Low voltage user power internet of things monitoring system based on LoRa wireless technology

Abstract

The operational efficiency of the current smart grid system is seriously affected by the stability of the operating system, and Internet of Things technology has good applicability in power grid information perception. This study uses LoRa technology to construct a monitoring system for the electric energy Internet of Things. Additionally, an optimization model based on a particle swarm optimization algorithm and backpropagation neural network for optimizing base station positioning and channel quality evaluation is proposed. In addition, a multi-channel adaptive frequency hopping technology has been developed. The experimental results showed that the adaptive frequency hopping technology of the system could complete frequency switching within 2 min, which was more efficient than the traditional sampling and statistical technology that took 4 min. In terms of coverage, the research method had a coverage radius of 25 km, which was superior to other communication technologies such as NB IoT and ZigBee. In terms of data transmission success rate, the research method achieved 98.11%, significantly higher than Sigfox’s 90.02%. In addition, the system had a latency of only 150ms and low power consumption. In summary, the PSO-BP LoRa model proposed in the study has high application value in smart grids and industrial environments, providing technical support for wide-area, low-power, and high-stability Internet of Things monitoring systems.