motion tracking to identify and alert when individuals are in the path of moving equipment, specifically pipes. The system utilizes advanced machine learning models for person detection and pipe segmentation, combined with a robust alert mechanism, to enhance safety measures.

SPE Annual Technical Conference and Exhibition
Openalex Percentile: Top 53%
Fire Detection and Safety Systems
DOISourceOpenAlex
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Advancing Oilfield Safety: A Computer Vision Approach to Line of Fire Risk Detection — D. Radha Krishna, Vignesh Santhalingam, et al. · SPE Annual Technical Conference and Exhibition (2024) | TGRS Research Map | TGRS