System

Abstract

A system is provided.SOLUTION: A system for evaluating works of art, comprising: means for a user to input a work of art and metadata; means for a server to receive and store the input work of art and metadata in a database; means for the server to send the stored work of art and metadata to a AI analysis engine to generate analysis results; and means for displaying the analysis results to the user.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The technology of the present disclosure relates to a system. [Background technology]

[0002] Patent document 1 discloses a persona chatbot control method performed by at least one processor, the method including the steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to a description of the chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Publication No. 2022-180282 Summary of the Invention [Problem to be solved by the invention]

[0004] Currently, the evaluation of the value of artworks relies on professional art critics and experts, and the evaluations are often subjective and opaque. It is also difficult for artists to understand the appropriate value of their work and sell it at a fair price. As a result, many artists are unable to know the true value of their work and are unable to set an appropriate price. Furthermore, it is difficult for ordinary consumers to purchase artworks based on a fair price evaluation. To solve these problems, an objective and transparent evaluation method is needed. [Means for solving the problem]

[0005] The present invention solves the above-mentioned problems by providing a system for evaluating artworks. Specifically, the system includes the following components:

[0006] The system includes a means for a user to input artworks and metadata, a server receiving the input artworks and metadata and storing them in a database, a server transmitting the stored artworks and metadata to an AI analysis engine to generate analysis results, and a displaying means for the analysis results to the user. This allows users to understand the accurate value of their artworks and set appropriate prices based on fair and transparent evaluations. It also enables general consumers to purchase artworks that have been evaluated at fair prices.

[0007] "User" refers to a person who accesses the system and inputs artwork and metadata.

[0008] A "work of art" refers to any visual or literary work resulting from human creativity, such as a painting, poem, novel, or photograph.

[0009] "Metadata" refers to additional information about a work of art, such as its title, artist name, year of creation, and other details.

[0010] "Server" refers to a computer system that receives input information from users, stores it in a database, and then sends the data to an AI analysis engine to generate analysis results.

[0011] "Database" refers to digital storage for organizing and managing information about artworks and their metadata.

[0012] An "AI analysis engine" is a software module that uses artificial intelligence technology to analyze works of art and evaluate them based on various criteria, including aesthetic value, historical value, popularity, and influence.

[0013] "Analysis results" refers to evaluation information generated by the AI ​​analysis engine, such as the aesthetic value, historical value, popularity, and influence of a work of art.

[0014] "Display" refers to visually presenting the analysis results generated by the server on the user's terminal.

[0015] "Sale Listing" means a list of artworks published on the System based on a selling price set by a User.

[0016] "Pricing" refers to the amount a user decides to sell their artwork for. [Brief explanation of the drawings]

[0017] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12]FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0018] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0019] First, the terms used in the following description will be explained.

[0020] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0021] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0022] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0023] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0024] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0025] [First embodiment]

[0026] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0027] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0028] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0029] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0030] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0031] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0032] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0033] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0034] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0035] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0036] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0037] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0038] This invention provides a system for fairly and transparently evaluating the value of artworks. This system allows users to upload their own artworks, and an AI analysis engine is used to evaluate the artworks in detail based on their aesthetic value, historical value, popularity, influence, etc. Below, we will show the processing details and specific examples of the program for this system.

[0039] Basic processing flow

[0040] 1. User Registration and Login

[0041] User: Access the system and register a new account by entering an email address, password, and username, then log in to the account.

[0042] Server: Receives registration information and stores it in a database. Receives login information and returns an authentication token to the user if authentication is successful.

[0043] 2. Upload your work

[0044] User: Select a work of art such as a painting, poem, novel, or photograph and enter metadata such as title, artist, and year of creation.

[0045] On the device: Sends the uploaded file and metadata to the server.

[0046] Server: Stores received files and metadata and prepares them for analysis.

[0047] 3. AI-based analysis

[0048] Server (AI analysis engine): The saved artwork data is sent to the analysis engine, which evaluates it based on specified criteria, including aesthetic value, historical value, popularity, and influence.

[0049] Server: Receives the analysis results and stores them in a database.

[0050] 4. Displaying the analysis results

[0051] Users: Log in to their account and check the analysis results. View detailed analysis results from the work list.

[0052] Server: Visually presents the analysis results to the user.

[0053] 5. Buying and Selling Artworks

[0054] User (seller): Sets the selling price based on the analysis results and sends it to the server.

[0055] Server: Adds the work to the sales list at a set price.

[0056] User (Buyer): Selects the work of interest from the sales list and completes the purchase process.

[0057] Server: Validates purchase payments and sends digital copies of the work to the buyer.

[0058] Specific examples

[0059] Example 1: Evaluation of a painting

[0060] 1. User: The user accesses the system with the desire to have the drawing he or she has drawn evaluated.

[0061] 2. Device: Upload the painting file "autumn_landscape.jpg" and enter the metadata (title "Autumn Landscape", artist "Ichiro Tanaka", year of creation "2023").

[0062] 3. Server: Stores received files and data and passes them to the AI ​​analysis engine.

[0063] 4. AI analysis engine: Analyzes artworks and evaluates their aesthetic value, historical value, popularity, and influence.

[0064] 5. Server: Stores the analysis results (e.g. aesthetic value rating 8.5 / 10, historical value rating 7 / 10, popularity rating 6 / 10, influence rating 7.5 / 10) and displays them to the user.

[0065] 6. User: Check the evaluation results and list the work for sale for 10,000 yen.

[0066] Example 2: Poetry rating

[0067] 1. User: The user accesses the system because they want to know the value of the poem they have written.

[0068] 2. Device: Upload the poem file "winter_scene.txt" and enter the metadata (title "Winter Scene," author "Jiro Sato," and year of creation "2022").

[0069] 3. Server: Stores received files and data and passes them to the AI ​​analysis engine.

[0070] 4. AI analysis engine: Analyzes poems and evaluates their aesthetic value, historical value, popularity, and influence.

[0071] 5. Server: Stores the analysis results (e.g. aesthetic value rating 7.5 / 10, historical value rating 6 / 10, popularity rating 7 / 10, influence rating 8 / 10) and displays them to the user.

[0072] 6. User: Checks the evaluation results and lists the poem for sale for 5,000 yen.

[0073] In this way, the system of the present invention provides users with a means to objectively and fairly evaluate their own artworks, enabling them to buy and sell their artworks at fair prices based on that evaluation, thereby enabling a more accurate understanding of the value of artworks and promoting fair transactions.

[0074] The processing flow will be explained below.

[0075] Step 1:

[0076] A user accesses the system and registers a new account by entering an email address, password, and username.

[0077] Step 2:

[0078] The device sends the entered registration information to the server in JSON format.

[0079] Step 3:

[0080] The server stores the received registration information in a database and sends a confirmation email to the user.

[0081] Step 4:

[0082] The user confirms their email address by clicking the link in the confirmation email they receive.

[0083] Step 5:

[0084] The server verifies the email address and records the user registration in the database.

[0085] Step 6:

[0086] The user logs in by entering their email address and password.

[0087] Step 7:

[0088] The terminal sends the entered login information to the server in JSON format.

[0089] Step 8:

[0090] The server verifies the entered login information and, if authentication is successful, generates an authentication token and returns it to the user.

[0091] Step 9:

[0092] The user logs back into the system and opens the account screen.

[0093] Step 10:

[0094] The user selects a work of art (e.g., an image file of a painting) and enters metadata such as the title, artist name, and year of creation.

[0095] Step 11:

[0096] The terminal transmits the selected file and the entered metadata to the server.

[0097] Step 12:

[0098] The server temporarily stores the received file and metadata, and stores the work file in file storage.

[0099] Step 13:

[0100] The server prepares to pass the stored artwork data and metadata to the AI ​​analysis engine.

[0101] Step 14:

[0102] The server (AI analysis engine) performs analysis to evaluate the work's aesthetic value, historical value, popularity, influence, etc.

[0103] Step 15:

[0104] The AI ​​analysis engine (on the server) generates the analysis results and generates scores for aesthetic value, historical value, popularity, and influence.

[0105] Step 16:

[0106] The server receives the analysis results and stores them in a database.

[0107] Step 17:

[0108] The user checks the analysis results from the account screen.

[0109] Step 18:

[0110] The server displays the analysis results to the user.

[0111] Step 19:

[0112] The user (seller) sets the selling price of the work based on the analysis results and lists it for sale.

[0113] Step 20:

[0114] The server adds the work to the sales list at the set price.

[0115] Step 20:

[0116] The user (buyer) selects the work of interest from the sales list and completes the purchase procedure.

[0117] Step 21:

[0118] The server verifies the purchase payment and transmits the digital copy of the work to the buyer.

[0119] Through these steps, the system will ensure fair and transparent evaluation of artworks and the sale and purchase of artworks at fair prices.

[0120] Example 1

[0121] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0122] The conventional art evaluation system relied on subjective evaluation and lacked fairness and transparency. It was also difficult to grasp the true value of a work of art, and the system was unreliable in transactions, making it difficult to promote fair transactions.

[0123] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0124] In this invention, the server includes means for a user to input artworks and metadata, means for a terminal to transmit the input artworks and metadata to the server, means for the server to receive the input artworks and metadata and store them in a database, means for the server to transmit the stored artworks and metadata to an AI analysis engine and generate analysis results, means for visually presenting the analysis results to the user, means for the user to set a selling price based on the analysis results and for the server to add the artwork to a sales list at that price, means for the user to purchase the artwork from the sales list, and means for the server to process the purchase procedure and transmit artwork data to the purchaser. This makes it possible to fairly and transparently evaluate the value of artworks and promote fair transactions.

[0125] "Users" are entities that use the system to upload artworks and evaluate and sell them.

[0126] A "terminal" is a device used by a user, such as a computer or smartphone, that includes a means for transmitting input artworks and metadata to a server.

[0127] A "server" is the computer that serves as the core of the system, receiving input information, storing it in a database, and analyzing it using an AI analysis engine.

[0128] "Work of art" refers to any work of creative expression, such as a painting, poem, novel, or photograph.

[0129] "Metadata" is additional information about a work of art, including the title, artist name, and year of creation.

[0130] The "database" is an information storage system for efficiently managing and storing received artworks, metadata, analysis results, etc.

[0131] The "AI Analysis Engine" is an artificial intelligence engine that analyzes works of art and evaluates their aesthetic value, historical value, popularity, and influence.

[0132] "Analysis results" are evaluation results provided by the AI ​​analysis engine, and include evaluation indicators such as aesthetic value, historical value, popularity, and influence.

[0133] "Visual presentation" refers to providing analysis results to users in an easy-to-read format such as graphs or charts.

[0134] "Sales List" means a list of artworks that can be viewed and purchased by other Users along with the selling price set by the User.

[0135] "Purchase procedure" refers to the process by which a user purchases an artwork selected from a sales list, including payment and the transfer of artwork data.

[0136] "Artwork Data" refers to the digital file of the Artwork sent to the Purchaser.

[0137] The present invention provides a system for fair and transparent evaluation of the value of artworks. This system allows users to upload their own artworks and uses an AI analysis engine to evaluate the artworks in detail based on their aesthetic value, historical value, popularity, influence, etc.

[0138] Specifically, the following hardware and software are used:

[0139] Hardware: Servers, devices (computers, smartphones, etc.)

[0140] Software: Databases (e.g., MySQL, PostgreSQL), cloud storage (e.g., Amazon S3, Google Cloud Storage), AI analytics engines (e.g., TensorFlow, PyTorch)

[0141] First, a user accesses the system using a terminal and registers a new account by entering their email address, password, and username. Then, they log in with their email address and password. The server receives the information entered by the user and stores it in a database. It also verifies the login information and securely authenticates the user.

[0142] Next, the user selects a file of an artwork (e.g., painting, poem, novel, photograph, etc.) from the device through the on-screen interface and enters metadata such as the title, artist name, and year of production. The device then sends this information to the server. The server saves the received file and metadata in storage and returns a notification to the user that saving is complete.

[0143] The server then sends the stored artwork data to an AI analysis engine, which evaluates the artwork based on specified criteria such as aesthetic value, historical value, popularity, and influence. During this process, the AI ​​analysis engine analyzes the input artwork from various perspectives and generates results based on each evaluation indicator. The server then stores the evaluation results received from the AI ​​analysis engine in a database.

[0144] After logging in to the system, users can check the evaluation results of their work. The server presents the analysis results to users in a visually easy-to-read format (e.g., graphs or charts), allowing users to concretely grasp the value of their work.

[0145] Furthermore, when a user wants to sell their artwork, they can set an appropriate selling price based on the evaluation results and send that information to the server. The server then adds the artwork to a sales list at the set price, making it available for other users to view. When a potential buyer (user) selects a piece of artwork and completes the purchase procedure, the server confirms the buyer's payment and sends the artwork data to the buyer.

[0146] Specific examples

[0147] 1. A user accesses the system because they want their drawing to be evaluated.

[0148] 2. The device uploads the painting file "autumn_landscape.jpg" and enters the metadata (title "Autumn Landscape", artist "Ichiro Tanaka", year of creation "2023").

[0149] 3. The server stores the received files and data and passes them to the AI ​​analysis engine.

[0150] 4. An AI analysis engine analyzes the artwork and evaluates its aesthetic value, historical value, popularity, and influence.

[0151] 5. The server stores the analysis results (e.g., aesthetic value rating 8.5 / 10, historical value rating 7 / 10, popularity rating 6 / 10, influence rating 7.5 / 10) and displays them to the user.

[0152] 6. The user checks the evaluation results and lists the work for sale for 10,000 yen.

[0153] Example prompt: "Evaluate this painting's aesthetic value, historical value, popularity, and influence."

[0154] In this way, the system of the present invention provides users with a means to objectively and fairly evaluate their own artworks, enabling them to buy and sell their artworks at fair prices based on that evaluation, thereby enabling a more accurate understanding of the value of artworks and promoting fair transactions.

[0155] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0156] Step 1: User Registration and Login

[0157] The user accesses the system's registration screen and creates a new account by entering an email address, password, and username. The user enters this information (input data: email address, password, username) and presses the "Register" button.

[0158] The server saves the received registration information in a database (output data: Save registration information to database), and then returns a message to the user indicating that registration was successful.

[0159] The user accesses the login screen and enters the registered email address and password. The user enters this information (input data: email address, password) and presses the "Login" button.

[0160] The server receives the login information and authenticates it against the database. If authentication is successful, it generates an authentication token (such as a JWT) and returns it to the user (output data: authentication token).

[0161] Step 2: Upload your work

[0162] After logging in, the user opens the artwork upload screen and selects the artwork file. They also enter metadata such as the title, artist name, and year of production. The user enters this information (input data: artwork file, title, artist name, year of production) and presses the "Upload" button.

[0163] The terminal transmits the selected file and metadata to the server (input data: file, metadata).

[0164] The server saves the received file in a storage system (e.g., Amazon S3) and saves the metadata in a database (output data: file saved in storage, metadata saved in database). After saving is complete, it returns a message to the user saying "upload successful."

[0165] Step 3: AI analysis

[0166] The server sends the saved artwork data to the AI ​​analysis engine (input data: artwork data).

[0167] The AI ​​analysis engine uses the submitted artwork data to evaluate its aesthetic value, historical value, popularity, and influence (data calculation: aesthetic value analysis, historical value analysis, popularity analysis, influence analysis). Evaluation criteria include various factors such as color, composition, and theme.

[0168] The server stores the evaluation results received from the AI ​​analysis engine in a database (output data: evaluation results stored in the database).

[0169] Step 4: Viewing the analysis results

[0170] The user logs in to their account and opens the analysis results screen. The user then sends a request to check the analysis results (input data: user ID, analysis result confirmation request).

[0171] The server receives a request from the user and retrieves the corresponding analysis results from the database (output data: analysis results). It then generates graphs and charts to visually present the retrieved analysis results to the user (data processing: graphing and charting the analysis results). These results are then displayed to the user.

[0172] Step 5: Buying and Selling Your Artwork

[0173] The user (seller) sets a selling price based on the evaluation results and sends that information to the server (input data: selling price, work information).

[0174] The server adds the work to the sales list at the set price, making it available for other users to view (output data: work information added to the sales list).

[0175] The user (buyer) selects the work they wish to purchase from the sales list, presses the "Purchase" button, and enters the information required to complete the purchase (input data: purchase request, payment information).

[0176] The server executes the purchase procedure, and after successful payment, sends the digital data of the work to the buyer (output data: digital data of the work sent to the buyer). It also sends a sale notification to the seller.

[0177] (Application example 1)

[0178] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0179] Conventional art evaluation systems use an AI analysis engine to evaluate artworks based on artworks and metadata entered by users, but lack a way to visually present the evaluation results in real time. This requires users to use a separate device to check the evaluation results, which is inconvenient. Furthermore, the lack of instant feedback of evaluation results makes them difficult to use in galleries, museums, and other settings. Therefore, the present invention aims to provide an evaluation system that solves these problems.

[0180] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0181] In this invention, the server includes means for a user to input artworks and metadata, means for the server to receive the input artworks and metadata and store them in a database, means for the server to transmit the stored artworks and metadata to an AI analysis engine and generate analysis results, means for displaying the analysis results to the user, and means for a display device to visually overlay the analysis results in front of the user's eyes, allowing the user to instantly visually confirm the evaluation results while appreciating the artworks.

[0182] "User" refers to a person who accesses the system and inputs or views artwork.

[0183] "Work of art" refers to any artistic or literary work, such as a painting, poem, novel, or photograph.

[0184] "Metadata" is additional information about a work of art, such as its title, artist name, and year of creation.

[0185] "Server" refers to a computer system that receives, stores, and processes information entered by users over a network.

[0186] "Database" refers to a digital storage device for the systematic preservation of artworks and metadata.

[0187] "AI analysis engine" refers to software that uses artificial intelligence technology to evaluate input artworks.

[0188] "Analysis results" refers to the evaluation results of the aesthetic value, historical value, popularity, influence, etc. of the artwork as assessed by the AI ​​analysis engine.

[0189] A "display device" is a device that allows a user to visually check the evaluation results, and includes smart glasses, AR glasses, etc.

[0190] "Visually overlaying" refers to the ability of a display device to superimpose on a visible object or content.

[0191] The present invention will be described in detail below with reference to an embodiment thereof. This system links a display device such as smart glasses with a server, and visually displays the evaluation results of artworks to a user in real time.

[0192] Hardware and software used

[0193] 1. Hardware:

[0194] Smart glasses: Examples include AR glasses such as Microsoft HoloLens and Google Glass.

[0195] Server: A computer system for processing and storing data over a network.

[0196] 2. Software:

[0197] Operating System (OS): The basic software that runs on the smart glasses and the server.

[0198] Python: A programming language used in the present invention for image processing and server communication.

[0199] OpenCV: A library for image capture and processing.

[0200] AI Analytics Engine: Deep learning models for assessing the aesthetic value, historical value, popularity, and influence of artworks.

[0201] Processing flow

[0202] 1. User views a work of art:

[0203] A user wears smart glasses and visits a gallery or museum, and the glasses' camera captures the artwork on display.

[0204] 2. Image capture:

[0205] The smart glasses' camera captures images of artwork within the user's field of view.

[0206] 3. Send to server:

[0207] The captured image is sent from the smart glasses to the server, which then receives the image and sends the data to the AI ​​analysis engine.

[0208] 4. AI analysis:

[0209] Based on the image data received, the AI ​​analysis engine evaluates the aesthetic value, historical value, popularity, and influence of the artwork.

[0210] 5. Receiving and storing evaluation results:

[0211] The server receives the evaluation results from the AI ​​analysis engine and stores them in a database, after which the evaluation results are sent to the smart glasses.

[0212] 6. Overlay display:

[0213] The smart glasses overlay the received evaluation results in the user's field of view, allowing the user to check the evaluation results in real time while viewing the artwork.

[0214] Specific examples

[0215] 1. Example of a painting evaluation:

[0216] A user puts on the smart glasses and looks at the painting "Spring Landscape" in a gallery. The glasses capture the painting and send it to the server. The server analyzes it using an AI analysis engine and sends the evaluation results (e.g., aesthetic value 9.0, historical value 8.0, popularity 7.5, influence 8.5) to the smart glasses. The user can visually confirm these evaluations.

[0217] 2. Poetry evaluation examples:

[0218] A user views the poem "Summer Memories" at an art museum. The smart glasses capture a digital representation of the poem and send it to a server. An AI analysis engine analyzes the poem and rates it on aesthetic value (8.0), historical value (6.5), popularity (7.0), and influence (9.0). These results are overlaid on the smart glasses, allowing the user to view the results in real time.

[0219] Prompt Sentence Examples

[0220] An example of a prompt used by this system is:

[0221] "This image is of a Spring Landscape from a famous art museum. Please rate the artwork's aesthetic value, historical value, popularity, and influence."

[0222] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0223] Step 1:

[0224] Users appreciate artwork

[0225] A user wears smart glasses and visits a gallery or museum, and the glasses' camera visually captures the artworks on display.

[0226] Input: Live video of artwork captured through the smart glasses camera

[0227] Output: Image data of the captured artwork

[0228] Step 2:

[0229] Image capture

[0230] As the user views the artwork, the camera in the smart glasses captures an image of the artwork.

[0231] Input: Live video from the smart glasses camera

[0232] Output: Still image data of artwork captured within the smart glasses

[0233] Step 3:

[0234] Send to server

[0235] The smart glasses capture images of paintings and poems and send them to a server, along with the metadata.

[0236] Input: Image data and metadata of the captured artwork (e.g., title, artist name, year of creation)

[0237] Output: Image data and metadata sent to the server

[0238] Step 4:

[0239] AI-based analysis

[0240] The server sends the received image data and metadata to an AI analysis engine for evaluation, which uses deep learning models to analyze aesthetic value, historical value, popularity, influence, and other factors.

[0241] Input: Image data and metadata sent to the server

[0242] Output: The evaluation results returned by the AI ​​analysis engine (e.g., aesthetic value 9.0, historical value 8.0, popularity 7.5, influence 8.5)

[0243] Step 5:

[0244] Receiving and storing evaluation results

[0245] The server receives the evaluation results returned by the AI ​​analysis engine and stores them in a database.

[0246] Input: Evaluation results from the AI ​​analysis engine

[0247] Output: Evaluation result data stored in a database

[0248] Step 6:

[0249] Overlay Display

[0250] The smart glasses overlay the evaluation results received from the server in the user's field of view, allowing the user to simultaneously view the artwork and its evaluation results.

[0251] Input: Evaluation result data sent from the server

[0252] Output: Evaluation results overlaid on the smart glasses display

[0253] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0254] The present invention provides a system that allows users to rate artworks and, by combining it with an emotion engine, customizes the evaluation and display of the artworks based on the user's emotional state. This system allows users to upload artworks, which are evaluated using an AI analysis engine, and further analyzes the user's emotions using the emotion engine, with the results reflected in the evaluation and display. The processing content and specific examples of the program for this system are shown below.

[0255] Basic processing flow

[0256] 1. User Registration and Login

[0257] A user accesses the system, registers a new account by entering an email address, password, and username, and then logs in to the account.

[0258] The server receives the registration information, stores it in a database, receives the login information, and if authentication is successful, returns an authentication token to the user.

[0259] 2. Upload your work

[0260] The user selects a work of art such as a painting, poem, novel, or photograph and enters metadata such as the title, artist name, and year of creation.

[0261] The device sends the uploaded file and metadata to the server.

[0262] The server stores the received files and metadata and prepares them for analysis.

[0263] 3. User sentiment analysis

[0264] When a user inputs their work or checks the evaluation results, the emotion engine analyzes the user's emotional state from their facial expressions and voice input.

[0265] The emotion engine (in the server) analyzes the user's emotions and adds the results to the metadata or reflects them in the display of the analysis results.

[0266] 4. AI-based analysis

[0267] The server (AI analysis engine) evaluates the work's aesthetic value, historical value, popularity, influence, etc.

[0268] The AI ​​analysis engine (on the server) generates the analysis results and generates scores for aesthetic value, historical value, popularity, and influence.

[0269] The emotion engine (within the server) uses the emotion analysis results to make corrections and add supplementary information to the AI ​​analysis results.

[0270] 5. Displaying the analysis results

[0271] The user checks the analysis results from their account.

[0272] The server displays the analysis results to the user, which may be customized according to the user's emotional state.

[0273] 6. Buying and Selling Works

[0274] The user (seller) sets the selling price of the work based on the analysis results and lists it for sale.

[0275] The server adds the work to the sales list at the set price.

[0276] The user (buyer) selects the work of interest from the sales list and completes the purchase procedure.

[0277] The server verifies the purchase payment and transmits the digital copy of the work to the buyer.

[0278] Specific examples

[0279] Example 1: Painting rating and sentiment analysis

[0280] 1. A user accesses the system because they want their drawing to be evaluated.

[0281] 2. The device uploads the painting file "autumn_landscape.jpg" and enters the metadata (title "Autumn Landscape", artist "Ichiro Tanaka", year of production "2023").

[0282] 3. The server stores the received files and data and passes them to the AI ​​analysis engine.

[0283] 4. When the user enters their work or checks the evaluation results, the emotion engine analyzes their emotional state from their facial expressions.

[0284] 5. An AI analysis engine analyzes the artwork and evaluates its aesthetic value, historical value, popularity, and influence.

[0285] 6. Based on the analysis results, the emotion engine customizes the display format and focus points to suit the user's preferences.

[0286] 7. The server stores the analysis results (e.g., aesthetic value rating 8.5 / 10, historical value rating 7 / 10, popularity rating 6 / 10, influence rating 7.5 / 10) and displays them to the user.

[0287] 8. The user checks the evaluation results and lists the work for sale for 10,000 yen.

[0288] Example 2: Poetry rating and sentiment analysis

[0289] 1. A user accesses the system because they want to know the value of a poem they have written.

[0290] 2. The device uploads the poem file "winter_scene.txt" and enters the metadata (title "Winter Scene," author "Jiro Sato," and year of creation "2022").

[0291] 3. The server stores the received files and data and passes them to the AI ​​analysis engine.

[0292] 4. When the user inputs their work or checks the evaluation results, the emotion engine analyzes their emotional state from their voice input.

[0293] 5. An AI analysis engine analyzes the poem and evaluates its aesthetic value, historical value, popularity, and influence.

[0294] 6. The emotion engine uses the analysis results to customize the display to attract the user's interest.

[0295] 7. The server stores the analysis results (e.g., aesthetic value rating 7.5 / 10, historical value rating 6 / 10, popularity rating 7 / 10, influence rating 8 / 10) and displays them to the user.

[0296] 8. The user checks the rating and lists the poem for sale for 5,000 yen.

[0297] In this way, the system of the present invention provides users with a means to objectively and fairly evaluate their own artworks, enabling them to buy and sell artworks at fair prices based on those evaluations. Furthermore, by using an emotion engine to analyze the user's emotional state and reflecting the results in evaluations and displays, the system can provide a more personalized experience.

[0298] The processing flow will be explained below.

[0299] Step 1:

[0300] A user accesses the system and registers a new account by entering an email address, password, and username.

[0301] Step 2:

[0302] The device sends the entered registration information to the server in JSON format.

[0303] Step 3:

[0304] The server stores the received registration information in a database and sends a confirmation email to the user.

[0305] Step 4:

[0306] The user confirms their email address by clicking the link in the confirmation email they receive.

[0307] Step 5:

[0308] The server verifies the email address and records the user registration in the database.

[0309] Step 6:

[0310] The user logs in by entering their email address and password.

[0311] Step 7:

[0312] The terminal sends the entered login information to the server in JSON format.

[0313] Step 8:

[0314] The server verifies the entered login information and, if authentication is successful, generates an authentication token and returns it to the user.

[0315] Step 9:

[0316] The user logs back into the system and opens the account screen.

[0317] Step 10:

[0318] The user selects a work of art such as a painting, poem, novel, or photograph and enters metadata such as the title, artist name, and year of creation.

[0319] Step 11:

[0320] The terminal transmits the selected file and the entered metadata to the server.

[0321] Step 12:

[0322] The server temporarily stores the received file and metadata, and stores the work file in file storage.

[0323] Step 13:

[0324] When a user inputs their work, the emotion engine analyzes their emotional state from their facial expressions and voice input.

[0325] Step 14:

[0326] The emotion engine (in the server) analyzes the emotional state and adds the results to the metadata or reflects them in the display of the analysis results.

[0327] Step 15:

[0328] The server prepares to pass the stored artwork data and metadata to the AI ​​analysis engine.

[0329] Step 16:

[0330] The server (AI analysis engine) performs analysis to evaluate the work's aesthetic value, historical value, popularity, influence, etc.

[0331] Step 17:

[0332] The AI ​​analysis engine (on the server) generates the analysis results and generates scores for aesthetic value, historical value, popularity, and influence.

[0333] Step 18:

[0334] The server receives the analysis results and stores them in a database.

[0335] Step 19:

[0336] The server displays the analysis results to the user, which may be customized according to the user's emotional state.

[0337] Step 20:

[0338] The user checks the analysis results.

[0339] Step 21:

[0340] The user (seller) sets the selling price of the work based on the analysis results and lists it for sale.

[0341] Step 22:

[0342] The server adds the work to the sales list at the set price.

[0343] Step 23:

[0344] The user (buyer) selects the work of interest from the sales list and completes the purchase procedure.

[0345] Step 24:

[0346] The server verifies the purchase payment and transmits the digital copy of the work to the buyer.

[0347] Example 2

[0348] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0349] Conventional art evaluation systems evaluate artworks without considering the user's emotional state, resulting in uniform evaluation results. Furthermore, when users sell artworks, it is difficult to set an appropriate price, and there is a lack of systems that provide an appropriate sales process. Furthermore, there is a problem that the method of presenting analysis results to users is not personalized, beyond simply evaluating artworks.

[0350] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0351] In this invention, the server includes means for a user to input digital content and metadata, means for the server to receive the input digital content and metadata and store them in a database, means for the server to transmit the stored digital content and metadata to an AI analysis engine and generate analysis results, means for the emotion engine to analyze the user's emotional state and correct the analysis results, and means for displaying the analysis results to the user. This makes it possible to present individualized evaluation results that take the user's emotional state into consideration, and by providing appropriate pricing and sales processes, a system that is highly convenient for users is realized.

[0352] "Digital Content" refers to artistic works stored or displayed in digital form, such as paintings, poems, novels, and photographs.

[0353] "Metadata" is additional information related to digital content, including attribute information such as title, author name, and production year.

[0354] "AI analysis engine" refers to an artificial intelligence-based system that analyzes digital content and generates evaluation scores based on aesthetic value, historical value, popularity, influence, etc.

[0355] An "emotion engine" is a system that analyzes a user's facial expressions and voice input to identify their emotional state and reflects the results in the evaluation of digital content.

[0356] "Server" refers to a central computer system for storing, processing, and analyzing digital content and metadata submitted by users.

[0357] "User" means any individual or legal entity that uses the System to upload, review, or sell digital content.

[0358] "Database" refers to a system built on a server that can efficiently store and search input digital content and metadata.

[0359] "Analysis results" refers to the final evaluation information that combines the evaluation score generated by the AI ​​analysis engine and the correction information provided by the emotion engine.

[0360] "Sales Listing" means a listing for publishing and selling Digital Content at a price set by a User.

[0361] An "authentication token" refers to a unique identification code that is issued when a user logs in to a system and is used as authentication information.

[0362] This invention is a system that allows users to rate digital content and customizes the ratings and display of works based on the user's emotional state by combining it with an emotion engine. This system allows users to upload digital content, has an AI analysis engine to rate it, and further uses the emotion engine to analyze the user's emotions, and has the function of reflecting the results in the ratings and display.

[0363] The hardware used includes the user's device (PC, smartphone, tablet, etc.), a server for storing and analyzing data, a camera and microphone for analyzing the user's emotional state, etc. The software used includes a web application for uploading digital content, a database management system, an AI analysis engine, an emotion analysis engine, etc.

[0364] Basic processing flow

[0365] This system mainly has the following functions:

[0366] 1. User Registration and Login:

[0367] A user accesses the system and registers a new account by entering an email address, password, and username. The terminal sends the entered information to the server, which stores it in a database. The user then enters login information, which the terminal sends to the server, which verifies it against the database and returns an authentication token to the user.

[0368] 2. Upload your work:

[0369] The user selects digital content (paintings, poems, novels, photographs, etc.) and enters metadata (title, author, year of creation, etc.). The device sends the selected file and metadata to the server, which receives it and stores it in a database.

[0370] 3. User sentiment analysis:

[0371] While the user is entering digital content or checking the evaluation results, the emotion engine analyzes the user's facial expressions and voice via the camera and microphone. The server analyzes the user's emotional state and adds the results to the metadata or reflects them in the analysis results.

[0372] 4. AI analysis:

[0373] The server sends the digital content and metadata to an AI analysis engine, which evaluates the work's aesthetic value, historical value, popularity, influence, etc. The AI ​​analysis engine generates these scores, and the emotion engine modifies and supplements them, taking into account the user's emotional state. The final analysis results are stored on the server.

[0374] 5. Displaying the analysis results:

[0375] Users can check the analysis results from their account, and the server retrieves the saved analysis results and displays them on the device. The display content is customized according to the user's emotional state.

[0376] 6. Buying and Selling Works:

[0377] The user (seller) sets a selling price based on the analysis results and posts it on the sales list. The server receives this and adds it to the sales list. The user (buyer) selects the work they are interested in from the list and completes the purchase procedure. The server confirms the purchase payment and sends the digital content to the buyer.

[0378] Specific examples

[0379] Example 1: Painting rating and sentiment analysis

[0380] A user accesses the system wanting to have a painting they have drawn evaluated. The terminal uploads the painting file "example_painting.jpg" and inputs metadata (title "Landscape", artist "Yamada Taro", year of production "2023"). The server receives this, saves it, and passes it to the AI ​​analysis engine. When the user enters the work or checks the evaluation results, the emotion engine analyzes the user's emotional state from their facial expressions. The AI ​​analysis engine evaluates the work, and the emotion engine customizes the display. The server saves the analysis results and displays them to the user. The user checks the evaluation results and places the work on the sales list.

[0381] Example 2: Poetry rating and sentiment analysis

[0382] A user accesses the system wanting to know the value of a poem they have written. The device uploads the poem file "example_poem.txt" and inputs metadata (title "Seasonal Poem", author "Sato Hanako", year of creation "2022"). The server receives this, saves it, and passes it to the AI ​​analysis engine. When the user enters a poem or checks the evaluation results, the emotion engine analyzes the user's emotional state from their voice input. The AI ​​analysis engine evaluates the poem, and the emotion engine customizes the display. The server saves the analysis results and displays them to the user. The user checks the evaluation results and places the poem on the sales list.

[0383] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0384] Step 1:

[0385] User Registration and Login

[0386] User Registration

[0387] A user accesses the system and registers a new account by entering an email address, password, and username.

[0388] Input: Email address, password, username

[0389] The terminal sends the entered information to the server.

[0390] The server stores the received information in a database and generates a registration completion message.

[0391] Output: Registration complete message

[0392] Log in

[0393] The user goes to the login screen, enters their email address and password, and clicks the login button.

[0394] Input: Email address, password

[0395] The terminal sends the entered login information to the server.

[0396] The server checks the information against its database and generates an authentication token if authentication is successful, or a login error message if it fails.

[0397] Output: Authentication token or login error message

[0398] Step 2:

[0399] Upload your work

[0400] Work selection

[0401] The user selects digital content and enters metadata such as title, artist name, and year of production.

[0402] Input: Digital content file (e.g. painting, poem, novel, photograph), title, artist name, year of creation

[0403] The device sends the selected files and metadata to the server.

[0404] The server stores the received files and metadata in a database.

[0405] Output: Save success message or error message

[0406] Step 3:

[0407] User sentiment analysis

[0408] Emotional Data Collection

[0409] Users are given permission to use the camera and microphone to collect emotional data while they are entering digital content or reviewing evaluation results.

[0410] Input: Facial expression data, voice data

[0411] The device sends facial expression and voice data to the server.

[0412] Emotion analysis

[0413] The server's emotion engine analyzes the received facial expressions and voice data to determine the user's emotional state.

[0414] Data processing: facial expression analysis, voice analysis

[0415] The server generates the analysis results and adds them to the metadata or uses them to correct the analysis results.

[0416] Output: Analysis results

[0417] Step 4:

[0418] AI-based analysis

[0419] Data analysis preparation

[0420] The server sends the stored digital content and metadata to the AI ​​analysis engine.

[0421] Input: Digital content files, metadata

[0422] AI analysis

[0423] The server's AI analysis engine analyzes digital content and evaluates its aesthetic value, historical value, popularity, influence, etc.

[0424] Data operations: aesthetic value evaluation, historical value evaluation, popularity evaluation, influence evaluation

[0425] The emotion engine corrects and supplements the AI ​​analysis results based on the user's emotional state.

[0426] Output: Final analysis results

[0427] Save analysis results

[0428] The server stores the final analysis results in a database.

[0429] Output: Message that final analysis results have been saved

[0430] Step 5:

[0431] Displaying analysis results

[0432] Result acquisition and display

[0433] Users log in to their account and select the digital content for which they want to check the analysis results.

[0434] Input: User ID, Digital Content ID

[0435] The server retrieves the analysis results of the relevant digital content from the database.

[0436] The terminal displays the obtained analysis results to the user.

[0437] Output: Analysis result display

[0438] Step 6:

[0439] Buying and selling artwork

[0440] Sales Settings

[0441] The user (seller) sets a selling price based on the analysis results and lists the item for sale.

[0442] Input: Digital content ID, sales price

[0443] The server adds the set price and digital content information to the sales list.

[0444] Output: Sales list update completion message

[0445] Purchase procedure

[0446] The user (buyer) selects the digital content they wish to purchase from the sales list and completes the purchase procedure.

[0447] Input: Digital content ID to purchase, payment information

[0448] The server verifies the purchase payment and sends the digital content data to the buyer.

[0449] Output: Purchase confirmation message and digital content delivery completion message

[0450] (Application example 2)

[0451] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0452] It is necessary to analyze the emotional state of passengers in self-driving vehicles in real time and display artwork or play music that is appropriate for that state to improve passenger comfort and satisfaction. However, conventional self-driving vehicles do not have such functionality, and there is a problem in that they cannot provide services that correspond to the emotional state of passengers.

[0453] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0454] In this invention, the server includes: a means for a user to input artworks and metadata; a means for the server to receive the input artworks and metadata and store them in a database; a means for the server to transmit the stored artworks and metadata to an AI analysis engine and generate analysis results; a means for the server to display the analysis results to the user; a means for an emotion analysis engine in the autonomous vehicle to analyze the emotional state of passengers using a camera and a microphone; and a means for controlling the display and sound system in the vehicle to display artworks or play music based on the emotional state of the passengers, thereby enabling the provision of optimal services according to the emotional state of passengers.

[0455] "Works of art" is a general term for works including visual arts such as paintings, poems, novels, and photographs, as well as written art.

[0456] "Metadata" refers to additional information associated with a work of art, such as the title, artist, and year of creation.

[0457] A "server" is a computer system that receives, stores, and analyzes data entered by a user.

[0458] An "AI analysis engine" refers to an artificial intelligence model for evaluating works of art, and has the ability to analyze aesthetic value, historical value, popularity, influence, etc.

[0459] The "emotion analysis engine" is a system that uses cameras and microphones to analyze passengers' emotional states from their facial expressions and voices.

[0460] A "display" is a screen installed inside the vehicle, and is a device for visually displaying analysis results and artwork.

[0461] "Sound system" refers to audio equipment such as speakers for playing music or voice in a vehicle.

[0462] "User" refers to the person who inputs artwork into the system and reviews the analysis results.

[0463] "Passenger" refers to a person riding in an autonomous vehicle and is the subject of emotion analysis.

[0464] The system of this invention analyzes passenger emotions and displays and plays artworks in autonomous vehicles. The user inputs artworks and metadata, and the server receives, stores, and analyzes them, then displays the results to the user. An emotion analysis engine is also installed in the autonomous vehicle, and it uses cameras and microphones to analyze the passengers' emotional state in real time.

[0465] The hardware used includes:

[0466] High-resolution camera: Captures passengers' facial expressions.

[0467] Microphone: Collects passenger voices.

[0468] Display: An in-car monitor for displaying analytical results or artwork.

[0469] Sound system: Speakers and other devices that play music and audio inside the vehicle.

[0470] The software used includes:

[0471] OpenCV: A library for face detection.

[0472] TensorFlow: An artificial intelligence model for sentiment analysis.

[0473] Front-end application: A web or mobile app that provides the user interface.

[0474] Back-end server: A server system that manages databases and performs AI analysis.

[0475] The specific process is as follows: users first access the system and input artworks and their metadata. The device then sends this data to the server, which receives and stores it. The server then sends the stored data to the AI ​​analysis engine, which generates analysis results. Users can then view the analysis results in their account.

[0476] Furthermore, an emotion analysis engine inside the autonomous vehicle will analyze passengers' facial expressions and voices in real time to detect their emotional state, and based on this emotional state, it will display appropriate artwork on the display and play appropriate music or poetry through the sound system, thereby providing a comfortable in-car environment optimized for passengers' emotions.

[0477] Specific examples

[0478] Example 1: Stress reduction

[0479] If a passenger is feeling stressed, the emotion analysis engine will detect the emotion of "anger." Based on the results of emotion analysis performed on camera footage and audio data, relaxing nature scenes will be displayed on the in-car display and relaxing music will be played over the sound system.

[0480] Example 2: Promoting relaxation

[0481] If the passenger is relaxed, the emotion analysis engine detects the emotion of "happiness." Depending on the passenger's emotional state, bright landscape images will be displayed on the in-car display and upbeat music will be played over the sound system.

[0482] Specifically, the system operates by inputting the following prompt sentence into the generative AI model:

[0483] "Write a program that uses real-time camera footage to analyze a person's emotions. Based on that analysis, add functionality to show appropriate images on the display and play appropriate music on the sound system."

[0484] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0485] Step 1:

[0486] The user inputs the artwork and metadata.

[0487] A user accesses the system and inputs files of artworks such as paintings, poems, novels, and photographs, along with metadata such as the title, artist name, and year of production. The input data is sent from the terminal to the server.

[0488] Step 2:

[0489] A server receives the input artwork and metadata and stores them in a database.

[0490] The server receives the artwork files and metadata sent from the device and stores them in a database, which is then used for subsequent AI analysis.

[0491] Step 3:

[0492] The server sends the stored artworks and metadata to an AI analysis engine to generate analysis results.

[0493] The server sends the artworks and metadata stored in the database to an AI analysis engine, which uses generative AI models to evaluate them based on aesthetic value, historical value, popularity, influence, etc. A numerical score is generated as a result of the evaluation.

[0494] Step 4:

[0495] The server displays the analysis results to the user.

[0496] The server sends the generated analysis results to the user's device and displays them through the user's account. The user can check the evaluation results and decide on appropriate actions (e.g., buying or selling the work).

[0497] Step 5:

[0498] An emotion analysis engine within the autonomous vehicle uses cameras and microphones to analyze the emotional state of passengers.

[0499] Cameras and microphones collect facial expressions and voice recordings of passengers in the car in real time and send them to an emotion analysis engine, which uses a TensorFlow model to analyze this data and determine the passenger's emotional state.

[0500] Step 6:

[0501] Controlling the in-car display and sound systems based on the passenger's emotional state to display artwork or play music.

[0502] Based on the output of the emotion analysis engine, the server selects an appropriate artwork or music file, and the display shows images or videos that match the emotional state, while the sound system plays relaxing or upbeat music.

[0503] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0504] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0505] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0506] [Second embodiment]

[0507] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0508] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0509] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0510] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0511] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0512] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0513] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0514] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0515] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0516] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0517] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0518] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0519] This invention provides a system for fairly and transparently evaluating the value of artworks. This system allows users to upload their own artworks, and an AI analysis engine is used to evaluate the artworks in detail based on their aesthetic value, historical value, popularity, influence, etc. Below, we will show the processing details and specific examples of the program for this system.

[0520] Basic processing flow

[0521] 1. User Registration and Login

[0522] User: Access the system and register a new account by entering an email address, password, and username, then log in to the account.

[0523] Server: Receives registration information and stores it in a database. Receives login information and returns an authentication token to the user if authentication is successful.

[0524] 2. Upload your work

[0525] User: Select a work of art such as a painting, poem, novel, or photograph and enter metadata such as title, artist, and year of creation.

[0526] On the device: Sends the uploaded file and metadata to the server.

[0527] Server: Stores received files and metadata and prepares them for analysis.

[0528] 3. AI-based analysis

[0529] Server (AI analysis engine): The saved artwork data is sent to the analysis engine, which evaluates it based on specified criteria, including aesthetic value, historical value, popularity, and influence.

[0530] Server: Receives the analysis results and stores them in a database.

[0531] 4. Displaying the analysis results

[0532] Users: Log in to their account and check the analysis results. View detailed analysis results from the work list.

[0533] Server: Visually presents the analysis results to the user.

[0534] 5. Buying and Selling Artworks

[0535] User (seller): Sets the selling price based on the analysis results and sends it to the server.

[0536] Server: Adds the work to the sales list at a set price.

[0537] User (Buyer): Selects the work of interest from the sales list and completes the purchase process.

[0538] Server: Validates purchase payments and sends digital copies of the work to the buyer.

[0539] Specific examples

[0540] Example 1: Evaluation of a painting

[0541] 1. User: The user accesses the system with the desire to have the drawing he or she has drawn evaluated.

[0542] 2. Device: Upload the painting file "autumn_landscape.jpg" and enter the metadata (title "Autumn Landscape", artist "Ichiro Tanaka", year of creation "2023").

[0543] 3. Server: Stores received files and data and passes them to the AI ​​analysis engine.

[0544] 4. AI analysis engine: Analyzes artworks and evaluates their aesthetic value, historical value, popularity, and influence.

[0545] 5. Server: Stores the analysis results (e.g. aesthetic value rating 8.5 / 10, historical value rating 7 / 10, popularity rating 6 / 10, influence rating 7.5 / 10) and displays them to the user.

[0546] 6. User: Check the evaluation results and list the work for sale for 10,000 yen.

[0547] Example 2: Poetry rating

[0548] 1. User: The user accesses the system because they want to know the value of the poem they have written.

[0549] 2. Device: Upload the poem file "winter_scene.txt" and enter the metadata (title "Winter Scene," author "Jiro Sato," and year of creation "2022").

[0550] 3. Server: Stores received files and data and passes them to the AI ​​analysis engine.

[0551] 4. AI analysis engine: Analyzes poems and evaluates their aesthetic value, historical value, popularity, and influence.

[0552] 5. Server: Stores the analysis results (e.g. aesthetic value rating 7.5 / 10, historical value rating 6 / 10, popularity rating 7 / 10, influence rating 8 / 10) and displays them to the user.

[0553] 6. User: Checks the evaluation results and lists the poem for sale for 5,000 yen.

[0554] In this way, the system of the present invention provides users with a means to objectively and fairly evaluate their own artworks, enabling them to buy and sell their artworks at fair prices based on that evaluation, thereby enabling a more accurate understanding of the value of artworks and promoting fair transactions.

[0555] The processing flow will be explained below.

[0556] Step 1:

[0557] A user accesses the system and registers a new account by entering an email address, password, and username.

[0558] Step 2:

[0559] The device sends the entered registration information to the server in JSON format.

[0560] Step 3:

[0561] The server stores the received registration information in a database and sends a confirmation email to the user.

[0562] Step 4:

[0563] The user confirms their email address by clicking the link in the confirmation email they receive.

[0564] Step 5:

[0565] The server verifies the email address and records the user registration in the database.

[0566] Step 6:

[0567] The user logs in by entering their email address and password.

[0568] Step 7:

[0569] The terminal sends the entered login information to the server in JSON format.

[0570] Step 8:

[0571] The server verifies the entered login information and, if authentication is successful, generates an authentication token and returns it to the user.

[0572] Step 9:

[0573] The user logs back into the system and opens the account screen.

[0574] Step 10:

[0575] The user selects a work of art (e.g., an image file of a painting) and enters metadata such as the title, artist name, and year of creation.

[0576] Step 11:

[0577] The terminal transmits the selected file and the entered metadata to the server.

[0578] Step 12:

[0579] The server temporarily stores the received file and metadata, and stores the work file in file storage.

[0580] Step 13:

[0581] The server prepares to pass the stored artwork data and metadata to the AI ​​analysis engine.

[0582] Step 14:

[0583] The server (AI analysis engine) performs analysis to evaluate the work's aesthetic value, historical value, popularity, influence, etc.

[0584] Step 15:

[0585] The AI ​​analysis engine (on the server) generates the analysis results and generates scores for aesthetic value, historical value, popularity, and influence.

[0586] Step 16:

[0587] The server receives the analysis results and stores them in a database.

[0588] Step 17:

[0589] The user checks the analysis results from the account screen.

[0590] Step 18:

[0591] The server displays the analysis results to the user.

[0592] Step 19:

[0593] The user (seller) sets the selling price of the work based on the analysis results and lists it for sale.

[0594] Step 20:

[0595] The server adds the work to the sales list at the set price.

[0596] Step 20:

[0597] The user (buyer) selects the work of interest from the sales list and completes the purchase procedure.

[0598] Step 21:

[0599] The server verifies the purchase payment and transmits the digital copy of the work to the buyer.

[0600] Through these steps, the system will ensure fair and transparent evaluation of artworks and the sale and purchase of artworks at fair prices.

[0601] Example 1

[0602] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0603] The conventional art evaluation system relied on subjective evaluation and lacked fairness and transparency. It was also difficult to grasp the true value of a work of art, and the system was unreliable in transactions, making it difficult to promote fair transactions.

[0604] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0605] In this invention, the server includes means for a user to input artworks and metadata, means for a terminal to transmit the input artworks and metadata to the server, means for the server to receive the input artworks and metadata and store them in a database, means for the server to transmit the stored artworks and metadata to an AI analysis engine and generate analysis results, means for visually presenting the analysis results to the user, means for the user to set a selling price based on the analysis results and for the server to add the artwork to a sales list at that price, means for the user to purchase the artwork from the sales list, and means for the server to process the purchase procedure and transmit artwork data to the purchaser. This makes it possible to fairly and transparently evaluate the value of artworks and promote fair transactions.

[0606] "Users" are entities that use the system to upload artworks and evaluate and sell them.

[0607] A "terminal" is a device used by a user, such as a computer or smartphone, that includes a means for transmitting input artworks and metadata to a server.

[0608] A "server" is the computer that serves as the core of the system, receiving input information, storing it in a database, and analyzing it using an AI analysis engine.

[0609] "Work of art" refers to any work of creative expression, such as a painting, poem, novel, or photograph.

[0610] "Metadata" is additional information about a work of art, including the title, artist name, and year of creation.

[0611] The "database" is an information storage system for efficiently managing and storing received artworks, metadata, analysis results, etc.

[0612] The "AI Analysis Engine" is an artificial intelligence engine that analyzes works of art and evaluates their aesthetic value, historical value, popularity, and influence.

[0613] "Analysis results" are evaluation results provided by the AI ​​analysis engine, and include evaluation indicators such as aesthetic value, historical value, popularity, and influence.

[0614] "Visual presentation" refers to providing analysis results to users in an easy-to-read format such as graphs or charts.

[0615] "Sales List" means a list of artworks that can be viewed and purchased by other Users along with the selling price set by the User.

[0616] "Purchase procedure" refers to the process by which a user purchases an artwork selected from a sales list, including payment and the transfer of artwork data.

[0617] "Artwork Data" refers to the digital file of the Artwork sent to the Purchaser.

[0618] The present invention provides a system for fair and transparent evaluation of the value of artworks. This system allows users to upload their own artworks and uses an AI analysis engine to evaluate the artworks in detail based on their aesthetic value, historical value, popularity, influence, etc.

[0619] Specifically, the following hardware and software are used:

[0620] Hardware: Servers, devices (computers, smartphones, etc.)

[0621] Software: Databases (e.g., MySQL, PostgreSQL), cloud storage (e.g., Amazon S3, Google Cloud Storage), AI analytics engines (e.g., TensorFlow, PyTorch)

[0622] First, a user accesses the system using a terminal and registers a new account by entering their email address, password, and username. Then, they log in with their email address and password. The server receives the information entered by the user and stores it in a database. It also verifies the login information and securely authenticates the user.

[0623] Next, the user selects a file of an artwork (e.g., painting, poem, novel, photograph, etc.) from the device through the on-screen interface and enters metadata such as the title, artist name, and year of production. The device then sends this information to the server. The server saves the received file and metadata in storage and returns a notification to the user that saving is complete.

[0624] The server then sends the stored artwork data to an AI analysis engine, which evaluates the artwork based on specified criteria such as aesthetic value, historical value, popularity, and influence. During this process, the AI ​​analysis engine analyzes the input artwork from various perspectives and generates results based on each evaluation indicator. The server then stores the evaluation results received from the AI ​​analysis engine in a database.

[0625] After logging in to the system, users can check the evaluation results of their work. The server presents the analysis results to users in a visually easy-to-read format (e.g., graphs or charts), allowing users to concretely grasp the value of their work.

[0626] Furthermore, when a user wants to sell their artwork, they can set an appropriate selling price based on the evaluation results and send that information to the server. The server then adds the artwork to a sales list at the set price, making it available for other users to view. When a potential buyer (user) selects a piece of artwork and completes the purchase procedure, the server confirms the buyer's payment and sends the artwork data to the buyer.

[0627] Specific examples

[0628] 1. A user accesses the system because they want their drawing to be evaluated.

[0629] 2. The device uploads the painting file "autumn_landscape.jpg" and enters the metadata (title "Autumn Landscape", artist "Ichiro Tanaka", year of creation "2023").

[0630] 3. The server stores the received files and data and passes them to the AI ​​analysis engine.

[0631] 4. An AI analysis engine analyzes the artwork and evaluates its aesthetic value, historical value, popularity, and influence.

[0632] 5. The server stores the analysis results (e.g., aesthetic value rating 8.5 / 10, historical value rating 7 / 10, popularity rating 6 / 10, influence rating 7.5 / 10) and displays them to the user.

[0633] 6. The user checks the evaluation results and lists the work for sale for 10,000 yen.

[0634] Example prompt: "Evaluate this painting's aesthetic value, historical value, popularity, and influence."

[0635] In this way, the system of the present invention provides users with a means to objectively and fairly evaluate their own artworks, enabling them to buy and sell their artworks at fair prices based on that evaluation, thereby enabling a more accurate understanding of the value of artworks and promoting fair transactions.

[0636] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0637] Step 1: User Registration and Login

[0638] The user accesses the system's registration screen and creates a new account by entering an email address, password, and username. The user enters this information (input data: email address, password, username) and presses the "Register" button.

[0639] The server saves the received registration information in a database (output data: Save registration information to database), and then returns a message to the user indicating that registration was successful.

[0640] The user accesses the login screen and enters the registered email address and password. The user enters this information (input data: email address, password) and presses the "Login" button.

[0641] The server receives the login information and authenticates it against the database. If authentication is successful, it generates an authentication token (such as a JWT) and returns it to the user (output data: authentication token).

[0642] Step 2: Upload your work

[0643] After logging in, the user opens the artwork upload screen and selects the artwork file. They also enter metadata such as the title, artist name, and year of production. The user enters this information (input data: artwork file, title, artist name, year of production) and presses the "Upload" button.

[0644] The terminal transmits the selected file and metadata to the server (input data: file, metadata).

[0645] The server saves the received file in a storage system (e.g., Amazon S3) and saves the metadata in a database (output data: file saved in storage, metadata saved in database). After saving is complete, it returns a message to the user saying "upload successful."

[0646] Step 3: AI analysis

[0647] The server sends the saved artwork data to the AI ​​analysis engine (input data: artwork data).

[0648] The AI ​​analysis engine uses the submitted artwork data to evaluate its aesthetic value, historical value, popularity, and influence (data calculation: aesthetic value analysis, historical value analysis, popularity analysis, influence analysis). Evaluation criteria include various factors such as color, composition, and theme.

[0649] The server stores the evaluation results received from the AI ​​analysis engine in a database (output data: evaluation results stored in the database).

[0650] Step 4: Viewing the analysis results

[0651] The user logs in to their account and opens the analysis results screen. The user then sends a request to check the analysis results (input data: user ID, analysis result confirmation request).

[0652] The server receives a request from the user and retrieves the corresponding analysis results from the database (output data: analysis results). It then generates graphs and charts to visually present the retrieved analysis results to the user (data processing: graphing and charting the analysis results). These results are then displayed to the user.

[0653] Step 5: Buying and Selling Your Artwork

[0654] The user (seller) sets a selling price based on the evaluation results and sends that information to the server (input data: selling price, work information).

[0655] The server adds the work to the sales list at the set price, making it available for other users to view (output data: work information added to the sales list).

[0656] The user (buyer) selects the work they wish to purchase from the sales list, presses the "Purchase" button, and enters the information required to complete the purchase (input data: purchase request, payment information).

[0657] The server executes the purchase procedure, and after successful payment, sends the digital data of the work to the buyer (output data: digital data of the work sent to the buyer). It also sends a sale notification to the seller.

[0658] (Application example 1)

[0659] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0660] Conventional art evaluation systems use an AI analysis engine to evaluate artworks based on artworks and metadata entered by users, but lack a way to visually present the evaluation results in real time. This requires users to use a separate device to check the evaluation results, which is inconvenient. Furthermore, the lack of instant feedback of evaluation results makes them difficult to use in galleries, museums, and other settings. Therefore, the present invention aims to provide an evaluation system that solves these problems.

[0661] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0662] In this invention, the server includes means for a user to input artworks and metadata, means for the server to receive the input artworks and metadata and store them in a database, means for the server to transmit the stored artworks and metadata to an AI analysis engine and generate analysis results, means for displaying the analysis results to the user, and means for a display device to visually overlay the analysis results in front of the user's eyes, allowing the user to instantly visually confirm the evaluation results while appreciating the artworks.

[0663] "User" refers to a person who accesses the system and inputs or views artwork.

[0664] "Work of art" refers to any artistic or literary work, such as a painting, poem, novel, or photograph.

[0665] "Metadata" is additional information about a work of art, such as its title, artist name, and year of creation.

[0666] "Server" refers to a computer system that receives, stores, and processes information entered by users over a network.

[0667] "Database" refers to a digital storage device for the systematic preservation of artworks and metadata.

[0668] "AI analysis engine" refers to software that uses artificial intelligence technology to evaluate input artworks.

[0669] "Analysis results" refers to the evaluation results of the aesthetic value, historical value, popularity, influence, etc. of the artwork as assessed by the AI ​​analysis engine.

[0670] A "display device" is a device that allows a user to visually check the evaluation results, and includes smart glasses, AR glasses, etc.

[0671] "Visually overlaying" refers to the ability of a display device to superimpose on a visible object or content.

[0672] The present invention will be described in detail below with reference to an embodiment thereof. This system links a display device such as smart glasses with a server, and visually displays the evaluation results of artworks to a user in real time.

[0673] Hardware and software used

[0674] 1. Hardware:

[0675] Smart glasses: Examples include AR glasses such as Microsoft HoloLens and Google Glass.

[0676] Server: A computer system for processing and storing data over a network.

[0677] 2. Software:

[0678] Operating System (OS): The basic software that runs on the smart glasses and the server.

[0679] Python: A programming language used in the present invention for image processing and server communication.

[0680] OpenCV: A library for image capture and processing.

[0681] AI Analytics Engine: Deep learning models for assessing the aesthetic value, historical value, popularity, and influence of artworks.

[0682] Processing flow

[0683] 1. User views a work of art:

[0684] A user wears smart glasses and visits a gallery or museum, and the glasses' camera captures the artwork on display.

[0685] 2. Image capture:

[0686] The smart glasses' camera captures images of artwork within the user's field of view.

[0687] 3. Send to server:

[0688] The captured image is sent from the smart glasses to the server, which then receives the image and sends the data to the AI ​​analysis engine.

[0689] 4. AI analysis:

[0690] Based on the image data received, the AI ​​analysis engine evaluates the aesthetic value, historical value, popularity, and influence of the artwork.

[0691] 5. Receiving and storing evaluation results:

[0692] The server receives the evaluation results from the AI ​​analysis engine and stores them in a database, after which the evaluation results are sent to the smart glasses.

[0693] 6. Overlay display:

[0694] The smart glasses overlay the received evaluation results in the user's field of view, allowing the user to check the evaluation results in real time while viewing the artwork.

[0695] Specific examples

[0696] 1. Example of a painting evaluation:

[0697] A user puts on the smart glasses and looks at the painting "Spring Landscape" in a gallery. The glasses capture the painting and send it to the server. The server analyzes it using an AI analysis engine and sends the evaluation results (e.g., aesthetic value 9.0, historical value 8.0, popularity 7.5, influence 8.5) to the smart glasses. The user can visually confirm these evaluations.

[0698] 2. Poetry evaluation examples:

[0699] A user views the poem "Summer Memories" at an art museum. The smart glasses capture a digital representation of the poem and send it to a server. An AI analysis engine analyzes the poem and rates it on aesthetic value (8.0), historical value (6.5), popularity (7.0), and influence (9.0). These results are overlaid on the smart glasses, allowing the user to view the results in real time.

[0700] Prompt Sentence Examples

[0701] An example of a prompt used by this system is:

[0702] "This image is of a Spring Landscape from a famous art museum. Please rate the artwork's aesthetic value, historical value, popularity, and influence."

[0703] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0704] Step 1:

[0705] Users appreciate artwork

[0706] A user wears smart glasses and visits a gallery or museum, and the glasses' camera visually captures the artworks on display.

[0707] Input: Live video of artwork captured through the smart glasses camera

[0708] Output: Image data of the captured artwork

[0709] Step 2:

[0710] Image capture

[0711] As the user views the artwork, the camera in the smart glasses captures an image of the artwork.

[0712] Input: Live video from the smart glasses camera

[0713] Output: Still image data of artwork captured within the smart glasses

[0714] Step 3:

[0715] Send to server

[0716] The smart glasses capture images of paintings and poems and send them to a server, along with the metadata.

[0717] Input: Image data and metadata of the captured artwork (e.g., title, artist name, year of creation)

[0718] Output: Image data and metadata sent to the server

[0719] Step 4:

[0720] AI-based analysis

[0721] The server sends the received image data and metadata to an AI analysis engine for evaluation, which uses deep learning models to analyze aesthetic value, historical value, popularity, influence, and other factors.

[0722] Input: Image data and metadata sent to the server

[0723] Output: The evaluation results returned by the AI ​​analysis engine (e.g., aesthetic value 9.0, historical value 8.0, popularity 7.5, influence 8.5)

[0724] Step 5:

[0725] Receiving and storing evaluation results

[0726] The server receives the evaluation results returned by the AI ​​analysis engine and stores them in a database.

[0727] Input: Evaluation results from the AI ​​analysis engine

[0728] Output: Evaluation result data stored in a database

[0729] Step 6:

[0730] Overlay Display

[0731] The smart glasses overlay the evaluation results received from the server in the user's field of view, allowing the user to simultaneously view the artwork and its evaluation results.

[0732] Input: Evaluation result data sent from the server

[0733] Output: Evaluation results overlaid on the smart glasses display

[0734] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0735] The present invention provides a system that allows users to rate artworks and, by combining it with an emotion engine, customizes the evaluation and display of the artworks based on the user's emotional state. This system allows users to upload artworks, which are evaluated using an AI analysis engine, and further analyzes the user's emotions using the emotion engine, with the results reflected in the evaluation and display. The processing content and specific examples of the program for this system are shown below.

[0736] Basic processing flow

[0737] 1. User Registration and Login

[0738] A user accesses the system, registers a new account by entering an email address, password, and username, and then logs in to the account.

[0739] The server receives the registration information, stores it in a database, receives the login information, and if authentication is successful, returns an authentication token to the user.

[0740] 2. Upload your work

[0741] The user selects a work of art such as a painting, poem, novel, or photograph and enters metadata such as the title, artist name, and year of creation.

[0742] The device sends the uploaded file and metadata to the server.

[0743] The server stores the received files and metadata and prepares them for analysis.

[0744] 3. User sentiment analysis

[0745] When a user inputs their work or checks the evaluation results, the emotion engine analyzes the user's emotional state from their facial expressions and voice input.

[0746] The emotion engine (in the server) analyzes the user's emotions and adds the results to the metadata or reflects them in the display of the analysis results.

[0747] 4. AI-based analysis

[0748] The server (AI analysis engine) evaluates the work's aesthetic value, historical value, popularity, influence, etc.

[0749] The AI ​​analysis engine (on the server) generates the analysis results and generates scores for aesthetic value, historical value, popularity, and influence.

[0750] The emotion engine (within the server) uses the emotion analysis results to make corrections and add supplementary information to the AI ​​analysis results.

[0751] 5. Displaying the analysis results

[0752] The user checks the analysis results from their account.

[0753] The server displays the analysis results to the user, which may be customized according to the user's emotional state.

[0754] 6. Buying and Selling Works

[0755] The user (seller) sets the selling price of the work based on the analysis results and lists it for sale.

[0756] The server adds the work to the sales list at the set price.

[0757] The user (buyer) selects the work of interest from the sales list and completes the purchase procedure.

[0758] The server verifies the purchase payment and transmits the digital copy of the work to the buyer.

[0759] Specific examples

[0760] Example 1: Painting rating and sentiment analysis

[0761] 1. A user accesses the system because they want their drawing to be evaluated.

[0762] 2. The device uploads the painting file "autumn_landscape.jpg" and enters the metadata (title "Autumn Landscape", artist "Ichiro Tanaka", year of production "2023").

[0763] 3. The server stores the received files and data and passes them to the AI ​​analysis engine.

[0764] 4. When the user enters their work or checks the evaluation results, the emotion engine analyzes their emotional state from their facial expressions.

[0765] 5. An AI analysis engine analyzes the artwork and evaluates its aesthetic value, historical value, popularity, and influence.

[0766] 6. Based on the analysis results, the emotion engine customizes the display format and focus points to suit the user's preferences.

[0767] 7. The server stores the analysis results (e.g., aesthetic value rating 8.5 / 10, historical value rating 7 / 10, popularity rating 6 / 10, influence rating 7.5 / 10) and displays them to the user.

[0768] 8. The user checks the evaluation results and lists the work for sale for 10,000 yen.

[0769] Example 2: Poetry rating and sentiment analysis

[0770] 1. A user accesses the system because they want to know the value of a poem they have written.

[0771] 2. The device uploads the poem file "winter_scene.txt" and enters the metadata (title "Winter Scene," author "Jiro Sato," and year of creation "2022").

[0772] 3. The server stores the received files and data and passes them to the AI ​​analysis engine.

[0773] 4. When the user inputs their work or checks the evaluation results, the emotion engine analyzes their emotional state from their voice input.

[0774] 5. An AI analysis engine analyzes the poem and evaluates its aesthetic value, historical value, popularity, and influence.

[0775] 6. The emotion engine uses the analysis results to customize the display to attract the user's interest.

[0776] 7. The server stores the analysis results (e.g., aesthetic value rating 7.5 / 10, historical value rating 6 / 10, popularity rating 7 / 10, influence rating 8 / 10) and displays them to the user.

[0777] 8. The user checks the rating and lists the poem for sale for 5,000 yen.

[0778] In this way, the system of the present invention provides users with a means to objectively and fairly evaluate their own artworks, enabling them to buy and sell artworks at fair prices based on those evaluations. Furthermore, by using an emotion engine to analyze the user's emotional state and reflecting the results in evaluations and displays, the system can provide a more personalized experience.

[0779] The processing flow will be explained below.

[0780] Step 1:

[0781] A user accesses the system and registers a new account by entering an email address, password, and username.

[0782] Step 2:

[0783] The device sends the entered registration information to the server in JSON format.

[0784] Step 3:

[0785] The server stores the received registration information in a database and sends a confirmation email to the user.

[0786] Step 4:

[0787] The user confirms their email address by clicking the link in the confirmation email they receive.

[0788] Step 5:

[0789] The server verifies the email address and records the user registration in the database.

[0790] Step 6:

[0791] The user logs in by entering their email address and password.

[0792] Step 7:

[0793] The terminal sends the entered login information to the server in JSON format.

[0794] Step 8:

[0795] The server verifies the entered login information and, if authentication is successful, generates an authentication token and returns it to the user.

[0796] Step 9:

[0797] The user logs back into the system and opens the account screen.

[0798] Step 10:

[0799] The user selects a work of art such as a painting, poem, novel, or photograph and enters metadata such as the title, artist name, and year of creation.

[0800] Step 11:

[0801] The terminal transmits the selected file and the entered metadata to the server.

[0802] Step 12:

[0803] The server temporarily stores the received file and metadata, and stores the work file in file storage.

[0804] Step 13:

[0805] When a user inputs their work, the emotion engine analyzes their emotional state from their facial expressions and voice input.

[0806] Step 14:

[0807] The emotion engine (in the server) analyzes the emotional state and adds the results to the metadata or reflects them in the display of the analysis results.

[0808] Step 15:

[0809] The server prepares to pass the stored artwork data and metadata to the AI ​​analysis engine.

[0810] Step 16:

[0811] The server (AI analysis engine) performs analysis to evaluate the work's aesthetic value, historical value, popularity, influence, etc.

[0812] Step 17:

[0813] The AI ​​analysis engine (on the server) generates the analysis results and generates scores for aesthetic value, historical value, popularity, and influence.

[0814] Step 18:

[0815] The server receives the analysis results and stores them in a database.

[0816] Step 19:

[0817] The server displays the analysis results to the user, which may be customized according to the user's emotional state.

[0818] Step 20:

[0819] The user checks the analysis results.

[0820] Step 21:

[0821] The user (seller) sets the selling price of the work based on the analysis results and lists it for sale.

[0822] Step 22:

[0823] The server adds the work to the sales list at the set price.

[0824] Step 23:

[0825] The user (buyer) selects the work of interest from the sales list and completes the purchase procedure.

[0826] Step 24:

[0827] The server verifies the purchase payment and transmits the digital copy of the work to the buyer.

[0828] Example 2

[0829] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0830] Conventional art evaluation systems evaluate artworks without considering the user's emotional state, resulting in uniform evaluation results. Furthermore, when users sell artworks, it is difficult to set an appropriate price, and there is a lack of systems that provide an appropriate sales process. Furthermore, there is a problem that the method of presenting analysis results to users is not personalized, beyond simply evaluating artworks.

[0831] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0832] In this invention, the server includes means for a user to input digital content and metadata, means for the server to receive the input digital content and metadata and store them in a database, means for the server to transmit the stored digital content and metadata to an AI analysis engine and generate analysis results, means for the emotion engine to analyze the user's emotional state and correct the analysis results, and means for displaying the analysis results to the user. This makes it possible to present individualized evaluation results that take the user's emotional state into consideration, and by providing appropriate pricing and sales processes, a system that is highly convenient for users is realized.

[0833] "Digital Content" refers to artistic works stored or displayed in digital form, such as paintings, poems, novels, and photographs.

[0834] "Metadata" is additional information related to digital content, including attribute information such as title, author name, and production year.

[0835] "AI analysis engine" refers to an artificial intelligence-based system that analyzes digital content and generates evaluation scores based on aesthetic value, historical value, popularity, influence, etc.

[0836] An "emotion engine" is a system that analyzes a user's facial expressions and voice input to identify their emotional state and reflects the results in the evaluation of digital content.

[0837] "Server" refers to a central computer system for storing, processing, and analyzing digital content and metadata submitted by users.

[0838] "User" means any individual or legal entity that uses the System to upload, review, or sell digital content.

[0839] "Database" refers to a system built on a server that can efficiently store and search input digital content and metadata.

[0840] "Analysis results" refers to the final evaluation information that combines the evaluation score generated by the AI ​​analysis engine and the correction information provided by the emotion engine.

[0841] "Sales Listing" means a listing for publishing and selling Digital Content at a price set by a User.

[0842] An "authentication token" refers to a unique identification code that is issued when a user logs in to a system and is used as authentication information.

[0843] This invention is a system that allows users to rate digital content and customizes the ratings and display of works based on the user's emotional state by combining it with an emotion engine. This system allows users to upload digital content, has an AI analysis engine to rate it, and further uses the emotion engine to analyze the user's emotions, and has the function of reflecting the results in the ratings and display.

[0844] The hardware used includes the user's device (PC, smartphone, tablet, etc.), a server for storing and analyzing data, a camera and microphone for analyzing the user's emotional state, etc. The software used includes a web application for uploading digital content, a database management system, an AI analysis engine, an emotion analysis engine, etc.

[0845] Basic processing flow

[0846] This system mainly has the following functions:

[0847] 1. User Registration and Login:

[0848] A user accesses the system and registers a new account by entering an email address, password, and username. The terminal sends the entered information to the server, which stores it in a database. The user then enters login information, which the terminal sends to the server, which verifies it against the database and returns an authentication token to the user.

[0849] 2. Upload your work:

[0850] The user selects digital content (paintings, poems, novels, photographs, etc.) and enters metadata (title, author, year of creation, etc.). The device sends the selected file and metadata to the server, which receives it and stores it in a database.

[0851] 3. User sentiment analysis:

[0852] While the user is entering digital content or checking the evaluation results, the emotion engine analyzes the user's facial expressions and voice via the camera and microphone. The server analyzes the user's emotional state and adds the results to the metadata or reflects them in the analysis results.

[0853] 4. AI analysis:

[0854] The server sends the digital content and metadata to an AI analysis engine, which evaluates the work's aesthetic value, historical value, popularity, influence, etc. The AI ​​analysis engine generates these scores, and the emotion engine modifies and supplements them, taking into account the user's emotional state. The final analysis results are stored on the server.

[0855] 5. Displaying the analysis results:

[0856] Users can check the analysis results from their account, and the server retrieves the saved analysis results and displays them on the device. The display content is customized according to the user's emotional state.

[0857] 6. Buying and Selling Works:

[0858] The user (seller) sets a selling price based on the analysis results and posts it on the sales list. The server receives this and adds it to the sales list. The user (buyer) selects the work they are interested in from the list and completes the purchase procedure. The server confirms the purchase payment and sends the digital content to the buyer.

[0859] Specific examples

[0860] Example 1: Painting rating and sentiment analysis

[0861] A user accesses the system wanting to have a painting they have drawn evaluated. The terminal uploads the painting file "example_painting.jpg" and inputs metadata (title "Landscape", artist "Yamada Taro", year of production "2023"). The server receives this, saves it, and passes it to the AI ​​analysis engine. When the user enters the work or checks the evaluation results, the emotion engine analyzes the user's emotional state from their facial expressions. The AI ​​analysis engine evaluates the work, and the emotion engine customizes the display. The server saves the analysis results and displays them to the user. The user checks the evaluation results and places the work on the sales list.

[0862] Example 2: Poetry rating and sentiment analysis

[0863] A user accesses the system wanting to know the value of a poem they have written. The device uploads the poem file "example_poem.txt" and inputs metadata (title "Seasonal Poem", author "Sato Hanako", year of creation "2022"). The server receives this, saves it, and passes it to the AI ​​analysis engine. When the user enters a poem or checks the evaluation results, the emotion engine analyzes the user's emotional state from their voice input. The AI ​​analysis engine evaluates the poem, and the emotion engine customizes the display. The server saves the analysis results and displays them to the user. The user checks the evaluation results and places the poem on the sales list.

[0864] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0865] Step 1:

[0866] User Registration and Login

[0867] User Registration

[0868] A user accesses the system and registers a new account by entering an email address, password, and username.

[0869] Input: Email address, password, username

[0870] The terminal sends the entered information to the server.

[0871] The server stores the received information in a database and generates a registration completion message.

[0872] Output: Registration complete message

[0873] Log in

[0874] The user goes to the login screen, enters their email address and password, and clicks the login button.

[0875] Input: Email address, password

[0876] The terminal sends the entered login information to the server.

[0877] The server checks the information against its database and generates an authentication token if authentication is successful, or a login error message if it fails.

[0878] Output: Authentication token or login error message

[0879] Step 2:

[0880] Upload your work

[0881] Work selection

[0882] The user selects digital content and enters metadata such as title, artist name, and year of production.

[0883] Input: Digital content file (e.g. painting, poem, novel, photograph), title, artist name, year of creation

[0884] The device sends the selected files and metadata to the server.

[0885] The server stores the received files and metadata in a database.

[0886] Output: Save success message or error message

[0887] Step 3:

[0888] User sentiment analysis

[0889] Emotional Data Collection

[0890] Users are given permission to use the camera and microphone to collect emotional data while they are entering digital content or reviewing evaluation results.

[0891] Input: Facial expression data, voice data

[0892] The device sends facial expression and voice data to the server.

[0893] Emotion analysis

[0894] The server's emotion engine analyzes the received facial expressions and voice data to determine the user's emotional state.

[0895] Data processing: facial expression analysis, voice analysis

[0896] The server generates the analysis results and adds them to the metadata or uses them to correct the analysis results.

[0897] Output: Analysis results

[0898] Step 4:

[0899] AI-based analysis

[0900] Data analysis preparation

[0901] The server sends the stored digital content and metadata to the AI ​​analysis engine.

[0902] Input: Digital content files, metadata

[0903] AI analysis

[0904] The server's AI analysis engine analyzes digital content and evaluates its aesthetic value, historical value, popularity, influence, etc.

[0905] Data operations: aesthetic value evaluation, historical value evaluation, popularity evaluation, influence evaluation

[0906] The emotion engine corrects and supplements the AI ​​analysis results based on the user's emotional state.

[0907] Output: Final analysis results

[0908] Save analysis results

[0909] The server stores the final analysis results in a database.

[0910] Output: Message that final analysis results have been saved

[0911] Step 5:

[0912] Displaying analysis results

[0913] Result acquisition and display

[0914] Users log in to their account and select the digital content for which they want to check the analysis results.

[0915] Input: User ID, Digital Content ID

[0916] The server retrieves the analysis results of the relevant digital content from the database.

[0917] The terminal displays the obtained analysis results to the user.

[0918] Output: Analysis result display

[0919] Step 6:

[0920] Buying and selling artwork

[0921] Sales Settings

[0922] The user (seller) sets a selling price based on the analysis results and lists the item for sale.

[0923] Input: Digital content ID, sales price

[0924] The server adds the set price and digital content information to the sales list.

[0925] Output: Sales list update completion message

[0926] Purchase procedure

[0927] The user (buyer) selects the digital content they wish to purchase from the sales list and completes the purchase procedure.

[0928] Input: Digital content ID to purchase, payment information

[0929] The server verifies the purchase payment and sends the digital content data to the buyer.

[0930] Output: Purchase confirmation message and digital content delivery completion message

[0931] (Application example 2)

[0932] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0933] It is necessary to analyze the emotional state of passengers in self-driving vehicles in real time and display artwork or play music that is appropriate for that state to improve passenger comfort and satisfaction. However, conventional self-driving vehicles do not have such functionality, and there is a problem in that they cannot provide services that correspond to the emotional state of passengers.

[0934] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0935] In this invention, the server includes: a means for a user to input artworks and metadata; a means for the server to receive the input artworks and metadata and store them in a database; a means for the server to transmit the stored artworks and metadata to an AI analysis engine and generate analysis results; a means for the server to display the analysis results to the user; a means for an emotion analysis engine in the autonomous vehicle to analyze the emotional state of passengers using a camera and a microphone; and a means for controlling the display and sound system in the vehicle to display artworks or play music based on the emotional state of the passengers, thereby enabling the provision of optimal services according to the emotional state of passengers.

[0936] "Works of art" is a general term for works including visual arts such as paintings, poems, novels, and photographs, as well as written art.

[0937] "Metadata" refers to additional information associated with a work of art, such as the title, artist, and year of creation.

[0938] A "server" is a computer system that receives, stores, and analyzes data entered by a user.

[0939] An "AI analysis engine" refers to an artificial intelligence model for evaluating works of art, and has the ability to analyze aesthetic value, historical value, popularity, influence, etc.

[0940] The "emotion analysis engine" is a system that uses cameras and microphones to analyze passengers' emotional states from their facial expressions and voices.

[0941] A "display" is a screen installed inside the vehicle, and is a device for visually displaying analysis results and artwork.

[0942] "Sound system" refers to audio equipment such as speakers for playing music or voice in a vehicle.

[0943] "User" refers to the person who inputs artwork into the system and reviews the analysis results.

[0944] "Passenger" refers to a person riding in an autonomous vehicle and is the subject of emotion analysis.

[0945] The system of this invention analyzes passenger emotions and displays and plays artworks in autonomous vehicles. The user inputs artworks and metadata, and the server receives, stores, and analyzes them, then displays the results to the user. An emotion analysis engine is also installed in the autonomous vehicle, and it uses cameras and microphones to analyze the passengers' emotional state in real time.

[0946] The hardware used includes:

[0947] High-resolution camera: Captures passengers' facial expressions.

[0948] Microphone: Collects passenger voices.

[0949] Display: An in-car monitor for displaying analytical results or artwork.

[0950] Sound system: Speakers and other devices that play music and audio inside the vehicle.

[0951] The software used includes:

[0952] OpenCV: A library for face detection.

[0953] TensorFlow: An artificial intelligence model for sentiment analysis.

[0954] Front-end application: A web or mobile app that provides the user interface.

[0955] Back-end server: A server system that manages databases and performs AI analysis.

[0956] The specific process is as follows: users first access the system and input artworks and their metadata. The device then sends this data to the server, which receives and stores it. The server then sends the stored data to the AI ​​analysis engine, which generates analysis results. Users can then view the analysis results in their account.

[0957] Furthermore, an emotion analysis engine inside the autonomous vehicle will analyze passengers' facial expressions and voices in real time to detect their emotional state, and based on this emotional state, it will display appropriate artwork on the display and play appropriate music or poetry through the sound system, thereby providing a comfortable in-car environment optimized for passengers' emotions.

[0958] Specific examples

[0959] Example 1: Stress reduction

[0960] If a passenger is feeling stressed, the emotion analysis engine will detect the emotion of "anger." Based on the results of emotion analysis performed on camera footage and audio data, relaxing nature scenes will be displayed on the in-car display and relaxing music will be played over the sound system.

[0961] Example 2: Promoting relaxation

[0962] If the passenger is relaxed, the emotion analysis engine detects the emotion of "happiness." Depending on the passenger's emotional state, bright landscape images will be displayed on the in-car display and upbeat music will be played over the sound system.

[0963] Specifically, the system operates by inputting the following prompt sentence into the generative AI model:

[0964] "Write a program that uses real-time camera footage to analyze a person's emotions. Based on that analysis, add functionality to show appropriate images on the display and play appropriate music on the sound system."

[0965] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0966] Step 1:

[0967] The user inputs the artwork and metadata.

[0968] A user accesses the system and inputs files of artworks such as paintings, poems, novels, and photographs, along with metadata such as the title, artist name, and year of production. The input data is sent from the terminal to the server.

[0969] Step 2:

[0970] A server receives the input artwork and metadata and stores them in a database.

[0971] The server receives the artwork files and metadata sent from the device and stores them in a database, which is then used for subsequent AI analysis.

[0972] Step 3:

[0973] The server sends the stored artworks and metadata to an AI analysis engine to generate analysis results.

[0974] The server sends the artworks and metadata stored in the database to an AI analysis engine, which uses generative AI models to evaluate them based on aesthetic value, historical value, popularity, influence, etc. A numerical score is generated as a result of the evaluation.

[0975] Step 4:

[0976] The server displays the analysis results to the user.

[0977] The server sends the generated analysis results to the user's device and displays them through the user's account. The user can check the evaluation results and decide on appropriate actions (e.g., buying or selling the work).

[0978] Step 5:

[0979] An emotion analysis engine within the autonomous vehicle uses cameras and microphones to analyze the emotional state of passengers.

[0980] Cameras and microphones collect facial expressions and voice recordings of passengers in the car in real time and send them to an emotion analysis engine, which uses a TensorFlow model to analyze this data and determine the passenger's emotional state.

[0981] Step 6:

[0982] Controlling the in-car display and sound systems based on the passenger's emotional state to display artwork or play music.

[0983] Based on the output of the emotion analysis engine, the server selects an appropriate artwork or music file, and the display shows images or videos that match the emotional state, while the sound system plays relaxing or upbeat music.

[0984] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0985] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0986] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0987] [Third embodiment]

[0988] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0989] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0990] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0991] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0992] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0993] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0994] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0995] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0996] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0997] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0998] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0999] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[1000] This invention provides a system for fairly and transparently evaluating the value of artworks. This system allows users to upload their own artworks, and an AI analysis engine is used to evaluate the artworks in detail based on their aesthetic value, historical value, popularity, influence, etc. Below, we will show the processing details and specific examples of the program for this system.

[1001] Basic processing flow

[1002] 1. User Registration and Login

[1003] User: Access the system and register a new account by entering an email address, password, and username, then log in to the account.

[1004] Server: Receives registration information and stores it in a database. Receives login information and returns an authentication token to the user if authentication is successful.

[1005] 2. Upload your work

[1006] User: Select a work of art such as a painting, poem, novel, or photograph and enter metadata such as title, artist, and year of creation.

[1007] On the device: Sends the uploaded file and metadata to the server.

[1008] Server: Stores received files and metadata and prepares them for analysis.

[1009] 3. AI-based analysis

[1010] Server (AI analysis engine): The saved artwork data is sent to the analysis engine, which evaluates it based on specified criteria, including aesthetic value, historical value, popularity, and influence.

[1011] Server: Receives the analysis results and stores them in a database.

[1012] 4. Displaying the analysis results

[1013] Users: Log in to their account and check the analysis results. View detailed analysis results from the work list.

[1014] Server: Visually presents the analysis results to the user.

[1015] 5. Buying and Selling Artworks

[1016] User (seller): Sets the selling price based on the analysis results and sends it to the server.

[1017] Server: Adds the work to the sales list at a set price.

[1018] User (Buyer): Selects the work of interest from the sales list and completes the purchase process.

[1019] Server: Validates purchase payments and sends digital copies of the work to the buyer.

[1020] Specific examples

[1021] Example 1: Evaluation of a painting

[1022] 1. User: The user accesses the system with the desire to have the drawing he or she has drawn evaluated.

[1023] 2. Device: Upload the painting file "autumn_landscape.jpg" and enter the metadata (title "Autumn Landscape", artist "Ichiro Tanaka", year of creation "2023").

[1024] 3. Server: Stores received files and data and passes them to the AI ​​analysis engine.

[1025] 4. AI analysis engine: Analyzes artworks and evaluates their aesthetic value, historical value, popularity, and influence.

[1026] 5. Server: Stores the analysis results (e.g. aesthetic value rating 8.5 / 10, historical value rating 7 / 10, popularity rating 6 / 10, influence rating 7.5 / 10) and displays them to the user.

[1027] 6. User: Check the evaluation results and list the work for sale for 10,000 yen.

[1028] Example 2: Poetry rating

[1029] 1. User: The user accesses the system because they want to know the value of the poem they have written.

[1030] 2. Device: Upload the poem file "winter_scene.txt" and enter the metadata (title "Winter Scene," author "Jiro Sato," and year of creation "2022").

[1031] 3. Server: Stores received files and data and passes them to the AI ​​analysis engine.

[1032] 4. AI analysis engine: Analyzes poems and evaluates their aesthetic value, historical value, popularity, and influence.

[1033] 5. Server: Stores the analysis results (e.g. aesthetic value rating 7.5 / 10, historical value rating 6 / 10, popularity rating 7 / 10, influence rating 8 / 10) and displays them to the user.

[1034] 6. User: Checks the evaluation results and lists the poem for sale for 5,000 yen.

[1035] In this way, the system of the present invention provides users with a means to objectively and fairly evaluate their own artworks, enabling them to buy and sell their artworks at fair prices based on that evaluation, thereby enabling a more accurate understanding of the value of artworks and promoting fair transactions.

[1036] The processing flow will be explained below.

[1037] Step 1:

[1038] A user accesses the system and registers a new account by entering an email address, password, and username.

[1039] Step 2:

[1040] The device sends the entered registration information to the server in JSON format.

[1041] Step 3:

[1042] The server stores the received registration information in a database and sends a confirmation email to the user.

[1043] Step 4:

[1044] The user confirms their email address by clicking the link in the confirmation email they receive.

[1045] Step 5:

[1046] The server verifies the email address and records the user registration in the database.

[1047] Step 6:

[1048] The user logs in by entering their email address and password.

[1049] Step 7:

[1050] The terminal sends the entered login information to the server in JSON format.

[1051] Step 8:

[1052] The server verifies the entered login information and, if authentication is successful, generates an authentication token and returns it to the user.

[1053] Step 9:

[1054] The user logs back into the system and opens the account screen.

[1055] Step 10:

[1056] The user selects a work of art (e.g., an image file of a painting) and enters metadata such as the title, artist name, and year of creation.

[1057] Step 11:

[1058] The terminal transmits the selected file and the entered metadata to the server.

[1059] Step 12:

[1060] The server temporarily stores the received file and metadata, and stores the work file in file storage.

[1061] Step 13:

[1062] The server prepares to pass the stored artwork data and metadata to the AI ​​analysis engine.

[1063] Step 14:

[1064] The server (AI analysis engine) performs analysis to evaluate the work's aesthetic value, historical value, popularity, influence, etc.

[1065] Step 15:

[1066] The AI ​​analysis engine (on the server) generates the analysis results and generates scores for aesthetic value, historical value, popularity, and influence.

[1067] Step 16:

[1068] The server receives the analysis results and stores them in a database.

[1069] Step 17:

[1070] The user checks the analysis results from the account screen.

[1071] Step 18:

[1072] The server displays the analysis results to the user.

[1073] Step 19:

[1074] The user (seller) sets the selling price of the work based on the analysis results and lists it for sale.

[1075] Step 20:

[1076] The server adds the work to the sales list at the set price.

[1077] Step 20:

[1078] The user (buyer) selects the work of interest from the sales list and completes the purchase procedure.

[1079] Step 21:

[1080] The server verifies the purchase payment and transmits the digital copy of the work to the buyer.

[1081] Through these steps, the system will ensure fair and transparent evaluation of artworks and the sale and purchase of artworks at fair prices.

[1082] Example 1

[1083] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1084] The conventional art evaluation system relied on subjective evaluation and lacked fairness and transparency. It was also difficult to grasp the true value of a work of art, and the system was unreliable in transactions, making it difficult to promote fair transactions.

[1085] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1086] In this invention, the server includes means for a user to input artworks and metadata, means for a terminal to transmit the input artworks and metadata to the server, means for the server to receive the input artworks and metadata and store them in a database, means for the server to transmit the stored artworks and metadata to an AI analysis engine and generate analysis results, means for visually presenting the analysis results to the user, means for the user to set a selling price based on the analysis results and for the server to add the artwork to a sales list at that price, means for the user to purchase the artwork from the sales list, and means for the server to process the purchase procedure and transmit artwork data to the purchaser. This makes it possible to fairly and transparently evaluate the value of artworks and promote fair transactions.

[1087] "Users" are entities that use the system to upload artworks and evaluate and sell them.

[1088] A "terminal" is a device used by a user, such as a computer or smartphone, that includes a means for transmitting input artworks and metadata to a server.

[1089] A "server" is the computer that serves as the core of the system, receiving input information, storing it in a database, and analyzing it using an AI analysis engine.

[1090] "Work of art" refers to any work of creative expression, such as a painting, poem, novel, or photograph.

[1091] "Metadata" is additional information about a work of art, including the title, artist name, and year of creation.

[1092] The "database" is an information storage system for efficiently managing and storing received artworks, metadata, analysis results, etc.

[1093] The "AI Analysis Engine" is an artificial intelligence engine that analyzes works of art and evaluates their aesthetic value, historical value, popularity, and influence.

[1094] "Analysis results" are evaluation results provided by the AI ​​analysis engine, and include evaluation indicators such as aesthetic value, historical value, popularity, and influence.

[1095] "Visual presentation" refers to providing analysis results to users in an easy-to-read format such as graphs or charts.

[1096] "Sales List" means a list of artworks that can be viewed and purchased by other Users along with the selling price set by the User.

[1097] "Purchase procedure" refers to the process by which a user purchases an artwork selected from a sales list, including payment and the transfer of artwork data.

[1098] "Artwork Data" refers to the digital file of the Artwork sent to the Purchaser.

[1099] The present invention provides a system for fair and transparent evaluation of the value of artworks. This system allows users to upload their own artworks and uses an AI analysis engine to evaluate the artworks in detail based on their aesthetic value, historical value, popularity, influence, etc.

[1100] Specifically, the following hardware and software are used:

[1101] Hardware: Servers, devices (computers, smartphones, etc.)

[1102] Software: Databases (e.g., MySQL, PostgreSQL), cloud storage (e.g., Amazon S3, Google Cloud Storage), AI analytics engines (e.g., TensorFlow, PyTorch)

[1103] First, a user accesses the system using a terminal and registers a new account by entering their email address, password, and username. Then, they log in with their email address and password. The server receives the information entered by the user and stores it in a database. It also verifies the login information and securely authenticates the user.

[1104] Next, the user selects a file of an artwork (e.g., painting, poem, novel, photograph, etc.) from the device through the on-screen interface and enters metadata such as the title, artist name, and year of production. The device then sends this information to the server. The server saves the received file and metadata in storage and returns a notification to the user that saving is complete.

[1105] The server then sends the stored artwork data to an AI analysis engine, which evaluates the artwork based on specified criteria such as aesthetic value, historical value, popularity, and influence. During this process, the AI ​​analysis engine analyzes the input artwork from various perspectives and generates results based on each evaluation indicator. The server then stores the evaluation results received from the AI ​​analysis engine in a database.

[1106] After logging in to the system, users can check the evaluation results of their work. The server presents the analysis results to users in a visually easy-to-read format (e.g., graphs or charts), allowing users to concretely grasp the value of their work.

[1107] Furthermore, when a user wants to sell their artwork, they can set an appropriate selling price based on the evaluation results and send that information to the server. The server then adds the artwork to a sales list at the set price, making it available for other users to view. When a potential buyer (user) selects a piece of artwork and completes the purchase procedure, the server confirms the buyer's payment and sends the artwork data to the buyer.

[1108] Specific examples

[1109] 1. A user accesses the system because they want their drawing to be evaluated.

[1110] 2. The device uploads the painting file "autumn_landscape.jpg" and enters the metadata (title "Autumn Landscape", artist "Ichiro Tanaka", year of creation "2023").

[1111] 3. The server stores the received files and data and passes them to the AI ​​analysis engine.

[1112] 4. An AI analysis engine analyzes the artwork and evaluates its aesthetic value, historical value, popularity, and influence.

[1113] 5. The server stores the analysis results (e.g., aesthetic value rating 8.5 / 10, historical value rating 7 / 10, popularity rating 6 / 10, influence rating 7.5 / 10) and displays them to the user.

[1114] 6. The user checks the evaluation results and lists the work for sale for 10,000 yen.

[1115] Example prompt: "Evaluate this painting's aesthetic value, historical value, popularity, and influence."

[1116] In this way, the system of the present invention provides users with a means to objectively and fairly evaluate their own artworks, enabling them to buy and sell their artworks at fair prices based on that evaluation, thereby enabling a more accurate understanding of the value of artworks and promoting fair transactions.

[1117] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1118] Step 1: User Registration and Login

[1119] The user accesses the system's registration screen and creates a new account by entering an email address, password, and username. The user enters this information (input data: email address, password, username) and presses the "Register" button.

[1120] The server saves the received registration information in a database (output data: Save registration information to database), and then returns a message to the user indicating that registration was successful.

[1121] The user accesses the login screen and enters the registered email address and password. The user enters this information (input data: email address, password) and presses the "Login" button.

[1122] The server receives the login information and authenticates it against the database. If authentication is successful, it generates an authentication token (such as a JWT) and returns it to the user (output data: authentication token).

[1123] Step 2: Upload your work

[1124] After logging in, the user opens the artwork upload screen and selects the artwork file. They also enter metadata such as the title, artist name, and year of production. The user enters this information (input data: artwork file, title, artist name, year of production) and presses the "Upload" button.

[1125] The terminal transmits the selected file and metadata to the server (input data: file, metadata).

[1126] The server saves the received file in a storage system (e.g., Amazon S3) and saves the metadata in a database (output data: file saved in storage, metadata saved in database). After saving is complete, it returns a message to the user saying "upload successful."

[1127] Step 3: AI analysis

[1128] The server sends the saved artwork data to the AI ​​analysis engine (input data: artwork data).

[1129] The AI ​​analysis engine uses the submitted artwork data to evaluate its aesthetic value, historical value, popularity, and influence (data calculation: aesthetic value analysis, historical value analysis, popularity analysis, influence analysis). Evaluation criteria include various factors such as color, composition, and theme.

[1130] The server stores the evaluation results received from the AI ​​analysis engine in a database (output data: evaluation results stored in the database).

[1131] Step 4: Viewing the analysis results

[1132] The user logs in to their account and opens the analysis results screen. The user then sends a request to check the analysis results (input data: user ID, analysis result confirmation request).

[1133] The server receives a request from the user and retrieves the corresponding analysis results from the database (output data: analysis results). It then generates graphs and charts to visually present the retrieved analysis results to the user (data processing: graphing and charting the analysis results). These results are then displayed to the user.

[1134] Step 5: Buying and Selling Your Artwork

[1135] The user (seller) sets a selling price based on the evaluation results and sends that information to the server (input data: selling price, work information).

[1136] The server adds the work to the sales list at the set price, making it available for other users to view (output data: work information added to the sales list).

[1137] The user (buyer) selects the work they wish to purchase from the sales list, presses the "Purchase" button, and enters the information required to complete the purchase (input data: purchase request, payment information).

[1138] The server executes the purchase procedure, and after successful payment, sends the digital data of the work to the buyer (output data: digital data of the work sent to the buyer). It also sends a sale notification to the seller.

[1139] (Application example 1)

[1140] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1141] Conventional art evaluation systems use an AI analysis engine to evaluate artworks based on artworks and metadata entered by users, but lack a way to visually present the evaluation results in real time. This requires users to use a separate device to check the evaluation results, which is inconvenient. Furthermore, the lack of instant feedback of evaluation results makes them difficult to use in galleries, museums, and other settings. Therefore, the present invention aims to provide an evaluation system that solves these problems.

[1142] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1143] In this invention, the server includes means for a user to input artworks and metadata, means for the server to receive the input artworks and metadata and store them in a database, means for the server to transmit the stored artworks and metadata to an AI analysis engine and generate analysis results, means for displaying the analysis results to the user, and means for a display device to visually overlay the analysis results in front of the user's eyes, allowing the user to instantly visually confirm the evaluation results while appreciating the artworks.

[1144] "User" refers to a person who accesses the system and inputs or views artwork.

[1145] "Work of art" refers to any artistic or literary work, such as a painting, poem, novel, or photograph.

[1146] "Metadata" is additional information about a work of art, such as its title, artist name, and year of creation.

[1147] "Server" refers to a computer system that receives, stores, and processes information entered by users over a network.

[1148] "Database" refers to a digital storage device for the systematic preservation of artworks and metadata.

[1149] "AI analysis engine" refers to software that uses artificial intelligence technology to evaluate input artworks.

[1150] "Analysis results" refers to the evaluation results of the aesthetic value, historical value, popularity, influence, etc. of the artwork as assessed by the AI ​​analysis engine.

[1151] A "display device" is a device that allows a user to visually check the evaluation results, and includes smart glasses, AR glasses, etc.

[1152] "Visually overlaying" refers to the ability of a display device to superimpose on a visible object or content.

[1153] The present invention will be described in detail below with reference to an embodiment thereof. This system links a display device such as smart glasses with a server, and visually displays the evaluation results of artworks to a user in real time.

[1154] Hardware and software used

[1155] 1. Hardware:

[1156] Smart glasses: Examples include AR glasses such as Microsoft HoloLens and Google Glass.

[1157] Server: A computer system for processing and storing data over a network.

[1158] 2. Software:

[1159] Operating System (OS): The basic software that runs on the smart glasses and the server.

[1160] Python: A programming language used in the present invention for image processing and server communication.

[1161] OpenCV: A library for image capture and processing.

[1162] AI Analytics Engine: Deep learning models for assessing the aesthetic value, historical value, popularity, and influence of artworks.

[1163] Processing flow

[1164] 1. User views a work of art:

[1165] A user wears smart glasses and visits a gallery or museum, and the glasses' camera captures the artwork on display.

[1166] 2. Image capture:

[1167] The smart glasses' camera captures images of artwork within the user's field of view.

[1168] 3. Send to server:

[1169] The captured image is sent from the smart glasses to the server, which then receives the image and sends the data to the AI ​​analysis engine.

[1170] 4. AI analysis:

[1171] Based on the image data received, the AI ​​analysis engine evaluates the aesthetic value, historical value, popularity, and influence of the artwork.

[1172] 5. Receiving and storing evaluation results:

[1173] The server receives the evaluation results from the AI ​​analysis engine and stores them in a database, after which the evaluation results are sent to the smart glasses.

[1174] 6. Overlay display:

[1175] The smart glasses overlay the received evaluation results in the user's field of view, allowing the user to check the evaluation results in real time while viewing the artwork.

[1176] Specific examples

[1177] 1. Example of a painting evaluation:

[1178] A user puts on the smart glasses and looks at the painting "Spring Landscape" in a gallery. The glasses capture the painting and send it to the server. The server analyzes it using an AI analysis engine and sends the evaluation results (e.g., aesthetic value 9.0, historical value 8.0, popularity 7.5, influence 8.5) to the smart glasses. The user can visually confirm these evaluations.

[1179] 2. Poetry evaluation examples:

[1180] A user views the poem "Summer Memories" at an art museum. The smart glasses capture a digital representation of the poem and send it to a server. An AI analysis engine analyzes the poem and rates it on aesthetic value (8.0), historical value (6.5), popularity (7.0), and influence (9.0). These results are overlaid on the smart glasses, allowing the user to view the results in real time.

[1181] Prompt Sentence Examples

[1182] An example of a prompt used by this system is:

[1183] "This image is of a Spring Landscape from a famous art museum. Please rate the artwork's aesthetic value, historical value, popularity, and influence."

[1184] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1185] Step 1:

[1186] Users appreciate artwork

[1187] A user wears smart glasses and visits a gallery or museum, and the glasses' camera visually captures the artworks on display.

[1188] Input: Live video of artwork captured through the smart glasses camera

[1189] Output: Image data of the captured artwork

[1190] Step 2:

[1191] Image capture

[1192] As the user views the artwork, the camera in the smart glasses captures an image of the artwork.

[1193] Input: Live video from the smart glasses camera

[1194] Output: Still image data of artwork captured within the smart glasses

[1195] Step 3:

[1196] Send to server

[1197] The smart glasses capture images of paintings and poems and send them to a server, along with the metadata.

[1198] Input: Image data and metadata of the captured artwork (e.g., title, artist name, year of creation)

[1199] Output: Image data and metadata sent to the server

[1200] Step 4:

[1201] AI-based analysis

[1202] The server sends the received image data and metadata to an AI analysis engine for evaluation, which uses deep learning models to analyze aesthetic value, historical value, popularity, influence, and other factors.

[1203] Input: Image data and metadata sent to the server

[1204] Output: The evaluation results returned by the AI ​​analysis engine (e.g., aesthetic value 9.0, historical value 8.0, popularity 7.5, influence 8.5)

[1205] Step 5:

[1206] Receiving and storing evaluation results

[1207] The server receives the evaluation results returned by the AI ​​analysis engine and stores them in a database.

[1208] Input: Evaluation results from the AI ​​analysis engine

[1209] Output: Evaluation result data stored in a database

[1210] Step 6:

[1211] Overlay Display

[1212] The smart glasses overlay the evaluation results received from the server onto the user's field of view, allowing the user to simultaneously view the artwork and its evaluation results.

[1213] Input: Evaluation result data sent from the server

[1214] Output: Evaluation results overlaid on the smart glasses display

[1215] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1216] The present invention provides a system that allows users to rate artworks and, by combining it with an emotion engine, customizes the evaluation and display of the artworks based on the user's emotional state. This system allows users to upload artworks, which are evaluated using an AI analysis engine, and further analyzes the user's emotions using the emotion engine, with the results reflected in the evaluation and display. The processing content and specific examples of the program for this system are shown below.

[1217] Basic processing flow

[1218] 1. User Registration and Login

[1219] A user accesses the system, registers a new account by entering an email address, password, and username, and then logs in to the account.

[1220] The server receives the registration information, stores it in a database, receives the login information, and if authentication is successful, returns an authentication token to the user.

[1221] 2. Upload your work

[1222] The user selects a work of art such as a painting, poem, novel, or photograph and enters metadata such as the title, artist name, and year of creation.

[1223] The device sends the uploaded file and metadata to the server.

[1224] The server stores the received files and metadata and prepares them for analysis.

[1225] 3. User sentiment analysis

[1226] When a user inputs their work or checks the evaluation results, the emotion engine analyzes the user's emotional state from their facial expressions and voice input.

[1227] The emotion engine (in the server) analyzes the user's emotions and adds the results to the metadata or reflects them in the display of the analysis results.

[1228] 4. AI-based analysis

[1229] The server (AI analysis engine) evaluates the work's aesthetic value, historical value, popularity, influence, etc.

[1230] The AI ​​analysis engine (on the server) generates the analysis results and generates scores for aesthetic value, historical value, popularity, and influence.

[1231] The emotion engine (within the server) uses the emotion analysis results to make corrections and add supplementary information to the AI ​​analysis results.

[1232] 5. Displaying the analysis results

[1233] The user checks the analysis results from their account.

[1234] The server displays the analysis results to the user, which may be customized according to the user's emotional state.

[1235] 6. Buying and Selling Works

[1236] The user (seller) sets the selling price of the work based on the analysis results and lists it for sale.

[1237] The server adds the work to the sales list at the set price.

[1238] The user (buyer) selects the work of interest from the sales list and completes the purchase procedure.

[1239] The server verifies the purchase payment and transmits the digital copy of the work to the buyer.

[1240] Specific examples

[1241] Example 1: Painting rating and sentiment analysis

[1242] 1. A user accesses the system because they want their drawing to be evaluated.

[1243] 2. The device uploads the painting file "autumn_landscape.jpg" and enters the metadata (title "Autumn Landscape", artist "Ichiro Tanaka", year of production "2023").

[1244] 3. The server stores the received files and data and passes them to the AI ​​analysis engine.

[1245] 4. When the user enters their work or checks the evaluation results, the emotion engine analyzes their emotional state from their facial expressions.

[1246] 5. An AI analysis engine analyzes the artwork and evaluates its aesthetic value, historical value, popularity, and influence.

[1247] 6. Based on the analysis results, the emotion engine customizes the display format and focus points to suit the user's preferences.

[1248] 7. The server stores the analysis results (e.g., aesthetic value rating 8.5 / 10, historical value rating 7 / 10, popularity rating 6 / 10, influence rating 7.5 / 10) and displays them to the user.

[1249] 8. The user checks the evaluation results and lists the work for sale for 10,000 yen.

[1250] Example 2: Poetry rating and sentiment analysis

[1251] 1. A user accesses the system because they want to know the value of a poem they have written.

[1252] 2. The device uploads the poem file "winter_scene.txt" and enters the metadata (title "Winter Scene," author "Jiro Sato," and year of creation "2022").

[1253] 3. The server stores the received files and data and passes them to the AI ​​analysis engine.

[1254] 4. When the user inputs their work or checks the evaluation results, the emotion engine analyzes their emotional state from their voice input.

[1255] 5. An AI analysis engine analyzes the poem and evaluates its aesthetic value, historical value, popularity, and influence.

[1256] 6. The emotion engine uses the analysis results to customize the display to attract the user's interest.

[1257] 7. The server stores the analysis results (e.g., aesthetic value rating 7.5 / 10, historical value rating 6 / 10, popularity rating 7 / 10, influence rating 8 / 10) and displays them to the user.

[1258] 8. The user checks the rating and lists the poem for sale for 5,000 yen.

[1259] In this way, the system of the present invention provides users with a means to objectively and fairly evaluate their own artworks, enabling them to buy and sell artworks at fair prices based on those evaluations. Furthermore, by using an emotion engine to analyze the user's emotional state and reflecting the results in evaluations and displays, the system can provide a more personalized experience.

[1260] The processing flow will be explained below.

[1261] Step 1:

[1262] A user accesses the system and registers a new account by entering an email address, password, and username.

[1263] Step 2:

[1264] The device sends the entered registration information to the server in JSON format.

[1265] Step 3:

[1266] The server stores the received registration information in a database and sends a confirmation email to the user.

[1267] Step 4:

[1268] The user confirms their email address by clicking the link in the confirmation email they receive.

[1269] Step 5:

[1270] The server verifies the email address and records the user registration in the database.

[1271] Step 6:

[1272] The user logs in by entering their email address and password.

[1273] Step 7:

[1274] The terminal sends the entered login information to the server in JSON format.

[1275] Step 8:

[1276] The server verifies the entered login information and, if authentication is successful, generates an authentication token and returns it to the user.

[1277] Step 9:

[1278] The user logs back into the system and opens the account screen.

[1279] Step 10:

[1280] The user selects a work of art such as a painting, poem, novel, or photograph and enters metadata such as the title, artist name, and year of creation.

[1281] Step 11:

[1282] The terminal transmits the selected file and the entered metadata to the server.

[1283] Step 12:

[1284] The server temporarily stores the received file and metadata, and stores the work file in file storage.

[1285] Step 13:

[1286] When a user inputs their work, the emotion engine analyzes their emotional state from their facial expressions and voice input.

[1287] Step 14:

[1288] The emotion engine (in the server) analyzes the emotional state and adds the results to the metadata or reflects them in the display of the analysis results.

[1289] Step 15:

[1290] The server prepares to pass the stored artwork data and metadata to the AI ​​analysis engine.

[1291] Step 16:

[1292] The server (AI analysis engine) performs analysis to evaluate the work's aesthetic value, historical value, popularity, influence, etc.

[1293] Step 17:

[1294] The AI ​​analysis engine (on the server) generates the analysis results and generates scores for aesthetic value, historical value, popularity, and influence.

[1295] Step 18:

[1296] The server receives the analysis results and stores them in a database.

[1297] Step 19:

[1298] The server displays the analysis results to the user, which may be customized according to the user's emotional state.

[1299] Step 20:

[1300] The user checks the analysis results.

[1301] Step 21:

[1302] The user (seller) sets the selling price of the work based on the analysis results and lists it for sale.

[1303] Step 22:

[1304] The server adds the work to the sales list at the set price.

[1305] Step 23:

[1306] The user (buyer) selects the work of interest from the sales list and completes the purchase procedure.

[1307] Step 24:

[1308] The server verifies the purchase payment and transmits the digital copy of the work to the buyer.

[1309] Example 2

[1310] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1311] Conventional art evaluation systems evaluate artworks without considering the user's emotional state, resulting in uniform evaluation results. Furthermore, when users sell artworks, it is difficult to set an appropriate price, and there is a lack of systems that provide an appropriate sales process. Furthermore, there is a problem that the method of presenting analysis results to users is not personalized, beyond simply evaluating artworks.

[1312] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1313] In this invention, the server includes means for a user to input digital content and metadata, means for the server to receive the input digital content and metadata and store them in a database, means for the server to transmit the stored digital content and metadata to an AI analysis engine and generate analysis results, means for the emotion engine to analyze the user's emotional state and correct the analysis results, and means for displaying the analysis results to the user. This makes it possible to present individualized evaluation results that take the user's emotional state into consideration, and by providing appropriate pricing and sales processes, a system that is highly convenient for users is realized.

[1314] "Digital Content" refers to artistic works stored or displayed in digital form, such as paintings, poems, novels, and photographs.

[1315] "Metadata" is additional information related to digital content, including attribute information such as title, author name, and production year.

[1316] "AI analysis engine" refers to an artificial intelligence-based system that analyzes digital content and generates evaluation scores based on aesthetic value, historical value, popularity, influence, etc.

[1317] An "emotion engine" is a system that analyzes a user's facial expressions and voice input to identify their emotional state and reflects the results in the evaluation of digital content.

[1318] "Server" refers to a central computer system for storing, processing, and analyzing digital content and metadata submitted by users.

[1319] "User" means any individual or legal entity that uses the System to upload, review, or sell digital content.

[1320] "Database" refers to a system built on a server that can efficiently store and search input digital content and metadata.

[1321] "Analysis results" refers to the final evaluation information that combines the evaluation score generated by the AI ​​analysis engine and the correction information provided by the emotion engine.

[1322] "Sales Listing" means a listing for publishing and selling Digital Content at a price set by a User.

[1323] An "authentication token" refers to a unique identification code that is issued when a user logs in to a system and is used as authentication information.

[1324] This invention is a system that allows users to rate digital content and customizes the ratings and display of works based on the user's emotional state by combining it with an emotion engine. This system allows users to upload digital content, has an AI analysis engine to rate it, and further uses the emotion engine to analyze the user's emotions, and has the function of reflecting the results in the ratings and display.

[1325] The hardware used includes the user's device (PC, smartphone, tablet, etc.), a server for storing and analyzing data, a camera and microphone for analyzing the user's emotional state, etc. The software used includes a web application for uploading digital content, a database management system, an AI analysis engine, an emotion analysis engine, etc.

[1326] Basic processing flow

[1327] This system mainly has the following functions:

[1328] 1. User Registration and Login:

[1329] A user accesses the system and registers a new account by entering an email address, password, and username. The terminal sends the entered information to the server, which stores it in a database. The user then enters login information, which the terminal sends to the server, which verifies it against the database and returns an authentication token to the user.

[1330] 2. Upload your work:

[1331] The user selects digital content (paintings, poems, novels, photographs, etc.) and enters metadata (title, author, year of creation, etc.). The device sends the selected file and metadata to the server, which receives it and stores it in a database.

[1332] 3. User sentiment analysis:

[1333] While the user is entering digital content or checking the evaluation results, the emotion engine analyzes the user's facial expressions and voice via the camera and microphone. The server analyzes the user's emotional state and adds the results to the metadata or reflects them in the analysis results.

[1334] 4. AI analysis:

[1335] The server sends the digital content and metadata to an AI analysis engine, which evaluates the work's aesthetic value, historical value, popularity, influence, etc. The AI ​​analysis engine generates these scores, and the emotion engine modifies and supplements them, taking into account the user's emotional state. The final analysis results are stored on the server.

[1336] 5. Displaying the analysis results:

[1337] Users can check the analysis results from their account, and the server retrieves the saved analysis results and displays them on the device. The display content is customized according to the user's emotional state.

[1338] 6. Buying and Selling Works:

[1339] The user (seller) sets a selling price based on the analysis results and posts it on the sales list. The server receives this and adds it to the sales list. The user (buyer) selects the work they are interested in from the list and completes the purchase procedure. The server confirms the purchase payment and sends the digital content to the buyer.

[1340] Specific examples

[1341] Example 1: Painting rating and sentiment analysis

[1342] A user accesses the system wanting to have a painting they have drawn evaluated. The terminal uploads the painting file "example_painting.jpg" and inputs metadata (title "Landscape", artist "Yamada Taro", year of production "2023"). The server receives this, saves it, and passes it to the AI ​​analysis engine. When the user enters the work or checks the evaluation results, the emotion engine analyzes the user's emotional state from their facial expressions. The AI ​​analysis engine evaluates the work, and the emotion engine customizes the display. The server saves the analysis results and displays them to the user. The user checks the evaluation results and places the work on the sales list.

[1343] Example 2: Poetry rating and sentiment analysis

[1344] A user accesses the system wanting to know the value of a poem they have written. The device uploads the poem file "example_poem.txt" and inputs metadata (title "Seasonal Poem", author "Sato Hanako", year of creation "2022"). The server receives this, saves it, and passes it to the AI ​​analysis engine. When the user enters a poem or checks the evaluation results, the emotion engine analyzes the user's emotional state from their voice input. The AI ​​analysis engine evaluates the poem, and the emotion engine customizes the display. The server saves the analysis results and displays them to the user. The user checks the evaluation results and places the poem on the sales list.

[1345] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1346] Step 1:

[1347] User Registration and Login

[1348] User Registration

[1349] A user accesses the system and registers a new account by entering an email address, password, and username.

[1350] Input: Email address, password, username

[1351] The terminal sends the entered information to the server.

[1352] The server stores the received information in a database and generates a registration completion message.

[1353] Output: Registration complete message

[1354] Log in

[1355] The user goes to the login screen, enters their email address and password, and clicks the login button.

[1356] Input: Email address, password

[1357] The terminal sends the entered login information to the server.

[1358] The server checks the information against its database and generates an authentication token if authentication is successful, or a login error message if it fails.

[1359] Output: Authentication token or login error message

[1360] Step 2:

[1361] Upload your work

[1362] Work selection

[1363] The user selects digital content and enters metadata such as title, artist name, and year of production.

[1364] Input: Digital content file (e.g. painting, poem, novel, photograph), title, artist name, year of creation

[1365] The device sends the selected files and metadata to the server.

[1366] The server stores the received files and metadata in a database.

[1367] Output: Save success message or error message

[1368] Step 3:

[1369] User sentiment analysis

[1370] Emotional Data Collection

[1371] Users are given permission to use the camera and microphone to collect emotional data while they are entering digital content or reviewing evaluation results.

[1372] Input: Facial expression data, voice data

[1373] The device sends facial expression and voice data to the server.

[1374] Emotion analysis

[1375] The server's emotion engine analyzes the received facial expressions and voice data to determine the user's emotional state.

[1376] Data processing: facial expression analysis, voice analysis

[1377] The server generates the analysis results and adds them to the metadata or uses them to correct the analysis results.

[1378] Output: Analysis results

[1379] Step 4:

[1380] AI-based analysis

[1381] Data analysis preparation

[1382] The server sends the stored digital content and metadata to the AI ​​analysis engine.

[1383] Input: Digital content files, metadata

[1384] AI analysis

[1385] The server's AI analysis engine analyzes digital content and evaluates its aesthetic value, historical value, popularity, influence, etc.

[1386] Data operations: aesthetic value evaluation, historical value evaluation, popularity evaluation, influence evaluation

[1387] The emotion engine corrects and supplements the AI ​​analysis results based on the user's emotional state.

[1388] Output: Final analysis results

[1389] Save analysis results

[1390] The server stores the final analysis results in a database.

[1391] Output: Message that final analysis results have been saved

[1392] Step 5:

[1393] Displaying analysis results

[1394] Result acquisition and display

[1395] Users log in to their account and select the digital content for which they want to check the analysis results.

[1396] Input: User ID, Digital Content ID

[1397] The server retrieves the analysis results of the relevant digital content from the database.

[1398] The terminal displays the obtained analysis results to the user.

[1399] Output: Analysis result display

[1400] Step 6:

[1401] Buying and selling artwork

[1402] Sales Settings

[1403] The user (seller) sets a selling price based on the analysis results and lists the item for sale.

[1404] Input: Digital content ID, sales price

[1405] The server adds the set price and digital content information to the sales list.

[1406] Output: Sales list update completion message

[1407] Purchase procedure

[1408] The user (buyer) selects the digital content they wish to purchase from the sales list and completes the purchase procedure.

[1409] Input: Digital content ID to purchase, payment information

[1410] The server verifies the purchase payment and sends the digital content data to the buyer.

[1411] Output: Purchase confirmation message and digital content delivery completion message

[1412] (Application example 2)

[1413] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1414] It is necessary to analyze the emotional state of passengers in self-driving vehicles in real time and display artwork or play music that is appropriate for that state to improve passenger comfort and satisfaction. However, conventional self-driving vehicles do not have such functionality, and there is a problem in that they cannot provide services that correspond to the emotional state of passengers.

[1415] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1416] In this invention, the server includes: a means for a user to input artworks and metadata; a means for the server to receive the input artworks and metadata and store them in a database; a means for the server to transmit the stored artworks and metadata to an AI analysis engine and generate analysis results; a means for the server to display the analysis results to the user; a means for an emotion analysis engine in the autonomous vehicle to analyze the emotional state of passengers using a camera and a microphone; and a means for controlling the display and sound system in the vehicle to display artworks or play music based on the emotional state of the passengers, thereby enabling the provision of optimal services according to the emotional state of passengers.

[1417] "Works of art" is a general term for works including visual arts such as paintings, poems, novels, and photographs, as well as written art.

[1418] "Metadata" refers to additional information associated with a work of art, such as the title, artist, and year of creation.

[1419] A "server" is a computer system that receives, stores, and analyzes data entered by a user.

[1420] An "AI analysis engine" refers to an artificial intelligence model for evaluating works of art, and has the ability to analyze aesthetic value, historical value, popularity, influence, etc.

[1421] The "emotion analysis engine" is a system that uses cameras and microphones to analyze passengers' emotional states from their facial expressions and voices.

[1422] A "display" is a screen installed inside the vehicle, and is a device for visually displaying analysis results and artwork.

[1423] "Sound system" refers to audio equipment such as speakers for playing music or voice in a vehicle.

[1424] "User" refers to the person who inputs artwork into the system and reviews the analysis results.

[1425] "Passenger" refers to a person riding in an autonomous vehicle and is the subject of emotion analysis.

[1426] The system of this invention analyzes passenger emotions and displays and plays artworks in autonomous vehicles. The user inputs artworks and metadata, and the server receives, stores, and analyzes them, then displays the results to the user. An emotion analysis engine is also installed in the autonomous vehicle, and it uses cameras and microphones to analyze the passengers' emotional state in real time.

[1427] The hardware used includes:

[1428] High-resolution camera: Captures passengers' facial expressions.

[1429] Microphone: Collects passenger voices.

[1430] Display: An in-car monitor for displaying analytical results or artwork.

[1431] Sound system: Speakers and other devices that play music and audio inside the vehicle.

[1432] The software used includes:

[1433] OpenCV: A library for face detection.

[1434] TensorFlow: An artificial intelligence model for sentiment analysis.

[1435] Front-end application: A web or mobile app that provides the user interface.

[1436] Back-end server: A server system that manages databases and performs AI analysis.

[1437] The specific process is as follows: users first access the system and input artworks and their metadata. The device then sends this data to the server, which receives and stores it. The server then sends the stored data to the AI ​​analysis engine, which generates analysis results. Users can then view the analysis results in their account.

[1438] Furthermore, an emotion analysis engine inside the autonomous vehicle will analyze passengers' facial expressions and voices in real time to detect their emotional state, and based on this emotional state, it will display appropriate artwork on the display and play appropriate music or poetry through the sound system, thereby providing a comfortable in-car environment optimized for passengers' emotions.

[1439] Specific examples

[1440] Example 1: Stress reduction

[1441] If a passenger is feeling stressed, the emotion analysis engine will detect the emotion of "anger." Based on the results of emotion analysis performed on camera footage and audio data, relaxing nature scenes will be displayed on the in-car display and relaxing music will be played over the sound system.

[1442] Example 2: Promoting relaxation

[1443] If the passenger is relaxed, the emotion analysis engine detects the emotion of "happiness." Depending on the passenger's emotional state, bright landscape images will be displayed on the in-car display and upbeat music will be played over the sound system.

[1444] Specifically, the system operates by inputting the following prompt sentence into the generative AI model:

[1445] "Write a program that uses real-time camera footage to analyze a person's emotions. Based on that analysis, add functionality to show appropriate images on the display and play appropriate music on the sound system."

[1446] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1447] Step 1:

[1448] The user inputs the artwork and metadata.

[1449] A user accesses the system and inputs files of artworks such as paintings, poems, novels, and photographs, along with metadata such as the title, artist name, and year of production. The input data is sent from the terminal to the server.

[1450] Step 2:

[1451] A server receives the input artwork and metadata and stores them in a database.

[1452] The server receives the artwork files and metadata sent from the device and stores them in a database, which is then used for subsequent AI analysis.

[1453] Step 3:

[1454] The server sends the stored artworks and metadata to an AI analysis engine to generate analysis results.

[1455] The server sends the artworks and metadata stored in the database to an AI analysis engine, which uses generative AI models to evaluate them based on aesthetic value, historical value, popularity, influence, etc. A numerical score is generated as a result of the evaluation.

[1456] Step 4:

[1457] The server displays the analysis results to the user.

[1458] The server sends the generated analysis results to the user's device and displays them through the user's account. The user can check the evaluation results and decide on appropriate actions (e.g., buying or selling the work).

[1459] Step 5:

[1460] An emotion analysis engine within the autonomous vehicle uses cameras and microphones to analyze the emotional state of passengers.

[1461] Cameras and microphones collect facial expressions and voice recordings of passengers in the car in real time and send them to an emotion analysis engine, which uses a TensorFlow model to analyze this data and determine the passenger's emotional state.

[1462] Step 6:

[1463] Controlling the in-car display and sound systems based on the passenger's emotional state to display artwork or play music.

[1464] Based on the output of the emotion analysis engine, the server selects an appropriate artwork or music file, and the display shows images or videos that match the emotional state, while the sound system plays relaxing or upbeat music.

[1465] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1466] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1467] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1468] [Fourth embodiment]

[1469] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1470] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1471] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1472] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1473] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1474] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1475] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1476] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1477] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1478] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1479] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1480] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1481] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1482] This invention provides a system for fairly and transparently evaluating the value of artworks. This system allows users to upload their own artworks, and an AI analysis engine is used to evaluate the artworks in detail based on their aesthetic value, historical value, popularity, influence, etc. Below, we will show the processing details and specific examples of the program for this system.

[1483] Basic processing flow

[1484] 1. User Registration and Login

[1485] User: Access the system and register a new account by entering an email address, password, and username, then log in to the account.

[1486] Server: Receives registration information and stores it in a database. Receives login information and returns an authentication token to the user if authentication is successful.

[1487] 2. Upload your work

[1488] User: Select a work of art such as a painting, poem, novel, or photograph and enter metadata such as title, artist, and year of creation.

[1489] On the device: Sends the uploaded file and metadata to the server.

[1490] Server: Stores received files and metadata and prepares them for analysis.

[1491] 3. AI-based analysis

[1492] Server (AI analysis engine): The saved artwork data is sent to the analysis engine, which evaluates it based on specified criteria, including aesthetic value, historical value, popularity, and influence.

[1493] Server: Receives the analysis results and stores them in a database.

[1494] 4. Displaying the analysis results

[1495] Users: Log in to their account and check the analysis results. View detailed analysis results from the work list.

[1496] Server: Visually presents the analysis results to the user.

[1497] 5. Buying and Selling Artworks

[1498] User (seller): Sets the selling price based on the analysis results and sends it to the server.

[1499] Server: Adds the work to the sales list at a set price.

[1500] User (Buyer): Selects the work of interest from the sales list and completes the purchase process.

[1501] Server: Validates purchase payments and sends digital copies of the work to the buyer.

[1502] Specific examples

[1503] Example 1: Evaluation of a painting

[1504] 1. User: The user accesses the system with the desire to have the drawing he or she has drawn evaluated.

[1505] 2. Device: Upload the painting file "autumn_landscape.jpg" and enter the metadata (title "Autumn Landscape", artist "Ichiro Tanaka", year of creation "2023").

[1506] 3. Server: Stores received files and data and passes them to the AI ​​analysis engine.

[1507] 4. AI analysis engine: Analyzes artworks and evaluates their aesthetic value, historical value, popularity, and influence.

[1508] 5. Server: Stores the analysis results (e.g. aesthetic value rating 8.5 / 10, historical value rating 7 / 10, popularity rating 6 / 10, influence rating 7.5 / 10) and displays them to the user.

[1509] 6. User: Check the evaluation results and list the work for sale for 10,000 yen.

[1510] Example 2: Poetry rating

[1511] 1. User: The user accesses the system because they want to know the value of the poem they have written.

[1512] 2. Device: Upload the poem file "winter_scene.txt" and enter the metadata (title "Winter Scene," author "Jiro Sato," and year of creation "2022").

[1513] 3. Server: Stores received files and data and passes them to the AI ​​analysis engine.

[1514] 4. AI analysis engine: Analyzes poems and evaluates their aesthetic value, historical value, popularity, and influence.

[1515] 5. Server: Stores the analysis results (e.g. aesthetic value rating 7.5 / 10, historical value rating 6 / 10, popularity rating 7 / 10, influence rating 8 / 10) and displays them to the user.

[1516] 6. User: Checks the evaluation results and lists the poem for sale for 5,000 yen.

[1517] In this way, the system of the present invention provides users with a means to objectively and fairly evaluate their own artworks, enabling them to buy and sell their artworks at fair prices based on that evaluation, thereby enabling a more accurate understanding of the value of artworks and promoting fair transactions.

[1518] The processing flow will be explained below.

[1519] Step 1:

[1520] A user accesses the system and registers a new account by entering an email address, password, and username.

[1521] Step 2:

[1522] The device sends the entered registration information to the server in JSON format.

[1523] Step 3:

[1524] The server stores the received registration information in a database and sends a confirmation email to the user.

[1525] Step 4:

[1526] The user confirms their email address by clicking the link in the confirmation email they receive.

[1527] Step 5:

[1528] The server verifies the email address and records the user registration in the database.

[1529] Step 6:

[1530] The user logs in by entering their email address and password.

[1531] Step 7:

[1532] The terminal sends the entered login information to the server in JSON format.

[1533] Step 8:

[1534] The server verifies the entered login information and, if authentication is successful, generates an authentication token and returns it to the user.

[1535] Step 9:

[1536] The user logs back into the system and opens the account screen.

[1537] Step 10:

[1538] The user selects a work of art (e.g., an image file of a painting) and enters metadata such as the title, artist name, and year of creation.

[1539] Step 11:

[1540] The terminal transmits the selected file and the entered metadata to the server.

[1541] Step 12:

[1542] The server temporarily stores the received file and metadata, and stores the work file in file storage.

[1543] Step 13:

[1544] The server prepares to pass the stored artwork data and metadata to the AI ​​analysis engine.

[1545] Step 14:

[1546] The server (AI analysis engine) performs analysis to evaluate the work's aesthetic value, historical value, popularity, influence, etc.

[1547] Step 15:

[1548] The AI ​​analysis engine (on the server) generates the analysis results and generates scores for aesthetic value, historical value, popularity, and influence.

[1549] Step 16:

[1550] The server receives the analysis results and stores them in a database.

[1551] Step 17:

[1552] The user checks the analysis results from the account screen.

[1553] Step 18:

[1554] The server displays the analysis results to the user.

[1555] Step 19:

[1556] The user (seller) sets the selling price of the work based on the analysis results and lists it for sale.

[1557] Step 20:

[1558] The server adds the work to the sales list at the set price.

[1559] Step 20:

[1560] The user (buyer) selects the work of interest from the sales list and completes the purchase procedure.

[1561] Step 21:

[1562] The server verifies the purchase payment and transmits the digital copy of the work to the buyer.

[1563] Through these steps, the system will ensure fair and transparent evaluation of artworks and the sale and purchase of artworks at fair prices.

[1564] Example 1

[1565] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1566] The conventional art evaluation system relied on subjective evaluation and lacked fairness and transparency. It was also difficult to grasp the true value of a work of art, and the system was unreliable in transactions, making it difficult to promote fair transactions.

[1567] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1568] In this invention, the server includes means for a user to input artworks and metadata, means for a terminal to transmit the input artworks and metadata to the server, means for the server to receive the input artworks and metadata and store them in a database, means for the server to transmit the stored artworks and metadata to an AI analysis engine and generate analysis results, means for visually presenting the analysis results to the user, means for the user to set a selling price based on the analysis results and for the server to add the artwork to a sales list at that price, means for the user to purchase the artwork from the sales list, and means for the server to process the purchase procedure and transmit artwork data to the purchaser. This makes it possible to fairly and transparently evaluate the value of artworks and promote fair transactions.

[1569] "Users" are entities that use the system to upload artworks and evaluate and sell them.

[1570] A "terminal" is a device used by a user, such as a computer or smartphone, that includes a means for transmitting input artworks and metadata to a server.

[1571] A "server" is the computer that serves as the core of the system, receiving input information, storing it in a database, and analyzing it using an AI analysis engine.

[1572] "Work of art" refers to any work of creative expression, such as a painting, poem, novel, or photograph.

[1573] "Metadata" is additional information about a work of art, including the title, artist name, and year of creation.

[1574] The "database" is an information storage system for efficiently managing and storing received artworks, metadata, analysis results, etc.

[1575] The "AI Analysis Engine" is an artificial intelligence engine that analyzes works of art and evaluates their aesthetic value, historical value, popularity, and influence.

[1576] "Analysis results" are evaluation results provided by the AI ​​analysis engine, and include evaluation indicators such as aesthetic value, historical value, popularity, and influence.

[1577] "Visual presentation" refers to providing analysis results to users in an easy-to-read format such as graphs or charts.

[1578] "Sales List" means a list of artworks that can be viewed and purchased by other Users along with the selling price set by the User.

[1579] "Purchase procedure" refers to the process by which a user purchases an artwork selected from a sales list, including payment and the transfer of artwork data.

[1580] "Artwork Data" refers to the digital file of the Artwork sent to the Purchaser.

[1581] The present invention provides a system for fair and transparent evaluation of the value of artworks. This system allows users to upload their own artworks and uses an AI analysis engine to evaluate the artworks in detail based on their aesthetic value, historical value, popularity, influence, etc.

[1582] Specifically, the following hardware and software are used:

[1583] Hardware: Servers, devices (computers, smartphones, etc.)

[1584] Software: Databases (e.g., MySQL, PostgreSQL), cloud storage (e.g., Amazon S3, Google Cloud Storage), AI analytics engines (e.g., TensorFlow, PyTorch)

[1585] First, a user accesses the system using a terminal and registers a new account by entering their email address, password, and username. Then, they log in with their email address and password. The server receives the information entered by the user and stores it in a database. It also verifies the login information and securely authenticates the user.

[1586] Next, the user selects a file of an artwork (e.g., painting, poem, novel, photograph, etc.) from the device through the on-screen interface and enters metadata such as the title, artist name, and year of production. The device then sends this information to the server. The server saves the received file and metadata in storage and returns a notification to the user that saving is complete.

[1587] The server then sends the stored artwork data to an AI analysis engine, which evaluates the artwork based on specified criteria such as aesthetic value, historical value, popularity, and influence. During this process, the AI ​​analysis engine analyzes the input artwork from various perspectives and generates results based on each evaluation indicator. The server then stores the evaluation results received from the AI ​​analysis engine in a database.

[1588] After logging in to the system, users can check the evaluation results of their work. The server presents the analysis results to users in a visually easy-to-read format (e.g., graphs or charts), allowing users to concretely grasp the value of their work.

[1589] Furthermore, when a user wants to sell their artwork, they can set an appropriate selling price based on the evaluation results and send that information to the server. The server then adds the artwork to a sales list at the set price, making it available for other users to view. When a potential buyer (user) selects a piece of artwork and completes the purchase procedure, the server confirms the buyer's payment and sends the artwork data to the buyer.

[1590] Specific examples

[1591] 1. A user accesses the system because they want their drawing to be evaluated.

[1592] 2. The device uploads the painting file "autumn_landscape.jpg" and enters the metadata (title "Autumn Landscape", artist "Ichiro Tanaka", year of creation "2023").

[1593] 3. The server stores the received files and data and passes them to the AI ​​analysis engine.

[1594] 4. An AI analysis engine analyzes the artwork and evaluates its aesthetic value, historical value, popularity, and influence.

[1595] 5. The server stores the analysis results (e.g., aesthetic value rating 8.5 / 10, historical value rating 7 / 10, popularity rating 6 / 10, influence rating 7.5 / 10) and displays them to the user.

[1596] 6. The user checks the evaluation results and lists the work for sale for 10,000 yen.

[1597] Example prompt: "Evaluate this painting's aesthetic value, historical value, popularity, and influence."

[1598] In this way, the system of the present invention provides users with a means to objectively and fairly evaluate their own artworks, enabling them to buy and sell their artworks at fair prices based on that evaluation, thereby enabling a more accurate understanding of the value of artworks and promoting fair transactions.

[1599] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1600] Step 1: User Registration and Login

[1601] The user accesses the system's registration screen and creates a new account by entering an email address, password, and username. The user enters this information (input data: email address, password, username) and presses the "Register" button.

[1602] The server saves the received registration information in a database (output data: Save registration information to database), and then returns a message to the user indicating that registration was successful.

[1603] The user accesses the login screen and enters the registered email address and password. The user enters this information (input data: email address, password) and presses the "Login" button.

[1604] The server receives the login information and authenticates it against the database. If authentication is successful, it generates an authentication token (such as a JWT) and returns it to the user (output data: authentication token).

[1605] Step 2: Upload your work

[1606] After logging in, the user opens the artwork upload screen and selects the artwork file. They also enter metadata such as the title, artist name, and year of production. The user enters this information (input data: artwork file, title, artist name, year of production) and presses the "Upload" button.

[1607] The terminal transmits the selected file and metadata to the server (input data: file, metadata).

[1608] The server saves the received file in a storage system (e.g., Amazon S3) and saves the metadata in a database (output data: file saved in storage, metadata saved in database). After saving is complete, it returns a message to the user saying "upload successful."

[1609] Step 3: AI analysis

[1610] The server sends the saved artwork data to the AI ​​analysis engine (input data: artwork data).

[1611] The AI ​​analysis engine uses the submitted artwork data to evaluate its aesthetic value, historical value, popularity, and influence (data calculation: aesthetic value analysis, historical value analysis, popularity analysis, influence analysis). Evaluation criteria include various factors such as color, composition, and theme.

[1612] The server stores the evaluation results received from the AI ​​analysis engine in a database (output data: evaluation results stored in the database).

[1613] Step 4: Viewing the analysis results

[1614] The user logs in to their account and opens the analysis results screen. The user then sends a request to check the analysis results (input data: user ID, analysis result confirmation request).

[1615] The server receives a request from the user and retrieves the corresponding analysis results from the database (output data: analysis results). It then generates graphs and charts to visually present the retrieved analysis results to the user (data processing: graphing and charting the analysis results). These results are then displayed to the user.

[1616] Step 5: Buying and Selling Your Artwork

[1617] The user (seller) sets a selling price based on the evaluation results and sends that information to the server (input data: selling price, work information).

[1618] The server adds the work to the sales list at the set price, making it available for other users to view (output data: work information added to the sales list).

[1619] The user (buyer) selects the work they wish to purchase from the sales list, presses the "Purchase" button, and enters the information required to complete the purchase (input data: purchase request, payment information).

[1620] The server executes the purchase procedure, and after successful payment, sends the digital data of the work to the buyer (output data: digital data of the work sent to the buyer). It also sends a sale notification to the seller.

[1621] (Application example 1)

[1622] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1623] Conventional art evaluation systems use an AI analysis engine to evaluate artworks based on artworks and metadata entered by users, but lack a way to visually present the evaluation results in real time. This requires users to use a separate device to check the evaluation results, which is inconvenient. Furthermore, the lack of instant feedback of evaluation results makes them difficult to use in galleries, museums, and other settings. Therefore, the present invention aims to provide an evaluation system that solves these problems.

[1624] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1625] In this invention, the server includes means for a user to input artworks and metadata, means for the server to receive the input artworks and metadata and store them in a database, means for the server to transmit the stored artworks and metadata to an AI analysis engine and generate analysis results, means for displaying the analysis results to the user, and means for a display device to visually overlay the analysis results in front of the user's eyes, allowing the user to instantly visually confirm the evaluation results while appreciating the artworks.

[1626] "User" refers to a person who accesses the system and inputs or views artwork.

[1627] "Work of art" refers to any artistic or literary work, such as a painting, poem, novel, or photograph.

[1628] "Metadata" is additional information about a work of art, such as its title, artist name, and year of creation.

[1629] "Server" refers to a computer system that receives, stores, and processes information entered by users over a network.

[1630] "Database" refers to a digital storage device for the systematic preservation of artworks and metadata.

[1631] "AI analysis engine" refers to software that uses artificial intelligence technology to evaluate input artworks.

[1632] "Analysis results" refers to the evaluation results of the aesthetic value, historical value, popularity, influence, etc. of the artwork as assessed by the AI ​​analysis engine.

[1633] A "display device" is a device that allows a user to visually check the evaluation results, and includes smart glasses, AR glasses, etc.

[1634] "Visually overlaying" refers to the ability of a display device to superimpose on a visible object or content.

[1635] The present invention will be described in detail below with reference to an embodiment thereof. This system links a display device such as smart glasses with a server, and visually displays the evaluation results of artworks to a user in real time.

[1636] Hardware and software used

[1637] 1. Hardware:

[1638] Smart glasses: Examples include AR glasses such as Microsoft HoloLens and Google Glass.

[1639] Server: A computer system for processing and storing data over a network.

[1640] 2. Software:

[1641] Operating System (OS): The basic software that runs on the smart glasses and the server.

[1642] Python: A programming language used in the present invention for image processing and server communication.

[1643] OpenCV: A library for image capture and processing.

[1644] AI Analytics Engine: Deep learning models for assessing the aesthetic value, historical value, popularity, and influence of artworks.

[1645] Processing flow

[1646] 1. User views a work of art:

[1647] A user wears smart glasses and visits a gallery or museum, and the glasses' camera captures the artwork on display.

[1648] 2. Image capture:

[1649] The smart glasses' camera captures images of artwork within the user's field of view.

[1650] 3. Send to server:

[1651] The captured image is sent from the smart glasses to the server, which then receives the image and sends the data to the AI ​​analysis engine.

[1652] 4. AI analysis:

[1653] Based on the image data received, the AI ​​analysis engine evaluates the aesthetic value, historical value, popularity, and influence of the artwork.

[1654] 5. Receiving and storing evaluation results:

[1655] The server receives the evaluation results from the AI ​​analysis engine and stores them in a database, after which the evaluation results are sent to the smart glasses.

[1656] 6. Overlay display:

[1657] The smart glasses overlay the received evaluation results in the user's field of view, allowing the user to check the evaluation results in real time while viewing the artwork.

[1658] Specific examples

[1659] 1. Example of a painting evaluation:

[1660] A user puts on the smart glasses and looks at the painting "Spring Landscape" in a gallery. The glasses capture the painting and send it to the server. The server analyzes it using an AI analysis engine and sends the evaluation results (e.g., aesthetic value 9.0, historical value 8.0, popularity 7.5, influence 8.5) to the smart glasses. The user can visually confirm these evaluations.

[1661] 2. Poetry evaluation examples:

[1662] A user views the poem "Summer Memories" at an art museum. The smart glasses capture a digital representation of the poem and send it to a server. An AI analysis engine analyzes the poem and rates it on aesthetic value (8.0), historical value (6.5), popularity (7.0), and influence (9.0). These results are overlaid on the smart glasses, allowing the user to view the results in real time.

[1663] Prompt Sentence Examples

[1664] An example of a prompt used by this system is:

[1665] "This image is of a Spring Landscape from a famous art museum. Please rate the artwork's aesthetic value, historical value, popularity, and influence."

[1666] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1667] Step 1:

[1668] Users appreciate artwork

[1669] A user wears smart glasses and visits a gallery or museum, and the glasses' camera visually captures the artworks on display.

[1670] Input: Live video of artwork captured through the smart glasses camera

[1671] Output: Image data of the captured artwork

[1672] Step 2:

[1673] Image capture

[1674] As the user views the artwork, the camera in the smart glasses captures an image of the artwork.

[1675] Input: Live video from the smart glasses camera

[1676] Output: Still image data of artwork captured within the smart glasses

[1677] Step 3:

[1678] Send to server

[1679] The smart glasses capture images of paintings and poems and send them to a server, along with the metadata.

[1680] Input: Image data and metadata of the captured artwork (e.g., title, artist name, year of creation)

[1681] Output: Image data and metadata sent to the server

[1682] Step 4:

[1683] AI-based analysis

[1684] The server sends the received image data and metadata to an AI analysis engine for evaluation, which uses deep learning models to analyze aesthetic value, historical value, popularity, influence, and other factors.

[1685] Input: Image data and metadata sent to the server

[1686] Output: The evaluation results returned by the AI ​​analysis engine (e.g., aesthetic value 9.0, historical value 8.0, popularity 7.5, influence 8.5)

[1687] Step 5:

[1688] Receiving and storing evaluation results

[1689] The server receives the evaluation results returned by the AI ​​analysis engine and stores them in a database.

[1690] Input: Evaluation results from the AI ​​analysis engine

[1691] Output: Evaluation result data stored in a database

[1692] Step 6:

[1693] Overlay Display

[1694] The smart glasses overlay the evaluation results received from the server in the user's field of view, allowing the user to simultaneously view the artwork and its evaluation results.

[1695] Input: Evaluation result data sent from the server

[1696] Output: Evaluation results overlaid on the smart glasses display

[1697] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1698] The present invention provides a system that allows users to rate artworks and, by combining it with an emotion engine, customizes the evaluation and display of the artworks based on the user's emotional state. This system allows users to upload artworks, which are evaluated using an AI analysis engine, and further analyzes the user's emotions using the emotion engine, with the results reflected in the evaluation and display. The processing content and specific examples of the program for this system are shown below.

[1699] Basic processing flow

[1700] 1. User Registration and Login

[1701] A user accesses the system, registers a new account by entering an email address, password, and username, and then logs in to the account.

[1702] The server receives the registration information, stores it in a database, receives the login information, and if authentication is successful, returns an authentication token to the user.

[1703] 2. Upload your work

[1704] The user selects a work of art such as a painting, poem, novel, or photograph and enters metadata such as the title, artist name, and year of creation.

[1705] The device sends the uploaded file and metadata to the server.

[1706] The server stores the received files and metadata and prepares them for analysis.

[1707] 3. User sentiment analysis

[1708] When a user inputs their work or checks the evaluation results, the emotion engine analyzes the user's emotional state from their facial expressions and voice input.

[1709] The emotion engine (in the server) analyzes the user's emotions and adds the results to the metadata or reflects them in the display of the analysis results.

[1710] 4. AI-based analysis

[1711] The server (AI analysis engine) evaluates the work's aesthetic value, historical value, popularity, influence, etc.

[1712] The AI ​​analysis engine (on the server) generates the analysis results and generates scores for aesthetic value, historical value, popularity, and influence.

[1713] The emotion engine (within the server) uses the emotion analysis results to make corrections and add supplementary information to the AI ​​analysis results.

[1714] 5. Displaying the analysis results

[1715] The user checks the analysis results from their account.

[1716] The server displays the analysis results to the user, which may be customized according to the user's emotional state.

[1717] 6. Buying and Selling Works

[1718] The user (seller) sets the selling price of the work based on the analysis results and lists it for sale.

[1719] The server adds the work to the sales list at the set price.

[1720] The user (buyer) selects the work of interest from the sales list and completes the purchase procedure.

[1721] The server verifies the purchase payment and transmits the digital copy of the work to the buyer.

[1722] Specific examples

[1723] Example 1: Painting rating and sentiment analysis

[1724] 1. A user accesses the system because they want their drawing to be evaluated.

[1725] 2. The device uploads the painting file "autumn_landscape.jpg" and enters the metadata (title "Autumn Landscape", artist "Ichiro Tanaka", year of production "2023").

[1726] 3. The server stores the received files and data and passes them to the AI ​​analysis engine.

[1727] 4. When the user enters their work or checks the evaluation results, the emotion engine analyzes their emotional state from their facial expressions.

[1728] 5. An AI analysis engine analyzes the artwork and evaluates its aesthetic value, historical value, popularity, and influence.

[1729] 6. Based on the analysis results, the emotion engine customizes the display format and focus points to suit the user's preferences.

[1730] 7. The server stores the analysis results (e.g., aesthetic value rating 8.5 / 10, historical value rating 7 / 10, popularity rating 6 / 10, influence rating 7.5 / 10) and displays them to the user.

[1731] 8. The user checks the evaluation results and lists the work for sale for 10,000 yen.

[1732] Example 2: Poetry rating and sentiment analysis

[1733] 1. A user accesses the system because they want to know the value of a poem they have written.

[1734] 2. The device uploads the poem file "winter_scene.txt" and enters the metadata (title "Winter Scene," author "Jiro Sato," and year of creation "2022").

[1735] 3. The server stores the received files and data and passes them to the AI ​​analysis engine.

[1736] 4. When the user inputs their work or checks the evaluation results, the emotion engine analyzes their emotional state from their voice input.

[1737] 5. An AI analysis engine analyzes the poem and evaluates its aesthetic value, historical value, popularity, and influence.

[1738] 6. The emotion engine uses the analysis results to customize the display to attract the user's interest.

[1739] 7. The server stores the analysis results (e.g., aesthetic value rating 7.5 / 10, historical value rating 6 / 10, popularity rating 7 / 10, influence rating 8 / 10) and displays them to the user.

[1740] 8. The user checks the rating and lists the poem for sale for 5,000 yen.

[1741] In this way, the system of the present invention provides users with a means to objectively and fairly evaluate their own artworks, enabling them to buy and sell artworks at fair prices based on those evaluations. Furthermore, by using an emotion engine to analyze the user's emotional state and reflecting the results in evaluations and displays, the system can provide a more personalized experience.

[1742] The processing flow will be explained below.

[1743] Step 1:

[1744] A user accesses the system and registers a new account by entering an email address, password, and username.

[1745] Step 2:

[1746] The device sends the entered registration information to the server in JSON format.

[1747] Step 3:

[1748] The server stores the received registration information in a database and sends a confirmation email to the user.

[1749] Step 4:

[1750] The user confirms their email address by clicking the link in the confirmation email they receive.

[1751] Step 5:

[1752] The server verifies the email address and records the user registration in the database.

[1753] Step 6:

[1754] The user logs in by entering their email address and password.

[1755] Step 7:

[1756] The terminal sends the entered login information to the server in JSON format.

[1757] Step 8:

[1758] The server verifies the entered login information and, if authentication is successful, generates an authentication token and returns it to the user.

[1759] Step 9:

[1760] The user logs back into the system and opens the account screen.

[1761] Step 10:

[1762] The user selects a work of art such as a painting, poem, novel, or photograph and enters metadata such as the title, artist name, and year of creation.

[1763] Step 11:

[1764] The terminal transmits the selected file and the entered metadata to the server.

[1765] Step 12:

[1766] The server temporarily stores the received file and metadata, and stores the work file in file storage.

[1767] Step 13:

[1768] When a user inputs their work, the emotion engine analyzes their emotional state from their facial expressions and voice input.

[1769] Step 14:

[1770] The emotion engine (in the server) analyzes the emotional state and adds the results to the metadata or reflects them in the display of the analysis results.

[1771] Step 15:

[1772] The server prepares to pass the stored artwork data and metadata to the AI ​​analysis engine.

[1773] Step 16:

[1774] The server (AI analysis engine) performs analysis to evaluate the work's aesthetic value, historical value, popularity, influence, etc.

[1775] Step 17:

[1776] The AI ​​analysis engine (on the server) generates the analysis results and generates scores for aesthetic value, historical value, popularity, and influence.

[1777] Step 18:

[1778] The server receives the analysis results and stores them in a database.

[1779] Step 19:

[1780] The server displays the analysis results to the user, which may be customized according to the user's emotional state.

[1781] Step 20:

[1782] The user checks the analysis results.

[1783] Step 21:

[1784] The user (seller) sets the selling price of the work based on the analysis results and lists it for sale.

[1785] Step 22:

[1786] The server adds the work to the sales list at the set price.

[1787] Step 23:

[1788] The user (buyer) selects the work of interest from the sales list and completes the purchase procedure.

[1789] Step 24:

[1790] The server verifies the purchase payment and transmits the digital copy of the work to the buyer.

[1791] Example 2

[1792] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1793] Conventional art evaluation systems evaluate artworks without considering the user's emotional state, resulting in uniform evaluation results. Furthermore, when users sell artworks, it is difficult to set an appropriate price, and there is a lack of systems that provide an appropriate sales process. Furthermore, there is a problem that the method of presenting analysis results to users is not personalized, beyond simply evaluating artworks.

[1794] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1795] In this invention, the server includes means for a user to input digital content and metadata, means for the server to receive the input digital content and metadata and store them in a database, means for the server to transmit the stored digital content and metadata to an AI analysis engine and generate analysis results, means for the emotion engine to analyze the user's emotional state and correct the analysis results, and means for displaying the analysis results to the user. This makes it possible to present individualized evaluation results that take the user's emotional state into consideration, and by providing appropriate pricing and sales processes, a system that is highly convenient for users is realized.

[1796] "Digital Content" refers to artistic works stored or displayed in digital form, such as paintings, poems, novels, and photographs.

[1797] "Metadata" is additional information related to digital content, including attribute information such as title, author name, and production year.

[1798] "AI analysis engine" refers to an artificial intelligence-based system that analyzes digital content and generates evaluation scores based on aesthetic value, historical value, popularity, influence, etc.

[1799] An "emotion engine" is a system that analyzes a user's facial expressions and voice input to identify their emotional state and reflects the results in the evaluation of digital content.

[1800] "Server" refers to a central computer system for storing, processing, and analyzing digital content and metadata submitted by users.

[1801] "User" means any individual or legal entity that uses the System to upload, review, or sell digital content.

[1802] "Database" refers to a system built on a server that can efficiently store and search input digital content and metadata.

[1803] "Analysis results" refers to the final evaluation information that combines the evaluation score generated by the AI ​​analysis engine and the correction information provided by the emotion engine.

[1804] "Sales Listing" means a listing for publishing and selling Digital Content at a price set by a User.

[1805] An "authentication token" refers to a unique identification code that is issued when a user logs in to a system and is used as authentication information.

[1806] This invention is a system that allows users to rate digital content and customizes the ratings and display of works based on the user's emotional state by combining it with an emotion engine. This system allows users to upload digital content, has an AI analysis engine to rate it, and further uses the emotion engine to analyze the user's emotions, and has the function of reflecting the results in the ratings and display.

[1807] The hardware used includes the user's device (PC, smartphone, tablet, etc.), a server for storing and analyzing data, a camera and microphone for analyzing the user's emotional state, etc. The software used includes a web application for uploading digital content, a database management system, an AI analysis engine, an emotion analysis engine, etc.

[1808] Basic processing flow

[1809] This system mainly has the following functions:

[1810] 1. User Registration and Login:

[1811] A user accesses the system and registers a new account by entering an email address, password, and username. The terminal sends the entered information to the server, which stores it in a database. The user then enters login information, which the terminal sends to the server, which verifies it against the database and returns an authentication token to the user.

[1812] 2. Upload your work:

[1813] The user selects digital content (paintings, poems, novels, photographs, etc.) and enters metadata (title, author, year of creation, etc.). The device sends the selected file and metadata to the server, which receives it and stores it in a database.

[1814] 3. User sentiment analysis:

[1815] While the user is entering digital content or checking the evaluation results, the emotion engine analyzes the user's facial expressions and voice via the camera and microphone. The server analyzes the user's emotional state and adds the results to the metadata or reflects them in the analysis results.

[1816] 4. AI analysis:

[1817] The server sends the digital content and metadata to an AI analysis engine, which evaluates the work's aesthetic value, historical value, popularity, influence, etc. The AI ​​analysis engine generates these scores, and the emotion engine modifies and supplements them, taking into account the user's emotional state. The final analysis results are stored on the server.

[1818] 5. Displaying the analysis results:

[1819] Users can check the analysis results from their account, and the server retrieves the saved analysis results and displays them on the device. The display content is customized according to the user's emotional state.

[1820] 6. Buying and Selling Works:

[1821] The user (seller) sets a selling price based on the analysis results and posts it on the sales list. The server receives this and adds it to the sales list. The user (buyer) selects the work they are interested in from the list and completes the purchase procedure. The server confirms the purchase payment and sends the digital content to the buyer.

[1822] Specific examples

[1823] Example 1: Painting rating and sentiment analysis

[1824] A user accesses the system wanting to have a painting they have drawn evaluated. The terminal uploads the painting file "example_painting.jpg" and inputs metadata (title "Landscape", artist "Yamada Taro", year of production "2023"). The server receives this, saves it, and passes it to the AI ​​analysis engine. When the user enters the work or checks the evaluation results, the emotion engine analyzes the user's emotional state from their facial expressions. The AI ​​analysis engine evaluates the work, and the emotion engine customizes the display. The server saves the analysis results and displays them to the user. The user checks the evaluation results and places the work on the sales list.

[1825] Example 2: Poetry rating and sentiment analysis

[1826] A user accesses the system wanting to know the value of a poem they have written. The device uploads the poem file "example_poem.txt" and inputs metadata (title "Seasonal Poem", author "Sato Hanako", year of creation "2022"). The server receives this, saves it, and passes it to the AI ​​analysis engine. When the user enters a poem or checks the evaluation results, the emotion engine analyzes the user's emotional state from their voice input. The AI ​​analysis engine evaluates the poem, and the emotion engine customizes the display. The server saves the analysis results and displays them to the user. The user checks the evaluation results and places the poem on the sales list.

[1827] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1828] Step 1:

[1829] User Registration and Login

[1830] User Registration

[1831] A user accesses the system and registers a new account by entering an email address, password, and username.

[1832] Input: Email address, password, username

[1833] The terminal sends the entered information to the server.

[1834] The server stores the received information in a database and generates a registration completion message.

[1835] Output: Registration complete message

[1836] Log in

[1837] The user goes to the login screen, enters their email address and password, and clicks the login button.

[1838] Input: Email address, password

[1839] The terminal sends the entered login information to the server.

[1840] The server checks the information against its database and generates an authentication token if authentication is successful, or a login error message if it fails.

[1841] Output: Authentication token or login error message

[1842] Step 2:

[1843] Upload your work

[1844] Work selection

[1845] The user selects digital content and enters metadata such as title, artist name, and year of production.

[1846] Input: Digital content file (e.g. painting, poem, novel, photograph), title, artist name, year of creation

[1847] The device sends the selected files and metadata to the server.

[1848] The server stores the received files and metadata in a database.

[1849] Output: Save success message or error message

[1850] Step 3:

[1851] User sentiment analysis

[1852] Emotional Data Collection

[1853] Users are given permission to use the camera and microphone to collect emotional data while they are entering digital content or reviewing evaluation results.

[1854] Input: Facial expression data, voice data

[1855] The device sends facial expression and voice data to the server.

[1856] Emotion analysis

[1857] The server's emotion engine analyzes the received facial expressions and voice data to determine the user's emotional state.

[1858] Data processing: facial expression analysis, voice analysis

[1859] The server generates the analysis results and adds them to the metadata or uses them to correct the analysis results.

[1860] Output: Analysis results

[1861] Step 4:

[1862] AI-based analysis

[1863] Data analysis preparation

[1864] The server sends the stored digital content and metadata to the AI ​​analysis engine.

[1865] Input: Digital content files, metadata

[1866] AI analysis

[1867] The server's AI analysis engine analyzes digital content and evaluates its aesthetic value, historical value, popularity, influence, etc.

[1868] Data operations: aesthetic value evaluation, historical value evaluation, popularity evaluation, influence evaluation

[1869] The emotion engine corrects and supplements the AI ​​analysis results based on the user's emotional state.

[1870] Output: Final analysis results

[1871] Save analysis results

[1872] The server stores the final analysis results in a database.

[1873] Output: Message that final analysis results have been saved

[1874] Step 5:

[1875] Displaying analysis results

[1876] Result acquisition and display

[1877] Users log in to their account and select the digital content for which they want to check the analysis results.

[1878] Input: User ID, Digital Content ID

[1879] The server retrieves the analysis results of the relevant digital content from the database.

[1880] The terminal displays the obtained analysis results to the user.

[1881] Output: Analysis result display

[1882] Step 6:

[1883] Buying and selling artwork

[1884] Sales Settings

[1885] The user (seller) sets a selling price based on the analysis results and lists the item for sale.

[1886] Input: Digital content ID, sales price

[1887] The server adds the set price and digital content information to the sales list.

[1888] Output: Sales list update completion message

[1889] Purchase procedure

[1890] The user (buyer) selects the digital content they wish to purchase from the sales list and completes the purchase procedure.

[1891] Input: Digital content ID to purchase, payment information

[1892] The server verifies the purchase payment and sends the digital content data to the buyer.

[1893] Output: Purchase confirmation message and digital content delivery completion message

[1894] (Application example 2)

[1895] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1896] It is necessary to analyze the emotional state of passengers in self-driving vehicles in real time and display artwork or play music that is appropriate for that state to improve passenger comfort and satisfaction. However, conventional self-driving vehicles do not have such functionality, and there is a problem in that they cannot provide services that correspond to the emotional state of passengers.

[1897] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1898] In this invention, the server includes: a means for a user to input artworks and metadata; a means for the server to receive the input artworks and metadata and store them in a database; a means for the server to transmit the stored artworks and metadata to an AI analysis engine and generate analysis results; a means for the server to display the analysis results to the user; a means for an emotion analysis engine in the autonomous vehicle to analyze the emotional state of passengers using a camera and a microphone; and a means for controlling the display and sound system in the vehicle to display artworks or play music based on the emotional state of the passengers, thereby enabling the provision of optimal services according to the emotional state of passengers.

[1899] "Works of art" is a general term for works including visual arts such as paintings, poems, novels, and photographs, as well as written art.

[1900] "Metadata" refers to additional information associated with a work of art, such as the title, artist, and year of creation.

[1901] A "server" is a computer system that receives, stores, and analyzes data entered by a user.

[1902] An "AI analysis engine" refers to an artificial intelligence model for evaluating works of art, and has the ability to analyze aesthetic value, historical value, popularity, influence, etc.

[1903] The "emotion analysis engine" is a system that uses cameras and microphones to analyze passengers' emotional states from their facial expressions and voices.

[1904] A "display" is a screen installed inside the vehicle, and is a device for visually displaying analysis results and artwork.

[1905] "Sound system" refers to audio equipment such as speakers for playing music or voice in a vehicle.

[1906] "User" refers to the person who inputs artwork into the system and reviews the analysis results.

[1907] "Passenger" refers to a person riding in an autonomous vehicle and is the subject of emotion analysis.

[1908] The system of this invention analyzes passenger emotions and displays and plays artworks in autonomous vehicles. The user inputs artworks and metadata, and the server receives, stores, and analyzes them, then displays the results to the user. An emotion analysis engine is also installed in the autonomous vehicle, and it uses cameras and microphones to analyze the passengers' emotional state in real time.

[1909] The hardware used includes:

[1910] High-resolution camera: Captures passengers' facial expressions.

[1911] Microphone: Collects passenger voices.

[1912] Display: An in-car monitor for displaying analytical results or artwork.

[1913] Sound system: Speakers and other devices that play music and audio inside the vehicle.

[1914] The software used includes:

[1915] OpenCV: A library for face detection.

[1916] TensorFlow: An artificial intelligence model for sentiment analysis.

[1917] Front-end application: A web or mobile app that provides the user interface.

[1918] Back-end server: A server system that manages databases and performs AI analysis.

[1919] The specific process is as follows: users first access the system and input artworks and their metadata. The device then sends this data to the server, which receives and stores it. The server then sends the stored data to the AI ​​analysis engine, which generates analysis results. Users can then view the analysis results in their account.

[1920] Furthermore, an emotion analysis engine inside the autonomous vehicle will analyze passengers' facial expressions and voices in real time to detect their emotional state, and based on this emotional state, it will display appropriate artwork on the display and play appropriate music or poetry through the sound system, thereby providing a comfortable in-car environment optimized for passengers' emotions.

[1921] Specific examples

[1922] Example 1: Stress reduction

[1923] If a passenger is feeling stressed, the emotion analysis engine will detect the emotion of "anger." Based on the results of emotion analysis performed on camera footage and audio data, relaxing nature scenes will be displayed on the in-car display and relaxing music will be played over the sound system.

[1924] Example 2: Promoting relaxation

[1925] If the passenger is relaxed, the emotion analysis engine detects the emotion of "happiness." Depending on the passenger's emotional state, bright landscape images will be displayed on the in-car display and upbeat music will be played over the sound system.

[1926] Specifically, the system operates by inputting the following prompt sentence into the generative AI model:

[1927] "Write a program that uses real-time camera footage to analyze a person's emotions. Based on that analysis, add functionality to show appropriate images on the display and play appropriate music on the sound system."

[1928] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1929] Step 1:

[1930] The user inputs the artwork and metadata.

[1931] A user accesses the system and inputs files of artworks such as paintings, poems, novels, and photographs, along with metadata such as the title, artist name, and year of production. The input data is sent from the terminal to the server.

[1932] Step 2:

[1933] A server receives the input artwork and metadata and stores them in a database.

[1934] The server receives the artwork files and metadata sent from the device and stores them in a database, which is then used for subsequent AI analysis.

[1935] Step 3:

[1936] The server sends the stored artworks and metadata to an AI analysis engine to generate analysis results.

[1937] The server sends the artworks and metadata stored in the database to an AI analysis engine, which uses generative AI models to evaluate them based on aesthetic value, historical value, popularity, influence, etc. A numerical score is generated as a result of the evaluation.

[1938] Step 4:

[1939] The server displays the analysis results to the user.

[1940] The server sends the generated analysis results to the user's device and displays them through the user's account. The user can check the evaluation results and decide on appropriate actions (e.g., buying or selling the work).

[1941] Step 5:

[1942] An emotion analysis engine within the autonomous vehicle uses cameras and microphones to analyze the emotional state of passengers.

[1943] Cameras and microphones collect facial expressions and voice recordings of passengers in the car in real time and send them to an emotion analysis engine, which uses a TensorFlow model to analyze this data and determine the passenger's emotional state.

[1944] Step 6:

[1945] Controlling the in-car display and sound systems based on the passenger's emotional state to display artwork or play music.

[1946] Based on the output of the emotion analysis engine, the server selects an appropriate artwork or music file, and the display shows images or videos that match the emotional state, while the sound system plays relaxing or upbeat music.

[1947] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1948] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1949] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1950] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1951] FIG. 9 illustrates an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and behaviors arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1952] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1953] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1954] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1955] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1956] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1957] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1958] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1959] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1960] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[1961] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1962] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1963] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1964] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1965] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1966] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1967] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1968] The following is further disclosed regarding the above embodiment.

[1969] (Claim 1)

[1970] 1. A system for evaluating works of art, comprising:

[1971] a means for a user to input artwork and metadata;

[1972] a server means for receiving the input artworks and metadata and storing them in a database;

[1973] A server sends the stored artworks and metadata to an AI analysis engine to generate analysis results;

[1974] The system includes means for displaying the analysis results to the user.

[1975] (Claim 2)

[1976] 2. The system of claim 1, wherein the AI ​​analysis engine uses an analytical model to evaluate the aesthetic value, historical value, popularity, influence, etc. of a work of art.

[1977] (Claim 3)

[1978] The system of claim 1 further comprising means for the user to set a price for selling the artwork based on the analysis results, and for the server to add the artwork to a sales list at that price.

[1979] "Example 1"

[1980] (Claim 1)

[1981] a means for a user to input artwork and metadata;

[1982] means for the terminal to transmit the input artwork and metadata to a server;

[1983] a server means for receiving the input artworks and metadata and storing them in a database;

[1984] A server sends the stored artworks and metadata to an AI analysis engine to generate analysis results;

[1985] means for visually presenting the analysis results to the user;

[1986] A means for a user to set a selling price based on the analysis result, and for the server to add the item to the selling list at that price;

[1987] A means for a user to purchase a work from said sales list;

[1988] The system includes a server that processes the purchase procedure and transmits the work data to the purchaser.

[1989] (Claim 2)

[1990] 2. The system of claim 1, wherein the AI ​​analysis engine uses an analytical model to evaluate the aesthetic value, historical value, popularity, influence, etc. of a work of art.

[1991] (Claim 3)

[1992] 2. The system according to claim 1, further comprising means for storing the analysis results in a database and providing an interface for visually presenting the analysis results to a user.

[1993] "Application Example 1"

[1994] (Claim 1)

[1995] a means for a user to input artwork and metadata;

[1996] a server means for receiving the input artworks and metadata and storing them in a database;

[1997] A server sends the stored artworks and metadata to an AI analysis engine to generate analysis results;

[1998] means for displaying the analysis results to the user;

[1999] a display device for visually overlaying and displaying the analysis results in front of the user;

[2000] ...

[2001] A system including:

[2002] (Claim 2)

[2003] 2. The system of claim 1, wherein the AI ​​analysis engine uses an analytical model to evaluate the aesthetic value, historical value, popularity, influence, etc. of a work of art.

[2004] (Claim 3)

[2005] The system of claim 1 further comprising means for the user to set a price for selling the artwork based on the analysis results, and for the server to add the artwork to a sales list at that price.

[2006] "Example 2: Combining Emotion Engines"

[2007] (Claim 1)

[2008] a means for a user to input digital content and metadata;

[2009] a server receiving the input digital content and metadata and storing them in a database;

[2010] A means for the server to transmit the stored digital content and metadata to an AI analysis engine and generate an analysis result;

[2011] a means for the emotion engine to analyze the user's emotional state and correct the analysis result;

[2012] The system includes means for displaying the analysis results to the user.

[2013] (Claim 2)

[2014] 2. The system of claim 1, wherein the AI ​​analysis engine uses an analysis model to evaluate the aesthetic value, historical value, popularity, influence, etc. of digital content.

[2015] (Claim 3)

[2016] 2. The system according to claim 1, further comprising means for the user to set a price for selling the digital content based on the analysis result, and for the server to add the digital content to a sales list at that price.

[2017] "Application example 2 when combining emotion engines"

[2018] (Claim 1)

[2019] a means for a user to input artwork and metadata;

[2020] a server means for receiving the input artworks and metadata and storing them in a database;

[2021] A server sends the stored artworks and metadata to an AI analysis engine to generate analysis results;

[2022] means for displaying the analysis results to the user;

[2023] a means for an emotion analysis engine within the autonomous vehicle to analyze the emotional state of a passenger using a camera and a microphone;

[2024] The system includes means for controlling the display and sound systems in the vehicle based on the emotional state of the passengers to display artwork or play music.

[2025] (Claim 2)

[2026] 2. The system of claim 1, wherein the AI ​​analysis engine uses an analytical model to evaluate the aesthetic value, historical value, popularity, influence, etc. of a work of art.

[2027] (Claim 3)

[2028] The system of claim 1 further comprising means for the user to set a price for selling the artwork based on the analysis results, and for the server to add the artwork to a sales list at that price. [Explanation of symbols]

[2029] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. 1. A system for evaluating works of art, comprising: a means for a user to input artwork and metadata; a server means for receiving the input artworks and metadata and storing them in a database; A server sends the stored artworks and metadata to an AI analysis engine to generate analysis results; The system includes means for displaying the analysis results to the user.

2. The system of claim 1 , wherein the AI ​​analysis engine uses an analytical model to evaluate the aesthetic value, historical value, popularity, influence, etc. of a work of art.

3. 2. The system of claim 1, further comprising means for the user to set a price for selling the artwork based on the analysis results, and for the server to add the artwork to a sales list at that price.

Images