Surface water monitoring management system and method

A technology for monitoring and management of surface water, applied in neural learning methods, instruments, biological neural network models, etc., can solve the problems of unwarranted, ignoring water surface floating objects and water color and other obvious changes.

Active Publication Date: 2021-02-26
重庆市生态环境大数据应用中心
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] The invention provides a surface water monitoring and management system, which solves the technical problem that the existing technology ignores the obvious chan

Method used

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  • Surface water monitoring management system and method
  • Surface water monitoring management system and method

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Experimental program
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Embodiment 1

[0051] The embodiment of the surface water monitoring and management system of the present invention is basically as attached figure 1shown, including:

[0052] The acquisition unit is used to collect the water body image of the surface water surface in real time and send the water body image;

[0053] The filtering unit is used to receive the water body image, perform filtering processing on the water body image, and send the filtered water body image;

[0054] a storage unit, configured to receive the filtered water body image and store the filtered water body image;

[0055] The training unit is used to obtain the filtered water body image, generate corresponding multi-scale training sample data based on the filtered water body image, and use the multi-scale training sample data to train the neural network to obtain a neural network model;

[0056] The processing unit is used to identify floating objects on the filtered water body image according to the neural network mod...

Embodiment 2

[0074] The only difference from Embodiment 1 is that when identifying the floating object, it is first identified by an edge detection algorithm, and if the floating object cannot be identified, then it is identified based on the key point data. The steps of identifying floating objects through the edge detection algorithm are as follows: First, image segmentation processing is performed on the water body image, for example, image segmentation processing is performed on the water body image collected this time using region segmentation technology, and information irrelevant to the water body is removed to obtain the segmented Image. Then, grayscale processing is performed on the segmented image, for example, the color water body image is processed into a grayscale water body image by using a maximum value method, an average value method or a weighted average value method. Finally, the edge detection algorithm is used to identify the floating objects in the grayscale water imag...

Embodiment 3

[0076] The only difference from Embodiment 2 is that it also includes a collection device, such as the attached figure 2 As shown, the collection device includes: a first pole 1, a second pole 2, a rotating rod 3, a pin 4, a spring 5, a tension sensor 6, a controller 7, a water quality detector 8, a filter plate 9, and a housing 10 . The housing 10 is cylindrical, and the left and right ends of the housing 10 are equipped with filter plates 9, for example, by screws; the filter plates 9 are drilled with a plurality of filter holes. One end of the first strut 1 is welded on the inner wall of the housing 10, and the controller 7 and the water quality detector 8 are fixedly installed on the other end of the first strut 1, for example, by screws or by steel wires. One end of the second pole 2 is welded on the inner wall of the housing 10 , and the other end is hinged with the rotating rod 3 , that is, hinged through the pin 4 , and the rotating rod 3 can rotate freely around the...

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Abstract

The invention relates to the technical field of water resource monitoring, in particular to a surface water monitoring management system, which comprises: an acquisition unit for acquiring a water body image of the surface water surface in real time; the filtering unit that is used for filtering the water body image; the storage unit that is used for storing the filtered water body image; the training unit that is used for obtaining a neural network model; the processing unit that is used for carrying out floater identification and color identification on the filtered water body image, judgingwhether the water body is abnormal or not and marking an abnormal area in the water body image when the water body is abnormal; and the display unit that is used for displaying the marked area on thevisual interface. Floating object and color identification is performed on the water sample image in combination with the neural network, the abnormal area is marked and displayed in a visual mode, and the technical problem that in the prior art, obvious changes of water surface floating objects, water body colors and the like are ignored, so that early warning cannot be performed in time when the water quality changes is solved.

Description

technical field [0001] The invention relates to the technical field of water resources monitoring, in particular to a surface water monitoring and management system and method. Background technique [0002] Surface water refers to the general term of dynamic water and static water on the land surface, including various liquid and solid water bodies, mainly including rivers, lakes and glaciers, which are very important sources of water for human life. With the increasing environmental pollution, it is particularly important to monitor the water quality of surface water such as rivers and lakes. [0003] For example, Chinese patent CN110456722A discloses a lake water quality monitoring and prediction system, including an image acquisition module, an image preprocessing module, a water quality detection module, a temperature detection module, a processing module, a water quality database, a prediction evaluation module and a display terminal; the image acquisition module It is...

Claims

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Application Information

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IPC IPC(8): G06K9/00G06K9/34G06K9/46G06K9/62G06N3/04G06N3/08
CPCG06N3/04G06N3/08G06V20/10G06V10/267G06V10/44G06V10/56G06V10/751G06F18/241
Inventor 刘明君余游刘海涵刘晓米雪晶耿京保刘建林
Owner 重庆市生态环境大数据应用中心
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