AI and ML-based Assessment to Reduce Risk in Oil and Gas Retail Filling Station: A Literature Review

Abstract

The oil crisis in recent years has pressurized petrol stations and associated service providers to improve efficiency and effectiveness. The accidents caused by human error and other technical incompetence lead to fatalities and environmental pollution. This paper analyses the role of Artificial Intelligence (AI) and Machine Learning (ML) in reducing the risk by various factors at retail oil and gas filling stations. The use of technology can help retail outlets in the oil and gas industry to reduce risks. This survey explores how to reduce workplace hazards at oil and gas filling stations to reduce fatalities, injuries, and other adverse health outcomes, which may be due to inhalation of toxic fumes, fire accidents, electrostatic charges, or any other artificial or natural reasons. Moreover, this review is done on how AI and ML can be used to reduce electrostatic discharges at the nozzles along with the automated replacement of human resources in hazardous situations. Therefore, the purpose includes the exploration of AI and ML technology to enhance safety at petrol and gas stations. This paper is a literature review of the articles published at different times.