Leakage Detection

Leak detection research focuses on developing accurate and efficient methods to identify leaks across various systems, from water distribution networks to oil and gas pipelines and carbon sequestration sites. Current approaches leverage diverse techniques, including graph neural networks informed by classical algorithms for analyzing network data, deep learning models like YOLO and RT-DETR for processing visual data (e.g., thermal images), and physics-informed machine learning for integrating hydraulic principles with pressure data. These advancements aim to improve the timeliness and accuracy of leak detection, leading to significant cost savings, reduced environmental risks, and enhanced safety in various industrial sectors.