Study on the Situational Awareness System of Mine Fire Rescue Using Faster Ross Girshick-Convolutional Neural Network

摘要

With the continuous development of society, with the advent of the era of big data, situational awareness systems are gradually becoming well known and play an important role. Situational awareness systems are based on safe big data, and they are environmentally, dynamically, and holistically aware of security. A comprehensive system of risk capabilities. Therefore, this article uses the situational awareness system to study the rescue problem of mine fires, in order to reduce the casualties and economic losses caused by mine fires. On this basis, the convolutional neural network algorithm is used for situational awareness. By optimizing the algorithm, from region-based convolutional neural network (R-CNN) model to fast R-CNN model, the optimal model of faster R-CNN is finally proposed and implemented. The mine fire rescue problem.