Study On The Analysis Of Big Data Of Fog And Haze Based On Internet Of Things And Its Efficiency

In recent years, fog and haze frequently occurred, which seriously influenced on people’s daily lives. Recent research demonstrates that PM2.5 and PM10 are the main factors in the formation of fog and haze. With establish a complete real-time monitoring information system of air quality, we can provide the scientific and accurate decision-making information for the prevention and control of fog and haze by the analysis of these data.Big data of fog and haze based on Internet of Things is the important basis for analysis and forecast of fog and haze. With the continuous accumulation of fog and haze monitoring data, a lot of unavailable data has increased, which leads to reduce the quality of monitoring data. Only ensure the availability of fog and haze monitoring data, the analysis of fog and haze monitoring data is significant. In this paper, data examination of fog and haze monitoring data were studied to improve the data availability, which lay a solid foundation for the study on the efficiency analysis and the efficiency forecast of fog and haze monitoring data.On the basis of the available data, this paper study the effectiveness forecast of fog and haze monitoring data. A forecast model based on Bayesian network is established to forecast the effectiveness level of fog and haze monitoring data from probability inference. Considering the nonlinear effect of each attribute in fog and haze monitoring data, this paper establishes the B-P neural network forecast model. The results show that the good performance of Bayesian network model and B-P neural network model in the effectiveness forecast of the fog and haze data, which proves the feasibility of the effectiveness forecast of the fog and haze data.