UK water company Wessex Water is joining forces with artificial intelligence company StormHarvester in a world first to expand the use of AI to detect blockages across its entire wastewater network. The deployment follows a successful trial of StormHarvester’s AI technology in May 2020.
The technology differentiates expected high sewer levels caused by heavy rainfall volumes from those arising from restrictions such as partial or total blockages — a prediction commonly found difficult with traditional means. Following this successful trial, Wessex Water has confirmed it will deploy the technology across its entire network over the next three years. The expansion will cover nearly 35,000 km of sewers and wastewater generated from 2.8 million people.
“We are very pleased to win the network rollout,” explained Brian Moloney, StormHarvester’s managing director. “This is the biggest commitment ever to deploy AI in wastewater networks, not just in the UK, but globally.
The agreement follows a trial in the city of Bath to test the scope of AI and see whether it was possible to use machine learning to identify early-forming sewer blockages, mute unnecessary control room alarms and establish an operational basis for a shift towards condition-based maintenance. During the trial, StormHarvester’s Intelligent Sewer Suite detected over 60 early blockage formations in real-time.
Sewer blockages can lead to costly service failures including pollution and flooding events but, if spotted early enough, they can be quickly remedied. Wet weather makes it difficult to differentiate expected high sewer levels caused by heavy rainfall volumes from those arising from restrictions such as partial or total blockages.
By deploying AI with the capacity to differentiate between these different events, both an improvement in alarm quality and alarm rationalization is made possible.
Jody Knight, asset technology manager, Wessex Water said, “We are really proud to be rolling out this innovative AI solution across our entire sewerage network. It’s a huge step in our ambitions to significantly reduce blockage incidents and improve efficiency in our sewerage operations.”
“We set out to test the ability of machine-learning to predict blockage formations in sewer networks early and intervene before they became service failures, better separate genuine control room alarms from alarms triggered because of high volume rainfall during wet weather and dramatically improve the response time to service failures. In short, the technology worked and exceeded expectations.”
Artificial intelligence is a booming industry, with the global smart water sector alone predicted to be worth more than US$97 billion by 2030.
SOURCE: StormHarvester
