AI successfully detects blockage formations for Wessex Water
Machine-learning technology trialled on part of Wessex Water’s sewerage network has identified early forming sewer blockages in real-time with a 92% accuracy rate.
This has also enabled an operational shift to condition-based maintenance approach, said Brian Moloney, the managing director of StormHarvester.
The potential of artificial technology (AI) to transform sewer network management was demonstrated during a three-month trial of StormHarvester’s Intelligent Sewer Suite with Wessex Water in the city of Bath.
The technology quickly demonstrated its value, with over 60 early blockage formations detected in real-time and control room alerts reduced by a staggering 97%.
Managing sewer blockages represents a significant operational challenge for water and wastewater utilities.
As well as problems arising from the blockages themselves, heavy rainfall events often trigger hundreds of alarms simply because of high levels within the sewer network caused by rainfall runoff.
The volume of these alarms during wet weather periods can be overwhelming for operational and maintenance teams.
The incumbent rules-based alarm system operating in the Wessex Water control room generated some 4,500 alarms during the trial period.
However, the AI tools was able to mute alarms where the high sewer levels were predicted by the AI software due to rainfall, reducing the total to 138, of which 124 were genuine blockage formations or sensor faults.
This gave the utility’s operational and maintenance crews capacity to respond rapidly to each alarm, even during periods of heavy rainfall.
The initiative started last year when Wessex Water invited 16 technology companies from around the world to demonstrate the value of applying artificial intelligence to the wastewater network.
As a finalist, Belfast-based StormHarvester was invited to run a three-month trial to carry out proof of concept.
The trial took place from June to August 2020 in the wastewater catchment of the historic city of Bath, Somerset, which comprises 3,500km of sewerage, representing 10% of Wessex’s total. Intelligent Sewer Suite was applied to an array of 98 level sensors already present in the network - 89 at combined sewer overflow (CSO) sites and the remainder at pumping lift stations.
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.”
This has also enabled an operational shift to condition-based maintenance approach, said Brian Moloney, the managing director of StormHarvester.
The potential of artificial technology (AI) to transform sewer network management was demonstrated during a three-month trial of StormHarvester’s Intelligent Sewer Suite with Wessex Water in the city of Bath.
The technology quickly demonstrated its value, with over 60 early blockage formations detected in real-time and control room alerts reduced by a staggering 97%.
Managing sewer blockages represents a significant operational challenge for water and wastewater utilities.
As well as problems arising from the blockages themselves, heavy rainfall events often trigger hundreds of alarms simply because of high levels within the sewer network caused by rainfall runoff.
The volume of these alarms during wet weather periods can be overwhelming for operational and maintenance teams.
The incumbent rules-based alarm system operating in the Wessex Water control room generated some 4,500 alarms during the trial period.
However, the AI tools was able to mute alarms where the high sewer levels were predicted by the AI software due to rainfall, reducing the total to 138, of which 124 were genuine blockage formations or sensor faults.
This gave the utility’s operational and maintenance crews capacity to respond rapidly to each alarm, even during periods of heavy rainfall.
The initiative started last year when Wessex Water invited 16 technology companies from around the world to demonstrate the value of applying artificial intelligence to the wastewater network.
As a finalist, Belfast-based StormHarvester was invited to run a three-month trial to carry out proof of concept.
The trial took place from June to August 2020 in the wastewater catchment of the historic city of Bath, Somerset, which comprises 3,500km of sewerage, representing 10% of Wessex’s total. Intelligent Sewer Suite was applied to an array of 98 level sensors already present in the network - 89 at combined sewer overflow (CSO) sites and the remainder at pumping lift stations.
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.”
