A Lab-Scale Prototype: Determining the Pipeline Networks Leakage Point Using Fuzzy Logic and IoT

Ching Yee Yong () and Johnathan Anak Empawi
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Ching Yee Yong: University of Technology Sarawak, Centre for Research of Innovation & Sustainable Development, School of Engineering and Technology
Johnathan Anak Empawi: University of Technology Sarawak, Centre for Research of Innovation & Sustainable Development, School of Engineering and Technology

A chapter in Generative AI and Optimization Techniques for Sustainable Water Management, 2026, pp 61-77 from Springer

Abstract: Abstract Water is delivered to residential, commercial, industrial, and other water consumption areas through water supply systems. However, leakage is becoming increasingly severe and worrisome. To address this serious leakage problem, this study proposes an efficient, simple, and low-cost pipe leak detection system. The system includes sensing units, such as water flow sensors and total dissolved solids (TDS) sensors. Existing water supply monitoring systems are expensive to maintain and require substantial manpower for leak detection, making them inconvenient to use. The main objective of this study is to design and build a reliable, low-cost pipe leak detection system that uses fuzzy logic in the Arduino IDE to communicate with the control unit and is equipped with an alarm system that sends a leak warning to the user via the SIM900A GSM module. The system’s pipe network covers an area of 1.5 m × 1.5 m, and leaks are detected at distances of 0.5 m, 1 m, and 1.5 m in the horizontal and vertical directions. The results indicate that the water flow rate measured with the water flow sensor ranges from 1 to 3 L per minute. If the flow rate is below 1 L per minute, the system detects the leak and sends a notification to the user. In short, the proposed leak detection system is more efficient than existing methods, including acoustic systems, ground-penetrating radar (GPR), pressure measurements, fiber-optic monitoring, and imaging-based systems. Leak detection is achieved through a graphical user interface (GUI) on a mobile phone or computer. The system is simple, reliable, low cost, safe, and environmentally friendly.

Date: 2026
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DOI: 10.1007/978-3-032-19012-3_5

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