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Aiming at the problem of energy waste in college classrooms, a smart classroom energy saving system based on ZigBee is designed. The system takes STM32 as the main control unit, and the local area network formed by ZigBee coordinator and terminal nodes constitutes the perception and execution layer. Through Wi-Fi network and cloud platform, the control center realizes the state perception and intelligent control of classroom electrical equipment. At the same time, aiming at the limited power of the temperature control equipment and the complex temperature interference environment in the room, the indoor temperature cannot be maintained in the appropriate range stably. Based on KNN algorithm, the NARX neural network temperature prediction model is constructed to realize the use of existing environmental data to predict the temperature at the next moment, so as to achieve accurate control of the temperature in the classroom. Finally, the function of the system and the improved prediction algorithm are verified by experiments. The running results show that the system can run stably and achieve the purpose of accurately controlling the electrical equipment and saving energy.