Acoustic leak detection using IoT sensors is a cost-effective solution to detect emerging leaks in water distribution networks. The acoustic system identifies and pin-points leakage events with high sensitivity, but it also detects non-leakage events which may overload the utility with data.
In collaboration with the University of Waterloo, and supported by the Southern Ontario Water Consortium, an Echologics team used machine learning techniques to narrow reported events to only the most relevant data visible to the water utility. To learn how machine learning supports pipe monitoring and asset management, click here to access the white paper on ensemble-based machine learning for improved leak detection in water mains.
Editor's Note: Scranton Gillette Communications and the SGC Water Group are not liable for the accuracy, efficacy and validity of the claims made in this piece. The views expressed in this content do not reflect the position of the editorial teams of Water & Wastes Digest, Water Quality Products and Storm Water Solutions.