Fuzzy PID-Based Temperature and Humidity Adaptive Air Conditioning Regulation System

In recent years, the proportion of electricity consumption in air conditioning systems (ACSs) has significantly increased. Unreasonable temperature settings of ACSs result in wasted energy and reduced user comfort. Therefore, it is necessary to design an intelligent temperature control system to ensure comfortable temperature and humidity while improving energy utilization efficiency. This paper proposes a fuzzy PID-based temperature and humidity adaptive ACS regulation system. Firstly, an indoor temperature and humidity collection module is designed to persist the environmental data collected by sensors into a database. Secondly, an ACS reservation module based on neural network prediction algorithm is designed to optimize the opening time and temperature of the ACS. Then, a temperature and humidity control module is designed to adjust the ACS conditions based on real-time measurement information. Finally, an ACS control module is built using the Internet of Things development board, which controls the ACS by driving the infrared transmitter. The actual case simulation proves that the proposed method has a significant regulatory effect, improving human comfort while reducing electrical energy waste.