LAUSR

In order to ensure production safety and improve production efficiency, mining enterprises are constantly accelerating the construction of mine Internet of Things systems. In the context of a substantial increase in the number of devices with network communication capabilities in the mine, the mine network communication facilities are under tremendous pressure. We propose a device business classifier based on convolutional neural networks to improve the service quality of mine network communication infrastructure. The classifier uses wavelet transform to extract the data flow and construct behavior characteristics to classify device business categories. According to the classification results, the system flexibly adjusts the parameters of network services provided to the terminal equipment. In this way, the network resources of the system can be allocated reasonably. We evaluate the performance of the classifier model through the test data set. The performance evaluation results show that the comprehensive recognition rate of the classifier model reaches 97.2%. We optimize and adjust the classifier model according to the hardware environment in which the classifier is actually deployed.