Internet of Things-driven intelligent ventilation system for buildings in humanized designs

This paper focuses on designing a personalized intelligent ventilation system based on the Internet of Things (IoT), which consists of a three-layer structure of workstations, network controllers and field controllers. The indoor environmental data is preprocessed using the Grubbs criterion, while the node data collected by multiple sensors are then weighted and fused to obtain the optimal data values. Through the fuzzy controller, the concentration deviation and dust concentration deviation are used as input quantities, and the final output of the fan on time under different environments. The simulation results of the experimental scenarios show that the stability test success rate of the system in this paper are more than 95%, and the degree of stability is very high. Compared with the conventional PID control, the steady state error of the fuzzy PID control is only 2%. The simulation experiment tested three functional rooms: bedroom, living room and kitchen. When the CO2 concentration in the bedroom, PM2.5 concentration in the living room and PM2.5 concentration in the kitchen exceeded the standard, the system in this paper can monitor and turn on the ventilation system in time to improve the indoor air quality. It also has the warning function of dangerous gas.