A Grassland Drought Monitoring System and Method Based on Computer Vision and Internet of Things

Abstract

The invention discloses a grassland drought status monitoring system based on computer vision and the Internet of things and a grassland drought status monitoring method. The system comprises an image acquisition unit, an Internet of things control unit, a communication unit and a computer vision processing unit, wherein the image acquisition unit and the communication unit are respectively in communication connection with the Internet of things control unit, the communication unit communicates with the computer vision processing unit through the network, the Internet of things control unit controls the image acquisition unit for acquiring images of plants from different angles, the images are transmitted through the communication unit to the computer vision processing unit, and the images acquired from different angles are analyzed and processed by the computer vision processing unit to acquire a drought status of the plants. Through the system and the method, the image processing speed and accuracy can be improved, under the common action of the Internet of things module and the computer vision module, grassland degradation and the drought status can be warned in advance, and thereby remote drought monitoring can be realized.

Description

technical field [0001] The invention relates to a grassland drought monitoring system based on computer vision and the Internet of Things, belonging to the field of agricultural information technology. Background technique [0002] With the economic development and population expansion of human beings, the shortage of water resources is becoming more and more serious, which directly leads to drought disasters. Drought trends have become a global concern. In order for people to minimize the disasters caused by drought, it is necessary to perceive the coming of drought and the water shortage of plants as early as possible. [0003] Such as figure 1 As shown, in the prior art, there is a plant growth status monitoring system based on computer vision and the Internet of Things to detect the water shortage status of plants in terms of plant growth status detection. Specifically, the relevant key technologies of the system are: it includes a high-speed DSP (Digital Signal Proce...

AI Technical Summary

Problems solved by technology

[0004] In the prior art, the plant leaves in the color image are detected by the DSP image processing module. The entire optimization process consumes a lot of labor and time. The use of the DSP system inevitably has some limitations compared to the computer hardware system.

The existing technology uses traditional methods such as histogram analysis and mean value filtering, which have the advantages of fast speed and easy transplantation. These methods are relatively simple, with low accuracy and poor adaptability

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