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iTwin, iTwin.js
To improve the performance, reliability, and energy efficiency of Finland’s water and district heating networks, Silo AI developed a smart, data-driven asset optimization service for city pipeline operators. System operators need to prioritize maintenance renovations, predicting and pinpointing areas where leaks are most probable. However, scattered and disconnected data systems and sources present challenges when developing systematic pipeline maintenance prioritization, resulting in significant renovation debt. To help address these issues and provide a holistic visual overview of network health, Silo AI needed an integrated, user-friendly digital platform.
Silo selected the Bentley iTwin platform to visualize and analyze data from multiple data sources in a connected, easily accessible, digital environment. Using the platform reduced visualization efforts by 50% and significantly shortened the time needed to deliver the AI solution for leakage predictions and flow optimization. As a result, they decreased their network supply temperature by three degrees, improving energy efficiency while decreasing fuel consumption. Network operators can increase ROI through pipeline system optimization, budgeting future maintenance and network investments.