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StormHarvester's successfully detects blockage formations for Wessex Water using its proprietary artificial intelligence (AI) software.
The potential for AI to transform sewer network management has been demonstrated during a three-month trial of StormHarvester's Intelligent Sewer Suite with Wessex Water in the city of Bath.
Results from the three-month trial showed significant alarm rationalisation and a high degree of accuracy in blockage detection. Over 60 early blockage formations were detected in real-time, at least two of which were likely to have caused pollution incidents – Environment Agency Category 3 or worse. Over 60 telemetry and sensor faults were also detected.
Jody Knight, asset technology manager at Wessex Water said: "The StormHarvester team identified sewer blockages that using our normal working processes we may not have spotted until they had resulted in unwanted sewer overflow events."
Deployment of StormHarvester's AI approach was shown to be 92% accurate, with no blockages missed. Additionally, a 97% reduction in control alarms was achieved with only 138 in total – little more than one-a-day over the period.
Wessex Water considered the alerts provided by StormHarvester to be a major improvement on the status quo, where operational staff were regularly overwhelmed by the large number of high-level and overflow alarms occurring during periods of heavy rainfall. It also makes the potential for predictive maintenance very realistic in the near future.
Edmund Willatts, asset reliability engineer, Wessex Water said: "This condition-based sewer maintenance versus the scheduled cleaning regime will be key to making operational teams more productive and efficient going forward."
The Wessex pilot revealed that StormHarvester technology has the capability for:
• High blockage prediction accuracy – 92% of alerts were relevant and required and not a single blockage resulting in a pollution incident was missed
• Few false positives – 8% of alerts were false positives
• Long-range blockage prediction - early blockage formations identified up to eight weeks before they would have resulted in service failures
• Condition-based maintenance - the three-month trial has enabled a shift in approach.
• Control room alarm rationalisation - a 97% reduction in control room alerts was achieved versus business as usual
Knight said: "One of the biggest problems we have serving our customers is not knowing where and when blockages will occur, or are likely to occur, in the wastewater network. During the three-month trial, StormHarvester identified at least two incidents that we are fairly confident would have resulted in Category 3 spillages, or worse, if it was not for the early blockage detection alerts received and the subsequent action taken by Wessex operational staff."
Neil Macdonald, co-founder of StormHarvester said: "The results have been excellent. Wessex Water have been great to work with and this trial has proven that Intelligent Sewer Suite is effective at scale.
"This is further endorsement of our five-year journey and multimillion pound investment to build an effective AI solution combining machine-learning, predictive analytics and hyperlocal rainfall forecasting leading to intelligent sewers that serve customers, communities and the environment."
He added, "Our technology proves that predictive maintenance is possible, with early blockage detection occurring from hours to weeks in advance. This represents a significant increase in the available time for operational crews to recover and repair assets.
"StormHarvester sees this as a real game-changer, with a clear route to achieving efficiencies for wastewater utilities, reducing wastewater pollution and both internal and curtilage flooding."
Based on the value brought by the StormHarvester alerts during the proof-of-concept trial, Wessex Water has maintained the solution running on the Bath wastewater catchment into 2021.