Research On LoRa-based Online Air Quality Monitoring System And Prediction Model

In recent years,people’s awareness of environmental protection has gradually increased,and the country’s environmental protection efforts have intensified.Although environmental pollution has improved,certain areas still have serious air pollution problems,which can bring respiratory,cardiovascular and neurological hazards to local residents.Online monitoring of air quality and prediction of pollution gas concentration can help people to carry out effective prevention work and make people’s living environment better.Traditional air quality monitoring systems generally monitor large cities and key areas,which have problems such as large size of monitoring equipment,high cost and limited monitoring range.To address these problems,this paper designs a LoRa-based air quality online monitoring system to monitor pollutant gases in the monitoring area in real time online,and constructs a GM（1,1）gray prediction model to predict the pollutant gases.The main work of the paper is as follows.（1）The air quality online monitoring system is designed.By forming a LoRa star topology network,the pollution gas concentration data collected by the monitoring nodes are transmitted to the LoRa gateway through the network,and the GPRS module is used to upload the data to the cloud platform to realize the remote monitoring of air quality,and users can log in to the cloud platform and cell phone terminal to monitor.（2）The system hardware and software are designed and implemented.The hardware mainly includes the hardware circuit of the monitoring node and the hardware circuit of the LoRa gateway.The software part includes the monitoring node entry and data upload,the communication protocol between the monitoring node and the LoRa gateway,the connection between the LoRa gateway node and the cloud platform,and the application development for the cloud platform.（3）Three improvement methods of gray prediction are proposed for the problems of the original sequence samples.For the problem that the original sequence data fluctuates a lot,a gray prediction model based on function transformation is proposed;for the problem that the original sequence is not suitable with the background value,a prediction model of background value reconstruction is proposed;for the problem that the outside world interferes with the original sequence,a metabolism prediction model is proposed.The pollution gas concentration data collected from monitoring nodes are used as the original sequence of the gray prediction model,and the prediction results are compared and analyzed,and the results show that the metabolic prediction model has a better prediction effect on the gas concentration.（4）A regionalized small-scale air quality monitoring system was built in a region,and the LoRa communication distance,packet loss rate and Received Signal Strength Indication（RSSI）were experimentally tested in a densely built urban area and an open suburban area,respectively,for the online air quality monitoring system.The data collected by the monitoring nodes are compared with the national standard air quality monitoring equipment,and the results meet the air quality monitoring accuracy requirements of this thesis.Through the test this system operates stably and can realize the online monitoring of air quality in the monitoring area,which has good application prospects.