West zone Maynilad Water Services, Inc. is now utilizing artificial intelligence (AI) to identify areas in its water distribution system with high likelihood of leaks to detect pipe leaks more quickly and efficiently.
“Through this advanced AI technology, we can proactively identify and address potential leaks in our water distribution system,” said Maynilad chief operations officer Randolph Estrellado on Wednesday.
“This not only enables us to respond more swiftly and efficiently to pipe network issues, (but) it also significantly enhances our ability to conserve water resources and improve service reliability for our customers,” he added.
The AI program is called Infrawise, which is owned and developed by Portugal-based AGS (Administração e Gestão de Sistemas de Salubridade), a wholly owned subsidiary of Marubeni Corporation.
Infrawise is an AI decision-making software that analyzes and identifies critical areas in the pipe network where Maynilad should focus its leak detection and pipe replacement activities.
The water firm started testing the technology application in October 2023 over an area covering 1,700 kilometers of water pipelines.
The AI software produced a map that identified vulnerabilities in over 750 kilometers of these pipelines, which later resulted in the positive identification of 1,525 leaks.
After the successful pilot run, Maynilad is expanding the monitoring coverage of Infrawise to another 1,500 kilometers of pipelines.
Apart from monitoring and assessing pipe condition, Maynilad also uses AI technology to detect underground pipe leaks.
Maynilad tapped the technology of satellite-based infrastructure intelligence company Asterra, particularly its patented algorithms that track the spectral signature of potable water underground captured in a satellite image.
Estrellado said the decision to integrate AI in their operations was driven by the need to maintain efficiency and accelerate the reduction of water losses.
The water company is still exploring other advanced technological solutions that have the potential to augment its existing equipment and capability on leak detection.
