Research and Application of Anti-electric Shock Communication Terminal Based on Internet of Things Technology

Abstract

Leakage protection cannot effectively identify the voltage and current reception signals of electric shock grounding points that may pose a danger to personal safety through analysis of electric shock parameters, which is inherently inadequate. When a communication electric shock safety accident occurs, the accident site can be visually displayed in the safety prevention and control center, and an alarm is sent out. Meanwhile, relevant control instructions are issued to cut off the accident communication phase line to prevent secondary injury. In this paper, artificial intelligence and Internet of Things technology are applied to the communication system. The tag sensor is used in the monitoring system and is also used as the perception layer. The electric shock receiving signal obtained under the control circuit structure of the Internet of Things is determined by means of S transformation. The physical characteristics of wave frequency sensitivity are analyzed. Then, the external characteristics of biological shock are extracted with the help of the working frequency of each band of wavelet multi-resolution analysis, so that the electric shock model can deal with the hazards that cannot be identified by the traditional perception layer. The deep neural network is optimized to improve the recognition probability. Experiments verify that the recognition rate of the biological electric shock is as high as 99%, which further improves the stability of the leakage protection device and provides a guarantee for the normal operation of the communication system.