Martin C. Peter; Steve Adeshina; Olabode Idowu-Bismark; Opeyemi Osanaiye; Oluseun Oyeleke

Digital Control and Management of Water Supply Infrastructure Using Embedded Systems and Machine Learning

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Author(s)

Martin C. Peter ¹ Steve Adeshina ¹ Olabode Idowu-Bismark ^2,* Opeyemi Osanaiye ³ Oluseun Oyeleke ¹

1. Department of Computer Engineering, Nile University of Nigeria, Abuja Nigeria

2. Department of Electrical and Information Engineering, Covenant University Ota, Nigeria

3. Department of Mechatronics Engineering, Nile University of Nigeria, Abuja Nigeria

* Corresponding author.

DOI: https://doi.org/10.5815/ijisa.2023.05.01

Received: 2 May 2023 / Revised: 24 Jul. 2023 / Accepted: 11 Aug. 2023 / Published: 8 Oct. 2023

Index Terms

Water Supply Infrastructure, Water Leakage Detection, Water Supply Efficiency, Water Distribution Losses, LCU Microcontroller

Abstract

Water supply infrastructure operational efficiency has a direct impact on the quantity of portable water available to end users. It is commonplace to find water supply infrastructure in a declining operational state in rural and some urban centers in developing countries. Maintenance issues result in unabated wastage and shortage of supply to users. This work proposes a cost-effective solution to the problem of water distribution losses using a Microcontroller-based digital control method and Machine Learning (ML) to forecast and manage portable water production and system maintenance. A fundamental concept of hydrostatic pressure equilibrium was used for the detection and control of leakages from pipeline segments. The results obtained from the analysis of collated data show a linear direct relationship between water distribution loss and production quantity; an inverse relationship between Mean Time Between Failure (MTBF) and yearly failure rates, which are the key problem factors affecting water supply efficiency and availability. Results from the prototype system test show water supply efficiency of 99% as distribution loss was reduced to 1% due to Line Control Unit (LCU) installed on the prototype pipeline. Hydrostatic pressure equilibrium being used as the logic criteria for leak detection and control indeed proved potent for significant efficiency improvement in the water supply infrastructure.

Cite This Paper

Martin C. Peter, Steve Adeshina, Olabode Idowu-Bismark, Opeyemi Osanaiye, Oluseun Oyeleke, "Digital Control and Management of Water Supply Infrastructure Using Embedded Systems and Machine Learning", International Journal of Intelligent Systems and Applications(IJISA), Vol.15, No.5, pp.1-11, 2023. DOI:10.5815/ijisa.2023.05.01

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International Journal of Intelligent Systems and Applications (IJISA)