Meteorological information prediction using images from webcams

One aspect of the present invention proposes a method of predicting meteorological information by using an artificial deep neural network. The present invention according to one example focuses on image processing, specifically on fusing a plurality of images obtained by different webcams. It introduces a novel neural network architecture that combines a convolutional neural network (CNN) and long short-term memory (LSTM). The purpose of this fusion is to enhance the accuracy of predicting meteorological information compared to using a single image. By leveraging the capabilities of CNN and LSTM, the invention aims to improve the fusion process by extracting significant features from the images (such as clouds and shades) while considering the temporal aspect of the data.