Urban air quality monitoring method based on mobile multi-source perception

Abstract

According to the urban air quality monitoring method based on mobile multi-source perception, in the stage of obtaining mobile air quality parameters, an environment monitoring sensor and a combined positioning module are used for recording the time position of a mobile carrier (a pedestrian wearable type, a shared bicycle, public transport and an unmanned aerial vehicle) at each collection pointand the environment parameters of the position; in the multi-source data processing stage, a data processing and storing module is used for carrying out heterogeneous fusion, denoising and filtering,space-time interpolation and database construction on the mobile air quality data; in the environment space-time analysis and evaluation stage, a clustering algorithm and thermodynamic diagram visualization are used for carrying out data modeling and space-time analysis on multi-source air data. Compared with traditional environment fixed monitoring, the method has the advantages that the number and cost of fixed monitoring nodes are greatly reduced in a mobile and multi-carrier data acquisition mode, noise is reduced through Kalman filtering, discrete points are interpolated to uniform grid space discrete points through a weighted K-nearest neighbor interpolation algorithm to draw a curved surface, and visualization is achieved.

Description

technical field [0001] The invention belongs to the field of urban air monitoring and relates to an urban air quality monitoring method based on mobile multi-source perception. Background technique [0002] The air quality of urban environment has an important impact on the health of residents. However, the extensive economic development mode has brought serious air pollution, which poses a threat to people's health. Therefore, the monitoring and governance of urban ambient air is imperative. At present, for the fixed-point monitoring of gas pollutants, foreign developed countries and regions have successively established relatively complete monitoring networks, and adopted statistical analysis techniques such as correlation analysis and cluster analysis. The country initially established a national air quality monitoring base station and network system in the 1990s. [0003] The existing air quality fixed monitoring network still needs to further optimize the station layo...

AI Technical Summary

Problems solved by technology

Therefore, in view of the shortcomings of traditional monitoring methods such as poor mobility and low timeliness, the use of crowdsourcing and multi-carrier data collection methods can greatly expand the scope of data collection and improve the efficiency of environmental monitoring.

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