IoT-Based Detection and Early Warning System for Acid Leaking in Underground Pipeline

Leaks in pipelines caused by acid are destructive to both economic growth and capital which should be avoided at all costs. Damage to underground pipelines is caused by a hard-to-find leak, the unavailability of a real-time monitoring system and the lack of a pipeline history database. The aim of th...

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Bibliographic Details
Published in:TEM Journal
Main Author: Hairuddin M.A.; Nazri M.F.; Saaid M.F.
Format: Article
Language:English
Published: UIKTEN - Association for Information Communication Technology Education and Science 2022
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85143788731&doi=10.18421%2fTEM114-31&partnerID=40&md5=18cc6889ef3b87c09bd6e854de691371
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Summary:Leaks in pipelines caused by acid are destructive to both economic growth and capital which should be avoided at all costs. Damage to underground pipelines is caused by a hard-to-find leak, the unavailability of a real-time monitoring system and the lack of a pipeline history database. The aim of this work is to develop an early warning system to detect acid leaking in the pipeline using Internet of Things (IoT) technology. To detect changes in the pH of acid soil parameters near the pipeline, two mechanisms are required: first, to provide an early warning before the leak is detected and second, to report the occurrence of the leak. The notification system is equipped with three LED indicators, each showing the offline, online and signal detection status. The novelty of the work is a prototype that can detect the acid leak in the pipeline and record the pH values in a database for future research. Using continuous pH monitoring, real-time analysis and a database, this system can detect leaks before they become a major problem. Consequently, the manufacturing industry will benefit from this initiative as it is automated, efficient and cost-effective. © 2022 Army Justitia et al; published by UIKTEN. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 License. The article is published with Open Access at https://www.temjournal.com/
ISSN:22178309
DOI:10.18421/TEM114-31