Design of remote detection and control technology for port equipment based on high-speed mobile communication
To improve the efficiency of remote detection and control of port equipment,this paper designs a remote detection and control platform for port equipment based on high-speed mobile commu-nication and deep learning technology.The platform adopts a combination of B/S and C/S architecture to improve the corresponding speed of the platform,and builds a 5G network through an independent SA private network to improve the security of data transmission.By integrating residual structures and convo-lutional neural networks,an IDCNN model with effective information transmission was established to im-prove the accuracy of feature extraction with a small number of data samples.Tests have shown that the constructed 5G private network has a SINR of 13.98 dB and an RSRP of-85 dBm,which can meet the platform's task requirements.Compared with SVM,CNN,and decision tree models,the proposed model achieves a fault recognition accuracy of over 86.1％,proving the feasibility of this scheme.
port equipmentremote detection and controlhigh speed mobile communicationdeep learningconvolutional neural network
万方数据
维普
