Research And Application Of Data Fusion Based On Deep Learning In Air Quality Monitoring

In recent years,the industrialization and modernization of the society has been developed to a certain extent.The scale of the city is getting larger and larger,and the number of urban population is increasing.It is these factors that increase the emissions of industrial and automobile exhaust,and bring a lot of environmental problems.It is precisely because of the imbalance between environment and development that air quality problems in cities have become increasingly prominent.Air quality is not only closely related to people’s health and life,but also has an impact on the sustainable development of society.Therefore,real-time and comprehensive monitoring of air quality becomes particularly important.In air quality monitoring,it is inevitable to encounter accidents such as damage to the monitoring equipment and the relocation of the station building,resulting in the lack of monitoring data.In response to this lack of monitoring data,in this paper,the data fusion technology based on deep learning supplements the missing data and implements an air quality monitoring system.This paper studies the methods of deep learning and data fusion.In order to improve the referenceability of data,based on the deep belief network,a data fusion method to improve the deep belief network is proposed to supplement the missing data in response to the lack of monitoring data.Compared with the traditional deep belief network fusion method of multi-source data,it can effectively provide relevant researchers with reference data for further analysis and research on air quality.In order to monitor air quality from multiple angles and in all directions,an air quality monitoring system is designed and implemented by combining air quality monitoring data,meteorological monitoring data and data fusion method based on deep learning,which includes user login,real-time air quality,period monitoring,user management,relevant knowledge and other modules.Through a comprehensive test and evaluation of the system,the system can provide certain technical support for effective monitoring of air quality,and has a certain use value.