Research On Smart Home Indoor Air Quality Monitoring System Based On Fuzzy Neural Network

Air pollution threatens human life at all times,under the background that outdoor air quality is not fundamentally changed,in this paper,an indoor air quality monitoring system which combines the idea of intelligent algorithm and smart home is studied,and the indoor air quality can be controlled intelligently in this system.In order to achieve the design goal,the main work of this paper is as follows:(1)Through the study of a large number of domestic and foreign references,this paper analyzes the requirements of the current indoor air quality monitoring and control system,and an indoor air quality monitoring system which made up of seven parts: data acquisition terminal,gateway,router,cloud server,aplication(APP)monitoring platform,ZigBee transform infrared module and control object is presented.In this paper,a data acquisition module is designed,it can collect and transfer indoor air quality data through temperature and humidity sensors SHT20,carbon dioxide sensor T6603-5,PM2.5 sensor SDS011 and CC2530 module.In this paper,an embedded gateway is designed based on Acorn RISC Machine(ARM),which can make use of the router to realize the connection between the home network and the external network.The structure of the cloud platform is designed and the function of running intelligent algorithms in the cloud server is implemented in this paper.(2)The indoor air quality monitoring system model is analyzed in this article,then the fuzzy neural network controller by combining the advantages of fuzzy control and neural network is designed.The controller model is able to train and learn the user life data and get the Matlab simulation results.In order to verify the superiority of the fuzzy neural network,The Back Propagation(BP)neural network to simulate the collected data is designed in this paper.By comparing the simulation results of the both,it is found that the fuzzy neural network has the advantages of high precision and fast convergence compared with the BP neural network.(3)In order to facilitate real-time monitoring of indoor air quality,an app monitoring platform based on Android is designed.This paper mainly designs the monitoring platform's database and communication function,and uses Model View Controller(MVC)framework to develop and design the application program.Finally,we use the monitoring platform to test and analyze the whole system function,and draw the conclusion that the system can meet the design requirements.