A Review on Current Technologies and Future Direction of Water Leakage Detection in Water Distribution Network

Abstract

Water leakage in the supply system is a silent problem that costs billions of dollars yearly. As these supply pipes are mostly underground, this leakage remains undetected for a long time. In 2019, Liemberger and Wyatt estimated an annual loss of thirty-nine billion dollars due to water leakage in the supply pipe. In this systematic review, we have analyzed forty-seven articles about water leakage detection and location research. The aim is to find the new technology, trends, and possible direction in this research field. We have derived four research questions. The first question was about how the research evolved over time, and we have observed that researchers focus more on experimental data collection, ML algorithms, and IoT technology. The second question was about the sensor the researcher was using. The most popular sensors researchers have used are: vibration, acoustic, and flow sensors, as they are cheap and easy to install. We can also see some novel applications of image and optical fiber sensors. The third question was about the trend in the algorithm. ML and threshold-based algorithms are dominating the field. The fourth question was about the communication technology trend, and WIFI, cellular IoT, and LoRa technology are leading the space capturing 80% of the research.

Recent Developments of Subsurface Small-Leak Detection Techniques in Water Distribution Networks: A Review

“…It is, therefore especially important to understand how effective existing detection technologies are at detecting small hidden leaks. Existing leakage detection techniques have already been covered by many extensive reviews [9], [10], [11], [12], [13]. Yet, there exists limited literature on the effectiveness of different detection techniques on smaller leaks.…”

Machine Learning Model for Leak Detection Using Water Pipeline Vibration Sensor

“…Water leakage in the supply system is a silent problem that costs billions of dollars yearly. This paper is a systematic review of forty-seven articles on water leakage detection and location research, with the aim of identifying new technology, trends, and possible future directions in the field [25]. Shen et al present a study on a tree-based machine learning method for pipeline leakage detection in water distribution systems, where the authors develop and compare three machine-learning-based models using on-site leak detection signals; they find that the AdaBoost model had the lowest false positive rate, and the recall rates of the random forest and AdaBoost models were 100% and 99.52%, respectively [26].…”

Analysis of Acoustic Signal Propagation for Reliable Digital Communication along Exposed and Buried Water Pipes

“…Water pipes, like any other civil infrastructure, are prone to deterioration and failures which compromise their ability to provide regular service to a community. Among the plethora of pipe monitoring techniques currently available across the utility industry (e.g., [1][2][3][4][5]), wireless sensor networks (WSN) have emerged as a robust and cost-effective solution for real-time condition monitoring of buried water pipes [6][7][8]. This is largely due to the small power availability (in the order of 1 watt/hour), low cost (tens of UK pounds (GBP) at most) and small size (centimetre scale) of wireless underground sensor nodes, which facilitate long-term operation for pipeline monitoring operations [9][10][11][12].…”