Application of artificial intelligence in remote monitoring of electrical parameters using LoRa and smart energy meters

Abstract

Smart energy monitoring and management systems play an important role in the process of saving electricity, helping to reduce costs and improve efficiency. In the process of digital transformation and development, this system supports decision-making based on actual collected data. This paper proposes to build a remote system for monitoring power parameters based on LoRa communication technology, smart electricity meters, and an artificial intelligence model. The system allows the collection of voltage, current, and power parameters via Modbus protocol to the center. Based on the Artificial Neural Network (ANN) on Matlab, it helps to forecast consumption load and detect faults in the power system. The research results show that the system operates stably with high accuracy and reliability, low latency, and the ability to transmit data far away for applications in areas with renewable energy. The system has the potential to be applied in power monitoring for distributed power grids and smart metering solutions in the future.

Keywords: Artificial intelligence, smart meter LoRa, remote monitoring, load forecasting, artificial neural network.