Automatic visualization of gas leakage in the domestic sector using spacial and temporal models with image processing techniques

The leakage of gas in the domestic sectors is a dangerous issue that causes various hazards. This is due to the damage in the pipelines that affects the overall functioning. Prior detection of leakage can help to avoid various dangerous consequences. The proposed system helps in the detection of gas leakage through artificial intelligence techniques evolving image processing. This includes infrared (IR) cameras that help to detect the leakage of gas. This helps in detecting the gas by analyzing and detecting the temperature of the leaking liquid with that of the surrounding temperature. This is a vision-based sensing system. To obtain accurate images, image enhancement processing with Gaussian filters is used. This helps to enhance the quality of the infrared images. Then the feature extraction phase is implemented to extract the most prominent features that aid to detect the leakage accurately. The proposed system is implemented using deep learning techniques with an optimization algorithm. This helps in obtaining accurate results that help to prevent leakages and protect from various constraints.