Prevention of blockages in the sewage pipes and improved pipe maintenance

Infrastructure
Machine learning

Together with HSY, we developed a machine learning-powered solution to improve pipe maintenance by predicting possible blockages.

Helsinki Region Environmental Service Authority HSY’s sewage network spans over 100 000 pipes, forming an over 3 000 kilometers long network.

Together with HSY, we developed a machine learning-powered solution to improve pipe maintenance by predicting possible blockages. The machine learning solution leverages data on previous blockages, combined with water and pipe features, and makes predictions on the most blockage-prone drain ranges. 

One third of blockages can be prevented

With the AI solution, up to one third of blockages on an annual level in HSY’s sewage network could be prevented. The intelligent solution points out the areas where most blockages are likely to occur. With this information, HSY is able to focus its sewer cleaning on the targeted areas, thus improving the efficiency of their operations but also avoiding costly consequences of a blockage.

Results

  • One third of blockages in the 3000 km long sewage pipe network can be prevented
  • Significant cost-savings due to reduced amount of blockages
  • A sewage network analysis on areas and materials most prone to blockages, improving HSY's operations

Read more in the press release.

“The AI solution is able to predict possible blockages efficiently. It seems that with a very small increase in sewer network maintenance, we could avoid up to a third of blockages”

Kia Aksela

Head of Department

HSY

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