Research And Design Of Indoor Air Quality Monitoring And Evaluation System

With the improvement of living standards in recent years,indoor air quality has become the focus of attention.For the description of indoor air quality pollution,it is necessary to obtain indoor pollutant concentration and then evaluates it.In the view of existing indoor air quality monitoring and evaluation system,when there are many monitoring points and wide distribution,it is difficult to carry out large-scale monitoring;subjective influence is greatly affected when conducting evaluation,and it is difficult to obtain a comprehensive objective evaluation.In this paper,a more intelligent indoor air quality monitoring and evaluation system is designed,which realizes large-scale monitoring and scientific evaluation.The main contents are as follows:The indoor air quality assessment methods commonly used in the room: air quality index,fuzzy mathematics,artificial neural network,fuzzy neural network for comparative analysis,fuzzy neural network to evaluate indoor air quality;analysis of the number and distribution of indoor monitoring points,etc.Comparing several communication technologies: ZigBee,WIFI,GPRS,LoRa and NB-IoT,selecting NBIoT as the data communication of the monitoring system;comparing and analyzing the local server and cloud server,and choosing a more suitable cloud server.Finally,the overall design of the system is obtained and the feasibility of the system is analyzed.In order to describe the non-linear effects of multi-polluting factors on the evaluation level,the T-S fuzzy neural network is used to construct the evaluation model,and the Beetle Antennae Search algorithm is used to optimize the T-S fuzzy neural network using random values as the initialization parameters,which is more objective.Evaluation model.There is no clear evaluation method and standard for indoor air quality.This design builds a standard evaluation form according to the national indoor air quality standard,and trains the constructed model.Objectively analyzes artificial neural network,TS fuzzy neural network and day by simulation results.The TS fuzzy neural network optimized by the cattle must find that the TS fuzzy neural network optimized by Beetle Antennae Search can better evaluate the indoor quality air and has a good application prospect.The hardware and software design of the indoor air quality monitoring and evaluation system are designed.The hardware includes: the minimum system of embedded microprocessor,each sensor of interface,NB-IoT module circuit,antenna and necessary peripheral circuits,and system power supply circuit.The software part includes: the microprocessor processeing the sensor data,the NB-IoT transmitting the data to the server,builds the Socket server software based on the Linux system on the cloud server,storing the MySQL data for the data,and the HTML5 web client visualization page Development.Taking a laboratory of Chengdu University of Technology as the actual monitoring and evaluation object,the concentration of 10.00-20.00 for 1 consecutive days in December 2018 and 10.00-20.00 for 2 consecutive days in March 2019 was selected and the results were obtained.Indicates the feasibility of the system design.