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Surface water monitoring and management system and method

A monitoring management and surface water technology, applied in neural learning methods, instruments, biological neural network models, etc., can solve problems such as failure to warn, ignore floating objects on the water surface and obvious changes in water body color, etc., and achieve accurate identification.

Active Publication Date: 2022-01-21
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 changes such as floating objects on the water surface and the color of the water body, so that it is impossible to give early warning in time when the water quality changes

Method used

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  • Surface water monitoring and management system and method
  • Surface water monitoring and management system and method
  • Surface water monitoring and 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 present invention relates to the technical field of water resource monitoring, in particular to a surface water monitoring and management system, comprising: a collection unit for collecting water body images of surface water surfaces in real time; a filtering unit for filtering water body images; a storage unit, It is used to store the filtered water body image; the training unit is used to obtain the neural network model; the processing unit is used to perform floating object recognition and color recognition on the filtered water body image, judge whether the water body is abnormal, and correct the water body when the water body is abnormal. The abnormal area in the water body image is marked; the display unit is used to display the marked area on the visual interface. The invention combines the neural network to identify the floating objects and colors of the water sample image, marks the abnormal area, and displays it in a visual way, which solves the problem that the existing technology ignores the obvious changes in the floating objects on the water surface and the color of the water body, so that the water quality cannot be improved. It is a technical problem of timely early warning when changes occur.

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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Patent Type & Authority Patents(China)
IPC IPC(8): G06V20/10G06V10/26G06V10/44G06V10/56G06V10/75G06V10/764G06V10/82G06K9/62G06N3/04G06N3/08
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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