The article proposes a method of automatic recognition of the type of building for an environmental monitoring system. based on convolutional neural networks. To train the neural network, the Keras library was chosen, containing numerous implementations of the main components of neural networks, such as layers, target and transfer functions, optimizers, and many tools to simplify working with images and text. The processes of network implementation using the Google Colab cloud platform, the preparation of a training set, the training of a constructed neural network, and its testing during training are described. The result of this work is a convolutional neural network model, capable of determining with accuracy of the order of 90-92 percent what type of buildings is shown on the cartographic image, which allows us to automate this process and use it as a subsystem for the environmental monitoring system of atmospheric air.
Keywords: environmental monitoring system for air, building type recognition, convolutional neural networks, machine learning, computer vision