AI and Sensors Help Utilities Get Ahead of Water Leaks

Water utilities are using acoustic sensors and AI to spot leaks early, cut losses, and shift from emergency repairs to smarter planning

16 Jan 2026

Water utilities are beginning to shift from reactive repairs towards predictive management as they adopt acoustic sensors and data analytics to detect leaks and anticipate pipe failures.

Instead of responding after pipes burst, operators are using continuous monitoring and AI driven models to identify hidden leaks earlier and forecast where failures are most likely. The approach is gaining attention as aging networks, rising water losses and tight budgets put pressure on utilities worldwide.

Sydney illustrates how the change is taking shape. Sydney Water has worked with the University of Technology Sydney to combine advanced acoustic sensing with predictive analytics to improve leak detection and asset planning. Trials of the system have helped save close to 10,000 megalitres of drinking water by identifying leaks that would otherwise have remained undetected, according to people involved in the project.

At the centre of the programme is a predictive model developed by UTS researchers. It analyses acoustic signals alongside information on pipe age, material and operating conditions to flag areas with a higher probability of main failure. Researchers say the model can identify potential failure zones with about 80 per cent accuracy within a defined radius, giving utilities greater confidence to intervene before pipes break.

For operators, this type of foresight allows maintenance to be planned more precisely. Crews can be directed to higher risk sections of the network, reducing the likelihood of disruptive bursts and limiting water loss, road damage and service interruptions.

The strategy reflects a broader shift in the water sector. Smart water management is increasingly focused on measurable operational gains rather than experimental technology. Acoustic monitoring and predictive analytics are becoming core tools for resilience planning and capital prioritisation.

Other technologies, such as robotic pipe inspection, continue to draw interest but remain largely at pilot or research stage. For now, utilities say the most reliable improvements are coming from sensors and data driven decision making.

Obstacles remain. Predictive systems need careful calibration to avoid false alerts, and utilities must build the skills and governance needed to trust automated insights. Even so, as analytics are integrated into daily operations, predictive leak control is moving closer to standard practice across the industry.