An Intelligent Multitask Framework for Industrial Gas Leak Detection and Analysis With Infrared Optical Gas Imaging

Infrared (IR) optical gas imaging (OGI) is widely adopted in industrial environments for detecting fugitive gas emissions. However, conventional IR OGI systems rely heavily on manual inspection, lacking capabilities for active leak localization and in-depth analysis, which increases labor costs and risks of human error. To address these challenges, we present LeakHunter, an intelligent multitask framework designed for industrial gas leak monitoring and decision support. LeakHunter integrates seamlessly with IR cameras and can be deployed on edge computing devices, enabling real-time, on-site leak detection in harsh industrial settings. At the core of LeakHunter is a novel keypoint detection paradigm tailored for IR OGI, capable of localizing both leak sources and diffusion endpoints to enable effective spatiotemporal trend analysis. The framework also estimates critical leak attributes, including plume morphology and flow rate, supporting rapid and informed response. To further enhance detection accuracy, we introduce a biomimetic attention module that improves gas-background separation under complex thermal conditions, and a collaborative multitask head for efficient cross-task feature sharing. In addition, two benchmark datasets are proposed, one of which is a field-test set collected in real industrial scenarios. Experiments demonstrate that LeakHunter achieves state-of-the-art performance across multiple tasks, with an F2 score of 94.8% for gas segmentation and 97.9% for leak keypoint localization, while running at 28.4 FPS on a portable IR OGI device. These results highlight its potential as a deployable, intelligent solution for enhancing industrial safety and automation.