Advances in Internet of Things

Volume 14, Issue 2 (April 2024)

ISSN Print: 2161-6817   ISSN Online: 2161-6825

Google-based Impact Factor: 2.8  Citations  

Development of a Low-Cost Prototype System for Pipeline Operational and Vandalism Spillage Detection and Validation Framework

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DOI: 10.4236/ait.2024.142002    44 Downloads   141 Views  

ABSTRACT

Crude oil spillage is a major challenge in Nigeria. It affects the environment, health, life, and livelihood of residents of the Niger Delta region, where oil is explored, processed, and transported via a network of pipelines. Oil spillage is primarily caused by vandalization/sabotage and operational issues such as corrosion, equipment failure, operation, and maintenance errors. Thus, prompt response is required to mitigate the impact of oil spills. In this study, we deployed low-cost Arduino systems, including sensors (vibration and flow), modules (GPS and Wifi) and an IoT platform (ThingSpeak) to detect spillage caused by vandalism and operational inefficiencies proactively. The results demonstrate that low-cost sensors can detect changes in the flow volume between the inflow and outflow attributable to spillage, and vibration shocks caused by vandalism can be detected and linked to the cause of the spillage and communicated in real time to inform response action. Moreover, we proposed a framework for field validation utilizing KoboToolBox (a crowdsourcing/citizen science platform). The prototype system designed and programmed showed promising results, as it could detect spillage for vandalism and operational scenarios in real-time, quantify the volume of spillage, and identify the location and time of spillage occurrence; indicators relevant for response planning to minimize the impact of oil spillage. A video demonstration of the prototype system developed is accessible via: https://youtu.be/wKa9MZvYf1w.

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Ekeu-Wei, B. and Ekeu-Wei, I. (2024) Development of a Low-Cost Prototype System for Pipeline Operational and Vandalism Spillage Detection and Validation Framework. Advances in Internet of Things, 14, 21-35. doi: 10.4236/ait.2024.142002.

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