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

Full Text (PDF, 519KB), PP.1-11

Views: 0 Downloads: 0


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.


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


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


[1]J. Alexander Saria, “Effects of Water Pipe Leaks on Water Quality and on Non-Revenue Water: Case of Arusha Municipality,” J. Water Resour. Ocean Sci., vol. 4, no. 6, p. 86, 2015, doi: 10.11648/j.wros.20150406.12.
[2]O. Pozos-Estrada, A. Sánchez-Huerta, J. A. Breña-Naranjo, and A. Pedrozo-Acuña, “Failure analysis of a water supply pumping pipeline system,” Water (Switzerland), vol. 8, no. 9, pp. 1–17, 2016, doi: 10.3390/w8090395.
[3]K. A. Porter, “Damage and Restoration of Water Supply Systems in an Earthquake Sequence,” no. July, p. 116, 2016.
[4]H. Saghi, “Effective Factors in Causing Leakage in Water Supply Systems and Urban Water Distribution Networks,” Am. J. Civ. Eng., vol. 3, no. 2, p. 60, 2015, doi: 10.11648/j.ajce.s.2015030202.22.
[5]J. Serrin, “Mathematical Principles of Classical Fluid Mechanics,” pp. 125–263, 1959, doi: 10.1007/978-3-642-45914-6_2.
[6]L. Minh Dang, M. J. Piran, D. Han, K. Min, and H. Moon, “A survey on internet of things and cloud computing for healthcare,” Electron., vol. 8, no. 7, pp. 1–49, 2019, doi: 10.3390/electronics8070768.
[7]G. Prathyusha, “Embedded Based Flow Control Using Fuzzy,” pp. 4958–4962, 2017, doi: 10.15662/IJAREEIE.2017.0606135.
[8]S. B. Nikhil Patil, “Embedded based Flow Control for Industrial Furnace Automation,” Int. J. Eng. Res. Technol., vol. 5, no. 8, pp. 298–301, 2016, [Online]. Available:
[9]U. C. Moon and K. Y. Lee, “Hybrid algorithm with fuzzy system and conventional PI control for the temperature control of TV glass furnace,” IEEE Trans. Control Syst. Technol., vol. 11, no. 4, pp. 548–554, 2003, doi: 10.1109/TCST.2003.813385.
[10]Neelshetty K, Avinash, and Jaleel, “Waste Water Treatment Using PLC and SCADA,” IRE Journals |, vol. 1, no. 11, pp. 24–27, 2018.
[11]E. Summary, “Petanu WTP,” 2013.
[12]R. N. Shashank, M. Santhosh, M. Deshpande, and V. K. M, “Low Cost Data Acquisition, Monitoring and Control for Small Scale Industries,” Int. J. Eng. Res. Technol., vol. 3, no. 5, pp. 1579–1582, 2014, [Online]. Available:
[13]M. Bakker, T. Rajewicz, H. Kien, J. H. G. Vreeburg, and L. C. Rietveld, “Advanced control of a water supply system: A case study,” Water Pract. Technol., vol. 9, no. 2, pp. 264–276, 2014, doi: 10.2166/wpt.2014.030.
[14]M. Rahbaralam, D. Modesto, J. Cardús, A. Abdollahi, and F. M. Cucchietti, “Predictive Analytics for Water Asset Management: Machine Learning and Survival Analysis,” no. July, 2020, [Online]. Available:
[15]P. Ross, K. Van Schagen, and L. Rietveld, “Design methodology to determine the water quality monitoring strategy of a surface water treatment plant in the Netherlands,” Drink. Water Eng. Sci., vol. 13, no. 1, pp. 1–13, 2020, doi: 10.5194/dwes-13-1-2020.
[16]H. I. Chaminé, M. J. Afonso, and M. Barbieri, “Advances in Urban Groundwater and Sustainable Water Resources Management and Planning: Insights for Improved Designs with Nature, Hazards, and Society,” Water (Switzerland), vol. 14, no. 20, 2022, doi: 10.3390/w14203347.
[17]R. Sood, M. Kaur, and H. Lenka, “D Esign and D Evelopment of a Utomatic,” vol. 3, no. 3, pp. 49–59, 2013.
[18]Y. Li, M. Potkonjak, and W. Wolf, “Real-time operating systems for embedded computing,” Proc. - IEEE Int. Conf. Comput. Des. VLSI Comput. Process., no. December 1998, pp. 388–392, 1997, doi: 10.1145/288548.289349.
[19]“Get smarter about the many benefits of P2P IoT Learn about P2P IoT solutions,” pp. 1–15.
[20]E. Baccelli, O. Hahm, M. Günes, M. Wählisch, and T. Schmidt, “OS for the IoT - Goals, Challenges, and Solutions,” Work. Interdiscip. sur la Sécurité Glob., pp. 1–10, 2013, [Online]. Available:
[21]M. C. Peter, S. Thomas, and J. Agajo, “Embedded Systems Application and Network in Water Utility Systems,” Proc. 2022 IEEE Niger. 4th Int. Conf. Disruptive Technol. Sustain. Dev. NIGERCON 2022, pp. 3–7, 2022, doi: 10.1109/NIGERCON54645.2022.9803143.
[22]A. Milinković, S. Milinković, and L. Lazić, “Choosing the right RTOS for IoT platform,” INFOTEH-JAHORINA Vol. 14, vol. 14, no. March 2015, p. 7, 2016.
[23]K. Brandon, “How to Pick an Orange?,” Los Angeles Times, pp. 0-MAG.18, 2005, [Online]. Available:
[24]S. R. Reddy, “Selection of RTOS for an Efficient Design of Embedded Systems,” vol. 6, no. 6, pp. 29–37, 2006.