The challenge

Thames Water has 10 million customers and a target of reducing reportable leakage by 20% between 2020 and 2025. Thames asked FIDO to help with the identification of leakage and the verification that a repair had been successful.

The FIDO AI Solution: 

A four-week trial was set up with Thames’ Leakage Strategy Team to demonstrate the value of the FIDO service.

The first step was to run the past four months’ worth of acoustic logger records through the FIDO AI algorithm and classify each point of interest (POI) as either a leak, possible leak or non-leak.

The results identified two DMAs that were of particular concern. Over a two-week period, FIDO leakage engineers accompanied two of Thames’ leakage detection service providers, Hydrosave and RPS, to visit as many POIs in the two DMAs as possible.

What we achieved: 

FIDO AI analysed over 35,000 historic sound files in 2.5 hours and returned a report that Thames Water retrospectively followed up with its own leakage repair records and dig data.

FIDO carried out analysis of Thames Water’s entire logger estate, an additional 6,810 new acoustic files. Thames Water identified 33 POIs for on-site follow-up verification. Of these, 11 led to the discovery of misaligned loggers, and 20 were correctly confirmed as leaks or no leaks (including 4 customer-side leaks), an accuracy of over 92%.


Historic files analysed in 2.5 hours


Accuracy, and improving


Leaks validated in six days


Misaligned loggers flagged for maintenance

Post-trial analysis showed 13 successful digs out of 13 work orders raised.

All new logger alarm files were processed by FIDO AI overnight to provide a start-of-day report showing new leaks over the full trial period. Thames Water then created its own logic table of POIs and therefore targeted, planned and scheduled POI visits with greater accuracy.

We undertook this trial to directly company the results of applying FIDO AI with that produced using our existing analysis of the data from our permanent acoustic loggers. Applying FIDO AI gave us a step change improvement in the confidence with which we could correctly predict the presence of a leak from our acoustic loggers. This would ensure we would not be missing leaks whilst maximising the efficiency of the follow-on activity in the field 

Andrew Oakes, Leakage Strategy and Development Manager, Thames Water

Our client was interested in the benefit that FIDO could bring to their end-to-end fixed network acoustic logging process, and wanted us to work with FIDO to review the effectiveness of their FIDO AI analysis. We found that FIDO AI helped us reduce our upfront analysis and identify points of interest for field investigation. We also had an opportunity to use the FIDO hardware in the field, which we found extremely helpful and easy to use.

Leon Fern, Framework Manager, Hydrosave