system

Abstract

Provide a system. 【Solution means】 Means for receiving image data input via a user interface; Means for evaluating a work of art based on the image data and performing scoring; Means for setting an appropriate theme based on the analysis and selecting a work according to the theme; Means for generating a layout of a virtual exhibition based on the selected work; Means for displaying digital content photographed and uploaded by a user in a virtual shop; Means for automatically generating promotion information and distributing it via an external network; Means for collecting and analyzing visitor data; A system including the above.

Description

Technical Field

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

Background Art

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

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] When publicly presenting artworks such as calligraphy online, there is a need for an environment that can quickly and automatically perform evaluation of works, selection by theme, holding of exhibitions, promotion, and analysis without the constraints of physical exhibitions and the high costs for operation. Also, this should provide opportunities for artists and enthusiasts to deliver their works to a wider range of audiences without limitations.

Means for Solving the Problems

[0005] This invention provides a system that automatically selects the most suitable artwork for a given theme and generates a virtual exhibition by evaluating and scoring image data of artworks received via a user interface. This system also includes means for generating an exhibition layout based on the selected artworks and for automatically distributing promotional materials. Furthermore, it can collect and analyze visitor data during the exhibition to help improve future exhibitions. In this way, it enables artists and enthusiasts to efficiently showcase their work to an international audience.

[0006] A "user interface" is an interface that allows a user to input data or retrieve information from a system.

[0007] "Image data" refers to data that represents visual information in a digital format.

[0008] "Evaluation" is the process of judging a work using numerical values ​​or indicators based on given criteria.

[0009] "Scoring" is the process of assigning specific numerical values ​​to works based on their evaluation.

[0010] A "theme" is a concept used to define the direction and concept of an exhibition.

[0011] "Selection" is the act of choosing the most suitable subject based on certain criteria.

[0012] A "virtual exhibition" is a digital exhibition held on the internet without a physical exhibition space.

[0013] "Layout" refers to the design and arrangement of the display positions and arrangements of artworks in an exhibition.

[0014] "Promotion" refers to advertising activities aimed at widely publicizing exhibitions or artworks.

[0015] "Visitor data" refers to statistical information and behavioral history data regarding visitors who accessed an exhibition.

Brief Explanation of Drawings

[0016] [Figure 1] It is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] It is a conceptual diagram showing an example of the main functions of a data processing device and a smart device according to the first embodiment. [Figure 3] It is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] It is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] It is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] It is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] It is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] It is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] It shows an emotion map to which multiple emotions are mapped. [Figure 10] It shows an emotion map to which multiple emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Example 2 when an emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when an emotion engine is combined.

Best Mode for Carrying Out the Invention

[0017] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0018] First, the terms used in the following description will be explained.

[0019] In the following embodiments, a labeled processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0020] In the following embodiments, a labeled RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0021] In the following embodiments, a labeled storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, and the like.

[0022] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0023] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0024] [First Embodiment]

[0025] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0026] As shown in Figure 1, the 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.

[0027] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0028] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0029] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and 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.

[0030] 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 perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0031] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0032] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0033] As shown in Figure 2, in the data processing device 12, a specific processing 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" related to the technology of this 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 according to the specific processing program 56 executed on the RAM 30.

[0034] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0035] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0036] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0037] The system in this invention begins with a process of uploading artistic works, such as calligraphy, online via a user's terminal. The terminal receives the artwork image through a user interface, performs pre-processing as needed, and then sends it to the server. Pre-processing here refers to adjusting the image size and correcting the image quality.

[0038] The server analyzes the received image data and uses a pre-trained AI model to evaluate and score the artwork. Evaluation criteria include aesthetic value, technical skill, and creativity, each of which may vary depending on industry standards and user customization. These evaluation results are stored in a database for further analysis.

[0039] Next, the server has a theme setting function, determining the exhibition theme based on accumulated evaluation data and external market trends. Based on this decision, the server selects the works that best fit the theme and designs the structure of the virtual exhibition.

[0040] The selected works are arranged in an optimized layout within the digital gallery, and each piece is accompanied by automatically generated descriptive text from the server. This allows viewers to deepen their understanding of the works and enhances the overall viewing experience.

[0041] Furthermore, the server generates information for promoting the exhibition and implements effective marketing through social media platforms and email. At this stage, the targeting of the promotion is also optimized by AI.

[0042] Once an exhibition is open, the server monitors visitor activity in real time and adjusts system resources as needed. Visitor data is collected and analyzed to improve future exhibitions. This entire process provides a platform for artists and enthusiasts to present their work to a wide audience and exchange feedback. For example, if a user uploads a calligraphy piece with a nature theme, the server analyzes it and selects it as part of a nature-related exhibition, potentially leading to the user's work being featured in an international virtual exhibition.

[0043] The following describes the processing flow.

[0044] Step 1:

[0045] The user takes their calligraphy artwork as an image to their device and prepares to upload it to the server using a dedicated application.

[0046] Step 2:

[0047] The device checks the image format and size, and if necessary, performs image optimization (e.g., resizing, adjusting resolution) before sending it to the server.

[0048] Step 3:

[0049] The server saves the received image data to a database and also inputs the image into an AI model to calculate an evaluation score for the artwork. This score is recorded in the database.

[0050] Step 4:

[0051] The server executes an algorithm that determines the theme for the exhibition based on past evaluation data and external data. This automatically sets the theme for the next exhibition.

[0052] Step 5:

[0053] The server selects the most relevant works based on the set theme, ranking them in order of highest rating, to form the exhibition collection.

[0054] Step 6:

[0055] The server generates a virtual exhibition layout based on the selected works and automatically creates a description for each work. This description includes background information and evaluation points for each work.

[0056] Step 7:

[0057] The server generates promotional information for the exhibition and begins distributing advertisements through platforms such as social media and email. At this time, it identifies the target audience for the promotion.

[0058] Step 8:

[0059] During the exhibition's public access period, the servers track visitor behavior in real time and adjust server resource allocation as needed to maintain smooth access.

[0060] Step 9:

[0061] The server collects and analyzes visitor behavior data after the exhibition ends. This includes data such as page views, time spent on the site, and identification of the most popular works.

[0062] Step 10:

[0063] The server generates insights from the analysis results that will help improve the next exhibition, and feeds them back into the system's operation.

[0064] (Example 1)

[0065] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0066] In evaluating and exhibiting cultural works on online platforms, the objectivity of evaluation criteria and the optimization of exhibitions are key challenges. Furthermore, appropriate promotion and analysis of visitor behavior are necessary to improve future exhibitions. These challenges can sometimes limit the user experience and the diversity of the works.

[0067] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0068] In this invention, the server includes means for receiving digital data via a user interface, means for evaluating and quantifying cultural works based on the digital data, and means for determining a theme based on the collected evaluation information and market trend information, and selecting works corresponding to that theme. This enables the selection of works based on objective evaluation criteria and diverse exhibitions.

[0069] A "user interface" is a means by which a user inputs and manipulates data and information.

[0070] "Digital data" refers to information in a format that is processed electronically and is primarily usable by computer systems.

[0071] A "cultural work" is an expression that possesses artistic or creative value, and includes a variety of forms such as visual arts and literature.

[0072] "Evaluation" is the process of analyzing and measuring the value and quality of an object based on specific criteria.

[0073] "Quantification" is a conversion process that expresses evaluation results as numerical values, making comparison and analysis easier.

[0074] "Collected evaluation information" refers to the collective term for evaluation results and related data collected according to various criteria.

[0075] "Market trend information" refers to data that shows current or future trends in a specific industry or field.

[0076] The "subject" is the central theme or topic of the exhibition or discussion.

[0077] "Means of selection" refers to the process of determining the appropriate option according to specific criteria or objectives.

[0078] This invention is a system that optimizes the evaluation and exhibition of cultural works via digital data, and consists of three main components: a terminal, a server, and a user. The user uploads cultural works as digital data using their terminal. The terminal performs data resizing and image quality correction using pre-specified format conversion and image processing software (e.g., image editing software).

[0079] The server uses this received digital data to evaluate the artwork using a generative AI model. The evaluation criteria include aesthetic value, technical skill, and creativity, each of which is recorded as numerical data. The evaluated data is stored in a database on the server and used for necessary analysis.

[0080] Furthermore, the server uses the collected evaluation information to perform comparative analysis with external market trend data and determine an appropriate exhibition theme. This process utilizes prompts such as: "Consider the latest trend information and suggest an exhibition theme that best suits the artwork."

[0081] The server automatically selects the most suitable cultural works based on the chosen theme and designs the structure of the virtual exhibition. Detailed explanatory information about the selected works is generated by a generative AI and provided to deepen the audience's understanding. The server also handles the promotion strategy, effectively distributing information using social media platforms and email networks. Here again, the prompt "Please propose an effective promotion strategy for a specific audience" is used.

[0082] Finally, the server monitors visitor activity in real time during the public exhibition. This allows for analysis of visitor interests and behavioral patterns, providing valuable insights to inform future exhibition planning. This entire process enables users to present their work to a broad audience and engage in discussions about it.

[0083] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0084] Step 1:

[0085] Users select and upload digital data of cultural works using their own devices. The input data is image files, which the device accepts. Specifically, the user performs file selection operations on the user interface. The device checks the image size and format, and if the format is inappropriate, it converts it to a standard format such as JPEG or PNG. As output, the image data converted to the appropriate format is sent to the server.

[0086] Step 2:

[0087] The server receives and stores image data sent from the terminal. The input data is mainly image files. Image processing software is used within the server to prepare the images for analysis. Specifically, the images are processed into a format that can be input into the AI ​​model. The output of this process is image data that has been formatted for processing by the AI ​​model.

[0088] Step 3:

[0089] The server passes image data to the AI ​​model and initiates the evaluation process. The input is pre-processed image data. The AI ​​model evaluates the aesthetic value, technical skill, and creativity of the image and quantifies them. The output of this data calculation is a numerical score for each evaluation criterion. The scores are recorded in a database and, if necessary, presented to the user as feedback.

[0090] Step 4:

[0091] The server determines the optimal exhibition theme using recorded evaluation scores and market trend information obtained from external sources. The input data consists of evaluation scores and market trend information. An AI model is used to perform analysis based on the prompt message, "Consider the latest trend information and suggest the most suitable exhibition theme for the artwork." The output is the selected exhibition theme, which is then used within the system for the next steps.

[0092] Step 5:

[0093] The server selects the most suitable cultural works for the exhibition based on the chosen theme and designs the layout of the virtual exhibition. The inputs are theme selection data and artwork evaluation scores. With the help of AI, it optimizes how to arrange the artworks on the screen. As output, data of the completed exhibition layout and explanatory information accompanying each artwork are generated and placed in the digital gallery.

[0094] Step 6:

[0095] The server plans the promotion of a virtual exhibition and generates information to appeal to a specific audience. The inputs are exhibition information and target audience data. The prompt "Propose an effective promotional strategy for a specific audience" is used to analyze the AI ​​model. The output is a specific promotional strategy and marketing message, which is distributed via social media and email.

[0096] Step 7:

[0097] The server monitors visitor behavior in real time during the exhibition. The input is visitor access data. The server analyzes behavioral data such as access patterns and dwell time, and dynamically adjusts system resources. This analysis generates a report on visitor behavior, which is used to improve future exhibitions.

[0098] (Application Example 1)

[0099] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0100] Contemporary artists and designers often lack effective channels for raising awareness of their work, and opportunities to participate in physical exhibitions are particularly limited. Furthermore, the evaluation and promotion of artworks are often manual processes, requiring considerable time and effort. Therefore, there is a need for a system that efficiently evaluates and promotes artworks online, and allows for broad public access through virtual exhibitions.

[0101] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0102] In this invention, the server includes means for receiving image data input via a user interface, means for evaluating and scoring works of art based on the image data, and means for displaying digital content photographed and uploaded by users in a virtual shop. This enables the efficient evaluation of works by artists and designers, their display in a themed virtual shop, and promotes widespread recognition.

[0103] A "user interface" is a visual or physical interface through which a user accesses a system and inputs or retrieves data.

[0104] "Image data" refers to visual information that has been captured or scanned and is represented in a digital format.

[0105] A "work of art" is an object created through creative activity that is visual or combines visual and other senses.

[0106] "Evaluation" is the act of measuring the value or performance of an object or process based on specific criteria.

[0107] "Scoring" is the process of expressing the evaluated results as a quantitative value.

[0108] A "theme" is a central concept or topic that unifies various elements within an exhibition or project.

[0109] A "virtual exhibition" is an event or platform that displays works of art online via the internet.

[0110] "Promotional information" refers to media content created to inform the public about a specific product or service and to convey its appeal.

[0111] An "external network" refers to external computer systems or data communication networks connected via the Internet.

[0112] "Visitor data" refers to information about the behavior and attributes of users who use the system.

[0113] "Real-time" refers to an environment where data or information can be processed and provided almost instantaneously.

[0114] In this embodiment of the invention, the system begins with the digitization and uploading of artwork by the user. The user uses a device such as a smartphone to photograph their artwork and upload the image data to the system. At this time, the device provides a user interface to allow the user to operate it easily. The device is also equipped with an image processing module that adjusts the image size and corrects the image quality, and pre-processing is performed using libraries such as OpenCV.

[0115] The server analyzes the received image data through an AI evaluation module. This uses a pre-trained generative AI model with machine learning frameworks such as TENSORFLOW®. This model evaluates and scores the aesthetic value, technical skill, and creativity of the artwork. Based on the evaluated information, the server performs analysis and displays the digital content photographed and uploaded by the user in a virtual shop with an appropriate theme.

[0116] Furthermore, the server generates promotional information and distributes it to external networks via social media and email. Targeting is optimized by AI, and the Python Twython library may be used for social media integration.

[0117] Visitor movements are monitored in real time, and visitor data is collected and analyzed. This allows the system to be used to improve future exhibitions and displays.

[0118] For example, if a user uploads a work with a nature theme, the server can analyze the work and display it in a virtual shop categorized as "Natural Beauty." An example prompt message: "Analyze the theme of the artwork and display it in the relevant virtual shop." This allows the user's work to reach a wider audience and provide opportunities for viewing and purchasing.

[0119] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0120] Step 1:

[0121] Users use their smartphones to photograph their artwork and upload the image data to the system via an application. The device receives the image data through the user interface and uses the OpenCV library to adjust the size and improve the image quality. The input is the captured image data, and the output is the processed image data.

[0122] Step 2:

[0123] The server receives processed image data sent from the terminal. It then sends the received image data to an AI evaluation module, where it is analyzed using a generative AI model with TensorFlow. This analysis quantifies the aesthetic value, technical skill, and creativity of the artwork, generating an evaluation score. Processed image data is used as input, and the evaluation score is obtained as output.

[0124] Step 3:

[0125] The server classifies the artwork into a suitable theme based on the generated evaluation score. Based on the analysis results, it displays the user-uploaded digital content in the relevant virtual shop category. The input is the evaluation score, and the output is classification information.

[0126] Step 4:

[0127] The server generates promotional information and distributes it via social media and email. AI optimizes targeting to enhance the effectiveness of promotional campaigns. Inputs include classification information and market trends, and the output is promotional materials.

[0128] Step 5:

[0129] The server monitors visitor behavior to the virtual shop in real time. It collects visitor data using Google Analytics and other tools, and analyzes it to determine improvements for future exhibitions. The input is visitor behavior data, and the output is an analysis report.

[0130] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0131] The system in this invention begins with a process of transmitting image data of a calligraphic work from a terminal to a server via a user interface. The terminal provides an interface for checking and optimizing the image quality and transferring it to the server. This process also includes a function to acquire the user's emotions as data.

[0132] The server stores the received image data and uses an AI model to evaluate and score the aesthetic value and technical achievement of the artwork. Furthermore, it can conduct a more multifaceted evaluation by taking into account user emotion data recognized by the emotion engine. For example, the program is designed to add points to the evaluation if the user has positive emotions towards the artwork.

[0133] Next, the server determines the exhibition theme based on the aforementioned evaluation results and sentiment data. This theme selection aligns with user interests and trends indicated by the sentiment data, resulting in an exhibition that is more relatable and engaging.

[0134] The selected works are incorporated into the virtual exhibition layout along with descriptive text based on sentiment analysis. The server takes into account user feedback analyzed by the sentiment engine and adjusts the descriptive text to include information that users are likely to emotionally respond to.

[0135] In promotional activities, the server uses emotional data obtained from an emotion engine to predict the audience's emotional response and appropriately adjust the content and timing of the promotion. For example, it might distribute information about an exhibition at a time when users have shown a very positive response in the past.

[0136] In this way, systems that utilize an emotion engine consider user emotions when evaluating and setting themes, providing a more fulfilling exhibition experience. For example, if a user expresses emotions such as "excitement" or "satisfaction" when uploading a work, the server will reflect those emotions in the theme setting and artwork selection, and that work will be presented in the exhibition alongside other works that resonate emotionally. This results in an exhibition that strengthens the emotional connection with the audience.

[0137] The following describes the processing flow.

[0138] Step 1:

[0139] The user uses a dedicated application to import an image of their calligraphy artwork into their device. At this stage, an emotion engine is activated via the camera and microphone to acquire emotion data from the user's facial expressions and voice.

[0140] Step 2:

[0141] The device packages the acquired image data along with the user's emotional data analyzed by the emotion engine, and prepares to send it to the server. At this time, it verifies that the image resolution and format are suitable for server processing.

[0142] Step 3:

[0143] The server inputs the received image data into an AI model, which then performs a technical and aesthetic evaluation of the artwork and assigns a score. In parallel, emotional data is also analyzed, and adjustments are made to ensure that the user's emotions are reflected in the artwork evaluation.

[0144] Step 4:

[0145] The server performs analysis to set appropriate themes based on scoring results and user sentiment data. Theme setting here is done by integrating the overall trends and sentiment data of the uploaded works.

[0146] Step 5:

[0147] Based on the set theme, the server selects artworks and incorporates them into the virtual exhibition. Selection criteria include the artwork's rating and the user's emotional resonance with it.

[0148] Step 6:

[0149] The server creates the layout of the virtual exhibition and generates descriptive text for each artwork. This text is customized based on sentiment data to evoke emotions in the user.

[0150] Step 7:

[0151] The server determines the exhibition's promotional strategy and distributes it to the target audience via social media and email. The content and timing of the promotion are optimized using sentiment data.

[0152] Step 8:

[0153] During the exhibition, the servers analyze visitor sentiment data in real time and adjust resources to maintain smooth access. This dynamic adjustment is made in response to visitors' emotions and behavior.

[0154] Step 9:

[0155] After the exhibition ends, the server collects and analyzes visitor sentiment and behavior data to generate insights that can be used to plan the next exhibition.

[0156] (Example 2)

[0157] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0158] In modern digital exhibitions, providing visitors with an engaging experience is challenging, requiring the selection of works and optimization of exhibition content based on individual user emotions. Furthermore, promotional activities must be tailored to appeal to the target audience's emotions, requiring careful timing and content adjustments. Additionally, there is a need for methods to utilize visitor behavior data to improve future exhibitions and promotions.

[0159] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0160] In this invention, the server includes means for verifying and optimizing the quality of visual data, means for acquiring user emotional information, evaluating and scoring the value of the artworks while taking this information into account, and means for setting appropriate themes and generating a selected collection of artworks using the evaluation results and emotional information. This makes it possible to set themes and select artworks based on user emotions, providing exhibition content that evokes empathy, and enabling effective promotion using emotional information.

[0161] A "user interface" is a means of providing users with screens and procedures for inputting data and performing operations on a system.

[0162] "Visual data" refers to digital data containing visual information, primarily images and video files.

[0163] "Quality check" is the process of verifying whether the resolution, brightness, color tone, and other aspects of visual data meet predetermined standards.

[0164] "Optimization" refers to the act of adjusting or modifying data so that it can be presented with higher quality.

[0165] "Emotional information" refers to data collected digitally about the emotions a user is experiencing, representing their intuitive reactions and emotional state in numerical and textual terms.

[0166] "Scoring" is the process of quantifying and ranking evaluation results, and is used as an indicator of evaluation based on specific criteria.

[0167] "Theme setting" is the act of determining the central concept or direction that will serve as the basis for a presentation or exhibition.

[0168] A "collection of works" is a group of works selected and organized based on their relatedness or commonalities.

[0169] A "digital exhibition" is an exhibition event held using an online environment, and is usually accessible through a website or application.

[0170] "Promotional information" refers to information used to announce or introduce events, products, or services, and is widely distributed for marketing purposes.

[0171] "Visitor information" refers to data about the behavior and reactions of people who participate in exhibitions and events, and is collected for analytical purposes.

[0172] "Computational resources" refer to the processing power and memory capacity of computers necessary to operate digital systems.

[0173] The system of this invention is a complex technical configuration including a user-owned terminal, a server, and an AI model. The user inputs digital visual data using a user interface on the terminal. The input image data is then quality-checked and optimized on the terminal. This process utilizes image processing software and specifically includes operations such as noise reduction and resolution correction.

[0174] Furthermore, users input emotional information when uploading their work. This emotional information is acquired through text input or selection and stored on the device as numerical or text data. The device then sends the optimized image data and emotional data to the server.

[0175] On the server, the transmitted data is first stored in a database. At this stage, a generative AI model is used to evaluate the images. The AI ​​model utilizes image recognition technology to calculate a score for the aesthetic value and technical achievement of the artwork.

[0176] The scoring results are integrated with user sentiment information, and the server uses this data to set appropriate themes. Theme setting is a crucial process that determines the direction of the exhibition, and a sentiment engine is used to design themes that resonate with users' emotions.

[0177] The selected works will be incorporated into the layout of the digital exhibition and accompanied by emotion-based explanatory information. This information will highlight the key aspects and emotional impact of each piece for the viewer.

[0178] The server also generates promotional information and distributes it through external networks at the optimal time. This promotional strategy is refined by analyzing past visit data and sentiment information.

[0179] For example, if a user inputs data expressing their emotion, such as "This artwork is wonderful!", this feeling of joy will be reflected in the theme setting and artwork selection. As a result, that artwork will be featured in the digital exhibition along with other works that evoke similar emotions.

[0180] An example of a prompt is: "Evaluate the aesthetic value and technical achievement of the calligraphy artwork submitted by the user, and take into account the user's emotional data to propose an exhibition theme."

[0181] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0182] Step 1:

[0183] Users input visual data using their devices. Specifically, users upload images of calligraphy artwork they have photographed to their devices. At the same time, they also input emotional information and supply this data to the system. The input data consists of image files (e.g., JPEG, PNG format) and emotional information in text format (e.g., "excited" or "satisfied").

[0184] Step 2:

[0185] The terminal checks the quality of the received image data and optimizes it as needed. Specifically, it performs noise reduction, resolution adjustment, and brightness and contrast correction. The input is an image file, and the output is an optimized image file. This ensures that the image is in its best condition before being sent to the server.

[0186] Step 3:

[0187] Optimized image data and sentiment information are sent from the terminal to the server. The server stores the image data in a database and appropriately records the sentiment information. The input is the image and sentiment information, and the output is the database record containing these.

[0188] Step 4:

[0189] The server processes the stored image data using a generating AI model to evaluate its aesthetic value and technical achievements. Specifically, the AI ​​model analyzes the images and calculates a score. The input for this step is image data, and the output is the evaluation score.

[0190] Step 5:

[0191] The server integrates evaluation scores from a generated AI model with user sentiment information to set the exhibition theme. The theme is set considering sentiment information, and works with high ratings and positive sentiment are selected. The input is evaluation scores and sentiment information, and the output is the exhibition theme and the selected works.

[0192] Step 6:

[0193] Based on the selected works, the server designs the layout of the digital exhibition and generates emotion-based explanatory information. It utilizes an emotion engine to ensure the explanations are easily understood by the user. The input is the selected works, and the output is the laid-out exhibition and explanatory information.

[0194] Step 7:

[0195] The server automatically generates promotional information based on sentiment data and distributes it via an external network. Specific actions include sending emails and posting on social media. Inputs are sentiment data and visitor data, while output is the distributed promotional information.

[0196] (Application Example 2)

[0197] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0198] In modern virtual exhibitions, the content of exhibited works often fails to consider the individual emotions of users, and promotional activities are not effectively conducted. Therefore, there is a need to further improve visitor satisfaction. However, conventional technologies make it difficult to create exhibits that take user emotions into account or to deliver promotional information tailored to visitors' interests. Thus, the construction of a new system is necessary to solve these problems.

[0199] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0200] In this invention, the server includes means for receiving visual data acquired via a user terminal, means for analyzing emotional data, selecting an appropriate theme based on the analysis results, selecting works corresponding to the theme, and means for automatically generating promotional information and transmitting it using an external information network. This makes it possible to display works based on the user's emotions and to deliver effective promotional information tailored to the interests of visitors.

[0201] A "user terminal" is a device used by individual users to input or retrieve information, and includes smartphones, personal computers, and other similar devices.

[0202] "Visual data" refers to digital data that records visual information, such as images and videos.

[0203] "Emotional data" refers to a numerical or categorical representation of the emotional state a user exhibits in a specific situation.

[0204] "Analysis results" refer to conclusions and evaluations derived from data analysis.

[0205] "Subject" refers to the central theme or concept of the artworks displayed in a virtual exhibition.

[0206] "Means of selecting works" refers to the method and technical elements for selecting suitable works from those provided based on specific criteria.

[0207] "Promotional information" refers to information intended to notify or arouse interest in a specific subject, and includes advertisements and announcements.

[0208] An "external information network" refers to a communication network used for sending and receiving digital data, and includes the internet and local networks.

[0209] The system for implementing this invention mainly consists of a server and a user terminal. The user uses a user terminal such as a smartphone or personal computer to acquire visual data such as calligraphy works and transmit it to the server through the terminal's interface.

[0210] The terminal checks the quality of the visual data and performs image processing as needed. For this purpose, it uses image processing libraries such as OpenCV. The image data is sent to the server via a communication module such as AWS Lambda. The server analyzes the received image data using an AI model based on TensorFlow, evaluates its aesthetic value, and quantifies it.

[0211] Meanwhile, users acquire emotional data using facial recognition technology. Using libraries such as EmotionAI, the user's emotions are quantified and sent to the server. The server takes this emotional data into consideration when selecting the theme for the exhibited works, and uses an AI model to select works that match the theme.

[0212] The server then creates the overall layout of the virtual exhibition based on the selected works. The interface used by visitors visually displays detailed information about the exhibited works, allowing users to intuitively understand the exhibition content.

[0213] Furthermore, the server is equipped with a means to transmit automatically generated promotional information using external information networks, according to the user's interests and emotions. This makes it possible to deliver promotional information at an effective time.

[0214] For example, when a user visits an exhibition, works themed around "serene mind" are displayed, and warm color schemes and background music are automatically selected accordingly. Furthermore, it is possible to engage in conversations using generative AI models, such as prompts like, "Please upload your work and have its aesthetic value evaluated," or "Let's customize the exhibition based on a theme that resonates with your emotions."

[0215] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0216] Step 1:

[0217] The user takes a picture of a calligraphy artwork with their device. The device uses OpenCV to check the image quality and adjust the brightness and contrast. The input is the captured image data, and the output is the adjusted image data.

[0218] Step 2:

[0219] The adjusted image data is sent from the device to the server via AWS Lambda. The server receives this image data and analyzes it using a generative AI model based on TensorFlow. The input is the adjusted image data, and the output is an evaluation score representing its aesthetic value.

[0220] Step 3:

[0221] The user uses their device's camera for facial recognition and the EmotionAI library to acquire emotion data in real time. The input is an image of the user's face, and the output is numerical emotion data.

[0222] Step 4:

[0223] The server combines the acquired evaluation scores and user sentiment data to select a theme for the exhibition and then selects artworks that match that theme. The inputs are evaluation scores and sentiment data, and the output is a list of the selected theme and artworks.

[0224] Step 5:

[0225] The server constructs a virtual exhibition on the platform based on the selected works. This includes generating an interface using Unity. The input is a list of works, and the output is the completed virtual exhibition layout.

[0226] Step 6:

[0227] When users visit an exhibition, they can obtain detailed information about the exhibits through prompts displayed on the interface. The server sends prompts based on a generated AI model. The input is visitor preference data, and the output is customized presentation information.

[0228] Step 7:

[0229] The server generates and sends promotional information at the appropriate time based on the user's emotions and interest in the exhibit. This also takes into account the user's past visit history and response data. The input is past visitor data, and the output is optimized promotional information.

[0230] 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 user input for the result of the specific processing. The control unit 46A transmits the audio data indicating 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.

[0231] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0232] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0233] [Second Embodiment]

[0234] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0235] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0236] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0237] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0238] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0239] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0240] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0241] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0242] The specific processing program 56 is an example of a "program" relating to the technology of this 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.

[0243] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0244] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0245] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. 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".

[0246] The system in this invention begins with a process of uploading artistic works, such as calligraphy, online via a user's terminal. The terminal receives the artwork image through a user interface, performs pre-processing as needed, and then sends it to the server. Pre-processing here refers to adjusting the image size and correcting the image quality.

[0247] The server analyzes the received image data and uses a pre-trained AI model to evaluate and score the artwork. Evaluation criteria include aesthetic value, technical skill, and creativity, each of which may vary depending on industry standards and user customization. These evaluation results are stored in a database for further analysis.

[0248] Next, the server has a theme setting function, determining the exhibition theme based on accumulated evaluation data and external market trends. Based on this decision, the server selects the works that best fit the theme and designs the structure of the virtual exhibition.

[0249] The selected works are arranged in an optimized layout within the digital gallery, and each piece is accompanied by automatically generated descriptive text from the server. This allows viewers to deepen their understanding of the works and enhances the overall viewing experience.

[0250] Furthermore, the server generates information for promoting the exhibition and implements effective marketing through social media platforms and email. At this stage, the targeting of the promotion is also optimized by AI.

[0251] Once an exhibition is open, the server monitors visitor activity in real time and adjusts system resources as needed. Visitor data is collected and analyzed to improve future exhibitions. This entire process provides a platform for artists and enthusiasts to present their work to a wide audience and exchange feedback. For example, if a user uploads a calligraphy piece with a nature theme, the server analyzes it and selects it as part of a nature-related exhibition, potentially leading to the user's work being featured in an international virtual exhibition.

[0252] The following describes the processing flow.

[0253] Step 1:

[0254] The user takes their calligraphy artwork as an image to their device and prepares to upload it to the server using a dedicated application.

[0255] Step 2:

[0256] The device checks the image format and size, and if necessary, performs image optimization (e.g., resizing, adjusting resolution) before sending it to the server.

[0257] Step 3:

[0258] The server saves the received image data to a database and also inputs the image into an AI model to calculate an evaluation score for the artwork. This score is recorded in the database.

[0259] Step 4:

[0260] The server executes an algorithm that determines the theme for the exhibition based on past evaluation data and external data. This automatically sets the theme for the next exhibition.

[0261] Step 5:

[0262] The server selects the most relevant works based on the set theme, ranking them in order of highest rating, to form the exhibition collection.

[0263] Step 6:

[0264] The server generates a virtual exhibition layout based on the selected works and automatically creates a description for each work. This description includes background information and evaluation points for each work.

[0265] Step 7:

[0266] The server generates promotional information for the exhibition and begins distributing advertisements through platforms such as social media and email. At this time, it identifies the target audience for the promotion.

[0267] Step 8:

[0268] During the exhibition's public access period, the servers track visitor behavior in real time and adjust server resource allocation as needed to maintain smooth access.

[0269] Step 9:

[0270] The server collects and analyzes visitor behavior data after the exhibition ends. This includes data such as page views, time spent on the site, and identification of the most popular works.

[0271] Step 10:

[0272] The server generates insights from the analysis results that will help improve the next exhibition, and feeds them back into the system's operation.

[0273] (Example 1)

[0274] Next, we will describe Example 1. 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".

[0275] In evaluating and exhibiting cultural works on online platforms, the objectivity of evaluation criteria and the optimization of exhibitions are key challenges. Furthermore, appropriate promotion and analysis of visitor behavior are necessary to improve future exhibitions. These challenges can sometimes limit the user experience and the diversity of the works.

[0276] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0277] In this invention, the server includes means for receiving digital data via a user interface, means for evaluating cultural works based on the digital data and performing digitization, and means for determining a theme based on the collected evaluation information and market trend information and selecting a work corresponding to the theme. Thereby, it becomes possible to select works based on objective evaluation criteria and to have a rich and diverse exhibition.

[0278] The "user interface" is a means for a user to input and operate data and information.

[0279] "Digital data" is information in an electronically processed form and is mainly in a form that can be used by a computer system.

[0280] A "cultural work" is an expression having artistic or creative value and includes various forms such as visual arts and literature.

[0281] "Evaluation" is a process of analyzing and measuring the value and quality of an object based on specific criteria.

[0282] "Digitization" is a conversion process for expressing evaluation results as numerical values to facilitate comparison and analysis.

[0283] "Collected evaluation information" is a general term for evaluation results and related data collected according to various criteria.

[0284] "Market trend information" is data indicating current or future trends in a specific industry or field.

[0285] A "theme" is a theme or topic that is the center of an exhibition or discussion.

[0286] The "means for selecting" is a process of determining suitable options according to specific criteria or purposes.

[0287] This invention is a system that optimizes the evaluation and exhibition of cultural works via digital data, and consists of three main components: a terminal, a server, and a user. The user uploads cultural works as digital data using their terminal. The terminal performs data resizing and image quality correction using pre-specified format conversion and image processing software (e.g., image editing software).

[0288] The server uses this received digital data to evaluate the artwork using a generative AI model. The evaluation criteria include aesthetic value, technical skill, and creativity, each of which is recorded as numerical data. The evaluated data is stored in a database on the server and used for necessary analysis.

[0289] Furthermore, the server uses the collected evaluation information to perform comparative analysis with external market trend data and determine an appropriate exhibition theme. This process utilizes prompts such as: "Consider the latest trend information and suggest an exhibition theme that best suits the artwork."

[0290] The server automatically selects the most suitable cultural works based on the chosen theme and designs the structure of the virtual exhibition. Detailed explanatory information about the selected works is generated by a generative AI and provided to deepen the audience's understanding. The server also handles the promotion strategy, effectively distributing information using social media platforms and email networks. Here again, the prompt "Please propose an effective promotion strategy for a specific audience" is used.

[0291] Finally, the server monitors visitor activity in real time during the public exhibition. This allows for analysis of visitor interests and behavioral patterns, providing valuable insights to inform future exhibition planning. This entire process enables users to present their work to a broad audience and engage in discussions about it.

[0292] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0293] Step 1:

[0294] Users select and upload digital data of cultural works using their own devices. The input data is image files, which the device accepts. Specifically, the user performs file selection operations on the user interface. The device checks the image size and format, and if the format is inappropriate, it converts it to a standard format such as JPEG or PNG. As output, the image data converted to the appropriate format is sent to the server.

[0295] Step 2:

[0296] The server receives and stores image data sent from the terminal. The input data is mainly image files. Image processing software is used within the server to prepare the images for analysis. Specifically, the images are processed into a format that can be input into the AI ​​model. The output of this process is image data that has been formatted for processing by the AI ​​model.

[0297] Step 3:

[0298] The server passes image data to the AI ​​model and initiates the evaluation process. The input is pre-processed image data. The AI ​​model evaluates the aesthetic value, technical skill, and creativity of the image and quantifies them. The output of this data calculation is a numerical score for each evaluation criterion. The scores are recorded in a database and, if necessary, presented to the user as feedback.

[0299] Step 4:

[0300] The server determines the optimal exhibition theme using the recorded evaluation scores and market trend information obtained from the outside. The input data is the evaluation scores and market trend information. Analysis is performed based on the prompt sentence "Please propose the optimal exhibition theme for the works considering the latest trend information" using the generative AI model. The output is the selected exhibition theme, which is utilized in the following procedures within the system.

[0301] Step 5:

[0302] The server selects the cultural works optimal for the exhibition based on the determined theme and designs the layout of the virtual exhibition. The input is the theme determination data and the work evaluation scores. With the assistance of AI, the optimization of how to arrange the works on the screen is carried out. As output, the data of the completed exhibition layout and the explanatory information attached to each work are generated and placed in the digital gallery.

[0303] Step 6:

[0304] The server plans the promotion of the virtual exhibition and generates information to appeal to a specific audience segment. The input is the exhibition information and the target audience data. The generative AI model is used to analyze the prompt sentence "Please propose an effective promotion strategy for a specific audience segment". The output is the specific promotion strategy and the marketing message, which are distributed via SNS and email.

[0305] Step 7:

[0306] The server monitors the actions of visitors in real time during the exhibition period. The input is the access data of the visitors. The server analyzes the behavioral data such as the access pattern and the staying time, and dynamically adjusts the system resources. Based on this analysis, a report on visitor behavior is generated as output and utilized for the improvement of the next exhibition.

[0307] (Application Example 1)

[0308] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0309] Contemporary artists and designers often lack effective channels for raising awareness of their work, and opportunities to participate in physical exhibitions are particularly limited. Furthermore, the evaluation and promotion of artworks are often manual processes, requiring considerable time and effort. Therefore, there is a need for a system that efficiently evaluates and promotes artworks online, and allows for broad public access through virtual exhibitions.

[0310] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0311] In this invention, the server includes means for receiving image data input via a user interface, means for evaluating and scoring works of art based on the image data, and means for displaying digital content photographed and uploaded by users in a virtual shop. This enables the efficient evaluation of works by artists and designers, their display in a themed virtual shop, and promotes widespread recognition.

[0312] A "user interface" is a visual or physical interface through which a user accesses a system and inputs or retrieves data.

[0313] "Image data" refers to visual information that has been captured or scanned and is represented in a digital format.

[0314] A "work of art" is an object created through creative activity that is visual or combines visual and other senses.

[0315] "Evaluation" is the act of measuring the value or performance of an object or process based on specific criteria.

[0316] "Scoring" is the process of expressing the evaluated results as a quantitative value.

[0317] A "theme" is a central concept or topic that unifies various elements within an exhibition or project.

[0318] A "virtual exhibition" is an event or platform that displays works of art online via the internet.

[0319] "Promotional information" refers to media content created to inform the public about a specific product or service and to convey its appeal.

[0320] An "external network" refers to external computer systems or data communication networks connected via the Internet.

[0321] "Visitor data" refers to information about the behavior and attributes of users who use the system.

[0322] "Real-time" refers to an environment where data or information can be processed and provided almost instantaneously.

[0323] In this embodiment of the invention, the system begins with the digitization and uploading of artwork by the user. The user uses a device such as a smartphone to photograph their artwork and upload the image data to the system. At this time, the device provides a user interface to allow the user to operate it easily. The device is also equipped with an image processing module that adjusts the image size and corrects the image quality, and pre-processing is performed using libraries such as OpenCV.

[0324] The server analyzes the received image data through an AI evaluation module. This uses a pre-trained generative AI model with machine learning frameworks such as TensorFlow. This model evaluates the aesthetic value, technical skill, and creativity of the artwork and performs scoring. Based on the evaluated information, the server performs analysis and displays the digital content photographed and uploaded by the user in a virtual shop with an appropriate theme.

[0325] Furthermore, the server generates promotional information and distributes it to external networks via social media and email. Targeting is optimized by AI, and the Python Twython library may be used for social media integration.

[0326] Visitor movements are monitored in real time, and visitor data is collected and analyzed. This allows the system to be used to improve future exhibitions and displays.

[0327] For example, if a user uploads a work with a nature theme, the server can analyze the work and display it in a virtual shop categorized as "Natural Beauty." An example prompt message: "Analyze the theme of the artwork and display it in the relevant virtual shop." This allows the user's work to reach a wider audience and provide opportunities for viewing and purchasing.

[0328] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0329] Step 1:

[0330] Users use their smartphones to photograph their artwork and upload the image data to the system via an application. The device receives the image data through the user interface and uses the OpenCV library to adjust the size and improve the image quality. The input is the captured image data, and the output is the processed image data.

[0331] Step 2:

[0332] The server receives processed image data sent from the terminal. It then sends the received image data to an AI evaluation module, where it is analyzed using a generative AI model with TensorFlow. This analysis quantifies the aesthetic value, technical skill, and creativity of the artwork, generating an evaluation score. Processed image data is used as input, and the evaluation score is obtained as output.

[0333] Step 3:

[0334] The server classifies the artwork into a suitable theme based on the generated evaluation score. Based on the analysis results, it displays the user-uploaded digital content in the relevant virtual shop category. The input is the evaluation score, and the output is classification information.

[0335] Step 4:

[0336] The server generates promotional information and distributes it via social media and email. AI optimizes targeting to enhance the effectiveness of promotional campaigns. Inputs include classification information and market trends, and the output is promotional materials.

[0337] Step 5:

[0338] The server monitors visitor behavior to the virtual shop in real time. It collects visitor data using tools like Google Analytics and analyzes it to identify areas for improvement for future exhibitions. The input is visitor behavior data, and the output is an analysis report.

[0339] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0340] The system in this invention begins with a process of transmitting image data of a calligraphic work from a terminal to a server via a user interface. The terminal provides an interface for checking and optimizing the image quality and transferring it to the server. This process also includes a function to acquire the user's emotions as data.

[0341] The server stores the received image data and uses an AI model to evaluate and score the aesthetic value and technical achievement of the artwork. Furthermore, it can conduct a more multifaceted evaluation by taking into account user emotion data recognized by the emotion engine. For example, the program is designed to add points to the evaluation if the user has positive emotions towards the artwork.

[0342] Next, the server determines the exhibition theme based on the aforementioned evaluation results and sentiment data. This theme selection aligns with user interests and trends indicated by the sentiment data, resulting in an exhibition that is more relatable and engaging.

[0343] The selected works are incorporated into the virtual exhibition layout along with descriptive text based on sentiment analysis. The server takes into account user feedback analyzed by the sentiment engine and adjusts the descriptive text to include information that users are likely to emotionally respond to.

[0344] In promotional activities, the server uses emotional data obtained from an emotion engine to predict the audience's emotional response and appropriately adjust the content and timing of the promotion. For example, it might distribute information about an exhibition at a time when users have shown a very positive response in the past.

[0345] In this way, systems that utilize an emotion engine consider user emotions when evaluating and setting themes, providing a more fulfilling exhibition experience. For example, if a user expresses emotions such as "excitement" or "satisfaction" when uploading a work, the server will reflect those emotions in the theme setting and artwork selection, and that work will be presented in the exhibition alongside other works that resonate emotionally. This results in an exhibition that strengthens the emotional connection with the audience.

[0346] The following describes the processing flow.

[0347] Step 1:

[0348] The user uses a dedicated application to import an image of their calligraphy artwork into their device. At this stage, an emotion engine is activated via the camera and microphone to acquire emotion data from the user's facial expressions and voice.

[0349] Step 2:

[0350] The device packages the acquired image data along with the user's emotional data analyzed by the emotion engine, and prepares to send it to the server. At this time, it verifies that the image resolution and format are suitable for server processing.

[0351] Step 3:

[0352] The server inputs the received image data into an AI model, which then performs a technical and aesthetic evaluation of the artwork and assigns a score. In parallel, emotional data is also analyzed, and adjustments are made to ensure that the user's emotions are reflected in the artwork evaluation.

[0353] Step 4:

[0354] The server performs analysis to set appropriate themes based on scoring results and user sentiment data. Theme setting here is done by integrating the overall trends and sentiment data of the uploaded works.

[0355] Step 5:

[0356] Based on the set theme, the server selects artworks and incorporates them into the virtual exhibition. Selection criteria include the artwork's rating and the user's emotional resonance with it.

[0357] Step 6:

[0358] The server creates the layout of the virtual exhibition and generates descriptive text for each artwork. This text is customized based on sentiment data to evoke emotions in the user.

[0359] Step 7:

[0360] The server determines the exhibition's promotional strategy and distributes it to the target audience via social media and email. The content and timing of the promotion are optimized using sentiment data.

[0361] Step 8:

[0362] During the exhibition, the servers analyze visitor sentiment data in real time and adjust resources to maintain smooth access. This dynamic adjustment is made in response to visitors' emotions and behavior.

[0363] Step 9:

[0364] After the exhibition ends, the server collects and analyzes visitor sentiment and behavior data to generate insights that can be used to plan the next exhibition.

[0365] (Example 2)

[0366] Next, we will describe Example 2. 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".

[0367] In modern digital exhibitions, providing visitors with an engaging experience is challenging, requiring the selection of works and optimization of exhibition content based on individual user emotions. Furthermore, promotional activities must be tailored to appeal to the target audience's emotions, requiring careful timing and content adjustments. Additionally, there is a need for methods to utilize visitor behavior data to improve future exhibitions and promotions.

[0368] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0369] In this invention, the server includes means for verifying and optimizing the quality of visual data, means for acquiring user emotional information, evaluating and scoring the value of the artworks while taking this information into account, and means for setting appropriate themes and generating a selected collection of artworks using the evaluation results and emotional information. This makes it possible to set themes and select artworks based on user emotions, providing exhibition content that evokes empathy, and enabling effective promotion using emotional information.

[0370] A "user interface" is a means of providing users with screens and procedures for inputting data and performing operations on a system.

[0371] "Visual data" refers to digital data containing visual information, primarily images and video files.

[0372] "Quality check" is the process of verifying whether the resolution, brightness, color tone, and other aspects of visual data meet predetermined standards.

[0373] "Optimization" refers to the act of adjusting or modifying data so that it can be presented with higher quality.

[0374] "Emotional information" refers to data collected digitally about the emotions a user is experiencing, representing their intuitive reactions and emotional state in numerical and textual terms.

[0375] "Scoring" is the process of quantifying and ranking evaluation results, and is used as an indicator of evaluation based on specific criteria.

[0376] "Theme setting" is the act of determining the central concept or direction that will serve as the basis for a presentation or exhibition.

[0377] A "collection of works" is a group of works selected and organized based on their relatedness or commonalities.

[0378] A "digital exhibition" is an exhibition event held using an online environment, and is usually accessible through a website or application.

[0379] "Promotional information" refers to information used to announce or introduce events, products, or services, and is widely distributed for marketing purposes.

[0380] "Visitor information" refers to data about the behavior and reactions of people who participate in exhibitions and events, and is collected for analytical purposes.

[0381] "Computational resources" refer to the processing power and memory capacity of computers necessary to operate digital systems.

[0382] The system of this invention is a complex technical configuration including a user-owned terminal, a server, and an AI model. The user inputs digital visual data using a user interface on the terminal. The input image data is then quality-checked and optimized on the terminal. This process utilizes image processing software and specifically includes operations such as noise reduction and resolution correction.

[0383] Furthermore, users input emotional information when uploading their work. This emotional information is acquired through text input or selection and stored on the device as numerical or text data. The device then sends the optimized image data and emotional data to the server.

[0384] On the server, the transmitted data is first stored in a database. At this stage, a generative AI model is used to evaluate the images. The AI ​​model utilizes image recognition technology to calculate a score for the aesthetic value and technical achievement of the artwork.

[0385] The scoring results are integrated with user sentiment information, and the server uses this data to set appropriate themes. Theme setting is a crucial process that determines the direction of the exhibition, and a sentiment engine is used to design themes that resonate with users' emotions.

[0386] The selected works will be incorporated into the layout of the digital exhibition and accompanied by emotion-based explanatory information. This information will highlight the key aspects and emotional impact of each piece for the viewer.

[0387] The server also generates promotional information and distributes it through external networks at the optimal time. This promotional strategy is refined by analyzing past visit data and sentiment information.

[0388] For example, if a user inputs data expressing their emotion, such as "This artwork is wonderful!", this feeling of joy will be reflected in the theme setting and artwork selection. As a result, that artwork will be featured in the digital exhibition along with other works that evoke similar emotions.

[0389] An example of a prompt is: "Evaluate the aesthetic value and technical achievement of the calligraphy artwork submitted by the user, and take into account the user's emotional data to propose an exhibition theme."

[0390] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0391] Step 1:

[0392] Users input visual data using their devices. Specifically, users upload images of calligraphy artwork they have photographed to their devices. At the same time, they also input emotional information and supply this data to the system. The input data consists of image files (e.g., JPEG, PNG format) and emotional information in text format (e.g., "excited" or "satisfied").

[0393] Step 2:

[0394] The terminal checks the quality of the received image data and optimizes it as needed. Specifically, it performs noise reduction, resolution adjustment, and brightness and contrast correction. The input is an image file, and the output is an optimized image file. This ensures that the image is in its best condition before being sent to the server.

[0395] Step 3:

[0396] Optimized image data and sentiment information are sent from the terminal to the server. The server stores the image data in a database and appropriately records the sentiment information. The input is the image and sentiment information, and the output is the database record containing these.

[0397] Step 4:

[0398] The server processes the stored image data using a generating AI model to evaluate its aesthetic value and technical achievements. Specifically, the AI ​​model analyzes the images and calculates a score. The input for this step is image data, and the output is the evaluation score.

[0399] Step 5:

[0400] The server integrates evaluation scores from a generated AI model with user sentiment information to set the exhibition theme. The theme is set considering sentiment information, and works with high ratings and positive sentiment are selected. The input is evaluation scores and sentiment information, and the output is the exhibition theme and the selected works.

[0401] Step 6:

[0402] Based on the selected works, the server designs the layout of the digital exhibition and generates emotion-based explanatory information. It utilizes an emotion engine to ensure the explanations are easily understood by the user. The input is the selected works, and the output is the laid-out exhibition and explanatory information.

[0403] Step 7:

[0404] The server automatically generates promotional information based on sentiment data and distributes it via an external network. Specific actions include sending emails and posting on social media. Inputs are sentiment data and visitor data, while output is the distributed promotional information.

[0405] (Application Example 2)

[0406] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0407] In modern virtual exhibitions, the content of exhibited works often fails to consider the individual emotions of users, and promotional activities are not effectively conducted. Therefore, there is a need to further improve visitor satisfaction. However, conventional technologies make it difficult to create exhibits that take user emotions into account or to deliver promotional information tailored to visitors' interests. Thus, the construction of a new system is necessary to solve these problems.

[0408] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0409] In this invention, the server includes means for receiving visual data acquired via a user terminal, means for analyzing emotional data, selecting an appropriate theme based on the analysis results, selecting works corresponding to the theme, and means for automatically generating promotional information and transmitting it using an external information network. This makes it possible to display works based on the user's emotions and to deliver effective promotional information tailored to the interests of visitors.

[0410] A "user terminal" is a device used by individual users to input or retrieve information, and includes smartphones, personal computers, and other similar devices.

[0411] "Visual data" refers to digital data that records visual information, such as images and videos.

[0412] "Emotional data" refers to a numerical or categorical representation of the emotional state a user exhibits in a specific situation.

[0413] "Analysis results" refer to conclusions and evaluations derived from data analysis.

[0414] "Subject" refers to the central theme or concept of the artworks displayed in a virtual exhibition.

[0415] "Means of selecting works" refers to the method and technical elements for selecting suitable works from those provided based on specific criteria.

[0416] "Promotional information" refers to information intended to notify or arouse interest in a specific subject, and includes advertisements and announcements.

[0417] An "external information network" refers to a communication network used for sending and receiving digital data, and includes the internet and local networks.

[0418] The system for implementing this invention mainly consists of a server and a user terminal. The user uses a user terminal such as a smartphone or personal computer to acquire visual data such as calligraphy works and transmit it to the server through the terminal's interface.

[0419] The terminal checks the quality of the visual data and performs image processing as needed. For this purpose, it utilizes image processing libraries such as OpenCV. The image data is sent to the server via a communication module, such as AWS Lambda. The server analyzes the received image data using an AI model based on TensorFlow, evaluates its aesthetic value, and quantifies it.

[0420] Meanwhile, users acquire emotional data using facial recognition technology. Using libraries such as EmotionAI, the user's emotions are quantified and sent to the server. The server takes this emotional data into consideration when selecting the theme for the exhibited works, and uses an AI model to select works that match the theme.

[0421] The server then creates the overall layout of the virtual exhibition based on the selected works. The interface used by visitors visually displays detailed information about the exhibited works, allowing users to intuitively understand the exhibition content.

[0422] Furthermore, the server is equipped with a means to transmit automatically generated promotional information using external information networks, according to the user's interests and emotions. This makes it possible to deliver promotional information at an effective time.

[0423] For example, when a user visits an exhibition, works themed around "serene mind" are displayed, and warm color schemes and background music are automatically selected accordingly. Furthermore, it is possible to engage in conversations using generative AI models, such as prompts like, "Please upload your work and have its aesthetic value evaluated," or "Let's customize the exhibition based on a theme that resonates with your emotions."

[0424] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0425] Step 1:

[0426] The user takes a picture of a calligraphy artwork with their device. The device uses OpenCV to check the image quality and adjust the brightness and contrast. The input is the captured image data, and the output is the adjusted image data.

[0427] Step 2:

[0428] The adjusted image data is sent from the device to the server via AWS Lambda. The server receives this image data and analyzes it using a generative AI model based on TensorFlow. The input is the adjusted image data, and the output is an evaluation score representing its aesthetic value.

[0429] Step 3:

[0430] The user uses their device's camera for facial recognition and the EmotionAI library to acquire emotion data in real time. The input is an image of the user's face, and the output is numerical emotion data.

[0431] Step 4:

[0432] The server combines the acquired evaluation scores and user sentiment data to select a theme for the exhibition and then selects artworks that match that theme. The inputs are evaluation scores and sentiment data, and the output is a list of the selected theme and artworks.

[0433] Step 5:

[0434] The server constructs a virtual exhibition on the platform based on the selected works. This includes generating an interface using Unity. The input is a list of works, and the output is the completed virtual exhibition layout.

[0435] Step 6:

[0436] When users visit an exhibition, they can obtain detailed information about the exhibits through prompts displayed on the interface. The server sends prompts based on a generated AI model. The input is visitor preference data, and the output is customized presentation information.

[0437] Step 7:

[0438] The server generates and sends promotional information at the appropriate time based on the user's emotions and interest in the exhibit. This also takes into account the user's past visit history and response data. The input is past visitor data, and the output is optimized promotional information.

[0439] 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 user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0440] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0441] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0442] [Third Embodiment]

[0443] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0444] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0445] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0446] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0447] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0448] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0449] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0450] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0451] The specific processing program 56 is an example of a "program" relating to the technology of this 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.

[0452] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0453] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0454] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0455] The system in this invention begins with a process of uploading artistic works, such as calligraphy, online via a user's terminal. The terminal receives the artwork image through a user interface, performs pre-processing as needed, and then sends it to the server. Pre-processing here refers to adjusting the image size and correcting the image quality.

[0456] The server analyzes the received image data and uses a pre-trained AI model to evaluate and score the artwork. Evaluation criteria include aesthetic value, technical skill, and creativity, each of which may vary depending on industry standards and user customization. These evaluation results are stored in a database for further analysis.

[0457] Next, the server has a theme setting function, determining the exhibition theme based on accumulated evaluation data and external market trends. Based on this decision, the server selects the works that best fit the theme and designs the structure of the virtual exhibition.

[0458] The selected works are arranged in an optimized layout within the digital gallery, and each piece is accompanied by automatically generated descriptive text from the server. This allows viewers to deepen their understanding of the works and enhances the overall viewing experience.

[0459] Furthermore, the server generates information for promoting the exhibition and implements effective marketing through social media platforms and email. At this stage, the targeting of the promotion is also optimized by AI.

[0460] Once an exhibition is open, the server monitors visitor activity in real time and adjusts system resources as needed. Visitor data is collected and analyzed to improve future exhibitions. This entire process provides a platform for artists and enthusiasts to present their work to a wide audience and exchange feedback. For example, if a user uploads a calligraphy piece with a nature theme, the server analyzes it and selects it as part of a nature-related exhibition, potentially leading to the user's work being featured in an international virtual exhibition.

[0461] The following describes the processing flow.

[0462] Step 1:

[0463] The user takes their calligraphy artwork as an image to their device and prepares to upload it to the server using a dedicated application.

[0464] Step 2:

[0465] The device checks the image format and size, and if necessary, performs image optimization (e.g., resizing, adjusting resolution) before sending it to the server.

[0466] Step 3:

[0467] The server saves the received image data to a database and also inputs the image into an AI model to calculate an evaluation score for the artwork. This score is recorded in the database.

[0468] Step 4:

[0469] The server executes an algorithm that determines the theme for the exhibition based on past evaluation data and external data. This automatically sets the theme for the next exhibition.

[0470] Step 5:

[0471] The server selects the most relevant works based on the set theme, ranking them in order of highest rating, to form the exhibition collection.

[0472] Step 6:

[0473] The server generates a virtual exhibition layout based on the selected works and automatically creates a description for each work. This description includes background information and evaluation points for each work.

[0474] Step 7:

[0475] The server generates promotional information for the exhibition and begins distributing advertisements through platforms such as social media and email. At this time, it identifies the target audience for the promotion.

[0476] Step 8:

[0477] During the exhibition's public access period, the servers track visitor behavior in real time and adjust server resource allocation as needed to maintain smooth access.

[0478] Step 9:

[0479] The server collects and analyzes visitor behavior data after the exhibition ends. This includes data such as page views, time spent on the site, and identification of the most popular works.

[0480] Step 10:

[0481] The server generates insights from the analysis results that will help improve the next exhibition, and feeds them back into the system's operation.

[0482] (Example 1)

[0483] Next, we will describe Example 1. 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."

[0484] In evaluating and exhibiting cultural works on online platforms, the objectivity of evaluation criteria and the optimization of exhibitions are key challenges. Furthermore, appropriate promotion and analysis of visitor behavior are necessary to improve future exhibitions. These challenges can sometimes limit the user experience and the diversity of the works.

[0485] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0486] In this invention, the server includes means for receiving digital data via a user interface, means for evaluating and quantifying cultural works based on the digital data, and means for determining a theme based on the collected evaluation information and market trend information, and selecting works corresponding to that theme. This enables the selection of works based on objective evaluation criteria and diverse exhibitions.

[0487] A "user interface" is a means by which a user inputs and manipulates data and information.

[0488] "Digital data" refers to information in a format that is processed electronically and is primarily usable by computer systems.

[0489] A "cultural work" is an expression that possesses artistic or creative value, and includes a variety of forms such as visual arts and literature.

[0490] "Evaluation" is the process of analyzing and measuring the value and quality of an object based on specific criteria.

[0491] "Quantification" is a conversion process that expresses evaluation results as numerical values, making comparison and analysis easier.

[0492] "Collected evaluation information" refers to the collective term for evaluation results and related data collected according to various criteria.

[0493] "Market trend information" refers to data that shows current or future trends in a specific industry or field.

[0494] The "subject" is the central theme or topic of the exhibition or discussion.

[0495] "Means of selection" refers to the process of determining the appropriate option according to specific criteria or objectives.

[0496] This invention is a system that optimizes the evaluation and exhibition of cultural works via digital data, and consists of three main components: a terminal, a server, and a user. The user uploads cultural works as digital data using their terminal. The terminal performs data resizing and image quality correction using pre-specified format conversion and image processing software (e.g., image editing software).

[0497] The server uses this received digital data to evaluate the artwork using a generative AI model. The evaluation criteria include aesthetic value, technical skill, and creativity, each of which is recorded as numerical data. The evaluated data is stored in a database on the server and used for necessary analysis.

[0498] Furthermore, the server uses the collected evaluation information to perform comparative analysis with external market trend data and determine an appropriate exhibition theme. This process utilizes prompts such as: "Consider the latest trend information and suggest an exhibition theme that best suits the artwork."

[0499] The server automatically selects the most suitable cultural works based on the chosen theme and designs the structure of the virtual exhibition. Detailed explanatory information about the selected works is generated by a generative AI and provided to deepen the audience's understanding. The server also handles the promotion strategy, effectively distributing information using social media platforms and email networks. Here again, the prompt "Please propose an effective promotion strategy for a specific audience" is used.

[0500] Finally, the server monitors visitor activity in real time during the public exhibition. This allows for analysis of visitor interests and behavioral patterns, providing valuable insights to inform future exhibition planning. This entire process enables users to present their work to a broad audience and engage in discussions about it.

[0501] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0502] Step 1:

[0503] Users select and upload digital data of cultural works using their own devices. The input data is image files, which the device accepts. Specifically, the user performs file selection operations on the user interface. The device checks the image size and format, and if the format is inappropriate, it converts it to a standard format such as JPEG or PNG. As output, the image data converted to the appropriate format is sent to the server.

[0504] Step 2:

[0505] The server receives and stores image data sent from the terminal. The input data is mainly image files. Image processing software is used within the server to prepare the images for analysis. Specifically, the images are processed into a format that can be input into the AI ​​model. The output of this process is image data that has been formatted for processing by the AI ​​model.

[0506] Step 3:

[0507] The server passes image data to the AI ​​model and initiates the evaluation process. The input is pre-processed image data. The AI ​​model evaluates the aesthetic value, technical skill, and creativity of the image and quantifies them. The output of this data calculation is a numerical score for each evaluation criterion. The scores are recorded in a database and, if necessary, presented to the user as feedback.

[0508] Step 4:

[0509] The server determines the optimal exhibition theme using recorded evaluation scores and market trend information obtained from external sources. The input data consists of evaluation scores and market trend information. An AI model is used to perform analysis based on the prompt message, "Consider the latest trend information and suggest the most suitable exhibition theme for the artwork." The output is the selected exhibition theme, which is then used within the system for the next steps.

[0510] Step 5:

[0511] The server selects the most suitable cultural works for the exhibition based on the chosen theme and designs the layout of the virtual exhibition. The inputs are theme selection data and artwork evaluation scores. With the help of AI, it optimizes how to arrange the artworks on the screen. As output, data of the completed exhibition layout and explanatory information accompanying each artwork are generated and placed in the digital gallery.

[0512] Step 6:

[0513] The server plans the promotion of a virtual exhibition and generates information to appeal to a specific audience. The inputs are exhibition information and target audience data. The prompt "Propose an effective promotional strategy for a specific audience" is used to analyze the AI ​​model. The output is a specific promotional strategy and marketing message, which is distributed via social media and email.

[0514] Step 7:

[0515] The server monitors visitor behavior in real time during the exhibition. The input is visitor access data. The server analyzes behavioral data such as access patterns and dwell time, and dynamically adjusts system resources. This analysis generates a report on visitor behavior, which is used to improve future exhibitions.

[0516] (Application Example 1)

[0517] Next, we will explain Application Example 1. In the following explanation, 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."

[0518] Contemporary artists and designers often lack effective channels for raising awareness of their work, and opportunities to participate in physical exhibitions are particularly limited. Furthermore, the evaluation and promotion of artworks are often manual processes, requiring considerable time and effort. Therefore, there is a need for a system that efficiently evaluates and promotes artworks online, and allows for broad public access through virtual exhibitions.

[0519] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0520] In this invention, the server includes means for receiving image data input via a user interface, means for evaluating and scoring works of art based on the image data, and means for displaying digital content photographed and uploaded by users in a virtual shop. This enables the efficient evaluation of works by artists and designers, their display in a themed virtual shop, and promotes widespread recognition.

[0521] A "user interface" is a visual or physical interface through which a user accesses a system and inputs or retrieves data.

[0522] "Image data" refers to visual information that has been captured or scanned and is represented in a digital format.

[0523] A "work of art" is an object created through creative activity that is visual or combines visual and other senses.

[0524] "Evaluation" is the act of measuring the value or performance of an object or process based on specific criteria.

[0525] "Scoring" is the process of expressing the evaluated results as a quantitative value.

[0526] A "theme" is a central concept or topic that unifies various elements within an exhibition or project.

[0527] A "virtual exhibition" is an event or platform that displays works of art online via the internet.

[0528] "Promotional information" refers to media content created to inform the public about a specific product or service and to convey its appeal.

[0529] An "external network" refers to external computer systems or data communication networks connected via the Internet.

[0530] "Visitor data" refers to information about the behavior and attributes of users who use the system.

[0531] "Real-time" refers to an environment where data or information can be processed and provided almost instantaneously.

[0532] In this embodiment of the invention, the system begins with the digitization and uploading of artwork by the user. The user uses a device such as a smartphone to photograph their artwork and upload the image data to the system. At this time, the device provides a user interface to allow the user to operate it easily. The device is also equipped with an image processing module that adjusts the image size and corrects the image quality, and pre-processing is performed using libraries such as OpenCV.

[0533] The server analyzes the received image data through an AI evaluation module. This uses a pre-trained generative AI model with machine learning frameworks such as TensorFlow. This model evaluates the aesthetic value, technical skill, and creativity of the artwork and performs scoring. Based on the evaluated information, the server performs analysis and displays the digital content photographed and uploaded by the user in a virtual shop with an appropriate theme.

[0534] Furthermore, the server generates promotional information and distributes it to external networks via social media and email. Targeting is optimized by AI, and the Python Twython library may be used for social media integration.

[0535] Visitor movements are monitored in real time, and visitor data is collected and analyzed. This allows the system to be used to improve future exhibitions and displays.

[0536] For example, if a user uploads a work with a nature theme, the server can analyze the work and display it in a virtual shop categorized as "Natural Beauty." An example prompt message: "Analyze the theme of the artwork and display it in the relevant virtual shop." This allows the user's work to reach a wider audience and provide opportunities for viewing and purchasing.

[0537] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0538] Step 1:

[0539] Users use their smartphones to photograph their artwork and upload the image data to the system via an application. The device receives the image data through the user interface and uses the OpenCV library to adjust the size and improve the image quality. The input is the captured image data, and the output is the processed image data.

[0540] Step 2:

[0541] The server receives processed image data sent from the terminal. It then sends the received image data to an AI evaluation module, where it is analyzed using a generative AI model with TensorFlow. This analysis quantifies the aesthetic value, technical skill, and creativity of the artwork, generating an evaluation score. Processed image data is used as input, and the evaluation score is obtained as output.

[0542] Step 3:

[0543] The server classifies the artwork into a suitable theme based on the generated evaluation score. Based on the analysis results, it displays the user-uploaded digital content in the relevant virtual shop category. The input is the evaluation score, and the output is classification information.

[0544] Step 4:

[0545] The server generates promotional information and distributes it via social media and email. AI optimizes targeting to enhance the effectiveness of promotional campaigns. Inputs include classification information and market trends, and the output is promotional materials.

[0546] Step 5:

[0547] The server monitors visitor behavior to the virtual shop in real time. It collects visitor data using tools like Google Analytics and analyzes it to identify areas for improvement for future exhibitions. The input is visitor behavior data, and the output is an analysis report.

[0548] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0549] The system in this invention begins with a process of transmitting image data of a calligraphic work from a terminal to a server via a user interface. The terminal provides an interface for checking and optimizing the image quality and transferring it to the server. This process also includes a function to acquire the user's emotions as data.

[0550] The server stores the received image data and uses an AI model to evaluate and score the aesthetic value and technical achievement of the artwork. Furthermore, it can conduct a more multifaceted evaluation by taking into account user emotion data recognized by the emotion engine. For example, the program is designed to add points to the evaluation if the user has positive emotions towards the artwork.

[0551] Next, the server determines the exhibition theme based on the aforementioned evaluation results and sentiment data. This theme selection aligns with user interests and trends indicated by the sentiment data, resulting in an exhibition that is more relatable and engaging.

[0552] The selected works are incorporated into the virtual exhibition layout along with descriptive text based on sentiment analysis. The server takes into account user feedback analyzed by the sentiment engine and adjusts the descriptive text to include information that users are likely to emotionally respond to.

[0553] In promotional activities, the server uses emotional data obtained from an emotion engine to predict the audience's emotional response and appropriately adjust the content and timing of the promotion. For example, it might distribute information about an exhibition at a time when users have shown a very positive response in the past.

[0554] In this way, systems that utilize an emotion engine consider user emotions when evaluating and setting themes, providing a more fulfilling exhibition experience. For example, if a user expresses emotions such as "excitement" or "satisfaction" when uploading a work, the server will reflect those emotions in the theme setting and artwork selection, and that work will be presented in the exhibition alongside other works that resonate emotionally. This results in an exhibition that strengthens the emotional connection with the audience.

[0555] The following describes the processing flow.

[0556] Step 1:

[0557] The user uses a dedicated application to import an image of their calligraphy artwork into their device. At this stage, an emotion engine is activated via the camera and microphone to acquire emotion data from the user's facial expressions and voice.

[0558] Step 2:

[0559] The device packages the acquired image data along with the user's emotional data analyzed by the emotion engine, and prepares to send it to the server. At this time, it verifies that the image resolution and format are suitable for server processing.

[0560] Step 3:

[0561] The server inputs the received image data into an AI model, which then performs a technical and aesthetic evaluation of the artwork and assigns a score. In parallel, emotional data is also analyzed, and adjustments are made to ensure that the user's emotions are reflected in the artwork evaluation.

[0562] Step 4:

[0563] The server performs analysis to set appropriate themes based on scoring results and user sentiment data. Theme setting here is done by integrating the overall trends and sentiment data of the uploaded works.

[0564] Step 5:

[0565] Based on the set theme, the server selects artworks and incorporates them into the virtual exhibition. Selection criteria include the artwork's rating and the user's emotional resonance with it.

[0566] Step 6:

[0567] The server creates the layout of the virtual exhibition and generates descriptive text for each artwork. This text is customized based on sentiment data to evoke emotions in the user.

[0568] Step 7:

[0569] The server determines the exhibition's promotional strategy and distributes it to the target audience via social media and email. The content and timing of the promotion are optimized using sentiment data.

[0570] Step 8:

[0571] During the exhibition, the servers analyze visitor sentiment data in real time and adjust resources to maintain smooth access. This dynamic adjustment is made in response to visitors' emotions and behavior.

[0572] Step 9:

[0573] After the exhibition ends, the server collects and analyzes visitor sentiment and behavior data to generate insights that can be used to plan the next exhibition.

[0574] (Example 2)

[0575] Next, we will describe Example 2. 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."

[0576] In modern digital exhibitions, providing visitors with an engaging experience is challenging, requiring the selection of works and optimization of exhibition content based on individual user emotions. Furthermore, promotional activities must be tailored to appeal to the target audience's emotions, requiring careful timing and content adjustments. Additionally, there is a need for methods to utilize visitor behavior data to improve future exhibitions and promotions.

[0577] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0578] In this invention, the server includes means for verifying and optimizing the quality of visual data, means for acquiring user emotional information, evaluating and scoring the value of the artworks while taking this information into account, and means for setting appropriate themes and generating a selected collection of artworks using the evaluation results and emotional information. This makes it possible to set themes and select artworks based on user emotions, providing exhibition content that evokes empathy, and enabling effective promotion using emotional information.

[0579] A "user interface" is a means of providing users with screens and procedures for inputting data and performing operations on a system.

[0580] "Visual data" refers to digital data containing visual information, primarily images and video files.

[0581] "Quality check" is the process of verifying whether the resolution, brightness, color tone, and other aspects of visual data meet predetermined standards.

[0582] "Optimization" refers to the act of adjusting or modifying data so that it can be presented with higher quality.

[0583] "Emotional information" refers to data collected digitally about the emotions a user is experiencing, representing their intuitive reactions and emotional state in numerical and textual terms.

[0584] "Scoring" is the process of quantifying and ranking evaluation results, and is used as an indicator of evaluation based on specific criteria.

[0585] "Theme setting" is the act of determining the central concept or direction that will serve as the basis for a presentation or exhibition.

[0586] A "collection of works" is a group of works selected and organized based on their relatedness or commonalities.

[0587] A "digital exhibition" is an exhibition event held using an online environment, and is usually accessible through a website or application.

[0588] "Promotional information" refers to information used to announce or introduce events, products, or services, and is widely distributed for marketing purposes.

[0589] "Visitor information" refers to data about the behavior and reactions of people who participate in exhibitions and events, and is collected for analytical purposes.

[0590] "Computational resources" refer to the processing power and memory capacity of computers necessary to operate digital systems.

[0591] The system of this invention is a complex technical configuration including a user-owned terminal, a server, and an AI model. The user inputs digital visual data using a user interface on the terminal. The input image data is then quality-checked and optimized on the terminal. This process utilizes image processing software and specifically includes operations such as noise reduction and resolution correction.

[0592] Furthermore, users input emotional information when uploading their work. This emotional information is acquired through text input or selection and stored on the device as numerical or text data. The device then sends the optimized image data and emotional data to the server.

[0593] On the server, the transmitted data is first stored in a database. At this stage, a generative AI model is used to evaluate the images. The AI ​​model utilizes image recognition technology to calculate a score for the aesthetic value and technical achievement of the artwork.

[0594] The scoring results are integrated with user sentiment information, and the server uses this data to set appropriate themes. Theme setting is a crucial process that determines the direction of the exhibition, and a sentiment engine is used to design themes that resonate with users' emotions.

[0595] The selected works will be incorporated into the layout of the digital exhibition and accompanied by emotion-based explanatory information. This information will highlight the key aspects and emotional impact of each piece for the viewer.

[0596] The server also generates promotional information and distributes it through external networks at the optimal time. This promotional strategy is refined by analyzing past visit data and sentiment information.

[0597] For example, if a user inputs data expressing their emotion, such as "This artwork is wonderful!", this feeling of joy will be reflected in the theme setting and artwork selection. As a result, that artwork will be featured in the digital exhibition along with other works that evoke similar emotions.

[0598] An example of a prompt is: "Evaluate the aesthetic value and technical achievement of the calligraphy artwork submitted by the user, and take into account the user's emotional data to propose an exhibition theme."

[0599] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0600] Step 1:

[0601] Users input visual data using their devices. Specifically, users upload images of calligraphy artwork they have photographed to their devices. At the same time, they also input emotional information and supply this data to the system. The input data consists of image files (e.g., JPEG, PNG format) and emotional information in text format (e.g., "excited" or "satisfied").

[0602] Step 2:

[0603] The terminal checks the quality of the received image data and optimizes it as needed. Specifically, it performs noise reduction, resolution adjustment, and brightness and contrast correction. The input is an image file, and the output is an optimized image file. This ensures that the image is in its best condition before being sent to the server.

[0604] Step 3:

[0605] Optimized image data and sentiment information are sent from the terminal to the server. The server stores the image data in a database and appropriately records the sentiment information. The input is the image and sentiment information, and the output is the database record containing these.

[0606] Step 4:

[0607] The server processes the stored image data using a generating AI model to evaluate its aesthetic value and technical achievements. Specifically, the AI ​​model analyzes the images and calculates a score. The input for this step is image data, and the output is the evaluation score.

[0608] Step 5:

[0609] The server integrates evaluation scores from a generated AI model with user sentiment information to set the exhibition theme. The theme is set considering sentiment information, and works with high ratings and positive sentiment are selected. The input is evaluation scores and sentiment information, and the output is the exhibition theme and the selected works.

[0610] Step 6:

[0611] Based on the selected works, the server designs the layout of the digital exhibition and generates emotion-based explanatory information. It utilizes an emotion engine to ensure the explanations are easily understood by the user. The input is the selected works, and the output is the laid-out exhibition and explanatory information.

[0612] Step 7:

[0613] The server automatically generates promotional information based on sentiment data and distributes it via an external network. Specific actions include sending emails and posting on social media. Inputs are sentiment data and visitor data, while output is the distributed promotional information.

[0614] (Application Example 2)

[0615] Next, we will explain application example 2. In the following explanation, 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."

[0616] In modern virtual exhibitions, the content of exhibited works often fails to consider the individual emotions of users, and promotional activities are not effectively conducted. Therefore, there is a need to further improve visitor satisfaction. However, conventional technologies make it difficult to create exhibits that take user emotions into account or to deliver promotional information tailored to visitors' interests. Thus, the construction of a new system is necessary to solve these problems.

[0617] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0618] In this invention, the server includes means for receiving visual data acquired via a user terminal, means for analyzing emotional data, selecting an appropriate theme based on the analysis results, selecting works corresponding to the theme, and means for automatically generating promotional information and transmitting it using an external information network. This makes it possible to display works based on the user's emotions and to deliver effective promotional information tailored to the interests of visitors.

[0619] A "user terminal" is a device used by individual users to input or retrieve information, and includes smartphones, personal computers, and other similar devices.

[0620] "Visual data" refers to digital data that records visual information, such as images and videos.

[0621] "Emotional data" refers to a numerical or categorical representation of the emotional state a user exhibits in a specific situation.

[0622] "Analysis results" refer to conclusions and evaluations derived from data analysis.

[0623] "Subject" refers to the central theme or concept of the artworks displayed in a virtual exhibition.

[0624] "Means of selecting works" refers to the method and technical elements for selecting suitable works from those provided based on specific criteria.

[0625] "Promotional information" refers to information intended to notify or arouse interest in a specific subject, and includes advertisements and announcements.

[0626] An "external information network" refers to a communication network used for sending and receiving digital data, and includes the internet and local networks.

[0627] The system for implementing this invention mainly consists of a server and a user terminal. The user uses a user terminal such as a smartphone or personal computer to acquire visual data such as calligraphy works and transmit it to the server through the terminal's interface.

[0628] The terminal checks the quality of the visual data and performs image processing as needed. For this purpose, it utilizes image processing libraries such as OpenCV. The image data is sent to the server via a communication module, such as AWS Lambda. The server analyzes the received image data using an AI model based on TensorFlow, evaluates its aesthetic value, and quantifies it.

[0629] Meanwhile, users acquire emotional data using facial recognition technology. Using libraries such as EmotionAI, the user's emotions are quantified and sent to the server. The server takes this emotional data into consideration when selecting the theme for the exhibited works, and uses an AI model to select works that match the theme.

[0630] The server then creates the overall layout of the virtual exhibition based on the selected works. The interface used by visitors visually displays detailed information about the exhibited works, allowing users to intuitively understand the exhibition content.

[0631] Furthermore, the server is equipped with a means to transmit automatically generated promotional information using external information networks, according to the user's interests and emotions. This makes it possible to deliver promotional information at an effective time.

[0632] For example, when a user visits an exhibition, works themed around "serene mind" are displayed, and warm color schemes and background music are automatically selected accordingly. Furthermore, it is possible to engage in conversations using generative AI models, such as prompts like, "Please upload your work and have its aesthetic value evaluated," or "Let's customize the exhibition based on a theme that resonates with your emotions."

[0633] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0634] Step 1:

[0635] The user takes a picture of a calligraphy artwork with their device. The device uses OpenCV to check the image quality and adjust the brightness and contrast. The input is the captured image data, and the output is the adjusted image data.

[0636] Step 2:

[0637] The adjusted image data is sent from the device to the server via AWS Lambda. The server receives this image data and analyzes it using a generative AI model based on TensorFlow. The input is the adjusted image data, and the output is an evaluation score representing its aesthetic value.

[0638] Step 3:

[0639] The user uses their device's camera for facial recognition and the EmotionAI library to acquire emotion data in real time. The input is an image of the user's face, and the output is numerical emotion data.

[0640] Step 4:

[0641] The server combines the acquired evaluation scores and user sentiment data to select a theme for the exhibition and then selects artworks that match that theme. The inputs are evaluation scores and sentiment data, and the output is a list of the selected theme and artworks.

[0642] Step 5:

[0643] The server constructs a virtual exhibition on the platform based on the selected works. This includes generating an interface using Unity. The input is a list of works, and the output is the completed virtual exhibition layout.

[0644] Step 6:

[0645] When users visit an exhibition, they can obtain detailed information about the exhibits through prompts displayed on the interface. The server sends prompts based on a generated AI model. The input is visitor preference data, and the output is customized presentation information.

[0646] Step 7:

[0647] The server generates and sends promotional information at the appropriate time based on the user's emotions and interest in the exhibit. This also takes into account the user's past visit history and response data. The input is past visitor data, and the output is optimized promotional information.

[0648] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0649] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0650] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0651] [Fourth Embodiment]

[0652] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0653] As shown in Figure 7, the 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.

[0654] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0655] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0656] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0657] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0658] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0659] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive 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 robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0660] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0661] The specific processing program 56 is an example of a "program" relating to the technology of this 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.

[0662] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0663] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0664] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0665] The system in this invention begins with a process of uploading artistic works, such as calligraphy, online via a user's terminal. The terminal receives the artwork image through a user interface, performs pre-processing as needed, and then sends it to the server. Pre-processing here refers to adjusting the image size and correcting the image quality.

[0666] The server analyzes the received image data and uses a pre-trained AI model to evaluate and score the artwork. Evaluation criteria include aesthetic value, technical skill, and creativity, each of which may vary depending on industry standards and user customization. These evaluation results are stored in a database for further analysis.

[0667] Next, the server has a theme setting function, determining the exhibition theme based on accumulated evaluation data and external market trends. Based on this decision, the server selects the works that best fit the theme and designs the structure of the virtual exhibition.

[0668] The selected works are arranged in an optimized layout within the digital gallery, and each piece is accompanied by automatically generated descriptive text from the server. This allows viewers to deepen their understanding of the works and enhances the overall viewing experience.

[0669] Furthermore, the server generates information for promoting the exhibition and implements effective marketing through social media platforms and email. At this stage, the targeting of the promotion is also optimized by AI.

[0670] Once an exhibition is open, the server monitors visitor activity in real time and adjusts system resources as needed. Visitor data is collected and analyzed to improve future exhibitions. This entire process provides a platform for artists and enthusiasts to present their work to a wide audience and exchange feedback. For example, if a user uploads a calligraphy piece with a nature theme, the server analyzes it and selects it as part of a nature-related exhibition, potentially leading to the user's work being featured in an international virtual exhibition.

[0671] The following describes the processing flow.

[0672] Step 1:

[0673] The user takes their calligraphy artwork as an image to their device and prepares to upload it to the server using a dedicated application.

[0674] Step 2:

[0675] The device checks the image format and size, and if necessary, performs image optimization (e.g., resizing, adjusting resolution) before sending it to the server.

[0676] Step 3:

[0677] The server saves the received image data to a database and also inputs the image into an AI model to calculate an evaluation score for the artwork. This score is recorded in the database.

[0678] Step 4:

[0679] The server executes an algorithm that determines the theme for the exhibition based on past evaluation data and external data. This automatically sets the theme for the next exhibition.

[0680] Step 5:

[0681] The server selects the most relevant works based on the set theme, ranking them in order of highest rating, to form the exhibition collection.

[0682] Step 6:

[0683] The server generates a virtual exhibition layout based on the selected works and automatically creates a description for each work. This description includes background information and evaluation points for each work.

[0684] Step 7:

[0685] The server generates promotional information for the exhibition and begins distributing advertisements through platforms such as social media and email. At this time, it identifies the target audience for the promotion.

[0686] Step 8:

[0687] During the exhibition's public access period, the servers track visitor behavior in real time and adjust server resource allocation as needed to maintain smooth access.

[0688] Step 9:

[0689] The server collects and analyzes visitor behavior data after the exhibition ends. This includes data such as page views, time spent on the site, and identification of the most popular works.

[0690] Step 10:

[0691] The server generates insights from the analysis results that will help improve the next exhibition, and feeds them back into the system's operation.

[0692] (Example 1)

[0693] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0694] In evaluating and exhibiting cultural works on online platforms, the objectivity of evaluation criteria and the optimization of exhibitions are key challenges. Furthermore, appropriate promotion and analysis of visitor behavior are necessary to improve future exhibitions. These challenges can sometimes limit the user experience and the diversity of the works.

[0695] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0696] In this invention, the server includes means for receiving digital data via a user interface, means for evaluating and quantifying cultural works based on the digital data, and means for determining a theme based on the collected evaluation information and market trend information, and selecting works corresponding to that theme. This enables the selection of works based on objective evaluation criteria and diverse exhibitions.

[0697] A "user interface" is a means by which a user inputs and manipulates data and information.

[0698] "Digital data" refers to information in a format that is processed electronically and is primarily usable by computer systems.

[0699] A "cultural work" is an expression that possesses artistic or creative value, and includes a variety of forms such as visual arts and literature.

[0700] "Evaluation" is the process of analyzing and measuring the value and quality of an object based on specific criteria.

[0701] "Quantification" is a conversion process that expresses evaluation results as numerical values, making comparison and analysis easier.

[0702] "Collected evaluation information" refers to the collective term for evaluation results and related data collected according to various criteria.

[0703] "Market trend information" refers to data that shows current or future trends in a specific industry or field.

[0704] The "subject" is the central theme or topic of the exhibition or discussion.

[0705] "Means of selection" refers to the process of determining the appropriate option according to specific criteria or objectives.

[0706] This invention is a system that optimizes the evaluation and exhibition of cultural works via digital data, and consists of three main components: a terminal, a server, and a user. The user uploads cultural works as digital data using their terminal. The terminal performs data resizing and image quality correction using pre-specified format conversion and image processing software (e.g., image editing software).

[0707] The server uses this received digital data to evaluate the artwork using a generative AI model. The evaluation criteria include aesthetic value, technical skill, and creativity, each of which is recorded as numerical data. The evaluated data is stored in a database on the server and used for necessary analysis.

[0708] Furthermore, the server uses the collected evaluation information to perform comparative analysis with external market trend data and determine an appropriate exhibition theme. This process utilizes prompts such as: "Consider the latest trend information and suggest an exhibition theme that best suits the artwork."

[0709] The server automatically selects the most suitable cultural works based on the chosen theme and designs the structure of the virtual exhibition. Detailed explanatory information about the selected works is generated by a generative AI and provided to deepen the audience's understanding. The server also handles the promotion strategy, effectively distributing information using social media platforms and email networks. Here again, the prompt "Please propose an effective promotion strategy for a specific audience" is used.

[0710] Finally, the server monitors visitor activity in real time during the public exhibition. This allows for analysis of visitor interests and behavioral patterns, providing valuable insights to inform future exhibition planning. This entire process enables users to present their work to a broad audience and engage in discussions about it.

[0711] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0712] Step 1:

[0713] Users select and upload digital data of cultural works using their own devices. The input data is image files, which the device accepts. Specifically, the user performs file selection operations on the user interface. The device checks the image size and format, and if the format is inappropriate, it converts it to a standard format such as JPEG or PNG. As output, the image data converted to the appropriate format is sent to the server.

[0714] Step 2:

[0715] The server receives and stores image data sent from the terminal. The input data is mainly image files. Image processing software is used within the server to prepare the images for analysis. Specifically, the images are processed into a format that can be input into the AI ​​model. The output of this process is image data that has been formatted for processing by the AI ​​model.

[0716] Step 3:

[0717] The server passes image data to the AI ​​model and initiates the evaluation process. The input is pre-processed image data. The AI ​​model evaluates the aesthetic value, technical skill, and creativity of the image and quantifies them. The output of this data calculation is a numerical score for each evaluation criterion. The scores are recorded in a database and, if necessary, presented to the user as feedback.

[0718] Step 4:

[0719] The server determines the optimal exhibition theme using recorded evaluation scores and market trend information obtained from external sources. The input data consists of evaluation scores and market trend information. An AI model is used to perform analysis based on the prompt message, "Consider the latest trend information and suggest the most suitable exhibition theme for the artwork." The output is the selected exhibition theme, which is then used within the system for the next steps.

[0720] Step 5:

[0721] The server selects the most suitable cultural works for the exhibition based on the chosen theme and designs the layout of the virtual exhibition. The inputs are theme selection data and artwork evaluation scores. With the help of AI, it optimizes how to arrange the artworks on the screen. As output, data of the completed exhibition layout and explanatory information accompanying each artwork are generated and placed in the digital gallery.

[0722] Step 6:

[0723] The server plans the promotion of a virtual exhibition and generates information to appeal to a specific audience. The inputs are exhibition information and target audience data. The prompt "Propose an effective promotional strategy for a specific audience" is used to analyze the AI ​​model. The output is a specific promotional strategy and marketing message, which is distributed via social media and email.

[0724] Step 7:

[0725] The server monitors visitor behavior in real time during the exhibition. The input is visitor access data. The server analyzes behavioral data such as access patterns and dwell time, and dynamically adjusts system resources. This analysis generates a report on visitor behavior, which is used to improve future exhibitions.

[0726] (Application Example 1)

[0727] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0728] Contemporary artists and designers often lack effective channels for raising awareness of their work, and opportunities to participate in physical exhibitions are particularly limited. Furthermore, the evaluation and promotion of artworks are often manual processes, requiring considerable time and effort. Therefore, there is a need for a system that efficiently evaluates and promotes artworks online, and allows for broad public access through virtual exhibitions.

[0729] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0730] In this invention, the server includes means for receiving image data input via a user interface, means for evaluating and scoring works of art based on the image data, and means for displaying digital content photographed and uploaded by users in a virtual shop. This enables the efficient evaluation of works by artists and designers, their display in a themed virtual shop, and promotes widespread recognition.

[0731] A "user interface" is a visual or physical interface through which a user accesses a system and inputs or retrieves data.

[0732] "Image data" refers to visual information that has been captured or scanned and is represented in a digital format.

[0733] A "work of art" is an object created through creative activity that is visual or combines visual and other senses.

[0734] "Evaluation" is the act of measuring the value or performance of an object or process based on specific criteria.

[0735] "Scoring" is the process of expressing the evaluated results as a quantitative value.

[0736] A "theme" is a central concept or topic that unifies various elements within an exhibition or project.

[0737] A "virtual exhibition" is an event or platform that displays works of art online via the internet.

[0738] "Promotional information" refers to media content created to inform the public about a specific product or service and to convey its appeal.

[0739] An "external network" refers to external computer systems or data communication networks connected via the Internet.

[0740] "Visitor data" refers to information about the behavior and attributes of users who use the system.

[0741] "Real-time" refers to an environment where data or information can be processed and provided almost instantaneously.

[0742] In this embodiment of the invention, the system begins with the digitization and uploading of artwork by the user. The user uses a device such as a smartphone to photograph their artwork and upload the image data to the system. At this time, the device provides a user interface to allow the user to operate it easily. The device is also equipped with an image processing module that adjusts the image size and corrects the image quality, and pre-processing is performed using libraries such as OpenCV.

[0743] The server analyzes the received image data through an AI evaluation module. This uses a pre-trained generative AI model with machine learning frameworks such as TensorFlow. This model evaluates the aesthetic value, technical skill, and creativity of the artwork and performs scoring. Based on the evaluated information, the server performs analysis and displays the digital content photographed and uploaded by the user in a virtual shop with an appropriate theme.

[0744] Furthermore, the server generates promotional information and distributes it to external networks via social media and email. Targeting is optimized by AI, and the Python Twython library may be used for social media integration.

[0745] Visitor movements are monitored in real time, and visitor data is collected and analyzed. This allows the system to be used to improve future exhibitions and displays.

[0746] For example, if a user uploads a work with a nature theme, the server can analyze the work and display it in a virtual shop categorized as "Natural Beauty." An example prompt message: "Analyze the theme of the artwork and display it in the relevant virtual shop." This allows the user's work to reach a wider audience and provide opportunities for viewing and purchasing.

[0747] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0748] Step 1:

[0749] Users use their smartphones to photograph their artwork and upload the image data to the system via an application. The device receives the image data through the user interface and uses the OpenCV library to adjust the size and improve the image quality. The input is the captured image data, and the output is the processed image data.

[0750] Step 2:

[0751] The server receives processed image data sent from the terminal. It then sends the received image data to an AI evaluation module, where it is analyzed using a generative AI model with TensorFlow. This analysis quantifies the aesthetic value, technical skill, and creativity of the artwork, generating an evaluation score. Processed image data is used as input, and the evaluation score is obtained as output.

[0752] Step 3:

[0753] The server classifies the artwork into a suitable theme based on the generated evaluation score. Based on the analysis results, it displays the user-uploaded digital content in the relevant virtual shop category. The input is the evaluation score, and the output is classification information.

[0754] Step 4:

[0755] The server generates promotional information and distributes it via social media and email. AI optimizes targeting to enhance the effectiveness of promotional campaigns. Inputs include classification information and market trends, and the output is promotional materials.

[0756] Step 5:

[0757] The server monitors visitor behavior to the virtual shop in real time. It collects visitor data using tools like Google Analytics and analyzes it to identify areas for improvement for future exhibitions. The input is visitor behavior data, and the output is an analysis report.

[0758] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0759] The system in this invention begins with a process of transmitting image data of a calligraphic work from a terminal to a server via a user interface. The terminal provides an interface for checking and optimizing the image quality and transferring it to the server. This process also includes a function to acquire the user's emotions as data.

[0760] The server stores the received image data and uses an AI model to evaluate and score the aesthetic value and technical achievement of the artwork. Furthermore, it can conduct a more multifaceted evaluation by taking into account user emotion data recognized by the emotion engine. For example, the program is designed to add points to the evaluation if the user has positive emotions towards the artwork.

[0761] Next, the server determines the exhibition theme based on the aforementioned evaluation results and sentiment data. This theme selection aligns with user interests and trends indicated by the sentiment data, resulting in an exhibition that is more relatable and engaging.

[0762] The selected works are incorporated into the virtual exhibition layout along with descriptive text based on sentiment analysis. The server takes into account user feedback analyzed by the sentiment engine and adjusts the descriptive text to include information that users are likely to emotionally respond to.

[0763] In promotional activities, the server uses emotional data obtained from an emotion engine to predict the audience's emotional response and appropriately adjust the content and timing of the promotion. For example, it might distribute information about an exhibition at a time when users have shown a very positive response in the past.

[0764] In this way, systems that utilize an emotion engine consider user emotions when evaluating and setting themes, providing a more fulfilling exhibition experience. For example, if a user expresses emotions such as "excitement" or "satisfaction" when uploading a work, the server will reflect those emotions in the theme setting and artwork selection, and that work will be presented in the exhibition alongside other works that resonate emotionally. This results in an exhibition that strengthens the emotional connection with the audience.

[0765] The following describes the processing flow.

[0766] Step 1:

[0767] The user uses a dedicated application to import an image of their calligraphy artwork into their device. At this stage, an emotion engine is activated via the camera and microphone to acquire emotion data from the user's facial expressions and voice.

[0768] Step 2:

[0769] The device packages the acquired image data along with the user's emotional data analyzed by the emotion engine, and prepares to send it to the server. At this time, it verifies that the image resolution and format are suitable for server processing.

[0770] Step 3:

[0771] The server inputs the received image data into an AI model, which then performs a technical and aesthetic evaluation of the artwork and assigns a score. In parallel, emotional data is also analyzed, and adjustments are made to ensure that the user's emotions are reflected in the artwork evaluation.

[0772] Step 4:

[0773] The server performs analysis to set appropriate themes based on scoring results and user sentiment data. Theme setting here is done by integrating the overall trends and sentiment data of the uploaded works.

[0774] Step 5:

[0775] Based on the set theme, the server selects artworks and incorporates them into the virtual exhibition. Selection criteria include the artwork's rating and the user's emotional resonance with it.

[0776] Step 6:

[0777] The server creates the layout of the virtual exhibition and generates descriptive text for each artwork. This text is customized based on sentiment data to evoke emotions in the user.

[0778] Step 7:

[0779] The server determines the exhibition's promotional strategy and distributes it to the target audience via social media and email. The content and timing of the promotion are optimized using sentiment data.

[0780] Step 8:

[0781] During the exhibition, the servers analyze visitor sentiment data in real time and adjust resources to maintain smooth access. This dynamic adjustment is made in response to visitors' emotions and behavior.

[0782] Step 9:

[0783] After the exhibition ends, the server collects and analyzes visitor sentiment and behavior data to generate insights that can be used to plan the next exhibition.

[0784] (Example 2)

[0785] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0786] In modern digital exhibitions, providing visitors with an engaging experience is challenging, requiring the selection of works and optimization of exhibition content based on individual user emotions. Furthermore, promotional activities must be tailored to appeal to the target audience's emotions, requiring careful timing and content adjustments. Additionally, there is a need for methods to utilize visitor behavior data to improve future exhibitions and promotions.

[0787] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0788] In this invention, the server includes means for verifying and optimizing the quality of visual data, means for acquiring user emotional information, evaluating and scoring the value of the artworks while taking this information into account, and means for setting appropriate themes and generating a selected collection of artworks using the evaluation results and emotional information. This makes it possible to set themes and select artworks based on user emotions, providing exhibition content that evokes empathy, and enabling effective promotion using emotional information.

[0789] A "user interface" is a means of providing users with screens and procedures for inputting data and performing operations on a system.

[0790] "Visual data" refers to digital data containing visual information, primarily images and video files.

[0791] "Quality check" is the process of verifying whether the resolution, brightness, color tone, and other aspects of visual data meet predetermined standards.

[0792] "Optimization" refers to the act of adjusting or modifying data so that it can be presented with higher quality.

[0793] "Emotional information" refers to data collected digitally about the emotions a user is experiencing, representing their intuitive reactions and emotional state in numerical and textual terms.

[0794] "Scoring" is the process of quantifying and ranking evaluation results, and is used as an indicator of evaluation based on specific criteria.

[0795] "Theme setting" is the act of determining the central concept or direction that will serve as the basis for a presentation or exhibition.

[0796] A "collection of works" is a group of works selected and organized based on their relatedness or commonalities.

[0797] A "digital exhibition" is an exhibition event held using an online environment, and is usually accessible through a website or application.

[0798] "Promotional information" refers to information used to announce or introduce events, products, or services, and is widely distributed for marketing purposes.

[0799] "Visitor information" refers to data about the behavior and reactions of people who participate in exhibitions and events, and is collected for analytical purposes.

[0800] "Computational resources" refer to the processing power and memory capacity of computers necessary to operate digital systems.

[0801] The system of this invention is a complex technical configuration including a user-owned terminal, a server, and an AI model. The user inputs digital visual data using a user interface on the terminal. The input image data is then quality-checked and optimized on the terminal. This process utilizes image processing software and specifically includes operations such as noise reduction and resolution correction.

[0802] Furthermore, users input emotional information when uploading their work. This emotional information is acquired through text input or selection and stored on the device as numerical or text data. The device then sends the optimized image data and emotional data to the server.

[0803] On the server, the transmitted data is first stored in a database. At this stage, a generative AI model is used to evaluate the images. The AI ​​model utilizes image recognition technology to calculate a score for the aesthetic value and technical achievement of the artwork.

[0804] The scoring results are integrated with user sentiment information, and the server uses this data to set appropriate themes. Theme setting is a crucial process that determines the direction of the exhibition, and a sentiment engine is used to design themes that resonate with users' emotions.

[0805] The selected works will be incorporated into the layout of the digital exhibition and accompanied by emotion-based explanatory information. This information will highlight the key aspects and emotional impact of each piece for the viewer.

[0806] The server also generates promotional information and distributes it through external networks at the optimal time. This promotional strategy is refined by analyzing past visit data and sentiment information.

[0807] For example, if a user inputs data expressing their emotion, such as "This artwork is wonderful!", this feeling of joy will be reflected in the theme setting and artwork selection. As a result, that artwork will be featured in the digital exhibition along with other works that evoke similar emotions.

[0808] An example of a prompt is: "Evaluate the aesthetic value and technical achievement of the calligraphy artwork submitted by the user, and take into account the user's emotional data to propose an exhibition theme."

[0809] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0810] Step 1:

[0811] Users input visual data using their devices. Specifically, users upload images of calligraphy artwork they have photographed to their devices. At the same time, they also input emotional information and supply this data to the system. The input data consists of image files (e.g., JPEG, PNG format) and emotional information in text format (e.g., "excited" or "satisfied").

[0812] Step 2:

[0813] The terminal checks the quality of the received image data and optimizes it as needed. Specifically, it performs noise reduction, resolution adjustment, and brightness and contrast correction. The input is an image file, and the output is an optimized image file. This ensures that the image is in its best condition before being sent to the server.

[0814] Step 3:

[0815] Optimized image data and sentiment information are sent from the terminal to the server. The server stores the image data in a database and appropriately records the sentiment information. The input is the image and sentiment information, and the output is the database record containing these.

[0816] Step 4:

[0817] The server processes the stored image data using a generating AI model to evaluate its aesthetic value and technical achievements. Specifically, the AI ​​model analyzes the images and calculates a score. The input for this step is image data, and the output is the evaluation score.

[0818] Step 5:

[0819] The server integrates evaluation scores from a generated AI model with user sentiment information to set the exhibition theme. The theme is set considering sentiment information, and works with high ratings and positive sentiment are selected. The input is evaluation scores and sentiment information, and the output is the exhibition theme and the selected works.

[0820] Step 6:

[0821] Based on the selected works, the server designs the layout of the digital exhibition and generates emotion-based explanatory information. It utilizes an emotion engine to ensure the explanations are easily understood by the user. The input is the selected works, and the output is the laid-out exhibition and explanatory information.

[0822] Step 7:

[0823] The server automatically generates promotional information based on sentiment data and distributes it via an external network. Specific actions include sending emails and posting on social media. Inputs are sentiment data and visitor data, while output is the distributed promotional information.

[0824] (Application Example 2)

[0825] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0826] In modern virtual exhibitions, the content of exhibited works often fails to consider the individual emotions of users, and promotional activities are not effectively conducted. Therefore, there is a need to further improve visitor satisfaction. However, conventional technologies make it difficult to create exhibits that take user emotions into account or to deliver promotional information tailored to visitors' interests. Thus, the construction of a new system is necessary to solve these problems.

[0827] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0828] In this invention, the server includes means for receiving visual data acquired via a user terminal, means for analyzing emotional data, selecting an appropriate theme based on the analysis results, selecting works corresponding to the theme, and means for automatically generating promotional information and transmitting it using an external information network. This makes it possible to display works based on the user's emotions and to deliver effective promotional information tailored to the interests of visitors.

[0829] A "user terminal" is a device used by individual users to input or retrieve information, and includes smartphones, personal computers, and other similar devices.

[0830] "Visual data" refers to digital data that records visual information, such as images and videos.

[0831] "Emotional data" refers to a numerical or categorical representation of the emotional state a user exhibits in a specific situation.

[0832] "Analysis results" refer to conclusions and evaluations derived from data analysis.

[0833] "Subject" refers to the central theme or concept of the artworks displayed in a virtual exhibition.

[0834] "Means of selecting works" refers to the method and technical elements for selecting suitable works from those provided based on specific criteria.

[0835] "Promotional information" refers to information intended to notify or arouse interest in a specific subject, and includes advertisements and announcements.

[0836] An "external information network" refers to a communication network used for sending and receiving digital data, and includes the internet and local networks.

[0837] The system for implementing this invention mainly consists of a server and a user terminal. The user uses a user terminal such as a smartphone or personal computer to acquire visual data such as calligraphy works and transmit it to the server through the terminal's interface.

[0838] The terminal checks the quality of the visual data and performs image processing as needed. For this purpose, it utilizes image processing libraries such as OpenCV. The image data is sent to the server via a communication module, such as AWS Lambda. The server analyzes the received image data using an AI model based on TensorFlow, evaluates its aesthetic value, and quantifies it.

[0839] Meanwhile, users acquire emotional data using facial recognition technology. Using libraries such as EmotionAI, the user's emotions are quantified and sent to the server. The server takes this emotional data into consideration when selecting the theme for the exhibited works, and uses an AI model to select works that match the theme.

[0840] The server then creates the overall layout of the virtual exhibition based on the selected works. The interface used by visitors visually displays detailed information about the exhibited works, allowing users to intuitively understand the exhibition content.

[0841] Furthermore, the server is equipped with a means to transmit automatically generated promotional information using external information networks, according to the user's interests and emotions. This makes it possible to deliver promotional information at an effective time.

[0842] For example, when a user visits an exhibition, works themed around "serene mind" are displayed, and warm color schemes and background music are automatically selected accordingly. Furthermore, it is possible to engage in conversations using generative AI models, such as prompts like, "Please upload your work and have its aesthetic value evaluated," or "Let's customize the exhibition based on a theme that resonates with your emotions."

[0843] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0844] Step 1:

[0845] The user takes a picture of a calligraphy artwork with their device. The device uses OpenCV to check the image quality and adjust the brightness and contrast. The input is the captured image data, and the output is the adjusted image data.

[0846] Step 2:

[0847] The adjusted image data is sent from the device to the server via AWS Lambda. The server receives this image data and analyzes it using a generative AI model based on TensorFlow. The input is the adjusted image data, and the output is an evaluation score representing its aesthetic value.

[0848] Step 3:

[0849] The user uses their device's camera for facial recognition and the EmotionAI library to acquire emotion data in real time. The input is an image of the user's face, and the output is numerical emotion data.

[0850] Step 4:

[0851] The server combines the acquired evaluation scores and user sentiment data to select a theme for the exhibition and then selects artworks that match that theme. The inputs are evaluation scores and sentiment data, and the output is a list of the selected theme and artworks.

[0852] Step 5:

[0853] The server constructs a virtual exhibition on the platform based on the selected works. This includes generating an interface using Unity. The input is a list of works, and the output is the completed virtual exhibition layout.

[0854] Step 6:

[0855] When users visit an exhibition, they can obtain detailed information about the exhibits through prompts displayed on the interface. The server sends prompts based on a generated AI model. The input is visitor preference data, and the output is customized presentation information.

[0856] Step 7:

[0857] The server generates and sends promotional information at the appropriate time based on the user's emotions and interest in the exhibit. This also takes into account the user's past visit history and response data. The input is past visitor data, and the output is optimized promotional information.

[0858] 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 controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0859] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0860] 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 this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0861] Furthermore, the emotion identification model 59, acting 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 a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0862] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0863] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0864] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0865] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0866] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is 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 the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0867] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0868] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0869] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0870] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0871] 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.

[0872] Furthermore, it is not necessary to store the entirety 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 the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0873] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0874] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of 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). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0875] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0876] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0877] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0878] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0879] The following is further disclosed regarding the embodiments described above.

[0880] (Claim 1)

[0881] A means for receiving image data input via a user interface,

[0882] A means for evaluating and scoring a work of art based on the aforementioned image data,

[0883] A means of setting an appropriate theme based on analysis and selecting works that fit that theme,

[0884] A method for generating a virtual exhibition layout based on selected works,

[0885] A method for automatically generating promotional information and distributing it via an external network,

[0886] Means for collecting and analyzing visitor data,

[0887] A system that includes this.

[0888] (Claim 2)

[0889] The system according to claim 1, further comprising means for generating and displaying explanatory information related to the artworks after the exhibition layout has been generated.

[0890] (Claim 3)

[0891] The system according to claim 1, further comprising means for adjusting the necessary resources in order to maintain real-time accessibility for visitors.

[0892] "Example 1"

[0893] (Claim 1)

[0894] A means of receiving digital data via a user interface,

[0895] A means for evaluating and quantifying cultural works based on the aforementioned digital data,

[0896] A means for determining a theme based on collected evaluation information and market trend information, and for selecting works that correspond to that theme,

[0897] A means of generating a virtual exhibition array based on selected works,

[0898] A method for automatically generating advertising information and distributing it via a communication network,

[0899] A means for aggregating and analyzing visitor information,

[0900] A system that includes this.

[0901] (Claim 2)

[0902] The system according to claim 1, further comprising means for generating and displaying explanatory information related to the artwork after generating the display arrangement.

[0903] (Claim 3)

[0904] The system according to claim 1, further comprising means for adjusting the necessary resources in order to maintain a continuously connectable state for visitors.

[0905] "Application Example 1"

[0906] (Claim 1)

[0907] A means for receiving image data input via a user interface,

[0908] A means for evaluating and scoring a work of art based on the aforementioned image data,

[0909] A means of setting an appropriate theme based on analysis and selecting works that fit that theme,

[0910] A method for generating a virtual exhibition layout based on selected works,

[0911] A means of displaying digital content that users have photographed and uploaded in a virtual shop,

[0912] A method for automatically generating promotional information and distributing it via an external network,

[0913] Means for collecting and analyzing visitor data,

[0914] A system that includes this.

[0915] (Claim 2)

[0916] The system according to claim 1, further comprising means for generating and displaying explanatory information related to the artworks after the exhibition layout has been generated.

[0917] (Claim 3)

[0918] The system according to claim 1, further comprising means for adjusting the necessary resources in order to maintain real-time accessibility for visitors.

[0919] "Example 2 of combining an emotion engine"

[0920] (Claim 1)

[0921] A means for receiving visual data input via a user interface,

[0922] Means for checking and optimizing the quality of the aforementioned visual data,

[0923] A method for acquiring user sentiment information, taking it into consideration, and evaluating and scoring the value of a work,

[0924] A means for setting an appropriate theme using the evaluated results and emotional information, and for generating a selected collection of works,

[0925] A method for constructing the layout of a digital exhibition based on the generated collection of works,

[0926] A means of generating promotional information based on received emotional information and distributing it via an external communication network,

[0927] A means of collecting and analyzing visitor information and reflecting it in future exhibitions and promotions,

[0928] A system that includes this.

[0929] (Claim 2)

[0930] The system according to claim 1, further comprising means for generating and displaying explanatory information based on sentiment analysis results after constructing an exhibition layout.

[0931] (Claim 3)

[0932] The system according to claim 1, further comprising means for adjusting the necessary computing resources to maintain a state in which visitors can access the digital exhibition in real time.

[0933] "Application example 2 when combining with an emotional engine"

[0934] (Claim 1)

[0935] A means for receiving visual data acquired via a user terminal,

[0936] A means for evaluating and quantifying artistic value based on the aforementioned visual data,

[0937] A means of analyzing emotional data, selecting an appropriate theme based on the analysis results, and selecting works corresponding to that theme,

[0938] A means of arranging the virtual exhibition based on selected works,

[0939] A means of automatically generating promotional information and transmitting it using an external information network,

[0940] Means for acquiring and analyzing visitor information,

[0941] A system that includes this.

[0942] (Claim 2)

[0943] The system according to claim 1, further comprising means for generating and visually presenting detailed information related to the artworks after the exhibition layout has been formed.

[0944] (Claim 3)

[0945] The system according to claim 1, further comprising means for adjusting the necessary computing resources in order to maintain an immediately accessible state for visitors. [Explanation of symbols]

[0946] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A means for receiving image data input via a user interface, A means for evaluating and scoring a work of art based on the aforementioned image data, A means of setting an appropriate theme based on analysis and selecting works that fit that theme, A method for generating a virtual exhibition layout based on selected works, A means of displaying digital content that users have photographed and uploaded in a virtual shop, A method for automatically generating promotional information and distributing it via an external network, Means for collecting and analyzing visitor data, A system that includes this.

2. The system according to claim 1, further comprising means for generating and displaying explanatory information related to the artwork after the exhibition layout has been generated.

3. The system according to claim 1, further comprising means for adjusting the necessary resources in order to maintain real-time accessibility for visitors.

Images