Utility Week

23 ISSUE 03 MAY/2019 find and fix leaks in its network around Hebden Bridge and west Sheffield with the aim of avoiding interruptions to services for customers. As part of the trial, it will provide data to both remote monitoring specialists Servelec Technologies and water consultants Artesia Consulting, who look for disruptions to normal patterns. Any discrepancies will then be flagged and passed back to Yorkshire Water to investigate. In October last year, United Utilities became the first water company in the UK to introduce large-scale AI into its operational systems. e Warrington- based company has signed a framework agreement with the Canadian technology firm Emagin after a successful trial earlier in the year. Emagin's artificial intelligence platform, called HARVI, can assess vast amounts of data on a wide range of factors such as weather, demand for water, pump performance and electricity prices. is is used to help make decisions on the most cost-effective and efficient way to run pumps, detect burst pipes and minimise the risk of discoloured water. During the 12-week trial, which took place across Oldham in Greater Manchester, HARVI demonstrated energy savings of 22 per cent. United Utilities now plans to deploy the artificial intelligence platform in phases across the whole North West region by the end of 2019. Meanwhile, Yorkshire Water started trialling smart analytics in January to Finally, after teaming up with Capgemini, Severn Trent announced in December last year that it has started to use machine learning – which is a form of AI that allows systems to automatically learn and improve – to help transform the way it approaches leaks. " ere are a plethora of solutions to detect leakages, such as smart balls, which can put be put in to the main pipes, which can detect leaks, or acoustic loggers, which can listen to the sounds of leakage like a traditional hydrophone and log them," explains Capgemini's head of insights and data for UK energy and utilities, Raj Malayathil. "One area water companies should be exploring is the power of data and AI in detecting leakages," he adds. "Water companies hold a lot of data such as pressure and flow from the network and also information on historic leakage incidents such as the location of a leak, interventions done, weather data, soil conditions, etc. Using AI and machine-learning techniques on these data sets, water companies can // We've had a good record historically on leakage and are near the top of the league table in England, but we have to do more // Phil Tapping, water demand manager, Southern Water

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