AUTOMATED DETECTION OF DUSTY SOLAR PANELS USING PRE-TRAINED CONVOLUTIONAL NEURAL NETWORKS

Creative Commons License

Noğay H. S.

3rd INTERNATIONAL CONGRESS ON ENGINEERING AND SCIENCES, 10 - 11 Mayıs 2024, ss.97-104, (Tam Metin Bildiri)

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Sayfa Sayıları: ss.97-104
  • Açık Arşiv Koleksiyonu: AVESİS Açık Erişim Koleksiyonu
  • Bursa Uludağ Üniversitesi Adresli: Evet

Özet

Abstract: Solar panels play a crucial role in renewable energy systems, but their efficiency can be compromised by the accumulation of dust and debris. In this study, we propose an automated approach for the binary classification of solar panels as either clean or dusty using deep learning techniques. The success of this study highlights the importance of leveraging deep learning and transfer learning techniques for addressing environmental challenges in renewable energy systems. By automating the detection of dusty solar panels, our approach offers a cost-effective and efficient solution to optimize solar panel performance and maximize energy generation.