Muscat – A group of students from the University of Technology and Applied Sciences (UTAS) in Shinas has developed a drone-based system to detect defects in solar panels, enhancing the efficiency of solar energy systems.
The innovation integrates thermal imaging and deep learning to identify defects caused by environmental, electrical, and mechanical stresses.
It aims to improve detection accuracy while reducing maintenance time.
Led by Fatima Mohammed al Maamari, the team received multiple awards at local and regional levels. The project has been recognised at several scientific conferences and exhibitions.
The system uses a thermal camera to scan solar panels and artificial intelligence to analyse irregularities. Advanced technologies such as augmented reality and 3D modelling have been incorporated to refine the detection process.
Team member Zahraa bint Saleh al Sanani said, “We’re working on integrating augmented reality with drones to provide a more accurate and efficient defect visualisation system.”
The project has been featured in international scientific journals, including Energy and IEEE Xplore, and presented at events such as the Oman Science Festival, the International Gas Conference at Qatar University, and the Hydroelectric Power Conference at the University of Sharjah.
With its practical applications already demonstrated, the technology has the potential to contribute significantly to the advancement of solar energy in Oman and beyond.
