How a Low-Voltage Current Is Exposing Hidden Water Loss

Electro Scan's TRIDENT platform combines ERT, CCTV, and AI to pinpoint leaks inside live US water mains with unprecedented precision

8 Apr 2026

Water is disappearing beneath Cleveland's streets. Not dramatically, but steadily, through ageing joints and hairline cracks in pressurised mains that conventional cameras and acoustic probes have failed to find. A recent inspection of a 30-inch transmission main running under a railway corridor illustrates the scale of what utilities are missing, and what a new generation of sensor technology may at last be able to locate.

Electro Scan's TRIDENT platform works by sending a low-voltage electrical current through water flowing inside a live pipe. Where water escapes through a joint or fracture, the current follows. The resulting signal pinpoints each defect's location and estimates its flow loss in gallons per minute. Only then does a camera intervene, pausing at sites already flagged by the electrical scan. AI algorithms track particles suspended in the water column, confirming exactly where losses occur. The approach reverses conventional practice: instead of using cameras to search and acoustics to guess, it uses electrical data to locate and cameras to verify.

In Cleveland, the method found dozens of joint defects that standard CCTV had entirely overlooked. In one stretch of pipe, the camera recorded nothing unusual; electrical resistance data showed water escaping. A defect near a bridge abutment corresponded to a surface leak that engineers had previously observed but not traced to source. The sensor readings and field evidence matched.

The commercial logic is straightforward. Exploratory excavation is expensive, and acoustic surveys regularly send crews to dry holes. A system that narrows the search to confirmed leak sites reduces both cost and disruption. The regulatory logic is equally clear: the American Water Works Association has called for accurate, repeatable data to underpin water-loss control programmes, and utilities are under growing pressure to reduce non-revenue water.

Whether multi-sensor AI inspection can scale from showcase projects to routine practice remains the harder question. Procurement cycles at public utilities are slow. The upfront cost of more sophisticated surveys is real, even if downstream savings are substantial. And the technology's value depends on what utilities do with the data once they have it: finding a leak is only useful if fixing it follows. The pipes beneath Cleveland are talking. The question is whether anyone is listening fast enough.