A Case study: Pump Digital Twins for Sewage Systems Boosts Efficiency and Sustainability in Alavieska Area

Nov 15, 2022 | Customer case

During the last 18 months, the municipality of Alavieska, Finland, has piloted the usage of IoT devices in sewage system pumps. The aim has been to get exact measures on the amounts of wastewater collected in the area. The data allows for heightened efficiency and sustainability in sewer management operations.

Leakages in sewage systems put pumping stations and treatment plans under unnecessary pressure

Pumping stations are a fundamental part of sewage pipe networks. They function as nodes in gravity-flow systems, transferring wastewater from urban areas towards treatment plants. Pumping is required to lift sewage from lower elevations, channeling it towards the desired destination.

Typical waste water pumping station in the country side

The wastewater transferred in the sewage system originates from households and commercial buildings. However, leaking pipes cause an unknown amount of surface runoff to filter into the system as well. The added material will put an extra strain on the pumps and treatment plants.

The added water in the sewage system comes with several issues. Firstly, the aggregated amount of wastewater will increase the treatment plant utilization rate. This will increase costs and add to the environmental hazards related to the process. Additionally, the cooling effect of infiltrated water will decrease treatment efficiency.

Secondly, increased amounts of liquids in the sewage system can lead to overrides of network capacity. This can lead to pump overflows, imposing an environmental and health risk in the area. Increased surface runoff, such as during heavy rain or snowfall, is a usual reason for sewage system overrides.

Currently, sewage system managers have limited ways to evaluate the amount of surface runoff in wastewater networks. Hence, making necessary investments and changes to the infrastructure to avoid the occurring problems is difficult.

Viimatech Digital provides an easy and cost-effective solution for getting necessary data and insight from sewage systems

Alavieska municipality works with Viimatech to gain new insight into the sewage pipes and pumps. They use IoT technology in pumping stations to measure region-specific amounts of wastewater pumped and transferred in the network.

Data capture devices are installed in electrical cabinets. There is no need to install any sensor in the pumps underground.

The technology is used to gather information on pump usage, creating a digital twin for each pump in the area. Then, a digital pump model calculates the amount of liquid transferred from each part of the sewage system.

The IoT arrangement allows for accurate volumetric measurements from across the Alavieska region. And the gathered data can also be used to estimate the amount of surface runoff leakage in various areas, and thus to localize impairments in the pipe system.

Pumping station volume

Ossi Laakso, Technical Director at Alavieska municipality, comments on the collaboration: “By using the digital twin model, we see that the amount of freshwater used in certain areas is persistently lower than the amount of wastewater collected, indicating infiltration of surface runoff into the pipes. We can use this information to make informed decisions on where it is necessary to make improvements and initiate repairs.”

Using an IoT technology-based approach is a cost-effective and easy way to get insight into the sewage system. Tracking the pumps eliminates the need for expensive flow measurements done directly in the sewage pipes.

Get in contact here with Viimatech to see how IoT could benefit your operations.


Founded in 2017, Viimatech Digital has proven the technical and commercial advantage of its digital solutions which rely on phase current of the motor driving the pump.

The company is lowering barriers of industrial and utility digitalization by offering cost effective and easy to use IoT to optimize maintenance and energy costs of pumping.

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