Utility Week

24 www.utilityweek.co.uk/fLeX easily detect and locate leaks faster than traditional methodologies. "By taking these techniques one step further, water companies can use these AI and machine learning solutions to plan their mains replacement activities by identifying pipes and assets that have a higher propensity to fail and replace them quickly to improve the network resilience. " ese systems can also provide a higher level of situational awareness in planning incidents in the network due to extreme weather conditions, like the Beast from the East in 2018, and plan mitigations much faster and improve operational resilience." Predicting bursts Mott MacDonald's head of asset performance optimisation, Tom Joseph, says AI is increasingly being used to predict where the next burst will happen. "You can predict where pipes will fail," explains Joseph. "You can do that by using data on previous bursts and other parameters, like if a pipe is under a road, what the traffic is like on that road and what the temperature is on the ground. "We are also doing a lot of AI work on the wastewater side of things," he adds. "We've been working on correlation work on blockages, and rain-induced spillages, and when a sewer might spill and the effect it might have on the environment." In terms of other benefits, Graeme Wright, chief technology officer for manufacturing, Utilities and Services at Fujitsu UK, also sees a big role for AI in helping workers out in the field. " rough the use of AI, utility companies will be able to harvest their knowledge and skills and transfer information onto a platform that is readily available to advise engineers on-site, changing the way they work significantly," says Wright. "For instance, engineers in the field will be able to receive information on their next task in real time, with a complete view of its status and maintenance history. Engineers can also gain access to further information that may help their task, such as manuals or information on how the system ought to be performing. is access will help them assess what needs to be done more expediently and enable them to progress the task in a more efficient manner. "With the more data that the AI can collect, we will also see engineers start to use and be guided by 'co-bots' and 'chat- bots', which will provide guidance based on previous tasks and history, sharing knowledge captured from previous works and past expert interventions. "As a result, utility companies will be able to share knowledge more easily and work more effectively as tasks will be resolved more often in the first instance, without the need to call for another engineer as they will have all the knowledge and capabilities required," adds Wright. Capgemini's Malayathil adds: "In the utilities world, with the advances of AI, we could potentially see self-healing networks in water and electricity. "As an example, in water networks with an eco-system of intelligent sensors and edge computing, they will be able to automatically detect a potential leak based on sensor data and automatically adjust the network attributes such as pressure and flow to avoid a leakage incident." And Kevan Mossman, transformation director at the Odgers Interim Network, says AI will also help utilities build profiles of their customer base. "For example, an AI system could monitor search trends around problems in a specific postcode, such as leaks or outages. e AI could then assess that problem and distribute relevant communication to customers who may be affected almost immediately, without the customer needing to contact them," says Mossman. "However, AI cannot work without being fed 'big data'; something that utilities have historically been poor at making available. 3,183 million litres of water are lost per day in England and Wales As a result, the sector as a whole has been a late adopter and it's only in the past couple of years that companies have begun implementing large-scale digital transformation programmes to 'crunch' the data that they need." While the sentient AI systems of science fiction are still some way off, there is no doubt that the utilities sector, like many other sectors, is starting to explore the opportunities the technology can offer, especially as it comes under renewed pressure from politicians and regulators alike. Interestingly, a study by PwC published this year revealed 85 per cent of international chief executives agree that AI will significantly change the way they do business in the next five years. Two-thirds even said it would be bigger than the internet, which itself has turned out to be fairly revolutionary. PINPOINTING A PIPE AMONG 600,000 DRAWINGS Northumbrian Water has developed an innovative approach to managing records by using a cognitive service approach to build a data system with quicker response times. e utility's asset master data manager, Colin Richardson, says the "sheer volume of data and information" held by the company prompted the development of the new system. Northumbrian Water has more than 20 million electronic documents, including more than 600,000 technical drawings. Richardson says there were issues with some drawings being lost or stored on different drives, which made them hard to find. e company has now built a new single system, which is currently in a beta stage of development, before being officially launched in July. It uses cognitive services to differentiate between different types of drawing and build up a rich set of metadata, which can be searched against a wide variety of keywords. "It's an engine rather than a database," explains Richardson. "In the past, you would have systems where you shared documents, but people have problems with folder structures or the documents themselves were not named very well. It does store data, but only what is needed to allow intelligent mapping between the files and their metadata, such as location, asset, drawing type, etc. " is new system can scan all the network drives, pull all the information together and enriches the records with metadata, so they are easier to search and maintain," he says. "Last month, we had a site in the North East which could not identify the source of a heavy water leak. After digging many holes, the manager contacted us to see if our solution could help. Within a few minutes, we had managed to locate the long-lost site drawings from 1999. is led the workforce directly to where they needed to be and was an early indication of its value." A I A N D R E S I L I E N C E

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