Viktoriya Degeler and Alexander Lazovik have been awarded a NWO Smart Industry 2020 grant for research into Digital Twin for Evolutionary Changes (DiTEC) in water networks.

DiTEC proposes an evolutionary approach to real-time monitoring of water networks that detects inconsistency between measured sensor data and the expected situation, and performs real-time model update without needing additional calibration. Deep learning will be applied to create a data-driven simulation of the system. In case of leaks, valve degradation or sensor faults, the model is adapted to the degraded network until the maintenance takes place, which can take a long time. We will analyse the effect on data readings of different malfunctions, and construct a mitigating mechanism that allows to continue using the data, albeit in a limited capacity.