Wide-area water status visualization system and method using artificial intelligence analysis

Abstract

The invention discloses a wide-area water status visualization method using artificial intelligence analysis, which includes the following steps: firstly calculate at least one change feature of the historical data of water body parameters uploaded by at least part of the monitoring sites in the water area, and obtain the change characteristics of each monitoring site Then, based on the indicator vector, the monitoring sites are classified according to the changes of water body parameters, and multiple classes are obtained. After that, in the current update round, the number of monitoring sites with updated data contained in each class is different. If it is lower than the update percentage or update quantity threshold of the corresponding class, analyze the parameters of the current update round for the water area, obtain the water area analysis result, and finally display the water area analysis result. This method can enable the system to not affect the parameter analysis and display of the current update round when the water body parameter collection and uploading of some monitoring sites are not synchronized, so as to ensure that the staff can understand the water situation on time.

Description

technical field [0001] The invention relates to the technical field of water monitoring, in particular to a wide-area water state visualization system applying artificial intelligence analysis, and a wide-area water state visualization method applying artificial intelligence analysis. Background technique [0002] In the water management of smart cities, monitoring points can be arranged within the water body, and various types of water parameters such as water quality and flow velocity can be measured at each monitoring point through multi-functional sensor equipment, and then the water body parameters can be uploaded to the water system. Platform server for analysis and display. [0003] When facing a water body with a very wide spatial distribution, such as a large lake or a water system covering the entire urban space, in order to ensure the reliability of the data, it is necessary to arrange a sufficient number and density of monitoring points when performing the above ...

AI Technical Summary

Problems solved by technology

[0007] In addition, for the display content of the platform, if the water body parameters of a large number of monitoring points are directly superimposed on the water body map for display, the visual effect will be poor, which may cause misunderstandings by the water platform staff when watching , and it is difficult for the staff to find the key areas worthy of attention in the wide-area water body

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