Development of Solar Panels Detector

Author: Golovko V., Kroshchanka A., Bezobrazov S., Sachenko A., Komar M

Abstract: The paper describes the method of detection of roof-installed solar photovoltaic panels in low-quality satellite photos. It is important to receive the geospatial data (such as country, zip code, street and home number) of installed solar panels, because they are connected directly to the local power. It will be helpful to estimate a power capacity and an energy production using the satellite photos. For this purpose, a Convolutional Neural Network was used. For training and testing dataset consists of low-quality Google satellite images was used. The experimental results show a high rate accuracy of detection with low rate incorrect classifications of the proposed approach. The proposed approach has enormous implementation and can be improved in future.

Keywords: convolutional neural network; solar panels detection; satellite photos; geospatial data; power capacity; energy production, artificial intelligence, computer vision.