The situation
Severn Trent Water (STW) provides essential freshwater and sewage treatment services to households and businesses in the Midlands of England and a small area of Wales. The utility supplies around 8 million people with sewage treatment and water services.
STW had an ambition to transform their wastewater network with a longer-term view to have an intelligent data platform where advanced analytics could be used to provide data-driven decision-making to ultimately benefit STW and its customers.
The solution
Grundfos’ telemetry solutions for wastewater applications met SWT’s requirements for a Wastewater Network Monitoring Solution, and thus STW decided to utilise them for the Commonwealth Games in July 2022.
STW required a cost-effective, reliable monitoring solution that could provide the necessary intelligence with advanced analytics to inform of network strain points due to increased visitors to the area. Around 4.6 million people visited the Games during the period 28 July 2022 to 8 August 2022. STW requested to deploy Grundfos Connect Sewer Insights for the Games. The solution includes a data analytics platform which was used to monitor the Severn Trent Water network in the Birmingham area for the duration of the Games.
About Grundfos Connect Sewer Insights
Grundfos Connect Sewer Insights is an intelligent, machine-learning and data analytics platform that forms part of a powerful data network management system. The platform helps users to proactively manage their wastewater network as it delivers full network visibility, performance, and forecasting. It comprises four elements to help wastewater utilities prevent wastewater spills, thereby reducing pollution to keep the natural environment clean and protected.
The Grundfos Connect Sewer Insights solution for STW uses smart IoT level sensors which were deployed as a first phase at strategic monitoring points in the network.
The secondary phase utilises the platform to provide STW with predictive analytics that are data-driven and automated to deliver operational intelligence and insight at every level in STW’s wastewater network.
The solution combines wastewater level and rainfall data to provide intelligent alarms that highlight those high-risk areas within the STW network. This allows for proactive management to reduce the likelihood of potential spills. Blockages in a network form over time and are caused by debris in the network, including fat, wet wipes and fatbergs, leading to wastewater spills.
Another major cause of spills is significant rainfall which, when combined with current wastewater levels in a network, also contribute to wastewater spills.
It provides insight to detect these blockages as they form, providing STW with the necessary time to proactively clear these blockages and prevent spills before they happen.
Grundfos Sense Level IoT devices (part of the Grundfos Connect Sewer Insights solution) use contactless sensor technology to monitor sewer levels and send the data into the powerful data collection and device management platform. The data visualisation platform presents this data in a concise manner. It then combines the sewer level data with historic, current, and forecasted rainfall data to provide real insight including detecting partial sewer blockages.
The outcome
The key benefit to STW was to obtain intelligent data with advanced analytics to inform STW of strain points on their network due to increased visitors during the Games. Within days of deploying this, the platform detected a blockage and STW was able to clear this blockage before a pollution spill event could occur. For the duration of the Games, within the Grundfos solution coverage locations, no blockages went undetected.
All detected blockages were cleared before they could become spill events. By deploying the Grundfos solution, STW was able to meet environmental compliance and prevent reputational damage as they were able to deliver a consistently high-quality service during the Commonwealth Games with no spill incidents recorded throughout the course of the event.