Public Funding for MWH Treatment Limited

Developing a Leak Prediction System (LeaPS) using Data Mining, Machine Learning & Neural Networks. This project has a clear vision: revolutionise the way in which WaCos (Water Companies) reduce leakage. The Water sector is being challenged (by Ofwat, the industry regulator) to understand how Artificial Intelligence (AI) can be utilised in this major worldwide societal challenge. Leakage has wide ranging impacts; customers facing higher bills, climate change, WaCos penalised for not complying to strict Ofwat targets, businesses and the general public suffering due to water outages. Reducing wasted water is of utmost importance not only to UK but worldwide. We must treat our natural resources as finite and invest to save. An innovative and cost-effective method is proposed, combining AI technology with historic data to develop a Leak Prediction System: LeaPS. The collaboration between EnginSoft UK (ESUK) and MWH Treatment (MWHT) and will lead to a promising and sophisticated technology demonstrator ready for the next stage of commercialisation. The outcomes will be presented (via a cloud-based platform) via an analytics dashboard and a leak predictor heat map. LeaPS will prove to be an asset to the Water sector worldwide as it will enable WaCos to meet regulatory targets and avoid penalties whilst reducing wastage. In short, LeaPS provides the route to a more efficient, cost-effective and environmentally friendly Water Industry.