📝 Description

The project focuses on applying advanced deep learning techniques to detect leaks in water distribution networks. The data will be represented as spatiotemporal graph, where sensor data is integrated as node and edge features. The student will implement and fine-tune Spatiotemporal Graph Neural Networks (STGNNs) models using PyTorch and Torch Spatiotemporal, experimenting with different architectures and hyperparameters. By the end of the project, the student will have developed a strong understanding of graph-based modeling, spatiotemporal deep learning, and its application to real-world anomaly detection tasks.

Data: An open-source leakage dataset for water distribution networks, which consits of a large number of leakage scenarios, on different water distribution networks, under varying conditions.

📨 Contact:

Filippo Maria Bianchi filippo.m.bianchi@uit.no