Exploring the Gains of Artificial Intelligence for Addressing the Menance of Pipeline Vandalization in Nigeria: A Review

Abstract

Abstract Pipeline transport is a commonly utilised method for moving petroleum products from one location to another. It is considered as one of the safest, fastest, and most reliable options for transporting petroleum products. However, the use of pipelines for oil transport is associated with the risk of pipeline failure, a challenge caused by a range of factors including corrosion, ignition of natural gas, accidental damage during excavation work, lapses in maintenance as well as vandalization. Most prevalent in Nigeria is the menace of pipeline vandalization and oil thefts which is a critical factor responsible for most pipeline failures across the country. Varied efforts aimed at addressing the problem of vandalization and oil thefts in Nigeria have, over the years, yielded minimal benefits. Therefore, this review investigates the usefulness and suitability of artificial intelligence (AI) for securing Nigeria’s pipeline network. The review focuses on summarizing available evidence on the use of some relevant AI components such as Image Analytics, Convolutional Neural Network (CNN) as well as Edge-Based AI Solutions, for securing oil pipelines. Based on the findings of case studies and other primary research materials utilized in this review, this paper concludes that while there is need for further research on the subject, AI offers a promising and useful solution to Nigeria’s endemic challenge of pipeline vandalization and oil theft. This is as AI promotes early detection of illicit activities on pipelines and can relay signals to appropriate authorities on the need for urgent action. The use of AI in securing Nigeria’s vast pipeline network will not only minimize the economic losses caused by vandalization but will equally contribute towards mitigating the adverse environmental impact of oil pipeline vandalization in Nigeria.