Application of colorimetry in neural network methods of fire detection in woodlands

Currently, neural network methods of fire detection have been used to monitor fires in forests. To date, such systems have been developed as the Prometheus project, the Fire Video Detector, and the Artificial Intelligence University method. These methods make it possible to determine a fire with an accuracy of more than 90 %, for which a combination of recurrent and light-line neural networks is used. The article proposes a method for improving the efficiency of neural network methods for determining fires in forests based on computer colorimetry. The use of this method makes it possible to increase the efficiency of neural network methods for detecting fire when using multiple cameras of a video surveillance system. Thus, the article presents a comparison of the performance of a convolutional neural network with and without the use of a colorimetric module. According to the results, the efficiency of work has increased by more than 20 %.