Yorkshire Water hosts leakage hackathon

Yorkshire Water hosted its first leakage hackathon as part of a bid to increase transparency for customers.

The Open Data showcase forms part of the company’s initiative to release the majority of its operational and service data by 2020.

It has started with critical areas such as leakage and pollution, having set ambitious targets of reducing internal sewer flooding by 70 per cent, reducing pollution incidents by 40 per cent and leakage reduction by 40 per cent.

Using data better could be critical in achieving those reductions and following a launch event workshop in March, Yorkshire Water gathered a panel of data experts to come up with new concepts for the hackathon.

As part of the showcase, the hackathon participants were split into seven teams and used the millions of lines of data the company has released on the Data Mill North website.

“We have a lot of incredibly useful data which can have a significant impact on improving our service to customers,” said Yorkshire Water director of communications Richard Emmott.

“Events such as this are vital to unlocking the potential of the data. For us this is just the beginning, but there were some terrific ideas which will certainly help us get to that target of a 40 per cent reduction in leakage.”

Yorkshire Water is now looking to progress two ideas from the event, both of which focused on utilising data captured by acoustic loggers.

The first idea was to catalogue the sounds captured by the loggers using a spectrograph. The concept was inspired by Shazam – an application which can identify films, movies and music based on a short sample. This means that when new sounds are recorded they can be matched with recorded sounds, making it quicker to identify what is and is not a leak.

The second idea introduced a graphic user interface (GUI) for a quick assessment of the logger data, allowing the company to prioritise leaks by the size of bursts and history of the site.

The firm is also investing in staff numbers, bringing in more data scientists who will also be used to improve the performance of the company’s assets and processes.