AQUALEARN - Deep learning-based digital twins for real time anomaly detection in water supply systems

AQUALEARN aims to develop and demonstrate the application of machine learning-based digital twins to detect anomalies (breaks, blockages) in water supply systems. The methodology involves the detection and classification of anomalies using continuous monitoring, and their localisation and quantification using pressure records.

Team Researchers