Solar Panel Damage Detection and Localization of Thermal Images

Solar panels have grown in popularity as a source of renewable energy, but their efficiency is hampered by surface damage or defects. Manual visual inspection of solar panels is the traditional method of inspection, which can be time-consuming and costly. This study proposes a method for detecting and localizing solar panel damage using thermal images. The proposed method employs image processing techniques to detect and localize hotspots on the surface of a solar panel, which can indicate damage or defects. The findings of this study show that the proposed method is effective in detecting and localizing solar panel damage and can reduce inspection time and cost. This study proposes a method for detecting and localizing solar panel damage using thermal images. The proposed method employs image processing techniques to detect and localize hotspots on the surface of a solar panel, which can indicate damage or defects. The findings of this study show that the proposed method is effective in detecting and localizing solar panel damage and can reduce inspection time and cost. The proposed method has the potential to improve the efficiency and lifespan of solar panels while also contributing to the wider adoption of renewable energy. This research suggests a way for detecting and localizing solar panel damage using thermal imaging, which could get rid of the requirement for manual visual examination. The suggested technology detects and localizes hotspots on the surface of solar panels, which indicate faults or damage. This method can increase the efficiency and longevity of solar panels, hence promoting the use of renewable energy. Future improvements, such as incorporating AI and ML algorithms and advances in thermal imaging technologies, could improve the accuracy of this method even further.