Solar panel hotspot detector - Baderul Hisham, Muhammad Nabil Aiman; Isa, Iza Sazanita; Saad, Zuraidi; Che Soh, Zainal Hisham (Universiti Teknologi MARA Cawangan Johor Kampus Pasir Gudang, 2025)
The solar industry that continues to grow bigger is facing a huge obstacle in maintaining solar panel lifespan and efficiency due to normal occurrence of hotspots and cracks on solar panel surface. These defects not only shorten the panels' lifespan and limit their energy output but also accelerate their disintegration, resulting in substantial financial losses. Traditional detection techniques are largely manual, time-consuming and prone to errors making it difficult to implement effective preventive maintenance strategies. To address this issue, this mobile solar panel hotspot detector is designed to ease the detection process by making the detection in real-time on mobile smartphone with practical application of a FOMO (Faster Object, More Object)-based machine learning model for the detection of defects on solar panels. The significance of this product lies in improving the efficiency of solar panels defect detection and no longer uses human’s eyes capabilities only during human inspection. In addition, by ensuring that solar panels are well maintained and working optimally will guarantee a steady supply of solar energy. In the end, this simple product has the potential to yield important breakthroughs in renewable energy technology, promoting worldwide economic savings and energy security