Artificial intelligence analysis-based gem and jade identification certificate generation system

Abstract

The invention discloses a gem and jade identification certificate generation system based on artificial intelligence analysis, and the system comprises a gem and jade detection data collection module which collects gem and jade physical information, converts the gem and jade physical information into digital information, and stores the digital information; the gem and jade detection data standard management module is used for setting a gem and jade data standard dictionary database and configuring and managing digital information of different types of gems and jades according to a data node tree; the gem and jade data detection large model is used for analyzing multimedia parameters and physical parameters of gem and jade and completing market value evaluation; and the gem and jade digital certificate output module is used for issuing and displaying the gem and jade digital certificate. According to the gem and jade authentication certificate generation system based on artificial intelligence analysis, the authentication result can be automatically obtained, and the corresponding digital certificate is generated.

Description

TECHNICAL FIELD

[0001] The present application relates to a gemstone identification certificate generation system, and in particular to a gemstone identification certificate generation system based on artificial intelligence analysis. BACKGROUND

[0002] The existing gemstone identification certificate generation system mainly has the following problems: 1. Artificial identification is prone to deviation.

[0003] 2. The overall identification process requires human intervention, and the identification period is long.

[0004] 3. In the identification process, the identification standards of various gemstones are unevenly implemented in different places, which can easily lead to inaccurate identification results.

[0005] Therefore, a gemstone identification certificate generation system based on artificial intelligence analysis is provided, which can establish a basic model according to the national identification standard, input the relevant parameters, product pictures and optical spectrum of various gemstones into the identification algorithm model, automatically obtain the identification result, and generate the corresponding digital certificate. SUMMARY

[0006] The technical problem to be solved by the present application is to provide a gemstone identification certificate generation system based on artificial intelligence analysis, which can automatically obtain the identification result and generate the corresponding digital certificate.

[0007] To solve the above technical problems, the present application provides a gemstone identification certificate generation system based on artificial intelligence analysis, which comprises: a gemstone detection data acquisition module for collecting gemstone physical information, converting gemstone physical information into digital information and storing; a gemstone detection data standard management module for setting a gemstone data standard dictionary library and configuring and managing the digital information of different types of gemstones according to the data node tree; a gemstone data detection large model for analyzing the multimedia parameters and physical parameters of gemstones and completing market value evaluation; a gemstone digital certificate output module for completing gemstone digital certificate issuance and display.

[0008] Further, the gemstone detection data acquisition module comprises: a multimedia resource collector for collecting and storing gemstone images, including product surround 3D images, photos and spectrum photos; a digital resource collector for converting gemstone physical information into digital information and storing; and a third party resource collector for obtaining digital information and multimedia information through a third party interface.

[0009] Further, the gemstone detection data standard management module comprises: a gemstone data standard dictionary library containing identification standards, market value evaluation standards, similarity threshold range standards, and data entry standards of various gemstones; a gemstone data node tree management module recording additional node information and corresponding node fields of each gemstone, wherein the node information comprises mine information, customs information, and processing information; the mine information comprises the country of origin, mine, and time; the customs information comprises the customs declaration number and time; and the processing information comprises the processing country, processing content, and time.

[0010] Further, the gemstone data node tree management module supports dynamic expansion of node structure, dynamically adds and modifies node attributes through a graphical interface, and models the implicit association between gemstone nodes using a graph convolution network to output a visual knowledge graph.

[0011] Further, the gemstone data detection large model comprises: a gemstone digital AI large model analyzing multimedia parameters and physical parameters of gemstones to complete market value evaluation; a gemstone algorithm basic configuration module mainly adjusting and reallocating the basic values and proportions of various parameters in the algorithm, which can choose to restart the calculation and evaluation or choose to repair historical data; and a big data screening and duplication detection module screening multimedia and digitized digital codes, mainly comparing the generated codes with historical data in terms of similarity, and when the similarity exceeds a preset percentage, issuing a warning and separately screening them out for subsequent manual confirmation.

[0012] Further, the gemstone digital AI large model adopts a multi-modal fusion architecture based on Transformer, simultaneously encodes high-resolution images, spectral data, 3D point cloud data, and physical parameters, and realizes semantic alignment between features through cross-modal attention mechanism.

[0013] Further, the gemstone digital AI large model scores according to the following formula: GEMAI = (0.15×T + 0.20×V + 0.18×RI + 0.22×C + 0.12×O + 0.08×I +0.05×P) × CF; T is the gemstone type value coefficient, V is the volume coefficient, RI is the refractive index coefficient, C is the color score coefficient, O is the origin coefficient, I is the inclusion system coefficient, P is the processing method, and CF is the correction stamp. The default value of T is 0.6, and according to market scarcity classification, it is as follows: diamond: 1.0, ruby / sapphire: 0.95, emerald: 0.90, golden green cat's eye: 0.88, spinel: 0.85, and other rare gemstones: 0.8. V = log10(Volume mm3) / 2 x Cut Correction Factor, and V value x extra value as carat premium when weight > 1 carat; RI = (Measured RI - 1.3) / (2.5 - 1.3) + Dispersion value x 0.2; C = 0.5-1.0; for preset rare color, C = 1.0; for other color, C = 0.5 + (Saturation% / 200), when Saturation > 80%, C = 0.8 + (Lightness% / 100) x 0.2; I = 1 - (Inclusion number x 0.05 + Maximum size mm x 0.3) + Special inclusion bonus; Special inclusion bonus as follows: Ceylonese hair inclusion + 0.2, Dauphine structure + 0.1. CF = 1 + Certificate bonus + Optical effect bonus; GIA certificate + 0.15, other authoritative certificate + 0.1, fire / starlight / cat's eye + 0.2.

[0014] Further, the gemstone digital certificate output module comprises a terminal digital certificate display module, which mainly displays the gemstone digital certificate, including the picture of the gemstone, the basic physical parameters of the commodity, part of the node information on the supply chain and the evaluation information given by the large model; the terminal digital certificate display module integrates an augmented reality visualization component, which displays the gemstone three-dimensional model in real time, simulates the optical effects with optical effect bonus, and visually labels the key physical parameters; a terminal digital certificate security authentication module is used for security authentication of the digital certificate, protection of the number of daily logins for the same IP address, setting of a security firewall to prevent data crawling, and provision of a query interface whitelist and interface call encryption protection for third parties.

[0015] Further, the gemstone digital certificate output module further comprises a terminal property right management module, which binds and authenticates the digital certificate through real-name authentication, and the holder of the binding can view all information of the digital certificate and has the right to hide or display the related information, and can input related transaction information; when the property right is transferred, the property right transfer process is triggered, the digital certificate is temporarily transferred to the new holder account through the property right transfer process, and the transfer is completed after real-name authentication, the new holder can input transfer remarks, and the digital certificate is used as a digital transaction certificate, and the transfer operation is completed after confirmation by the original holder; the related property right transfer record is recorded and authenticated on the blockchain as a node for traceability.

[0016] Further, the gem digital certificate output module also comprises a certificate storage and traceability module based on a block chain, the hash value of each digital certificate after generation is written into the block chain, and all queries and verification operations on the certificate are recorded through a smart contract, ensuring that the data is not tamperable and the operation is auditable.

[0017] The gem identification certificate generation system based on artificial intelligence analysis provided by the present application can automatically obtain an identification result and generate a corresponding digital certificate, and has the following advantages: 1. The data basis is strictly implemented according to national standards, and the identification content, range and conclusion are all based on unified standards. 2. The AI large model outputs the result according to the numerical content, ensuring consistency. 3. The certificate issuing efficiency is improved, and is no longer dependent on manual operation, and the cycle is shortened. BRIEF DESCRIPTION OF DRAWINGS

[0018] Figure 1 The gem identification certificate generation system based on artificial intelligence analysis provided by the present application is shown in the accompanying drawings. Figure 2 The score result graph of the gem identification certificate generated by the present application is shown in the accompanying drawings. Figure 3 The block chain authentication result graph of the gem identification certificate generated by the present application is shown in the accompanying drawings. Figure 4 The gem identification certificate cover and directory generated by the present application are shown in the accompanying drawings. DETAILED DESCRIPTION

[0019] The present application will be further described below in combination with the accompanying drawings and embodiments.

[0020] Figure 1 The gem identification certificate generation system based on artificial intelligence analysis provided by the present application is shown in the accompanying drawings.

[0021] Please refer to Figure 1 The gem identification certificate generation system based on artificial intelligence analysis provided by the present application comprises four parts: a gem detection data acquisition module, a gem detection data standard management module, a gem data detection large model and a gem digital certificate output module.

[0022] I. Gem detection data acquisition module This module mainly has three parts: a multimedia resource collector (for image collection and storage, mainly commodity surround 3D graph, photo and spectrum photo), a digital resource collector (gem physical information is converted into digital information and stored) and a third party resource collector (digital information and multimedia information are obtained through a third party interface); 1、Multimedia resource collector is used for image collection and storage, mainly the commodity around 3D map, photo and spectral photo; gem has particularity and uniqueness, although the same shape and the same color of gem may look exactly the same, but in fact each gem has its own unique identification, this module is through the large model to record and save the image; large model can accurately record the shape of each gem image, mineral inclusions, the position of the flaw, according to the shape, position, number and type of flaw or inclusion to generate the corresponding code, and then combined with the data coding of digital resource collector to provide to the big data detection model for identification and use; 2、Digital resource collector is used for collecting and storing physical parameters, mainly the physical attribute parameters of the commodity, such as commodity type, origin, processing method, color and size, etc.; this part of data is different from multimedia data, with high similarity, but is an important reference for measuring market value, through the large model to generate corresponding code and multimedia collector data code together to provide to the big data detection model for identification and use; 3、The third party resource collector mainly obtains multimedia and physical parameter information transmitted by the third party interface, the interface will have a source field and define the data format (such as commodity type, size, origin, processing method, commodity picture field); after white list and interface information security check, the data meeting the data format requirements are transmitted to the multimedia resource collector and digital resource collector for processing.

[0023] II. Gem detection data standard management module This module mainly has two parts: gem data standard dictionary library (defines various standards in the system) and gem data node tree management module (configure and manage digital information of different types of gem); 1、Gem data standard dictionary library is the basis of the whole system, which includes all gem identification standards (the standard mainly refers to the corresponding national standard of China), market value evaluation standard (the standard mainly refers to the collected market price), similarity threshold range standard (this part is compiled according to historical data, especially a large number of imported gem data, and according to the requirements of the supervising customs) and data entry standard, etc.; The similarity threshold range standard can be set as follows: similarity value between 80-90 is defined as possible similarity, 90-95 is defined as similarity, and above 95 is defined as extremely similar. Possible similarity will be checked, with a probability of ten to two; similar will also be checked, with a probability of five to three; extremely similar will be checked every time.

[0024] 2、Gemstone data node tree management module mainly records the additional node information and corresponding node fields (including multimedia parameters and physical parameters) of each gemstone, which can enrich the content of gemstone ai digital certificate. Currently, it records mineral information (country of origin, mine and time), customs information (customs declaration number and time), and processing information (processing country, processing content and time).

[0025] The gemstone data node tree management module supports dynamic expansion of node structure, allows users to customize node attributes according to the characteristics of gemstone categories, and can mine and model the implicit relationship between nodes through graph neural network (GNN), realizing deep analysis of gemstone traceability and quality correlation. For example, the gemstone data node tree management module supports users to dynamically add and modify node attributes through graphical interface, and uses graph convolution network (GCN) to model the complex relationship between gemstone nodes (such as the implicit correlation of origin-quality-market price), output visual knowledge graph, and assist appraisers to make more comprehensive judgments.

[0026] III. Gemstone data detection large model This module mainly has three parts: gemstone digital AI large model (algorithm model calculation) and gemstone algorithm basic configuration module (management of various coefficients and weighting content in algorithm) and big data discrimination verification module (discrimination confirms data similarity to prevent gemstone repeated identification); 1. The large-scale digital AI model for gemstones primarily analyzes the multimedia and physical parameters of gemstones to evaluate their market value. Multimedia parameters reveal surface flaws and inclusions, with the size and number of these flaws and inclusions affecting the value. However, certain types of gemstones require special processing. For example, amber containing biological material may be more valuable, while air bubbles decrease its value. Another type is star sapphire, where the internal texture is specially processed using multimedia images; the higher the proportion of starlight within the sapphire, the higher its value. However, the shape and form of the starlight cannot currently be processed by the large model and require human intervention for scoring. The same applies to refractive index; gemstones with a high refractive index are more dazzling and naturally more valuable. Physical parameters are relatively easy to score using large-scale models, but unlike other standardized products, the value of gemstones is influenced by a variety of factors. For example, Burmese rubies are more valuable than those from other origins, and Thai-processed rubies and sapphires are more valuable than those processed in other countries. Similarly, even within Brazilian tourmaline, different varieties (common tourmaline and Padparadscha) can have vastly different values. And for rubies of the same quality, pigeon blood red is much more expensive than other colors. While ideal multimedia parameters for a gemstone can make it seem more valuable, this is often not the case. Historical data shows that physical parameters have a greater impact on value, although multimedia data also plays a significant role. Therefore, large-scale models need to carefully control the proportions when evaluating value. Another major advantage of large-scale models is the ability to complete evaluations and issue certificates very quickly. What used to take at least half an hour can now be completed in seconds to minutes.

[0027] Algorithm details: GEMAI = (0.15×T + 0.20×V + 0.18×RI + 0.22×C + 0.12×O + 0.08×I +0.05×P) × CF iT is the value coefficient for gemstones, graded according to market scarcity. Diamond: 1.0, Ruby / Sapphire: 0.95, Emerald: 0.90, Chrysoberyl Cat's Eye: 0.88, Spinel: 0.85, Other rare gemstones (such as tourmaline): 0.8, Common semi-precious stones: 0.6.

[0028] ii.V is the volume factor = log10(volume mm³) / 2 × cutting correction factor (cutting correction factor: EX cutting = 1.2, VG ​​cutting = 1.0, others = 0.8, refer to the national 4C standard). Carat premium: When the weight is ≥1 carat, the V value × the extra value. According to the weight ratio, the extra value is 1.1 for 1-2 carats, 1.3 for 2-3 carats, and so on.

[0029] iii.RI is the refractive index coefficient RI = (measured RI - 1.3) / (2.5 - 1.3) + dispersion value x 0.2; the dispersion value is normalized (e.g. diamond 0.044, sapphire 0.018, ruby 0.018, emerald 0.017, and emerald 0.014).

[0030] iv.C is the color score coefficient, which needs to be supported by high-spectral quantitative data Color belongs to rare color (e.g. Paraiba blue, pigeon blood red): C = 1.0 Saturation > 80% and hue positive: C = 0.8 + (lightness% / 100) x 0.2 C = 0.5 + (saturation% / 200).

[0031] v.O is the origin coefficient (associated with the type of gemstone) Taking sapphire as an example, the origin premium reference is: Kashmir: 1.0, Myanmar: 0.95, Colombia: 0.9, Russia: 0.85, and other well-known producing areas: 0.7.

[0032] vi.I is the inclusion system number I = 1 - (number of inclusions x 0.05 + maximum size mm x 0.3) + special inclusion bonus Special inclusion bonus: e.g. chrysoberyl horse-tail inclusion +0.2, and davis structure +0.1.

[0033] vii.P is the processing method (associated with the type of gemstone) Taking sapphire as an example: with burning: 0.9, without burning: 1.0.

[0034] viii.CF is the correction mark CF = 1 + certificate bonus (GIA + 0.15, other authorities + 0.1) + optical effect (fire / catch / cat eye + 0.2); GIA certificate is a diamond grade certificate issued by the Gemological Institute of America (GIA). Other authorities such as GRS / GUILD / Gübelin / SSEF, etc. will be referred to, because the multimedia information and physical information of the identification agency are relatively accurate.

[0035] The public result (score 0-1, ≥0.9 is a collection level), the gemstone identification certificate generation system adopting the present application scores the result as shown in Figure 2 .

[0036] Preferably, the gemstone digital AI large model adopts a multi-modal fusion architecture based on Transformer, which can simultaneously encode high-resolution images, spectral data, 3D point cloud data and physical parameters, and realize semantic alignment between features through cross-modal attention mechanism (Cross-Modal Attention), to improve the accuracy and robustness of identification results, especially to significantly improve the identification and evaluation accuracy of rare gemstones (such as chameleon diamonds, alexander varicolored stones, etc.).

[0037] 2. The gemstone algorithm basic configuration module mainly adjusts and reallocates the basic values and proportions of various parameters in the algorithm. It can choose to start the calculation and evaluation again, or it can choose to repair the historical data.

[0038] 3. The big data identification and verification module mainly identifies the multimedia and digital coding, mainly compares the generated coding in the historical database for similarity, when the similarity exceeds a certain percentage, it will be prewarned and separately screened out for subsequent manual confirmation. Generally set at 95%, historical data correction is a batch operation on the original database, which generally needs manual operation and leaves operation logs.

[0039] Four, gemstone digital certificate output module This module mainly has two parts: terminal digital certificate display module (gemstone digital certificate display on terminal, including 3D photo and various digital information) and terminal digital certificate security authentication module (interface security authentication and identity authentication).

[0040] 1. The terminal digital certificate display module mainly displays the gemstone digital certificate, including the picture of the gemstone, the basic physical parameters of the commodity, part of the node information on the supply chain, and the evaluation information given by the large model; the terminal digital certificate display module integrates augmented reality (AR) visualization components, users can scan the digital certificate QR code through mobile terminal, real-time superimposed display of gemstone three-dimensional model, optical special effect simulation (such as starlight, cat eye effect) and visualization labeling of key physical parameters.

[0041] 2. The terminal digital certificate security authentication module is used for the security authentication of digital certificate, protects the daily login times of the same IP address, prevents data crawling, firewall security settings, third-party query interface whitelist, and interface call encryption protection, etc.

[0042] 3. The terminal ownership management module primarily allows terminal holders to bind and authenticate digital certificates through real-name authentication, transferring ownership to themselves. Unbound digital certificates can be directly bound using an ID card for the first time. After binding, the digital certificate belongs to that user, who can view all information on the digital certificate and has the right to hide or display relevant information, as well as enter transaction information. Other users cannot bind the digital certificate, view bound information, or information the holder does not wish to display. For ownership transfer to occur, the original holder needs to actively trigger the ownership transfer process, temporarily transferring the digital certificate to the new holder's account. After real-name authentication, the transfer is complete. The new holder can enter transfer notes, using the digital certificate as a digital transaction credential. The transfer is completed after confirmation by the original holder. Related ownership transfer records will also be used as traceability nodes for blockchain record authentication.

[0043] 4. A blockchain-based certificate storage and traceability module: Each generated digital certificate uses asymmetric encryption technology to generate a digital signature, and its hash value is written to a permissioned blockchain (such as Hyperledger Fabric). All queries and verification operations on this certificate are recorded through smart contracts, ensuring data immutability and auditable operations. In other words, any modification or query of the certificate requires authorization verification and operation recording through smart contracts, achieving fully traceable and non-repudiable data security management. The blockchain authentication result is as follows: Figure 3 As shown, the generated digital certificate and directory information are as follows: Figure 4 As shown.

[0044] The gemstone identification certificate generation system of this invention performs digital authentication and grading of each gemstone entirely through a large-scale model, possessing professional identification knowledge and unique characteristics specific to the gemstone industry. It incorporates multiple technical means, including multimodal artificial intelligence analysis, dynamic node management, augmented reality display, and blockchain evidence storage, into the traditional gemstone identification process, offering the following significant advantages: 1. The data sources are legal and the results are objective. The weighted correlation coefficients are derived from actual market sales and value. That is, the coefficients before T, V, RI, C, O, I, P, and CF are based on a comprehensive consideration of various gemstones in the market and the factors that affect their prices. Relevant information companies will provide suggestions. 2. By using multimodal fusion and attention mechanisms, the limitations of traditional single data source analysis are overcome, significantly improving the identification accuracy in complex scenarios; 3. Supports dynamically expandable data nodes and graph analysis. Utilizes scalable data node trees and graph neural networks to achieve deep correlation analysis of unstructured data, enhancing system flexibility and analytical depth; 4. Provide immersive AR certificate display to enhance the interactivity and user experience of digital certificates; 5. The authenticity and traceability of the guarantee are ensured by blockchain technology.

[0045] Although the present application has been disclosed with reference to preferred embodiments, it is not intended to limit the present application, and any person skilled in the art, without departing from the spirit and scope of the present application, can make some modifications and improvements, and therefore the scope of protection of the present application is defined by the claims.

Claims

1. A gemstone identification certificate generation system based on artificial intelligence analysis, comprising: a gemstone detection data collection module for collecting gemstone physical information, converting gemstone physical information into digital information and storing; a gemstone detection data standard management module for setting a gemstone data standard dictionary library and configuring and managing digital information of different types of gemstones according to a data node tree; a gemstone data detection large model for analyzing multimedia parameters and physical parameters of gemstones and completing market value evaluation; a gemstone digital certificate output module for completing gemstone digital certificate issuance and display.

2. The gemstone identification certificate generation system based on artificial intelligence analysis according to claim 1, wherein, The gemstone detection data collection module comprises: a multimedia resource collector for collecting and storing gemstone images, including commodity surround 3D images, photos and spectral photos; a digital resource collector for converting gemstone physical information into digital information and storing; a third-party resource collector for obtaining digital information and multimedia information through a third-party interface. 3.The gemstone identification certificate generation system based on artificial intelligence analysis of claim 1, wherein, The gemstone detection data standard management module comprises: a gemstone data standard dictionary library containing identification standards of various gemstones, evaluation standards of market value, similarity threshold range standards and data entry standards; a gemstone data node tree management module for recording additional node information and corresponding node fields of each gemstone, the node information including mineral information, customs information and processing information, the mineral information including country of origin, mine and time, the customs information including customs declaration number and time, and the processing information including processing country, processing content and time.

4. The gemstone identification certificate generation system based on artificial intelligence analysis of claim 3, wherein, The gemstone data node tree management module supports dynamic expansion of node structure, dynamically adds and modifies node attributes through a graphical interface, and models the implicit association between gemstone nodes using graph convolution network to output a visual knowledge graph.

5. The artificial intelligence analysis-based gemstone identification certificate generation system of claim 1, wherein, The gemstone data detection large model comprises: a gemstone digital AI large model for analyzing multimedia parameters and physical parameters of gemstones and completing market value evaluation; a gemstone algorithm basic configuration module for adjusting and reallocating basic values and proportions of various parameters in the algorithm, and selecting to start calculation and evaluation again or to repair historical data; a big data screening and verification module for screening multimedia and digitalized digital codes, mainly comparing the generated codes with historical data in terms of similarity, and when the similarity exceeds a preset percentage, issuing a warning and separately screening them out for subsequent manual confirmation.

6. The artificial intelligence analysis-based gemstone identification certificate generation system according to claim 5, characterized in that, The gemstone digital AI large model adopts a multi-modal fusion architecture based on Transformer, simultaneously encodes high-resolution images, spectral data, 3D point cloud data and physical parameters, and realizes semantic alignment between features through cross-modal attention mechanism.

7. The artificial intelligence analysis-based gemstone identification certificate generation system according to claim 5, characterized in that, The gemstone digital AI large model scores according to the following formula: GEMAI = (0.15×T + 0.20×V + 0.18×RI + 0.22×C + 0.12×O + 0.08×I +0.05×P) × CF; T is the gemstone species value coefficient, V is the volume coefficient, RI is the refractive index coefficient, C is the color score coefficient, O is the origin coefficient, I is the inclusion system coefficient, P is the processing method, and CF is the correction stamp; The default value of T is 0.6, and according to market scarcity classification: diamond: 1.0, ruby / sapphire: 0.95, emerald: 0.90, golden green cat's eye: 0.88, spinel: 0.85, other rare gemstones: 0.8; V = log10(Volume mm³) / 2 × Cut correction factor, and when the weight is ≥1 carat, V value × extra value as carat premium; RI = (measured RI - 1.3) / (2.5 - 1.3) + dispersion value × 0.2; The value of C is 0.5-1.0; for preset rare colors, C = 1.0; for other colors, C = 0.5 + (saturation% / 200), when saturation > 80%, C = 0.8 + (lightness% / 100) × 0.2; I = 1 - (inclusion number × 0.05 + maximum size mm × 0.3) + special inclusion bonus; special inclusion bonus: +0.2 for spirogyra inclusion of tsavorite, +0.1 for dauphine structure; CF = 1 + certificate bonus + optical effect bonus; GIA certificate +0.15, other authoritative certificates +0.1, fire color / starlight / cat's eye +0.

2.

8. The artificial intelligence analysis-based gemstone identification certificate generation system according to claim 1, characterized in that, The gemstone digital certificate output module comprises: A terminal digital certificate display module, which mainly displays the gemstone digital certificate, including the picture of the gemstone, the basic physical parameters of the product, part of the node information on the supply chain, and the evaluation information given by the large model; the terminal digital certificate display module integrates an augmented reality visualization component, which displays the gemstone three-dimensional model in real time, simulates the optical effects with optical effect bonus, and visually marks the key physical parameters; A terminal digital certificate security authentication module for the security authentication of the digital certificate, which protects the number of daily logins for the same IP address, sets a security firewall to prevent data crawling, and provides a query interface whitelist and interface call encryption protection for third parties. 9.The artificial intelligence analysis-based gemstone identification certificate generation system of claim 8, wherein, The gemstone digital certificate output module further comprises a terminal property right management module, which binds and authenticates the digital certificate through real-name authentication, and the holder of the binding can view all information of the digital certificate and has the right to hide or display related information, and can also input related transaction information; When the property right is transferred, the property right transfer process is triggered, the digital certificate is temporarily transferred to the new holder account through the property right transfer process, and the transfer is completed after real-name authentication, the new holder can input transfer remarks, and the digital certificate is used as a digital transaction certificate, and the transfer operation is completed after confirmation by the original holder; The relevant property right transfer record is recorded and authenticated on the blockchain as a node for tracing. 10.The gemstone identification certificate generation system based on artificial intelligence analysis of claim 8, wherein, The gem digital certificate output module further comprises a blockchain-based certificate storage and traceability module. The hash value of each digital certificate is written into the blockchain after the digital certificate is generated, and all queries and verification operations on the certificate are recorded through a smart contract, ensuring that the data is tamper-proof and the operation is auditable.

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