Data Analytics

The design of measurement campaigns, water districtualization, and hydraulic modeling are tackled with the assistance of genetic algorithms, in order to optimize activities and increase the precision of outputs.

Measures always go with some error. It is necessary to mathematically combine the different sources of error. Additional information to describe the quality of the measures may be hidden amongst the metadata.

The technology by which the measurement is realized brings with it further uncertainty: meters that change position, get dirty, drift. We clean the data by checking the measuring stations and indicate the need for any maintenance.

Measured parameters may be temporarily unavailable or redundant: the meters are subject to damages and they can be placed in a non-optimal way. We reconstruct the measures and we re-design the positioning of the meters.

Knowing in advance the value of specific parameters in crucial sections of the grid, leads to a breakthrough in the water network management. We apply our AI predictive algorithm to the sewage network.

Starting from the reconstruction of real- time or forecasted measures, we build a decision support system. We identify the combination of structural and operational, with the aim of optimizing the assets.