Flying dust detection method and system applied to urban governance

Abstract

The embodiment of the invention provides a flying dust detection method and system applied to urban governance, and the method comprises the steps: obtaining a video data flow and a sensor data flow,and carrying out the preprocessing of the video data flow and the sensor data flow; obtaining a dust raising graph, comparing the dust raising graph with the pictures in the video data stream, and identifying the dust raising graph; multiple sensor data streams are acquired and compared with a preset raise dust threshold value, and the data streams higher than the raise dust threshold value are raise dust data streams; taking the raise dust graph and the raise dust data flow as samples, inputting the samples into a pre-trained classifier, detecting whether raise dust exists or not, transmitting a detection result to a server, and performing visual display on an upper computer. According to the invention, real-time video streams and sensor data in a fixed scene are collected, and two statesof flying dust and non-flying dust are distinguished through data comparison, so the purpose of accurately identifying the flying dust is achieved.

Description

technical field [0001] The invention relates to the technical field of dust detection, in particular to a dust detection method and system applied to urban governance. Background technique [0002] Flying dust is an open pollution source that enters the atmosphere due to the dust on the ground being driven by wind, man-made or other drives, and is an important part of the total suspended particulate matter in the ambient air. Construction in house building. Dust particles are generated during human activities such as road and pipeline construction, house demolition, material transportation, material stacking, road cleaning, plant planting and maintenance, which easily pollute the atmosphere. [0003] Traditional fugitive dust detection method: obtain the image to be recognized from the collection point of fixed source dust, perform decomposition domain transformation in the spatial domain, decompose the image information into multiple scale spaces, and use the gradient oper...

AI Technical Summary

Problems solved by technology

Because external environmental factors (lighting, other object interference, etc.) have high requirements on the accuracy of the picture, the extraction has a great impact, and the noise points must be removed through multiple image preprocessing, and the uncertain factors increase. The accuracy of image recognition is low

Images