OGAR: Augmented Reality Application for Assisting Workers in the Oil and Gas Industry

This paper presents the design and implementation of a mobile augmented reality application, OGAR, to assist workers in the oil and gas industry. The application integrates GPS navigation and QR code scanning to provide instant access to vital information, improving productivity and safety. OGAR enhances the maintenance tasks by context-ware, on demand information through an intuitive user interface. The application was tested in a real-life setting with 14 participants. A paper-based questionnaire developed using Technology Acceptance Model (TAM) frame was used to get their perception on application's effectiveness. The results showed positive reception, indicating the application’s relevance and ease of use. The study highlights the potential of AR technologies in transforming workflows and identifies areas for future improvement.

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Publication Details

Published
2024-12-30
DOI
https://doi.org/10.1109/inmic64792.2024.11004414
Primary Topic
Reservoir Engineering and Simulation Methods
Type
article
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OGAR: Augmented Reality Application for Assisting Workers in the Oil and Gas Industry

A. Alhendi, Muhammad Nadeem, Fahad Alsubaiei, Khalifa Alkhalifa et al.
Reservoir Engineering and Simulation Methods
article

OGAR: Augmented Reality Application for Assisting Workers in the Oil and Gas Industry

A. Alhendi, Muhammad Nadeem, Fahad Alsubaiei, Khalifa Alkhalifa, Shaheen Alsharaf, Abdulaziz Alfoudari
article en

Abstract

This paper presents the design and implementation of a mobile augmented reality application, OGAR, to assist workers in the oil and gas industry. The application integrates GPS navigation and QR code scanning to provide instant access to vital information, improving productivity and safety. OGAR enhances the maintenance tasks by context-ware, on demand information through an intuitive user interface. The application was tested in a real-life setting with 14 participants. A paper-based questionnaire developed using Technology Acceptance Model (TAM) frame was used to get their perception on application's effectiveness. The results showed positive reception, indicating the application’s relevance and ease of use. The study highlights the potential of AR technologies in transforming workflows and identifies areas for future improvement.

American University of the Middle East (KW)
Decent work and economic growth
Openalex Percentile: Top 62%
Reservoir Engineering and Simulation Methods
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