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Photovoltaic panel damage AI identification

This paper presents an innovative explainable AI model for detecting anomalies in solar photovoltaic panels using an enhanced convolutional neural network (CNN) and the VGG16 architecture. The model effectively identifies physical and electrical changes, such as dust and bird droppings, and is. . Leveraging the power of IoT sensors and computer vision, a new framework is proposed for defect detection in solar cells as well as solar panels. Utilising drone technology, thermal images of the solar plant are taken; these images are then analysed through our AI model.

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