Method and equipment for identifying terminal user

Abstract

The invention discloses a method and equipment for identifying terminal users, which are used for identifying genders, ages and special groups of various terminal users and carrying out strategy recommendation on various terminals according to different application scenes. The method comprises the following steps: identifying sample data corresponding to different types of terminals through an edge data center according to network types and operating system versions in various types of collected sample data of the terminals; determining sample data corresponding to a preset type of terminal from the identified sample data corresponding to different types of terminals; and determining a preset user type corresponding to the sample data of the preset type terminal according to the sample data corresponding to the preset type terminal and an operating system version used by the preset user type.

Description

technical field [0001] The present invention relates to edge data, in particular to a method and device for identifying terminal users. Background technique [0002] In the prior art, although the monitoring system can be used to identify user groups, it has the following defects: [0003] Traditional user groups are manually monitored through closed-circuit television in the monitoring scene, which is time-consuming and laborious and lacks objectivity, and the workload is huge, the efficiency is low, quantitative judgments cannot be made, and user identification is highly subjective; [0004] The real-time monitoring system based on closed-circuit television uses some relatively simple image processing methods to extract the characteristics of the passenger group in the image. However, if this technology is applied to a scene with a high number of passenger groups, there will be a high misjudgment rate. , the reason is that there is an obvious overlap between people in the...

AI Technical Summary

Problems solved by technology

[0003] Traditional user groups are manually monitored through closed-circuit television in the monitoring scene, which is time-consuming and laborious and lacks objectivity, and the workload is huge, the efficiency is low, quantitative judgments cannot be made, and user identification is highly subjective;

[0004] The real-time monitoring system based on closed-circuit television uses some relatively simple image processing methods to extract the characteristics of the passenger group in the image. However, if this technology is applied to a scene with a high number of passenger groups, there will be a high misjudgment rate , the reason is that there is an obvious overlap between people in the number of high-density passenger groups, and it is difficult to identify them using image processing technology;

[0005] Faced with the increasing popularity of network terminals and the rapid development of 5G networks, in the existing technology, the 5G edge data center has not been used to analyze and judge the user terminals of various groups, identify and judge the gender, age and whether they are special or not. group

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