THE MAGAZINE FOR THE DRAINAGE, WATER & WASTEWATER INDUSTRIES
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us, for example, to determine how a wastewater asset will behave in the future or predict how a river level will change with catchment rainfall. We are not modelling what will happen, instead we are learning how an asset behaves based on historical data, and using this to predict a future state.
“The predictions AI generates will allow us to automate decision-making in response to different events, and perform tasks with limited or no intervention. ”
Increasingly, the predictions AI generates will allow us to automate decision-making in response to different events, and perform tasks with limited or no intervention. Indeed, ‘smart control’ already exists in the stormwater attenuation space and requires no human involvement.
Brian Moloney
Digital water solutions, of which AI is a major component, are expected to be worth more than US$97 billion globally by 2030. Urbanisation, climate change, and population growth are posing a challenge to ageing wastewater and drainage infrastructure around the world.
At a more local level, sewer performance is also affected by unflushable products and substances like wet wipes and fat, oils and grease, which can cause fatbergs and sewer blockages. Service failures can prove costly, but spotted early, they can be quickly remedied.
This is where AI has an important role to play in network management, as many of critical functions can be automated to dramatically improve network performance. Machine learning algorithms can identify abnormal sensor behaviour and provide an early-warning of asset degradation or failure.
On the customer service side, we see conversational technology – otherwise known as chatbots – playing a significant role. Chatbots help the organisations start customer conversations and push important literature from the website to them.
Currently conversational chatbots can be used to give status updates on applications and projects, and book appointments for visits to customer properties, at scale. In the future, through further automation and the development of AI, this type of technology will be used to undertake more and more customer interfaced tasks requiring a deeper or more specialist technical knowledge, for example liaising over engineering queries from developers.
AI increasingly important in network management Brian Moloney, Founder and Chief Executive, StormHarvester
Artificial intelligence (AI) is impacting the future of virtually every industry, yet it remains shrouded in mystery for many. Today, the amount of information generated by humans and machines far outpaces our ability to learn, interpret, and make complex decisions based on that data.
AI, including machine learning, allows us to analyse vast amounts of data and make repetitive, complex calculations very quickly using cloud computing, yielding very accurate predictions. It is the accuracy of these predictions that allow
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AI technology can also warn of leaks, bursts, and pollution incidents and – by monitoring variables such as the energy consumption of equipment – can predict when maintenance is required. An example of the potential of this technology to transform sewer network management is our successful trial with Wessex Water in the city of Bath.
In May 2020 StormHarvester carried out a three-month smart sewer trial 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. Our pilot showed 92% accuracy in identifying early forming blockages with zero missed and control room alarm rationalisation of 97 per cent.
The technology also identified at least two incidents that would likely have resulted in Category 3 spillage, or worse. Numbers like these make for a strong business case for utilities.
Following the trial’s success, Wessex Water has confirmed it will deploy our AI 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. This is the biggest commitment ever to deploy AI in wastewater networks, not just in the UK, but globally.
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