Automatic Solar Panel Cleaner
For far too long, the output of solar energy systems has been compromised by the accumulation of dust and particles on solar panels, particularly in dry areas. In response to this challenge, we designed and implemented an Automatic Solar Panel Cleaner prototype that uses a Convolutional Neural Network (CNN) and a Raspberry Pi camera to identify dust accumulations. The system includes a water-and-wiper cleaning mechanism that restores panel output without manual intervention. Our prototype was built on a scaled model and tested under controlled conditions to determine its performance, responsiveness, and reliability. The implemented solution, which includes real-time monitoring and an emphasis on cost-effectiveness, highlights the potential for automated solar panel maintenance and contributes to increasing the practicality and adoption of renewable energy technologies.Project Details
- Student(s): Tracy El Ashkar, Carl El Khoury, Jad Abboud
- Advisor(s): Dr. Raymond Ghajar
- Year: 2024-2025