ABSTRACT
This chapter analyzes the performance of the proposed Internet of Things (IoT) system for smart power management using several data mining algorithms. The real-time supervision of electricity consumption and the adaptive adjustment of electrical equipment usage are significant functions of most smart power consumption management applications. By integrating the private Long Range (LoRa) and public networks, a smart power management IoT system overcomes low-bandwidth transmission problems in difficult scenarios under weak signals, such as in tall skyscrapers and underground garages. If IoT equipment attempts to connect to a private network by delivering a joining request, the LoRa gateways confirm the connection request and generate the configured parameters. The LoRa gateways deliver received data to the cloud server for data storage and behavior feature analysis, which uses energy Big Data analysis, personalized energy-saving strategy planning, and power demand prediction.
