Grass and original ecology data monitoring and intelligent decision-making integrated solution system
A data monitoring and intelligent decision-making technology, applied in the field of Internet communication technology and artificial intelligence, it can solve the problems of data aggregation and analysis errors, limited data resolution, and inability to be returned in time, achieving low transmission delay, wide coverage, The effect of improving classification recognition
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Embodiment 1
[0087] see figure 1 , under the framework of the air-space-ground integrated communication system, the present invention utilizes UAVs equipped with multiple wireless sensors and multi-device collaboration acquisition methods to achieve ecological data perception with wide dynamic coverage and low data transmission delay. This function mainly realizes the collection of ecological environment data and ecological video data of the target area, and will provide data support for the subsequent ecological data analysis function. The whole design idea is to firstly use multi-UAV cooperation to realize dynamic area acquisition with wide coverage, and then upload massive data to the cloud server through access to 5G or satellite communication network, and display the video data of the target area in real time on the ground station interface , and use the Alibaba Cloud OSS storage service to store data in a fixed file path in an orderly manner for subsequent data query, modification, a...
Embodiment 2
[0101] The main modules involved in this system include: ecological environment data acquisition module, video data acquisition module in the target area, sensor module, data processing module and cloud service platform module, which are described as follows:
[0102] Ecological environment data collection module:
[0103] see image 3 and Figure 4 , ecological environment data monitoring mainly includes the acquisition of four types of data: water, soil, land, and light. There are many factors such as the need to compare and correct the data of multiple sensors of the same type with the same coverage radius, the sensor material should be heat-resistant and wind-resistant, and the sensor’s sensitivity to environmental perception. Therefore, sensors with high sensitivity and materials suitable for outdoor deployment are selected. The sensitive element converts the perceived ecological environment signal into a voltage signal that can be sampled through the signal conditionin...
Embodiment 3
[0121] The grassland plant classification recognition algorithm based on convolutional neural network involves modules including: data enhancement module, feature extraction network module, classification recognition module, attention mechanism module and GUI interface module (see Figure 11 ).
[0122] Data augmentation module:
[0123] Using single-sample ensemble transformations as well as multi-sample synthetic data augmentation. (1) Single-sample collection Transformation includes flipping, rotating, translating, cropping, and scaling. This method does not change the image itself, but only selects a part of the image or redistributes the pixel space. The schematic diagram of single-sample data enhancement is as follows: Figure 13 shown. (2) Multi-sample synthetic data enhances CutMix, randomly generates a cropping frame, cuts out the corresponding position in image A, and then uses the ROI of the corresponding position in image B to be placed in the cropped area in i...
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