With the help of "artificial intelligence", "visualization", "WeChat applet APP", "self-built server" and other technologies, we are now pleased to introduce our "TA seeking" WeChat applet to you. It is an intelligent matching clues and help information to find people (children) APP. We have always believed that technology can fight crime. In remote areas, hardware conditions are no longer a barrier to the advancement of the legal system. 1. Brief introduction of the core functions of TA (WeChat) applet: WeChat applet has the characteristics of fast startup and no installation, which is in line with the urgent use scenario of looking for children. (1) General information page (home page): You can see the "Help" or "Leads" information posted by users of this program in the home page. Similarly, click "I want to query" at the top of the panel to open the search box, where you can search for what you want. Similarly, on the right side of the panel, we have designed a selector, so you can filter different places, different children's characteristics, etc. by place. At the same time, if users find a suspected lost child on the homepage, they can ask the discoverer online. Our WeChat applet also supports chat. (2) Release information: You can post two different kinds of messages, -- clues -- and when you find a suspected missing child, you can upload this clue. ---- Help ----, when you are accidentally separated from your child and cannot find it, you can use the post help function. After publishing for help, the system will automatically match the clues of the database for you. (3) Personal center: Here you can see the number of messages you posted. And you can manage the content you publish, such as deleting the content you publish. And, when the applet backend matches a clue that may be relevant to your help, it will send a notification here. You can view the newly matched leads. (4) 3D visualization system: In order to present the relevant information clearly to the user, we introduce the visual design. Using visualization (graphics implementation), multiple pieces of data in the collection are collectively displayed and returned to the front-end page, which will display the location of the child on the map, and click on different "data" to display the corresponding "data elements". In addition, we also use Shader occlusion culling, the implementation principle is to test the depth of the graphics, so that the character is occluded can show the XRAY effect. 2. Introduction to TA (WeChat) applet programming: (1) Data structure: Data structure We use "parallel search set" to efficiently manage the dependency between clues and help, and when clues are associated with clues, they are merged into a set. When the clue matches the help, merge the collection and use the help as the root of the tree to speed up the program. (2) Core design artificial intelligence and data visualization algorithms: I used my own artificial intelligence program to run on the back end of the server. The face recognition algorithm uses PCA LDA implementation (abbreviation: Fisher linear discrimination and main component analysis). The algorithm has the characteristics of fast speed and accurate recognition. The visualization is divided into two-dimensional and three-dimensional systems, in which the two-dimensional system shows the regional distribution and quantity statistics of "missing child cases" in recent years, while the three-dimensional system shows the location of data elements in the data collection. (3) Server back end: The server is responsible for computing AI-related content and returning the results to the front end. Also responsible for writing and checking the database. The server is our own Aliyun server, and the performance is not particularly high, so the computing content is transferred to another local high-performance computer through Socket communication. The server backend is served by open source free Tomcat as a web container. The back-end interface aspect is written in the 1.17 version of the Java language, which is the latest LTS long-term support version of the Java language.