An intelligent environment monitoring system and method based on image recognition

Abstract

The present invention provides an intelligent environment monitoring system based on image recognition, comprising: an image acquisition unit for acquiring images in an environment monitoring area; a task dispatching unit for dispatching tasks to the image acquisition unit; an image preprocessing unit for It is used to preprocess the collected images and screen the processed images according to the tasks; the image analysis unit is used to identify the screened images according to the deep neural network; the disposal and emergency unit is used to The recognition result is matched with the preset emergency plan, and the matching result is generated and output; the present invention can use the existing image acquisition system to preprocess and screen the image without using large-scale laying of special sensors, which can not only reduce the cost, It can also realize an intelligent and efficient environmental monitoring system, which can provide more intensive and accurate feedback on environmental issues, and provide powerful tools and solutions for environmental protection.

Description

technical field [0001] The invention relates to the field of environment detection, in particular to an image recognition-based intelligent environment monitoring system and method. Background technique [0002] With the economic growth, the resources stored in nature are widely developed and utilized. Due to the establishment of densely populated large cities and industrial and mining areas, a large amount of chemical substances have entered the environment, surpassing the self-purification ability of nature, and continuously accumulating in the environment, resulting in public hazards that endanger human survival. In order to find the reasons for the change of environmental quality, it is necessary to start with the analysis of the nature, source, content and distribution of pollutants. However, to judge whether the environmental quality is good or bad, it is not enough to analyze the sample of a single pollutant for a short period of time. There must be data representing...

AI Technical Summary

Problems solved by technology

[0003] At present, the monitoring of the environment generally uses special sensors (such as particle detectors) or manually collects samples for evaluation (such as manual random inspection of dust pollution on construction sites). These monitoring methods generally require the deployment of a large number of special sensors. On the one hand, the cost is relatively high. On the other hand, the construction is often difficult, and the efficiency of manual monitoring is very low, and is limited by the experience of the operator, and the monitoring results will be inaccurate due to human factors

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