System

Abstract

An object of a system according to an embodiment is to immediately generate and provide a universe having characteristics desired by a user.SOLUTION: A system includes a reception unit, an analysis unit, a generation unit, and a provision unit. The reception unit inputs a feature of a universe desired by a user. The analysis unit analyzes the feature received by the reception unit. The generation unit generates a digital universe on the basis of the feature analyzed by the analysis unit. The provision unit provides the user with the digital universe generated by the generation unit.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] With conventional technology, it is difficult to instantly generate and provide a universe with the characteristics desired by the user, and there is room for improvement.

[0005] The system according to the embodiment aims to instantly generate and provide a universe with the characteristics desired by the user. [Means for solving the problem]

[0006] The system according to the embodiment includes a reception unit, an analysis unit, a generation unit, and a provision unit. The reception unit inputs the characteristics of the universe desired by the user. The analysis unit analyzes the characteristics received by the reception unit. The generation unit generates a digital universe based on the characteristics analyzed by the analysis unit. The provision unit provides the digital universe generated by the generation unit to the user. [Effects of the Invention]

[0007] The system according to the embodiment can instantly generate and provide a universe with the characteristics desired by the user. [Brief explanation of the drawings]

[0008] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. DETAILED DESCRIPTION OF THE INVENTION

[0009] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0010] First, the terms used in the following description will be explained.

[0011] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, the processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), or a TPU (Tensor Processing Unit).

[0012] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0013] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0014] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), and Bluetooth (registered trademark).

[0015] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0016] [First embodiment] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0017] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0018] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0019] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0020] The reception device 38 includes a touch panel 38A and a microphone 38B, and receives user input. The touch panel 38A detects contact with a pointer (for example, a pen or a finger) to receive user input by the touch of the pointer. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 (see FIG. 2) acquires the data indicating the user input.

[0021] Output device 40 includes a display 40A and a speaker 40B, and presents data to a user by outputting the data in a form of expression that the user can perceive (e.g., audio and / or text). Display 40A displays visible information such as text and images in accordance with instructions from processor 46. Speaker 40B outputs audio in accordance with instructions from processor 46. Camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0022] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0023] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0024] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0025] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0026] In the smart device 14, the specific processing is performed by the processor 46. The storage 50 stores a specific processing program 60. The specific processing program 60 is used together with the specific processing program 56 by the data processing system 10. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. Note that the smart device 14 has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can also perform processing similar to that of the specific processing unit 290 using these models.

[0027] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device (e.g., a generation server) may have the data generation model 58. In this case, the data processing device 12 obtains a processing result (prediction result, etc.) using the data generation model 58 by communicating with the server device having the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device owned by a user (e.g., a mobile phone, a robot, a home appliance, etc.). Next, an example of processing by the data processing system 10 according to the first embodiment will be described.

[0028] (Example 1) A system according to an embodiment of the present invention utilizes a generation AI to instantly create a universe desired by a user. This system allows users to input the characteristics of the desired universe, and the generation AI analyzes those characteristics to generate a digital universe for a realistic planetarium experience. For example, users can specify detailed features such as the arrangement of stars, the type of planets, and the shape of galaxies. The generation AI digitally recreates a realistic universe based on astronomical data, meeting the user's needs. This generated digital universe is then provided to the user through a planetarium or VR device. This system is ideal for astronomy education and creating a relaxing space, and is intended for space enthusiasts and event planners. The system allows users to instantly create the universe they desire and enjoy a realistic planetarium experience. For example, when learning astronomy in a school class, students can use the generated universe to visually learn about the arrangement of stars and the movement of planets. Furthermore, the generated universe can be used to create a relaxing atmosphere for relaxation. This allows users to enjoy a realistic planetarium experience.

[0029] A universe generation system according to an embodiment includes a reception unit, an analysis unit, a generation unit, and a provision unit. The reception unit inputs the characteristics of the universe desired by the user. The characteristics of the universe desired by the user include, but are not limited to, the arrangement of stars, the type of planets, and the shape of the galaxy. For example, the reception unit provides an interface for the user to specify the arrangement of stars. The reception unit can also provide an option for the user to select the type of planet. The reception unit can also display a guide for the user to input the shape of the galaxy. The analysis unit analyzes the characteristics received by the reception unit. For example, the analysis unit analyzes the arrangement of stars input by the user and generates data for generating an appropriate digital universe. The analysis unit can also analyze the type of planet selected by the user and provide information for reflecting the selected type in the digital universe. The analysis unit can also analyze the shape of the galaxy input by the user and provide data necessary for generating the digital universe. The generation unit generates the digital universe based on the characteristics analyzed by the analysis unit. The generation unit digitally recreates a realistic universe according to the user's wishes, based on, for example, astronomical data. The generation unit uses a generation AI to reproduce in detail the arrangement of stars, the types of planets, the shape of galaxies, and the like. For example, the generation AI uses a text generation AI (e.g., LLM) or a multimodal generation AI to generate a digital universe that meets the user's wishes. The provision unit provides the digital universe generated by the generation unit to the user. The provision unit provides the generated digital universe to the user, for example, through a planetarium or a VR device. The provision unit can also provide an interface that allows the user to visually experience the generated digital universe. For example, the provision unit projects the digital universe onto a dome-shaped screen in a planetarium. The provision unit can also allow the user to experience the digital universe using a VR headset. In this way, the universe generation system according to the embodiment can instantly generate the universe desired by the user and provide a realistic planetarium experience.

[0030] The generation unit can generate a digital universe based on astronomical data. The generation unit can generate a digital universe based on constellation data, for example. The generation unit can analyze the constellation data and recreate the arrangement of stars. The generation unit can also generate a digital universe based on planetary data. The generation unit can analyze the planetary data and recreate the types and arrangements of planets. The generation unit can also generate a digital universe based on galaxy data. The generation unit can analyze the galaxy data and recreate the shape and structure of galaxies. In this way, a realistic universe can be generated based on astronomical data. Some or all of the above-described processing in the generation unit may be performed using a generation AI, or may be performed without using a generation AI. For example, the generation unit can input astronomical data into the generation AI and cause the generation AI to generate a digital universe.

[0031] The providing unit can provide the generated digital universe to a user through a planetarium or a VR device. For example, the providing unit projects the generated digital universe onto a dome-shaped screen in a planetarium. The providing unit displays the digital universe on the planetarium screen, allowing the user to enjoy a realistic space experience. The providing unit can also provide the generated digital universe to a user through a VR device. The providing unit allows the user to experience the digital universe using a VR headset. For example, the providing unit allows the user to experience the digital universe with a 360-degree field of view through the VR headset. Furthermore, the providing unit can also provide the generated digital universe to a user through an AR device. The providing unit allows the user to experience the digital universe by overlaying it on the real world using AR glasses. This allows a realistic space experience to be provided through a planetarium or a VR device. Some or all of the above-described processing in the providing unit may be performed using AI or without AI. For example, the providing unit can input the generated digital universe into AI and have the AI ​​select the optimal method for providing it to the user.

[0032] The reception unit allows the user to input the characteristics of the star arrangement, the type of planet, and the shape of the galaxy. For example, the reception unit provides an interface for the user to input the star arrangement. The reception unit provides an option to input coordinate data for specifying the star arrangement. The reception unit can also provide an option for the user to select the type of planet. The reception unit displays a drop-down menu for selecting the type of planet. Furthermore, the reception unit can display a guide for the user to input the shape of the galaxy. The reception unit provides options for specifying the shape of the galaxy. This allows the user to input detailed characteristics and generate a universe that meets their wishes. Some or all of the above-mentioned processing in the reception unit may be performed using AI, or may be performed without using AI. For example, the reception unit may input the characteristics input by the user into AI and have the AI ​​suggest the optimal input method.

[0033] The generation unit can digitally recreate a realistic universe according to the user's wishes. For example, the generation unit digitally recreates the star arrangement desired by the user. The generation unit executes a physical simulation to recreate the star arrangement in detail. The generation unit can also digitally recreate the type of planet desired by the user. The generation unit uses astronomical data to recreate the type of planet in detail. Furthermore, the generation unit can digitally recreate the shape of a galaxy desired by the user. The generation unit uses simulation technology to recreate the shape of a galaxy in detail. This allows for the recreation of a realistic universe according to the user's wishes. Some or all of the above-described processing in the generation unit may be performed using a generation AI, or may be performed without using a generation AI. For example, the generation unit can input the user's wishes into the generation AI and cause the generation AI to recreate a realistic universe.

[0034] The providing unit can use the generated digital universe for astronomy education or to create a relaxing space. For example, the providing unit uses the generated digital universe for astronomy education in school classes. The providing unit enables students to visually learn about the arrangement of stars and the movement of planets using the generated universe. The providing unit can also use the generated digital universe to create a relaxing space. The providing unit adjusts music and lighting to create a relaxing atmosphere using the generated universe. Furthermore, the providing unit can also use the generated digital universe to create an event. The providing unit generates a universe tailored to a specific theme and uses it to create an event. In this way, the generated digital universe can be used for education or a relaxing space. Some or all of the above-mentioned processing in the providing unit may be performed using AI, or may be performed without using AI. For example, the providing unit can input the generated digital universe into AI and have the AI ​​suggest the optimal way to use it.

[0035] The reception unit can analyze the user's past input history and suggest the optimal input method. For example, the reception unit automatically displays features that the user has frequently input in the past as candidates. The reception unit analyzes past input data and identifies features that the user frequently uses. The reception unit can also preferentially suggest input methods (voice, text, etc.) that the user has used in the past. The reception unit suggests the most efficient input method for the user based on the past input history. Furthermore, the reception unit can predict and suggest features to be used in a specific time period based on the user's past input history. The reception unit predicts features that the user will input in a specific time period based on past data and displays them as input candidates. This makes it possible to suggest the optimal input method based on the past input history. Some or all of the above-mentioned processing in the reception unit may be performed using AI, or may be performed without using AI. For example, the reception unit can input the past input history into AI and have the AI ​​suggest the optimal input method.

[0036] The reception unit can dynamically change the input guide depending on the level of detail of the features input by the user. For example, when the user inputs detailed features, the reception unit displays a detailed input guide. The reception unit analyzes the level of detail of the features input by the user and provides an appropriate input guide. The reception unit can also display a simplified input guide when the user inputs simple features. The reception unit dynamically changes the content of the input guide depending on the level of detail of the features input by the user. Furthermore, when the user changes the level of detail of the features during input, the reception unit can dynamically adjust the input guide accordingly. When the user changes the level of detail of the features during input, the reception unit immediately updates the input guide. This makes it possible to provide an input guide according to the level of detail of the features. Some or all of the above-described processing in the reception unit may be performed using AI or without AI. For example, the reception unit can input the user's input data to AI and have the AI ​​suggest an optimal input guide.

[0037] The reception unit can filter input content based on the user's current environment. For example, at night, the reception unit prioritizes displaying inputs related to the alignment of stars. The reception unit analyzes the user's current environment (e.g., time of day and location) and provides appropriate input content. Furthermore, when the user is in a specific location, the reception unit can prioritize displaying astronomical data related to that location. The reception unit provides relevant input options based on the user's location information. Furthermore, the reception unit can automatically filter relevant input options based on the user's current environment. The reception unit removes unnecessary information and emphasizes important information based on the user's environmental data. This allows input content based on the current environment to be provided. Some or all of the above-described processing in the reception unit may be performed using AI, or may be performed without AI. For example, the reception unit can input the user's environmental data into AI and have the AI ​​suggest optimal input content.

[0038] The reception unit can reflect region-specific astronomical data in the input based on the user's geographical location information. For example, if the user is in a specific region, the reception unit reflects the arrangement of the starry sky in that region in the input. The reception unit analyzes the user's geographical location information and provides region-specific astronomical data. Furthermore, if the user is in a specific location, the reception unit can also reflect astronomical data related to that location in the input. The reception unit provides related astronomical data based on the user's location information. Furthermore, the reception unit can automatically reflect region-specific astronomical data in the input based on the user's geographical location information. The reception unit automatically obtains region-specific astronomical data based on the user's location data and reflects it in the input. This makes it possible to provide input reflecting region-specific astronomical data. Some or all of the above-described processing in the reception unit may be performed using AI, or may be performed without AI. For example, the reception unit can input the user's geographical location information to AI and have the AI ​​suggest optimal astronomical data.

[0039] The reception unit can analyze the user's social media activity and automatically suggest related features. For example, the reception unit can suggest features related to places where the user has checked in on social media. The reception unit analyzes the user's social media activity and identifies related features. The reception unit can also analyze the content of the user's social media posts and suggest related features. The reception unit automatically suggests related features based on the content of the user's posts. Furthermore, the reception unit can suggest related features by referring to the activities of the user's friends on social media. The reception unit suggests related features based on activity data of the user's friends. This makes it possible to suggest features based on social media activity. Some or all of the above-mentioned processing in the reception unit may be performed using AI, or may be performed without using AI. For example, the reception unit can input the user's social media data into AI and have the AI ​​suggest optimal features.

[0040] The reception unit can customize the input interface by reflecting the user's past feedback. The reception unit customizes the input interface, for example, based on feedback provided by the user in the past. The reception unit analyzes the user's feedback and provides an optimal interface design. The reception unit can also suggest an optimal input method based on the user's past feedback. The reception unit suggests an efficient input method based on the user's feedback data. The reception unit can also adjust the design of the input interface by reflecting the user's past feedback. The reception unit adjusts the interface layout and functions based on the user's feedback. This makes it possible to provide an interface based on the past feedback. Some or all of the above-described processing in the reception unit may be performed using AI, or may be performed without using AI. For example, the reception unit can input the user's feedback data into AI and have the AI ​​suggest an optimal interface design.

[0041] The analysis unit can adjust the level of detail of the analysis based on the importance of the input features. For example, the analysis unit performs a detailed analysis on features with high importance. The analysis unit evaluates the importance of features input by the user and selects an appropriate analysis method. The analysis unit can also perform a simplified analysis on features with low importance. The analysis unit dynamically adjusts the level of detail of the analysis based on the importance of features input by the user. Furthermore, the analysis unit can determine the priority of the analysis based on the importance of features input by the user. The analysis unit sets the priority of the analysis based on the importance of features input by the user. This makes it possible to provide an analysis according to the importance of features. Some or all of the above-mentioned processing in the analysis unit may be performed using AI or without AI. For example, the analysis unit can input user input data to AI and have the AI ​​suggest an optimal analysis method.

[0042] The analysis unit can improve the accuracy of the analysis by referring to the latest information on astronomical data. The analysis unit improves the accuracy of the analysis, for example, based on the latest astronomical data. The analysis unit refers to the latest astronomical database to obtain information necessary for the analysis. The analysis unit can also improve the accuracy of the analysis by referring to the latest astronomical research results. The analysis unit adjusts the analysis algorithm based on the latest research papers and academic articles. Furthermore, the analysis unit can improve the accuracy of the analysis by using the latest astronomical database. The analysis unit provides highly accurate analysis results based on information obtained from the latest database. This allows the analysis accuracy to be improved based on the latest astronomical data. Some or all of the above-mentioned processing in the analysis unit may be performed using AI, or may be performed without using AI. For example, the analysis unit can input the latest astronomical data into AI and have the AI ​​suggest the optimal analysis method.

[0043] The analysis unit can improve the accuracy of the analysis by referring to the user's past analysis results. The analysis unit improves the analysis accuracy, for example, based on the user's past analysis results. The analysis unit adjusts the analysis algorithm by referring to past analysis data. The analysis unit can also adjust the analysis algorithm by referring to the user's past analysis results. The analysis unit adjusts the level of detail of the analysis based on the past analysis results. Furthermore, the analysis unit can analyze the user's past analysis results and improve the analysis accuracy. The analysis unit builds a feedback loop to improve the accuracy of the analysis results based on the past data. This allows the analysis accuracy to be improved based on the past analysis results. Some or all of the above-mentioned processing in the analysis unit may be performed using AI, or may be performed without using AI. For example, the analysis unit can input the user's past analysis data into AI and have the AI ​​suggest the optimal analysis method.

[0044] The analysis unit can determine the analysis priority based on the submission time of the input features. For example, the analysis unit prioritizes analysis of features submitted earlier. The analysis unit evaluates the submission time of the features input by the user and sets the analysis priority. The analysis unit can also postpone analysis of features submitted later. The analysis unit dynamically adjusts the analysis priority based on the submission time of the features input by the user. Furthermore, the analysis unit can also determine the analysis priority based on the submission time. The analysis unit sets the analysis priority based on the submission time of the features input by the user. This makes it possible to provide analysis priority based on the submission time. Some or all of the above-mentioned processing in the analysis unit may be performed using AI, or may be performed without using AI. For example, the analysis unit can input user submission time data into AI and have the AI ​​suggest optimal analysis priorities.

[0045] The analysis unit can improve the accuracy of the analysis by referring to related astronomical literature. The analysis unit improves the accuracy of the analysis, for example, based on related astronomical literature. The analysis unit refers to related astronomical research results to obtain information necessary for the analysis. The analysis unit can also improve the accuracy of the analysis by referring to related astronomical literature. The analysis unit adjusts the analysis algorithm based on related research papers and academic articles. Furthermore, the analysis unit can improve the accuracy of the analysis by using related astronomical databases. The analysis unit provides highly accurate analysis results based on information obtained from the related databases. This allows the analysis accuracy to be improved based on related literature. Some or all of the above-mentioned processing in the analysis unit may be performed using AI, or may be performed without using AI. For example, the analysis unit can input related astronomical literature into AI and have the AI ​​suggest the optimal analysis method.

[0046] The analysis unit can adjust the use of technical terms in the analysis results according to the user's level of expertise. For example, if the user has technical expertise, the analysis unit displays analysis results that use a lot of technical terms. The analysis unit evaluates the user's level of expertise and provides appropriate analysis results. The analysis unit can also display analysis results in simple language if the user does not have technical expertise. The analysis unit dynamically adjusts the use of technical terms in the analysis results according to the user's level of expertise. Furthermore, the analysis unit can also adjust the display method of the analysis results based on the user's level of expertise. The analysis unit sets the display method of the analysis results based on the user's level of expertise. This allows analysis results to be provided that are appropriate for the user's level of expertise. Some or all of the above-mentioned processing in the analysis unit may be performed using AI, or may be performed without using AI. For example, the analysis unit can input the user's technical expertise data into AI and have the AI ​​suggest an optimal display method for the analysis results.

[0047] The generation unit can improve the accuracy of generation based on the latest information on astronomical data. The generation unit improves the accuracy of generation based on, for example, the latest astronomical data. The generation unit refers to the latest astronomical database to obtain information necessary for generation. The generation unit can also improve the accuracy of generation by referring to the latest astronomical research results. The generation unit adjusts the generation algorithm based on the latest research papers and academic articles. Furthermore, the generation unit can improve the accuracy of generation using the latest astronomical database. The generation unit provides highly accurate generation results based on information obtained from the latest database. This allows the accuracy of generation to be improved based on the latest astronomical data. Some or all of the above-mentioned processing in the generation unit may be performed using a generation AI, or may be performed without using a generation AI. For example, the generation unit can input the latest astronomical data into the generation AI and have the generation AI suggest an optimal generation method.

[0048] The generation unit can improve the accuracy of generation by referring to the user's past generation results. The generation unit improves the generation accuracy, for example, based on the user's past generation results. The generation unit adjusts the generation algorithm by referring to past generation data. The generation unit can also adjust the generation algorithm by referring to the user's past generation results. The generation unit adjusts the level of detail of the generation based on the past generation results. Furthermore, the generation unit can analyze the user's past generation results and improve the generation accuracy. The generation unit builds a feedback loop to improve the accuracy of the generation results based on the past data. This allows the generation accuracy to be improved based on the past generation results. Some or all of the above-mentioned processing in the generation unit may be performed using a generation AI, or may be performed without using a generation AI. For example, the generation unit can input the user's past generation data into the generation AI and have the generation AI suggest an optimal generation method.

[0049] The generation unit can adjust the level of detail of the universe to be generated based on the user's wishes. For example, if the user desires a detailed universe, the generation unit generates the universe based on detailed data. The generation unit analyzes the user's wishes and generates the universe with an appropriate level of detail. Furthermore, if the user desires a simplified universe, the generation unit can also generate the universe based on simplified data. The generation unit dynamically adjusts the level of detail of the universe to be generated based on the user's wishes. Furthermore, the generation unit can adjust the level of detail of the universe to be generated based on the user's wishes. The generation unit sets the level of detail of the universe to be generated based on the user's wishes. This makes it possible to provide a universe with a level of detail that meets the user's wishes. Some or all of the above-described processing in the generation unit may be performed using a generation AI, or may be performed without using a generation AI. For example, the generation unit can input the user's desired data into the generation AI and have the generation AI suggest a method for generating a universe with an optimal level of detail.

[0050] The generation unit can reflect region-specific astronomical data by taking into account the user's geographical location information. For example, if the user is in a specific region, the generation unit generates a universe that reflects the arrangement of stars in that region. The generation unit analyzes the user's geographical location information and provides region-specific astronomical data. Furthermore, if the user is in a specific location, the generation unit can also generate a universe that reflects astronomical data related to that location. The generation unit provides related astronomical data based on the user's location information. Furthermore, the generation unit can generate a universe that reflects region-specific astronomical data based on the user's geographical location information. The generation unit automatically obtains region-specific astronomical data based on the user's location data and reflects it in the universe. This makes it possible to provide a universe that reflects region-specific astronomical data. Some or all of the above-described processing in the generation unit may be performed using a generation AI, or may be performed without using a generation AI. For example, the generation unit can input the user's geographical location information into the generation AI and have the generation AI suggest optimal astronomical data.

[0051] The generation unit can improve the accuracy of generation by referring to related astronomical literature. The generation unit improves the accuracy of generation, for example, based on related astronomical literature. The generation unit refers to related astronomical research results to obtain information necessary for generation. The generation unit can also improve the accuracy of generation by referring to related astronomical literature. The generation unit adjusts the generation algorithm based on related research papers and academic articles. Furthermore, the generation unit can improve the accuracy of generation by using related astronomical databases. The generation unit provides highly accurate generation results based on information obtained from related databases. This allows the accuracy of generation to be improved based on related literature. Some or all of the above-mentioned processing in the generation unit may be performed using a generation AI, or may be performed without using a generation AI. For example, the generation unit can input related astronomical literature into the generation AI and have the generation AI suggest an optimal generation method.

[0052] The generation unit can adjust the use of technical terminology in the generated universe according to the user's level of expertise. For example, if the user has technical expertise, the generation unit generates a universe that uses a lot of technical terminology. The generation unit evaluates the user's level of expertise and provides an appropriate universe. The generation unit can also generate a universe that is explained in simple terms if the user does not have technical expertise. The generation unit dynamically adjusts the use of technical terminology in the generated universe according to the user's level of expertise. Furthermore, the generation unit can adjust the use of technical terminology in the generated universe based on the user's level of expertise. The generation unit sets the use of technical terminology in the generated universe based on the user's level of expertise. This makes it possible to provide a universe that suits the user's level of expertise. Some or all of the above-mentioned processing in the generation unit may be performed using a generation AI, or may be performed without using a generation AI. For example, the generation unit can input the user's technical expertise data into the generation AI and have the generation AI suggest the optimal way to use technical terminology.

[0053] The providing unit can select the optimal delivery method by referring to the user's past usage history. The providing unit selects the optimal delivery method, for example, based on a display method used by the user in the past. The providing unit refers to past usage data and identifies a method that the user can use most effectively. The providing unit can also select the most effective delivery method from the user's past usage history. The providing unit suggests the optimal delivery method based on the past usage history. Furthermore, the providing unit can analyze the user's past usage history and select the optimal delivery method. The providing unit suggests a method that the user can use most effectively based on the past data. This makes it possible to provide the optimal delivery method based on the past usage history. Some or all of the above-mentioned processing in the providing unit may be performed using AI, or may be performed without using AI. For example, the providing unit can input the user's past usage data into AI and have the AI ​​suggest the optimal delivery method.

[0054] The providing unit can customize the content provided based on the user's current environment. For example, at night, the providing unit customizes the content provided to emphasize the arrangement of the starry sky. The providing unit analyzes the user's current environment (e.g., time of day and location) and provides appropriate content provided. Furthermore, when the user is in a specific location, the providing unit can customize the content provided to emphasize astronomical data related to that location. The providing unit provides related astronomical data based on the user's location information. Furthermore, the providing unit can dynamically customize the content provided based on the user's current environment. The providing unit instantly adjusts the content provided based on the user's environmental data. This allows the content provided to be based on the current environment. Some or all of the above-mentioned processing in the providing unit may be performed using AI, or may be performed without using AI. For example, the providing unit can input the user's environmental data into AI and have the AI ​​suggest optimal content provided.

[0055] The providing unit can improve the providing method by reflecting the user's feedback. For example, when the user provides feedback on the provided content, the providing unit improves the providing method based on the feedback. The providing unit analyzes the user's feedback and suggests an optimal providing method. The providing unit can also improve the providing method by referring to the user's past feedback. The providing unit adjusts the providing method based on the past feedback. Furthermore, the providing unit can analyze the user's feedback and dynamically improve the providing method. The providing unit instantly adjusts the providing method based on the feedback data. This makes it possible to provide a providing method based on the feedback. Some or all of the above-mentioned processing in the providing unit may be performed using AI or may be performed without using AI. For example, the providing unit can input the user's feedback data into AI and have the AI ​​suggest an optimal providing method.

[0056] The providing unit can select the optimal providing method taking into account the user's geographical location information. For example, if the user is in a specific area, the providing unit selects a providing method that reflects the arrangement of the starry sky in that area. The providing unit analyzes the user's geographical location information and provides the optimal providing method. Furthermore, if the user is in a specific location, the providing unit can also select a providing method that reflects astronomical data related to that location. The providing unit provides related astronomical data based on the user's location information. Furthermore, the providing unit can select the optimal providing method based on the user's geographical location information. The providing unit automatically selects the optimal providing method based on the user's location data. This makes it possible to provide a providing method based on the geographical location information. Some or all of the above-mentioned processing in the providing unit may be performed using AI, or may be performed without using AI. For example, the providing unit can input the user's geographical location information into AI and have the AI ​​suggest the optimal providing method.

[0057] The providing unit can customize the content provided by analyzing the user's social media activity. For example, the providing unit customizes the content provided related to a location where the user has checked in on social media. The providing unit analyzes the user's social media activity and identifies related content provided. The providing unit can also analyze the user's social media posts and customize the related content provided. The providing unit automatically suggests related content provided based on the user's posts. Furthermore, the providing unit can customize the related content provided by referring to the activities of the user's friends on social media. The providing unit suggests related content provided based on activity data of the user's friends. This makes it possible to provide content provided based on social media activity. Some or all of the above-described processing by the providing unit may be performed using AI, or may be performed without using AI. For example, the providing unit can input the user's social media data into AI and have the AI ​​suggest optimal content provided.

[0058] The providing unit can customize the delivery method by reflecting the user's past feedback. The providing unit customizes the delivery method, for example, based on feedback provided by the user in the past. The providing unit analyzes the user's feedback and suggests an optimal delivery method. The providing unit can also customize the delivery method by referring to the user's past feedback. The providing unit adjusts the delivery method based on the past feedback. Furthermore, the providing unit can analyze the user's past feedback and dynamically customize the delivery method. The providing unit instantly adjusts the delivery method based on the feedback data. This makes it possible to provide a delivery method based on the past feedback. Some or all of the above-mentioned processing in the providing unit may be performed using AI, or may be performed without using AI. For example, the providing unit can input the user's feedback data into AI and have the AI ​​suggest an optimal delivery method.

[0059] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0060] The reception unit can also provide related astronomical trivia and facts based on the user's input. For example, if the user selects a particular constellation, the historical background and myths related to that constellation can be displayed. If the user selects a planet, the unit can provide information on the latest scientific discoveries and exploration missions related to that planet. Furthermore, if the user inputs the shape of a galaxy, the unit can display interesting facts and observation data about that galaxy. This allows the user to deepen their knowledge of the universe. Some or all of the above-mentioned processing in the reception unit may be performed using AI, or may be performed without using AI. For example, the reception unit can input the user's input data into AI and have the AI ​​suggest the most appropriate trivia and facts.

[0061] The analysis unit can also suggest related astronomical events and observation opportunities based on the user's input. For example, if a user selects a particular constellation, it can suggest the best time and location for that constellation to be visible. If a user selects a planet, it can provide the next opportunity to observe that planet and suitable conditions for observation. Furthermore, if a user inputs the shape of a galaxy, it can provide information about astronomical events and research projects in which that galaxy can be observed. This allows the user to enjoy a realistic observation experience. Some or all of the above-mentioned processing in the analysis unit may be performed using AI, or may be performed without AI. For example, the analysis unit can input the user's input data into AI and have it suggest optimal observation opportunities.

[0062] The providing unit can also customize the generated digital universe according to the user's preferences. For example, if the user selects a specific color or theme, the visuals of the digital universe can be adjusted based on that theme. Also, if the user selects specific music or sound effects, the music or sound effects can be incorporated into the digital universe experience. Furthermore, if the user desires a specific interactive element, the element can be added to the digital universe. This allows the user to enjoy a more personalized universe experience. Some or all of the above-described processing in the providing unit may be performed using AI, or may be performed without AI. For example, the providing unit can input user preference data into AI and have the AI ​​suggest the optimal customization method.

[0063] The reception unit can also provide related astronomical simulations based on the user's input. For example, if the user selects a particular constellation, the formation process and evolution of that constellation can be displayed in a simulation. If the user selects a planet, the climate change and geological activity of that planet can be reproduced in a simulation. Furthermore, if the user inputs the shape of a galaxy, a simulation of the collision or merging of that galaxy can be provided. This allows the user to visually understand the dynamic changes in the universe. Some or all of the above-mentioned processing in the reception unit may be performed using AI, or may be performed without using AI. For example, the reception unit can input the user's input data into AI and have the AI ​​suggest the optimal simulation.

[0064] When using the generated digital universe for educational purposes, the providing unit can also incorporate interactive quizzes and tests. For example, if a user is learning about a particular constellation, a quiz about that constellation can be displayed, and if the user answers correctly, the user can proceed to the next level. Also, if a user is learning about types of planets, a test about that planet can be administered to check the user's understanding. Furthermore, if a user is learning about the shape of galaxies, interactive questions about that galaxy can be provided to deepen the user's learning. This can enhance the educational effect. Some or all of the above-mentioned processing by the providing unit may be performed using AI, or may be performed without using AI. For example, the providing unit can input the user's learning data into AI and have the AI ​​suggest optimal quizzes and tests.

[0065] The providing unit can also adjust the generated digital universe based on the user's health condition. For example, if the user needs relaxation, it can provide a universe with calm colors and quiet movements. Alternatively, if the user needs energy, it can provide a universe with vivid colors and dynamic movements. Furthermore, if the user is feeling stressed, it can provide a universe that combines music or natural sounds with a relaxing effect. This allows the user to have an optimal space experience according to their health condition. Some or all of the above-mentioned processing in the providing unit may be performed using AI, or may be performed without using AI. For example, the providing unit can input the user's health data into AI and have the AI ​​suggest the optimal space experience.

[0066] The reception unit can also provide relevant astronomical news and the latest information based on the user's input. For example, if the user selects a particular constellation, the latest observation results and research results related to that constellation are displayed. If the user selects a planet, the latest exploration missions and discoveries related to that planet can be provided. Furthermore, if the user inputs the shape of a galaxy, the latest research papers and observation data related to that galaxy can be provided. This allows the user to always be aware of the latest astronomical information. Some or all of the above-mentioned processing in the reception unit may be performed using AI, or may be performed without using AI. For example, the reception unit can input the user's input data into AI and have the AI ​​suggest the most appropriate news and the latest information.

[0067] The providing unit can also adjust the generated digital universe based on the user's health condition. For example, if the user needs relaxation, it can provide a universe with calm colors and quiet movements. Alternatively, if the user needs energy, it can provide a universe with vivid colors and dynamic movements. Furthermore, if the user is feeling stressed, it can provide a universe that combines music or natural sounds with a relaxing effect. This allows the user to have an optimal space experience according to their health condition. Some or all of the above-mentioned processing in the providing unit may be performed using AI, or may be performed without using AI. For example, the providing unit can input the user's health data into AI and have the AI ​​suggest the optimal space experience.

[0068] The reception unit can also provide relevant astronomical news and the latest information based on the user's input. For example, if the user selects a particular constellation, the latest observation results and research results related to that constellation are displayed. If the user selects a planet, the latest exploration missions and discoveries related to that planet can be provided. Furthermore, if the user inputs the shape of a galaxy, the latest research papers and observation data related to that galaxy can be provided. This allows the user to always be aware of the latest astronomical information. Some or all of the above-mentioned processing in the reception unit may be performed using AI, or may be performed without using AI. For example, the reception unit can input the user's input data into AI and have the AI ​​suggest the most appropriate news and the latest information.

[0069] The providing unit can also adjust the generated digital universe based on the user's health condition. For example, if the user needs relaxation, it can provide a universe with calm colors and quiet movements. Alternatively, if the user needs energy, it can provide a universe with vivid colors and dynamic movements. Furthermore, if the user is feeling stressed, it can provide a universe that combines music or natural sounds with a relaxing effect. This allows the user to have an optimal space experience according to their health condition. Some or all of the above-mentioned processing in the providing unit may be performed using AI, or may be performed without using AI. For example, the providing unit can input the user's health data into AI and have the AI ​​suggest the optimal space experience.

[0070] The reception unit can also provide relevant astronomical news and the latest information based on the user's input. For example, if the user selects a particular constellation, the latest observation results and research results related to that constellation are displayed. If the user selects a planet, the latest exploration missions and discoveries related to that planet can be provided. Furthermore, if the user inputs the shape of a galaxy, the latest research papers and observation data related to that galaxy can be provided. This allows the user to always be aware of the latest astronomical information. Some or all of the above-mentioned processing in the reception unit may be performed using AI, or may be performed without using AI. For example, the reception unit can input the user's input data into AI and have the AI ​​suggest the most appropriate news and the latest information.

[0071] The providing unit can also adjust the generated digital universe based on the user's health condition. For example, if the user needs relaxation, it can provide a universe with calm colors and quiet movements. Alternatively, if the user needs energy, it can provide a universe with vivid colors and dynamic movements. Furthermore, if the user is feeling stressed, it can provide a universe that combines music or natural sounds with a relaxing effect. This allows the user to have an optimal space experience according to their health condition. Some or all of the above-mentioned processing in the providing unit may be performed using AI, or may be performed without using AI. For example, the providing unit can input the user's health data into AI and have the AI ​​suggest the optimal space experience.

[0072] The reception unit can also provide relevant astronomical news and the latest information based on the user's input. For example, if the user selects a particular constellation, the latest observation results and research results related to that constellation are displayed. If the user selects a planet, the latest exploration missions and discoveries related to that planet can be provided. Furthermore, if the user inputs the shape of a galaxy, the latest research papers and observation data related to that galaxy can be provided. This allows the user to always be aware of the latest astronomical information. Some or all of the above-mentioned processing in the reception unit may be performed using AI, or may be performed without using AI. For example, the reception unit can input the user's input data into AI and have the AI ​​suggest the most appropriate news and the latest information.

[0073] The providing unit can also adjust the generated digital universe based on the user's health condition. For example, if the user needs relaxation, it can provide a universe with calm colors and quiet movements. Alternatively, if the user needs energy, it can provide a universe with vivid colors and dynamic movements. Furthermore, if the user is feeling stressed, it can provide a universe that combines music or natural sounds with a relaxing effect. This allows the user to have an optimal space experience according to their health condition. Some or all of the above-mentioned processing in the providing unit may be performed using AI, or may be performed without using AI. For example, the providing unit can input the user's health data into AI and have the AI ​​suggest the optimal space experience.

[0074] The reception unit can also provide relevant astronomical news and the latest information based on the user's input. For example, if the user selects a particular constellation, the latest observation results and research results related to that constellation are displayed. If the user selects a planet, the latest exploration missions and discoveries related to that planet can be provided. Furthermore, if the user inputs the shape of a galaxy, the latest research papers and observation data related to that galaxy can be provided. This allows the user to always be aware of the latest astronomical information. Some or all of the above-mentioned processing in the reception unit may be performed using AI, or may be performed without using AI. For example, the reception unit can input the user's input data into AI and have the AI ​​suggest the most appropriate news and the latest information.

[0075] The providing unit can also adjust the generated digital universe based on the user's health condition. For example, if the user needs relaxation, it can provide a universe with calm colors and quiet movements. Alternatively, if the user needs energy, it can provide a universe with vivid colors and dynamic movements. Furthermore, if the user is feeling stressed, it can provide a universe that combines music or natural sounds with a relaxing effect. This allows the user to have an optimal space experience according to their health condition. Some or all of the above-mentioned processing in the providing unit may be performed using AI, or may be performed without using AI. For example, the providing unit can input the user's health data into AI and have the AI ​​suggest the optimal space experience.

[0076] The reception unit can also provide relevant astronomical news and the latest information based on the user's input. For example, if the user selects a particular constellation, the latest observation results and research results related to that constellation are displayed. If the user selects a planet, the latest exploration missions and discoveries related to that planet can be provided. Furthermore, if the user inputs the shape of a galaxy, the latest research papers and observation data related to that galaxy can be provided. This allows the user to always be aware of the latest astronomical information. Some or all of the above-mentioned processing in the reception unit may be performed using AI, or may be performed without using AI. For example, the reception unit can input the user's input data into AI and have the AI ​​suggest the most appropriate news and the latest information.

[0077] The providing unit can also adjust the generated digital universe based on the user's health condition. For example, if the user needs relaxation, it can provide a universe with calm colors and quiet movements. Alternatively, if the user needs energy, it can provide a universe with vivid colors and dynamic movements. Furthermore, if the user is feeling stressed, it can provide a universe that combines music or natural sounds with a relaxing effect. This allows the user to have an optimal space experience according to their health condition. Some or all of the above-mentioned processing in the providing unit may be performed using AI, or may be performed without using AI. For example, the providing unit can input the user's health data into AI and have the AI ​​suggest the optimal space experience.

[0078] The reception unit can also provide relevant astronomical news and the latest information based on the user's input. For example, if the user selects a particular constellation, the latest observation results and research results related to that constellation are displayed. If the user selects a planet, the latest exploration missions and discoveries related to that planet can be provided. Furthermore, if the user inputs the shape of a galaxy, the latest research papers and observation data related to that galaxy can be provided. This allows the user to always be aware of the latest astronomical information. Some or all of the above-mentioned processing in the reception unit may be performed using AI, or may be performed without using AI. For example, the reception unit can input the user's input data into AI and have the AI ​​suggest the most appropriate news and the latest information.

[0079] The providing unit can also adjust the generated digital universe based on the user's health condition. For example, if the user needs relaxation, it can provide a universe with calm colors and quiet movements. Alternatively, if the user needs energy, it can provide a universe with vivid colors and dynamic movements. Furthermore, if the user is feeling stressed, it can provide a universe that combines music or natural sounds with a relaxing effect. This allows the user to have an optimal space experience according to their health condition. Some or all of the above-mentioned processing in the providing unit may be performed using AI, or may be performed without using AI. For example, the providing unit can input the user's health data into AI and have the AI ​​suggest the optimal space experience.

[0080] The reception unit can also provide relevant astronomical news and the latest information based on the user's input. For example, if the user selects a particular constellation, the latest observation results and research results related to that constellation are displayed. If the user selects a planet, the latest exploration missions and discoveries related to that planet can be provided. Furthermore, if the user inputs the shape of a galaxy, the latest research papers and observation data related to that galaxy can be provided. This allows the user to always be aware of the latest astronomical information. Some or all of the above-mentioned processing in the reception unit may be performed using AI, or may be performed without using AI. For example, the reception unit can input the user's input data into AI and have the AI ​​suggest the most appropriate news and the latest information.

[0081] The providing unit can also adjust the generated digital universe based on the user's health condition. For example, if the user needs relaxation, it can provide a universe with calm colors and quiet movements. Alternatively, if the user needs energy, it can provide a universe with vivid colors and dynamic movements. Furthermore, if the user is feeling stressed, it can provide a universe that combines music or natural sounds with a relaxing effect. This allows the user to have an optimal space experience according to their health condition. Some or all of the above-mentioned processing in the providing unit may be performed using AI, or may be performed without using AI. For example, the providing unit can input the user's health data into AI and have the AI ​​suggest the optimal space experience.

[0082] The reception unit can also provide relevant astronomical news and the latest information based on the user's input. For example, if the user selects a particular constellation, the latest observation results and research results related to that constellation are displayed. If the user selects a planet, the latest exploration missions and discoveries related to that planet can be provided. Furthermore, if the user inputs the shape of a galaxy, the latest research papers and observation data related to that galaxy can be provided. This allows the user to always be aware of the latest astronomical information. Some or all of the above-mentioned processing in the reception unit may be performed using AI, or may be performed without using AI. For example, the reception unit can input the user's input data into AI and have the AI ​​suggest the most appropriate news and the latest information.

[0083] The providing unit can also adjust the generated digital universe based on the user's health condition. For example, if the user needs relaxation, it can provide a universe with calm colors and quiet movements. Alternatively, if the user needs energy, it can provide a universe with vivid colors and dynamic movements. Furthermore, if the user is feeling stressed, it can provide a universe that combines music or natural sounds with a relaxing effect. This allows the user to have an optimal space experience according to their health condition. Some or all of the above-mentioned processing in the providing unit may be performed using AI, or may be performed without using AI. For example, the providing unit can input the user's health data into AI and have the AI ​​suggest the optimal space experience.

[0084] The reception unit can also provide relevant astronomical news and the latest information based on the user's input. For example, if the user selects a particular constellation, the latest observation results and research results related to that constellation are displayed. If the user selects a planet, the latest exploration missions and discoveries related to that planet can be provided. Furthermore, if the user inputs the shape of a galaxy, the latest research papers and observation data related to that galaxy can be provided. This allows the user to always be aware of the latest astronomical information. Some or all of the above-mentioned processing in the reception unit may be performed using AI, or may be performed without using AI. For example, the reception unit can input the user's input data into AI and have the AI ​​suggest the most appropriate news and the latest information.

[0085] The providing unit can also adjust the generated digital universe based on the user's health condition. For example, if the user needs relaxation, it can provide a universe with calm colors and quiet movements. Alternatively, if the user needs energy, it can provide a universe with vivid colors and dynamic movements. Furthermore, if the user is feeling stressed, it can provide a universe that combines music or natural sounds with a relaxing effect. This allows the user to have an optimal space experience according to their health condition. Some or all of the above-mentioned processing in the providing unit may be performed using AI, or may be performed without using AI. For example, the providing unit can input the user's health data into AI and have the AI ​​suggest the optimal space experience.

[0086] The processing flow of the first embodiment will be briefly explained below.

[0087] Step 1: The reception unit inputs the space characteristics desired by the user. The space characteristics desired by the user include, for example, the arrangement of stars, the type of planets, the shape of the galaxy, etc. The reception unit provides an interface for the user to specify the arrangement of stars, an option for selecting the type of planets, and a guide for inputting the shape of the galaxy. Step 2: The analysis unit analyzes the features received by the reception unit. The analysis unit analyzes the star arrangement, planet types, and galaxy shapes entered by the user, and generates data for generating an appropriate digital universe. Step 3: The generator generates a digital universe based on the characteristics analyzed by the analyzer. The generator digitally recreates a realistic universe based on astronomical data, meeting the user's needs. Using generative AI, it recreates the arrangement of stars, the types of planets, the shape of galaxies, and more in detail. Step 4: The providing unit provides the digital universe generated by the generating unit to the user. The providing unit provides the generated digital universe to the user through a planetarium or a VR device, and provides an interface that allows the user to visually experience it.

[0088] (Example 2) A system according to an embodiment of the present invention utilizes a generation AI to instantly create a universe desired by a user. This system allows users to input the characteristics of the desired universe, and the generation AI analyzes those characteristics to generate a digital universe for a realistic planetarium experience. For example, users can specify detailed features such as the arrangement of stars, the type of planets, and the shape of galaxies. The generation AI digitally recreates a realistic universe based on astronomical data, meeting the user's needs. This generated digital universe is then provided to the user through a planetarium or VR device. This system is ideal for astronomy education and creating a relaxing space, and is intended for space enthusiasts and event planners. The system allows users to instantly create the universe they desire and enjoy a realistic planetarium experience. For example, when learning astronomy in a school class, students can use the generated universe to visually learn about the arrangement of stars and the movement of planets. Furthermore, the generated universe can be used to create a relaxing atmosphere for relaxation. This allows users to enjoy a realistic planetarium experience.

[0089] A universe generation system according to an embodiment includes a reception unit, an analysis unit, a generation unit, and a provision unit. The reception unit inputs the characteristics of the universe desired by the user. The characteristics of the universe desired by the user include, but are not limited to, the arrangement of stars, the type of planets, and the shape of the galaxy. For example, the reception unit provides an interface for the user to specify the arrangement of stars. The reception unit can also provide an option for the user to select the type of planet. The reception unit can also display a guide for the user to input the shape of the galaxy. The analysis unit analyzes the characteristics received by the reception unit. For example, the analysis unit analyzes the arrangement of stars input by the user and generates data for generating an appropriate digital universe. The analysis unit can also analyze the type of planet selected by the user and provide information for reflecting the selected type in the digital universe. The analysis unit can also analyze the shape of the galaxy input by the user and provide data necessary for generating the digital universe. The generation unit generates the digital universe based on the characteristics analyzed by the analysis unit. The generation unit digitally recreates a realistic universe according to the user's wishes, based on, for example, astronomical data. The generation unit uses a generation AI to reproduce in detail the arrangement of stars, the types of planets, the shape of galaxies, and the like. For example, the generation AI uses a text generation AI (e.g., LLM) or a multimodal generation AI to generate a digital universe that meets the user's wishes. The provision unit provides the digital universe generated by the generation unit to the user. The provision unit provides the generated digital universe to the user, for example, through a planetarium or a VR device. The provision unit can also provide an interface that allows the user to visually experience the generated digital universe. For example, the provision unit projects the digital universe onto a dome-shaped screen in a planetarium. The provision unit can also allow the user to experience the digital universe using a VR headset. In this way, the universe generation system according to the embodiment can instantly generate the universe desired by the user and provide a realistic planetarium experience.

[0090] The generation unit can generate a digital universe based on astronomical data. The generation unit can generate a digital universe based on constellation data, for example. The generation unit can analyze the constellation data and recreate the arrangement of stars. The generation unit can also generate a digital universe based on planetary data. The generation unit can analyze the planetary data and recreate the types and arrangements of planets. The generation unit can also generate a digital universe based on galaxy data. The generation unit can analyze the galaxy data and recreate the shape and structure of galaxies. In this way, a realistic universe can be generated based on astronomical data. Some or all of the above-described processing in the generation unit may be performed using a generation AI, or may be performed without using a generation AI. For example, the generation unit can input astronomical data into the generation AI and cause the generation AI to generate a digital universe.

[0091] The providing unit can provide the generated digital universe to a user through a planetarium or a VR device. For example, the providing unit projects the generated digital universe onto a dome-shaped screen in a planetarium. The providing unit displays the digital universe on the planetarium screen, allowing the user to enjoy a realistic space experience. The providing unit can also provide the generated digital universe to a user through a VR device. The providing unit allows the user to experience the digital universe using a VR headset. For example, the providing unit allows the user to experience the digital universe with a 360-degree field of view through the VR headset. Furthermore, the providing unit can also provide the generated digital universe to a user through an AR device. The providing unit allows the user to experience the digital universe by overlaying it on the real world using AR glasses. This allows a realistic space experience to be provided through a planetarium or a VR device. Some or all of the above-described processing in the providing unit may be performed using AI or without AI. For example, the providing unit can input the generated digital universe into AI and have the AI ​​select the optimal method for providing it to the user.

[0092] The reception unit allows the user to input the characteristics of the star arrangement, the type of planet, and the shape of the galaxy. For example, the reception unit provides an interface for the user to input the star arrangement. The reception unit provides an option to input coordinate data for specifying the star arrangement. The reception unit can also provide an option for the user to select the type of planet. The reception unit displays a drop-down menu for selecting the type of planet. Furthermore, the reception unit can display a guide for the user to input the shape of the galaxy. The reception unit provides options for specifying the shape of the galaxy. This allows the user to input detailed characteristics and generate a universe that meets their wishes. Some or all of the above-mentioned processing in the reception unit may be performed using AI, or may be performed without using AI. For example, the reception unit may input the characteristics input by the user into AI and have the AI ​​suggest the optimal input method.

[0093] The generation unit can digitally recreate a realistic universe according to the user's wishes. For example, the generation unit digitally recreates the star arrangement desired by the user. The generation unit executes a physical simulation to recreate the star arrangement in detail. The generation unit can also digitally recreate the type of planet desired by the user. The generation unit uses astronomical data to recreate the type of planet in detail. Furthermore, the generation unit can digitally recreate the shape of a galaxy desired by the user. The generation unit uses simulation technology to recreate the shape of a galaxy in detail. This allows for the recreation of a realistic universe according to the user's wishes. Some or all of the above-described processing in the generation unit may be performed using a generation AI, or may be performed without using a generation AI. For example, the generation unit can input the user's wishes into the generation AI and cause the generation AI to recreate a realistic universe.

[0094] The providing unit can use the generated digital universe for astronomy education or to create a relaxing space. For example, the providing unit uses the generated digital universe for astronomy education in school classes. The providing unit enables students to visually learn about the arrangement of stars and the movement of planets using the generated universe. The providing unit can also use the generated digital universe to create a relaxing space. The providing unit adjusts music and lighting to create a relaxing atmosphere using the generated universe. Furthermore, the providing unit can also use the generated digital universe to create an event. The providing unit generates a universe tailored to a specific theme and uses it to create an event. In this way, the generated digital universe can be used for education or a relaxing space. Some or all of the above-mentioned processing in the providing unit may be performed using AI, or may be performed without using AI. For example, the providing unit can input the generated digital universe into AI and have the AI ​​suggest the optimal way to use it.

[0095] The reception unit can estimate the user's emotions and adjust the design of the input interface based on the emotions. For example, if the user is relaxed, the reception unit provides an interface with soft colors and a simple design. The reception unit captures the user's facial expressions with a camera and estimates the emotion using an emotion estimation algorithm. For example, it calculates an emotion score based on changes in facial expressions. Alternatively, if the user is excited, the reception unit can provide an interface with vivid colors and a dynamic design. The reception unit records the user's voice and estimates the emotion using voice analysis technology. For example, it analyzes the tone and speed of the voice and calculates an emotion score. Alternatively, if the user is stressed, the reception unit can provide an interface with calm colors and an intuitive design. The reception unit collects the user's biometric data (heart rate and electrodermal activity) with a sensor and estimates the emotion using an emotion estimation algorithm. For example, it calculates an emotion score based on heart rate fluctuations. This allows the system to provide an interface that corresponds to the user's emotions. Emotion estimation is achieved using an emotion estimation function, for example, an emotion engine or generative AI. The generation AI may be, but is not limited to, a text generation AI (e.g., LLM) or a multimodal generation AI. Some or all of the above-described processing in the reception unit may be performed using AI, or may be performed without using AI. For example, the reception unit may input user emotion data into AI and have the AI ​​propose an optimal interface design.

[0096] The reception unit can analyze the user's past input history and suggest the optimal input method. For example, the reception unit automatically displays features that the user has frequently input in the past as candidates. The reception unit analyzes past input data and identifies features that the user frequently uses. The reception unit can also preferentially suggest input methods (voice, text, etc.) that the user has used in the past. The reception unit suggests the most efficient input method for the user based on the past input history. Furthermore, the reception unit can predict and suggest features to be used in a specific time period based on the user's past input history. The reception unit predicts features that the user will input in a specific time period based on past data and displays them as input candidates. This makes it possible to suggest the optimal input method based on the past input history. Some or all of the above-mentioned processing in the reception unit may be performed using AI, or may be performed without using AI. For example, the reception unit can input the past input history into AI and have the AI ​​suggest the optimal input method.

[0097] The reception unit can dynamically change the input guide depending on the level of detail of the features input by the user. For example, when the user inputs detailed features, the reception unit displays a detailed input guide. The reception unit analyzes the level of detail of the features input by the user and provides an appropriate input guide. The reception unit can also display a simplified input guide when the user inputs simple features. The reception unit dynamically changes the content of the input guide depending on the level of detail of the features input by the user. Furthermore, when the user changes the level of detail of the features during input, the reception unit can dynamically adjust the input guide accordingly. When the user changes the level of detail of the features during input, the reception unit immediately updates the input guide. This makes it possible to provide an input guide according to the level of detail of the features. Some or all of the above-described processing in the reception unit may be performed using AI or without AI. For example, the reception unit can input the user's input data to AI and have the AI ​​suggest an optimal input guide.

[0098] The reception unit can filter input content based on the user's current environment. For example, at night, the reception unit prioritizes displaying inputs related to the alignment of stars. The reception unit analyzes the user's current environment (e.g., time of day and location) and provides appropriate input content. Furthermore, when the user is in a specific location, the reception unit can prioritize displaying astronomical data related to that location. The reception unit provides relevant input options based on the user's location information. Furthermore, the reception unit can automatically filter relevant input options based on the user's current environment. The reception unit removes unnecessary information and emphasizes important information based on the user's environmental data. This allows input content based on the current environment to be provided. Some or all of the above-described processing in the reception unit may be performed using AI, or may be performed without AI. For example, the reception unit can input the user's environmental data into AI and have the AI ​​suggest optimal input content.

[0099] The reception unit can estimate the user's emotions and prioritize input content based on the emotions. For example, if the user is relaxed, the reception unit prioritizes input of detailed features. The reception unit captures the user's facial expressions with a camera and estimates the user's emotions using an emotion estimation algorithm. For example, it calculates an emotion score based on changes in facial expressions. The reception unit can also prioritize input of simple features if the user is in a hurry. The reception unit records the user's voice and estimates the user's emotions using voice analysis technology. For example, it analyzes the tone and speed of the voice and calculates an emotion score. The reception unit can also prioritize input of visually appealing features if the user is excited. The reception unit collects the user's biometric data (heart rate and electrodermal activity) using a sensor and estimates the user's emotions using an emotion estimation algorithm. For example, it calculates an emotion score based on heart rate fluctuations. This allows the system to prioritize input content according to the user's emotions. Emotion estimation is achieved using an emotion estimation function, for example, an emotion engine or generative AI. The generation AI may be, but is not limited to, a text generation AI (e.g., LLM) or a multimodal generation AI. Some or all of the above-described processing in the reception unit may be performed using AI, or may be performed without using AI. For example, the reception unit may input user emotion data into the AI ​​and have the AI ​​propose optimal input content priorities.

[0100] The reception unit can reflect region-specific astronomical data in the input based on the user's geographical location information. For example, if the user is in a specific region, the reception unit reflects the arrangement of the starry sky in that region in the input. The reception unit analyzes the user's geographical location information and provides region-specific astronomical data. Furthermore, if the user is in a specific location, the reception unit can also reflect astronomical data related to that location in the input. The reception unit provides related astronomical data based on the user's location information. Furthermore, the reception unit can automatically reflect region-specific astronomical data in the input based on the user's geographical location information. The reception unit automatically obtains region-specific astronomical data based on the user's location data and reflects it in the input. This makes it possible to provide input reflecting region-specific astronomical data. Some or all of the above-described processing in the reception unit may be performed using AI, or may be performed without AI. For example, the reception unit can input the user's geographical location information to AI and have the AI ​​suggest optimal astronomical data.

[0101] The reception unit can analyze the user's social media activity and automatically suggest related features. For example, the reception unit can suggest features related to places where the user has checked in on social media. The reception unit analyzes the user's social media activity and identifies related features. The reception unit can also analyze the content of the user's social media posts and suggest related features. The reception unit automatically suggests related features based on the content of the user's posts. Furthermore, the reception unit can suggest related features by referring to the activities of the user's friends on social media. The reception unit suggests related features based on activity data of the user's friends. This makes it possible to suggest features based on social media activity. Some or all of the above-mentioned processing in the reception unit may be performed using AI, or may be performed without using AI. For example, the reception unit can input the user's social media data into AI and have the AI ​​suggest optimal features.

[0102] The reception unit can customize the input interface by reflecting the user's past feedback. The reception unit customizes the input interface, for example, based on feedback provided by the user in the past. The reception unit analyzes the user's feedback and provides an optimal interface design. The reception unit can also suggest an optimal input method based on the user's past feedback. The reception unit suggests an efficient input method based on the user's feedback data. The reception unit can also adjust the design of the input interface by reflecting the user's past feedback. The reception unit adjusts the interface layout and functions based on the user's feedback. This makes it possible to provide an interface based on the past feedback. Some or all of the above-described processing in the reception unit may be performed using AI, or may be performed without using AI. For example, the reception unit can input the user's feedback data into AI and have the AI ​​suggest an optimal interface design.

[0103] The analysis unit can estimate the user's emotions and adjust the analysis algorithm based on the emotions. For example, if the user is relaxed, the analysis unit uses an algorithm that performs a detailed analysis. The analysis unit captures the user's facial expressions with a camera and estimates the emotions using an emotion estimation algorithm. For example, it calculates an emotion score based on changes in facial expressions. The analysis unit can also use an algorithm that performs a quick analysis if the user is in a hurry. The analysis unit records the user's voice and estimates the emotions using voice analysis technology. For example, it analyzes the tone and speed of the voice and calculates an emotion score. The analysis unit can also use an algorithm that provides visually appealing analysis results if the user is excited. The analysis unit collects the user's biometric data (heart rate and electrodermal activity) using a sensor and estimates the emotions using an emotion estimation algorithm. For example, it calculates an emotion score based on heart rate fluctuations. This makes it possible to provide an analysis algorithm that corresponds to the user's emotions. Emotion estimation is achieved using an emotion estimation function, for example, an emotion engine or generative AI. The generation AI may be, but is not limited to, a text generation AI (e.g., LLM) or a multimodal generation AI. Some or all of the above-described processing in the analysis unit may be performed using AI, or may be performed without using AI. For example, the analysis unit may input user emotion data into the AI ​​and have the AI ​​propose an optimal analysis algorithm.

[0104] The analysis unit can adjust the level of detail of the analysis based on the importance of the input features. For example, the analysis unit performs a detailed analysis on features with high importance. The analysis unit evaluates the importance of features input by the user and selects an appropriate analysis method. The analysis unit can also perform a simplified analysis on features with low importance. The analysis unit dynamically adjusts the level of detail of the analysis based on the importance of features input by the user. Furthermore, the analysis unit can determine the priority of the analysis based on the importance of features input by the user. The analysis unit sets the priority of the analysis based on the importance of features input by the user. This makes it possible to provide an analysis according to the importance of features. Some or all of the above-mentioned processing in the analysis unit may be performed using AI or without AI. For example, the analysis unit can input user input data to AI and have the AI ​​suggest an optimal analysis method.

[0105] The analysis unit can improve the accuracy of the analysis by referring to the latest information on astronomical data. The analysis unit improves the accuracy of the analysis, for example, based on the latest astronomical data. The analysis unit refers to the latest astronomical database to obtain information necessary for the analysis. The analysis unit can also improve the accuracy of the analysis by referring to the latest astronomical research results. The analysis unit adjusts the analysis algorithm based on the latest research papers and academic articles. Furthermore, the analysis unit can improve the accuracy of the analysis by using the latest astronomical database. The analysis unit provides highly accurate analysis results based on information obtained from the latest database. This allows the analysis accuracy to be improved based on the latest astronomical data. Some or all of the above-mentioned processing in the analysis unit may be performed using AI, or may be performed without using AI. For example, the analysis unit can input the latest astronomical data into AI and have the AI ​​suggest the optimal analysis method.

[0106] The analysis unit can improve the accuracy of the analysis by referring to the user's past analysis results. The analysis unit improves the analysis accuracy, for example, based on the user's past analysis results. The analysis unit adjusts the analysis algorithm by referring to past analysis data. The analysis unit can also adjust the analysis algorithm by referring to the user's past analysis results. The analysis unit adjusts the level of detail of the analysis based on the past analysis results. Furthermore, the analysis unit can analyze the user's past analysis results and improve the analysis accuracy. The analysis unit builds a feedback loop to improve the accuracy of the analysis results based on the past data. This allows the analysis accuracy to be improved based on the past analysis results. Some or all of the above-mentioned processing in the analysis unit may be performed using AI, or may be performed without using AI. For example, the analysis unit can input the user's past analysis data into AI and have the AI ​​suggest the optimal analysis method.

[0107] The analysis unit can estimate the user's emotions and adjust the display method of the analysis results based on the emotions. For example, if the user is relaxed, the analysis unit displays detailed analysis results. The analysis unit captures the user's facial expressions with a camera and estimates the emotions using an emotion estimation algorithm. For example, it calculates an emotion score based on changes in facial expressions. The analysis unit can also display concise analysis results if the user is in a hurry. The analysis unit records the user's voice and estimates the emotions using voice analysis technology. For example, it analyzes the tone and speed of the voice and calculates an emotion score. The analysis unit can also display visually appealing analysis results if the user is excited. The analysis unit collects the user's biometric data (heart rate and electrodermal activity) with a sensor and estimates the emotions using an emotion estimation algorithm. For example, it calculates an emotion score based on heart rate fluctuations. This makes it possible to provide a display method of the analysis results that corresponds to the user's emotions. Emotion estimation is achieved using an emotion estimation function, for example, an emotion engine or generative AI. The generation AI may be, but is not limited to, a text generation AI (e.g., LLM) or a multimodal generation AI. Some or all of the above-described processing in the analysis unit may be performed using AI, or may be performed without using AI. For example, the analysis unit may input user emotion data into AI and have the AI ​​suggest the optimal display method.

[0108] The analysis unit can determine the analysis priority based on the submission time of the input features. For example, the analysis unit prioritizes analysis of features submitted earlier. The analysis unit evaluates the submission time of the features input by the user and sets the analysis priority. The analysis unit can also postpone analysis of features submitted later. The analysis unit dynamically adjusts the analysis priority based on the submission time of the features input by the user. Furthermore, the analysis unit can also determine the analysis priority based on the submission time. The analysis unit sets the analysis priority based on the submission time of the features input by the user. This makes it possible to provide analysis priority based on the submission time. Some or all of the above-mentioned processing in the analysis unit may be performed using AI, or may be performed without using AI. For example, the analysis unit can input user submission time data into AI and have the AI ​​suggest optimal analysis priorities.

[0109] The analysis unit can improve the accuracy of the analysis by referring to related astronomical literature. The analysis unit improves the accuracy of the analysis, for example, based on related astronomical literature. The analysis unit refers to related astronomical research results to obtain information necessary for the analysis. The analysis unit can also improve the accuracy of the analysis by referring to related astronomical literature. The analysis unit adjusts the analysis algorithm based on related research papers and academic articles. Furthermore, the analysis unit can improve the accuracy of the analysis by using related astronomical databases. The analysis unit provides highly accurate analysis results based on information obtained from the related databases. This allows the analysis accuracy to be improved based on related literature. Some or all of the above-mentioned processing in the analysis unit may be performed using AI, or may be performed without using AI. For example, the analysis unit can input related astronomical literature into AI and have the AI ​​suggest the optimal analysis method.

[0110] The analysis unit can adjust the use of technical terms in the analysis results according to the user's level of expertise. For example, if the user has technical expertise, the analysis unit displays analysis results that use a lot of technical terms. The analysis unit evaluates the user's level of expertise and provides appropriate analysis results. The analysis unit can also display analysis results in simple language if the user does not have technical expertise. The analysis unit dynamically adjusts the use of technical terms in the analysis results according to the user's level of expertise. Furthermore, the analysis unit can also adjust the display method of the analysis results based on the user's level of expertise. The analysis unit sets the display method of the analysis results based on the user's level of expertise. This allows analysis results to be provided that are appropriate for the user's level of expertise. Some or all of the above-mentioned processing in the analysis unit may be performed using AI, or may be performed without using AI. For example, the analysis unit can input the user's technical expertise data into AI and have the AI ​​suggest an optimal display method for the analysis results.

[0111] The generation unit can estimate the user's emotions and adjust the expression method of the generated universe based on the emotions. For example, if the user is relaxed, the generation unit generates a universe with soft colors and gentle movements. The generation unit captures the user's facial expression with a camera and estimates the emotion using an emotion estimation algorithm. For example, it calculates an emotion score based on changes in facial expression. The generation unit can also generate a universe with vivid colors and dynamic movements if the user is excited. The generation unit records the user's voice and estimates the emotion using voice analysis technology. For example, it analyzes the tone and speed of the voice and calculates an emotion score. The generation unit can also generate a universe with calm colors and quiet movements if the user is stressed. The generation unit collects the user's biometric data (heart rate and electrodermal activity) with a sensor and estimates the emotion using an emotion estimation algorithm. For example, it calculates an emotion score based on heart rate fluctuations. This makes it possible to provide a universe expression method that corresponds to the user's emotions. Emotion estimation is achieved using an emotion estimation function, for example, an emotion engine or a generation AI. The generation AI may be, but is not limited to, a text generation AI (e.g., LLM) or a multimodal generation AI. Some or all of the above-described processing in the generation unit may be performed using AI, or may be performed without using AI. For example, the generation unit may input user emotional data into the AI ​​and have the AI ​​suggest the optimal way to express the universe.

[0112] The generation unit can improve the accuracy of generation based on the latest information on astronomical data. The generation unit improves the accuracy of generation based on, for example, the latest astronomical data. The generation unit refers to the latest astronomical database to obtain information necessary for generation. The generation unit can also improve the accuracy of generation by referring to the latest astronomical research results. The generation unit adjusts the generation algorithm based on the latest research papers and academic articles. Furthermore, the generation unit can improve the accuracy of generation using the latest astronomical database. The generation unit provides highly accurate generation results based on information obtained from the latest database. This allows the accuracy of generation to be improved based on the latest astronomical data. Some or all of the above-mentioned processing in the generation unit may be performed using a generation AI, or may be performed without using a generation AI. For example, the generation unit can input the latest astronomical data into the generation AI and have the generation AI suggest an optimal generation method.

[0113] The generation unit can improve the accuracy of generation by referring to the user's past generation results. The generation unit improves the generation accuracy, for example, based on the user's past generation results. The generation unit adjusts the generation algorithm by referring to past generation data. The generation unit can also adjust the generation algorithm by referring to the user's past generation results. The generation unit adjusts the level of detail of the generation based on the past generation results. Furthermore, the generation unit can analyze the user's past generation results and improve the generation accuracy. The generation unit builds a feedback loop to improve the accuracy of the generation results based on the past data. This allows the generation accuracy to be improved based on the past generation results. Some or all of the above-mentioned processing in the generation unit may be performed using a generation AI, or may be performed without using a generation AI. For example, the generation unit can input the user's past generation data into the generation AI and have the generation AI suggest an optimal generation method.

[0114] The generation unit can adjust the level of detail of the universe to be generated based on the user's wishes. For example, if the user desires a detailed universe, the generation unit generates the universe based on detailed data. The generation unit analyzes the user's wishes and generates the universe with an appropriate level of detail. Furthermore, if the user desires a simplified universe, the generation unit can also generate the universe based on simplified data. The generation unit dynamically adjusts the level of detail of the universe to be generated based on the user's wishes. Furthermore, the generation unit can adjust the level of detail of the universe to be generated based on the user's wishes. The generation unit sets the level of detail of the universe to be generated based on the user's wishes. This makes it possible to provide a universe with a level of detail that meets the user's wishes. Some or all of the above-described processing in the generation unit may be performed using a generation AI, or may be performed without using a generation AI. For example, the generation unit can input the user's desired data into the generation AI and have the generation AI suggest a method for generating a universe with an optimal level of detail.

[0115] The generation unit can estimate the user's emotions and determine the priority of the universes to be generated based on the emotions. For example, if the user is relaxed, the generation unit prioritizes generating universes with a high relaxing effect. The generation unit captures the user's facial expression with a camera and estimates the emotion using an emotion estimation algorithm. For example, the emotion score is calculated based on changes in facial expression. The generation unit can also prioritize generating a visually stimulating universe if the user is excited. The generation unit records the user's voice and estimates the emotion using voice analysis technology. For example, the tone and speed of the voice are analyzed to calculate the emotion score. The generation unit can also prioritize generating a universe with a calm atmosphere if the user is stressed. The generation unit collects the user's biometric data (heart rate and electrodermal activity) with a sensor and estimates the emotion using an emotion estimation algorithm. For example, the emotion score is calculated based on heart rate fluctuations. This allows the system to prioritize universes according to the user's emotions. Emotion estimation is achieved using an emotion estimation function, for example, an emotion engine or a generation AI. The generation AI may be, but is not limited to, a text generation AI (e.g., LLM) or a multimodal generation AI. Some or all of the above-described processing in the generation unit may be performed using the generation AI, or may be performed without using the generation AI. For example, the generation unit may input user emotion data into the generation AI and have the generation AI propose optimal universe priorities.

[0116] The generation unit can reflect region-specific astronomical data by taking into account the user's geographical location information. For example, if the user is in a specific region, the generation unit generates a universe that reflects the arrangement of stars in that region. The generation unit analyzes the user's geographical location information and provides region-specific astronomical data. Furthermore, if the user is in a specific location, the generation unit can also generate a universe that reflects astronomical data related to that location. The generation unit provides related astronomical data based on the user's location information. Furthermore, the generation unit can generate a universe that reflects region-specific astronomical data based on the user's geographical location information. The generation unit automatically obtains region-specific astronomical data based on the user's location data and reflects it in the universe. This makes it possible to provide a universe that reflects region-specific astronomical data. Some or all of the above-described processing in the generation unit may be performed using a generation AI, or may be performed without using a generation AI. For example, the generation unit can input the user's geographical location information into the generation AI and have the generation AI suggest optimal astronomical data.

[0117] The generation unit can improve the accuracy of generation by referring to related astronomical literature. The generation unit improves the accuracy of generation, for example, based on related astronomical literature. The generation unit refers to related astronomical research results to obtain information necessary for generation. The generation unit can also improve the accuracy of generation by referring to related astronomical literature. The generation unit adjusts the generation algorithm based on related research papers and academic articles. Furthermore, the generation unit can improve the accuracy of generation by using related astronomical databases. The generation unit provides highly accurate generation results based on information obtained from related databases. This allows the accuracy of generation to be improved based on related literature. Some or all of the above-mentioned processing in the generation unit may be performed using a generation AI, or may be performed without using a generation AI. For example, the generation unit can input related astronomical literature into the generation AI and have the generation AI suggest an optimal generation method.

[0118] The generation unit can adjust the use of technical terminology in the generated universe according to the user's level of expertise. For example, if the user has technical expertise, the generation unit generates a universe that uses a lot of technical terminology. The generation unit evaluates the user's level of expertise and provides an appropriate universe. The generation unit can also generate a universe that is explained in simple terms if the user does not have technical expertise. The generation unit dynamically adjusts the use of technical terminology in the generated universe according to the user's level of expertise. Furthermore, the generation unit can adjust the use of technical terminology in the generated universe based on the user's level of expertise. The generation unit sets the use of technical terminology in the generated universe based on the user's level of expertise. This makes it possible to provide a universe that suits the user's level of expertise. Some or all of the above-mentioned processing in the generation unit may be performed using a generation AI, or may be performed without using a generation AI. For example, the generation unit can input the user's technical expertise data into the generation AI and have the generation AI suggest the optimal way to use technical terminology.

[0119] The providing unit can estimate the user's emotions and adjust the display method of the universe based on the emotions. For example, if the user is relaxed, the providing unit can provide a display method with soft colors and gentle movements. The providing unit captures the user's facial expression with a camera and estimates the emotion using an emotion estimation algorithm. For example, it calculates an emotion score based on changes in facial expression. The providing unit can also provide a display method with vivid colors and dynamic movements if the user is excited. The providing unit records the user's voice and estimates the emotion using voice analysis technology. For example, it analyzes the tone and speed of the voice and calculates an emotion score. The providing unit can also provide a display method with calm colors and quiet movements if the user is stressed. The providing unit collects the user's biometric data (heart rate and electrodermal activity) with a sensor and estimates the emotion using an emotion estimation algorithm. For example, it calculates an emotion score based on heart rate fluctuations. This allows the display method to be tailored to the user's emotions. Emotion estimation is achieved using an emotion estimation function, for example, an emotion engine or generative AI. The generation AI may be, but is not limited to, a text generation AI (e.g., LLM) or a multimodal generation AI. Some or all of the above-described processing in the providing unit may be performed using AI, or may be performed without using AI. For example, the providing unit may input user emotion data into the AI ​​and have the AI ​​suggest the optimal display method.

[0120] The providing unit can select the optimal delivery method by referring to the user's past usage history. The providing unit selects the optimal delivery method, for example, based on a display method used by the user in the past. The providing unit refers to past usage data and identifies a method that the user can use most effectively. The providing unit can also select the most effective delivery method from the user's past usage history. The providing unit suggests the optimal delivery method based on the past usage history. Furthermore, the providing unit can analyze the user's past usage history and select the optimal delivery method. The providing unit suggests a method that the user can use most effectively based on the past data. This makes it possible to provide the optimal delivery method based on the past usage history. Some or all of the above-mentioned processing in the providing unit may be performed using AI, or may be performed without using AI. For example, the providing unit can input the user's past usage data into AI and have the AI ​​suggest the optimal delivery method.

[0121] The providing unit can customize the content provided based on the user's current environment. For example, at night, the providing unit customizes the content provided to emphasize the arrangement of the starry sky. The providing unit analyzes the user's current environment (e.g., time of day and location) and provides appropriate content provided. Furthermore, when the user is in a specific location, the providing unit can customize the content provided to emphasize astronomical data related to that location. The providing unit provides related astronomical data based on the user's location information. Furthermore, the providing unit can dynamically customize the content provided based on the user's current environment. The providing unit instantly adjusts the content provided based on the user's environmental data. This allows the content provided to be based on the current environment. Some or all of the above-mentioned processing in the providing unit may be performed using AI, or may be performed without using AI. For example, the providing unit can input the user's environmental data into AI and have the AI ​​suggest optimal content provided.

[0122] The providing unit can improve the providing method by reflecting the user's feedback. For example, when the user provides feedback on the provided content, the providing unit improves the providing method based on the feedback. The providing unit analyzes the user's feedback and suggests an optimal providing method. The providing unit can also improve the providing method by referring to the user's past feedback. The providing unit adjusts the providing method based on the past feedback. Furthermore, the providing unit can analyze the user's feedback and dynamically improve the providing method. The providing unit instantly adjusts the providing method based on the feedback data. This makes it possible to provide a providing method based on the feedback. Some or all of the above-mentioned processing in the providing unit may be performed using AI or may be performed without using AI. For example, the providing unit can input the user's feedback data into AI and have the AI ​​suggest an optimal providing method.

[0123] The providing unit can estimate the user's emotions and prioritize the universes to be provided based on the emotions. For example, if the user is relaxed, the providing unit can prioritize providing universes with a high relaxing effect. The providing unit captures the user's facial expression with a camera and estimates the emotion using an emotion estimation algorithm. For example, the emotion score is calculated based on changes in facial expression. Furthermore, if the user is excited, the providing unit can prioritize providing universes that are visually stimulating. The providing unit records the user's voice and estimates the emotion using voice analysis technology. For example, the tone and speed of the voice are analyzed to calculate the emotion score. Furthermore, if the user is feeling stressed, the providing unit can prioritize providing universes with a calming atmosphere. The providing unit collects the user's biometric data (heart rate and electrodermal activity) with a sensor and estimates the emotion using an emotion estimation algorithm. For example, the emotion score is calculated based on heart rate fluctuations. This allows the prioritization of universes according to the user's emotions. Emotion estimation is achieved using an emotion estimation function, for example, an emotion engine or a generative AI. The generation AI may be, but is not limited to, a text generation AI (e.g., LLM) or a multimodal generation AI. Some or all of the above-described processing in the providing unit may be performed using AI, or may be performed without using AI. For example, the providing unit may input user emotional data into the AI ​​and have the AI ​​propose optimal universe priorities.

[0124] The providing unit can select the optimal providing method taking into account the user's geographical location information. For example, if the user is in a specific area, the providing unit selects a providing method that reflects the arrangement of the starry sky in that area. The providing unit analyzes the user's geographical location information and provides the optimal providing method. Furthermore, if the user is in a specific location, the providing unit can also select a providing method that reflects astronomical data related to that location. The providing unit provides related astronomical data based on the user's location information. Furthermore, the providing unit can select the optimal providing method based on the user's geographical location information. The providing unit automatically selects the optimal providing method based on the user's location data. This makes it possible to provide a providing method based on the geographical location information. Some or all of the above-mentioned processing in the providing unit may be performed using AI, or may be performed without using AI. For example, the providing unit can input the user's geographical location information into AI and have the AI ​​suggest the optimal providing method.

[0125] The providing unit can customize the content provided by analyzing the user's social media activity. For example, the providing unit customizes the content provided related to a location where the user has checked in on social media. The providing unit analyzes the user's social media activity and identifies related content provided. The providing unit can also analyze the user's social media posts and customize the related content provided. The providing unit automatically suggests related content provided based on the user's posts. Furthermore, the providing unit can customize the related content provided by referring to the activities of the user's friends on social media. The providing unit suggests related content provided based on activity data of the user's friends. This makes it possible to provide content provided based on social media activity. Some or all of the above-described processing by the providing unit may be performed using AI, or may be performed without using AI. For example, the providing unit can input the user's social media data into AI and have the AI ​​suggest optimal content provided.

[0126] The providing unit can customize the delivery method by reflecting the user's past feedback. The providing unit customizes the delivery method, for example, based on feedback provided by the user in the past. The providing unit analyzes the user's feedback and suggests an optimal delivery method. The providing unit can also customize the delivery method by referring to the user's past feedback. The providing unit adjusts the delivery method based on the past feedback. Furthermore, the providing unit can analyze the user's past feedback and dynamically customize the delivery method. The providing unit instantly adjusts the delivery method based on the feedback data. This makes it possible to provide a delivery method based on the past feedback. Some or all of the above-mentioned processing in the providing unit may be performed using AI, or may be performed without using AI. For example, the providing unit can input the user's feedback data into AI and have the AI ​​suggest an optimal delivery method. === Hard Collateral 1-1 === Each of the multiple elements including the above-mentioned reception unit, analysis unit, generation unit, and provision unit is realized, for example, by at least one of the smart device 14 and the data processing device 12. For example, the reception unit can input the characteristics of the universe desired by the user using the reception device 38 of the smart device 14. The analysis unit is realized by the specific processing unit 290 of the data processing device 12 and analyzes the characteristics input by the user. The generation unit is realized by the specific processing unit 290 of the data processing device 12 and generates the digital universe using a generation AI. The provision unit can provide the generated digital universe to the user using the output device 40 of the smart device 14. === Hard Collateral 1-2 === Each of the multiple elements including the above-mentioned reception unit, analysis unit, generation unit, and provision unit is realized, for example, by at least one of the smart glasses 214 and the data processing device 12. For example, the reception unit can input the characteristics of the universe desired by the user using the microphone 238 of the smart glasses 214. The analysis unit is realized by the specific processing unit 290 of the data processing device 12 and analyzes the characteristics input by the user. The generation unit is realized by the specific processing unit 290 of the data processing device 12 and generates the digital universe using a generation AI. The provision unit can provide the generated digital universe to the user using the speaker 240 of the smart glasses 214. === Hard Collateral 1-3 === Each of the multiple elements including the above-mentioned reception unit, analysis unit, generation unit, and provision unit is realized, for example, by at least one of the headset type terminal 314 and the data processing device 12. For example, the reception unit can input the characteristics of the universe desired by the user using the microphone 238 of the headset type terminal 314. The analysis unit is realized by the specific processing unit 290 of the data processing device 12 and analyzes the characteristics input by the user. The generation unit is realized by the specific processing unit 290 of the data processing device 12 and generates the digital universe using a generation AI. The provision unit can provide the generated digital universe to the user using the display 343 of the headset type terminal 314. === Hard Collateral 1-4 === Each of the multiple elements including the above-mentioned reception unit, analysis unit, generation unit, and provision unit is realized, for example, by at least one of the robot 414 and the data processing device 12. For example, the reception unit can input the characteristics of the universe desired by the user using the microphone 238 of the robot 414. The analysis unit is realized by the specific processing unit 290 of the data processing device 12 and analyzes the characteristics input by the user. The generation unit is realized by the specific processing unit 290 of the data processing device 12 and generates the digital universe using a generation AI. The provision unit can provide the generated digital universe to the user using the speaker 240 of the robot 414.

[0127] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0128] The reception unit can also provide related astronomical trivia and facts based on the user's input. For example, if the user selects a particular constellation, the historical background and myths related to that constellation can be displayed. If the user selects a planet, the unit can provide information on the latest scientific discoveries and exploration missions related to that planet. Furthermore, if the user inputs the shape of a galaxy, the unit can display interesting facts and observation data about that galaxy. This allows the user to deepen their knowledge of the universe. Some or all of the above-mentioned processing in the reception unit may be performed using AI, or may be performed without using AI. For example, the reception unit can input the user's input data into AI and have the AI ​​suggest the most appropriate trivia and facts.

[0129] The analysis unit can also suggest related astronomical events and observation opportunities based on the user's input. For example, if a user selects a particular constellation, it can suggest the best time and location for that constellation to be visible. If a user selects a planet, it can provide the next opportunity to observe that planet and suitable conditions for observation. Furthermore, if a user inputs the shape of a galaxy, it can provide information about astronomical events and research projects in which that galaxy can be observed. This allows the user to enjoy a realistic observation experience. Some or all of the above-mentioned processing in the analysis unit may be performed using AI, or may be performed without AI. For example, the analysis unit can input the user's input data into AI and have it suggest optimal observation opportunities.

[0130] The providing unit can also customize the generated digital universe according to the user's preferences. For example, if the user selects a specific color or theme, the visuals of the digital universe can be adjusted based on that theme. Also, if the user selects specific music or sound effects, the music or sound effects can be incorporated into the digital universe experience. Furthermore, if the user desires a specific interactive element, the element can be added to the digital universe. This allows the user to enjoy a more personalized universe experience. Some or all of the above-described processing in the providing unit may be performed using AI, or may be performed without AI. For example, the providing unit can input user preference data into AI and have the AI ​​suggest the optimal customization method.

[0131] The reception unit can also provide related astronomical simulations based on the user's input. For example, if the user selects a particular constellation, the formation process and evolution of that constellation can be displayed in a simulation. If the user selects a planet, the climate change and geological activity of that planet can be reproduced in a simulation. Furthermore, if the user inputs the shape of a galaxy, a simulation of the collision or merging of that galaxy can be provided. This allows the user to visually understand the dynamic changes in the universe. Some or all of the above-mentioned processing in the reception unit may be performed using AI, or may be performed without using AI. For example, the reception unit can input the user's input data into AI and have the AI ​​suggest the optimal simulation.

[0132] The generation unit can also estimate the user's emotions and adjust the generated space sound effects based on the emotions. For example, if the user is relaxed, the generation unit can provide sound effects that combine calm music and natural sounds. The generation unit captures the user's facial expressions with a camera and estimates the emotion using an emotion estimation algorithm. For example, it calculates an emotion score based on changes in facial expressions. If the user is excited, the generation unit can provide energetic music and sound effects. The generation unit records the user's voice and estimates the emotion using voice analysis technology. For example, it analyzes the tone and speed of the voice and calculates an emotion score. If the user is stressed, the generation unit can provide sound effects with a high relaxing effect. The generation unit collects the user's biometric data (heart rate and electrodermal activity) with a sensor and estimates the emotion using an emotion estimation algorithm. For example, it calculates an emotion score based on heart rate fluctuations. This allows the generation unit to provide sound effects that correspond to the user's emotions. Emotion estimation is achieved using an emotion estimation function, for example, an emotion engine or a generation AI. The generation AI can be, but is not limited to, a text generation AI (e.g., LLM) or a multimodal generation AI. Some or all of the above-described processing in the generation unit may be performed using AI, or may be performed without using AI. For example, the generation unit may input user emotion data into AI and have the AI ​​suggest optimal sound effects.

[0133] When using the generated digital universe for educational purposes, the providing unit can also incorporate interactive quizzes and tests. For example, if a user is learning about a particular constellation, a quiz about that constellation can be displayed, and if the user answers correctly, the user can proceed to the next level. Also, if a user is learning about types of planets, a test about that planet can be administered to check the user's understanding. Furthermore, if a user is learning about the shape of galaxies, interactive questions about that galaxy can be provided to deepen the user's learning. This can enhance the educational effect. Some or all of the above-mentioned processing by the providing unit may be performed using AI, or may be performed without using AI. For example, the providing unit can input the user's learning data into AI and have the AI ​​suggest optimal quizzes and tests.

[0134] The reception unit can also estimate the user's emotions and adjust the voice assistant of the input interface based on the emotions. For example, if the user is relaxed, the voice assistant can provide guidance in a calm voice. The reception unit captures the user's facial expressions with a camera and estimates the emotion using an emotion estimation algorithm. For example, it calculates an emotion score based on changes in facial expressions. Alternatively, if the user is excited, the voice assistant can provide guidance in an energetic voice. The reception unit records the user's voice and estimates the emotion using voice analysis technology. For example, it analyzes the tone and speed of the voice and calculates an emotion score. Alternatively, if the user is stressed, the voice assistant can provide guidance in a voice that has a relaxing effect. The reception unit collects the user's biometric data (heart rate and electrodermal activity) using a sensor and estimates the emotion using an emotion estimation algorithm. For example, it calculates an emotion score based on heart rate fluctuations. This allows the voice assistant to provide guidance according to the user's emotions. Emotion estimation is achieved using an emotion estimation function, for example, an emotion engine or generative AI. The generation AI may be, but is not limited to, a text generation AI (e.g., LLM) or a multimodal generation AI. Some or all of the above-described processing in the reception unit may be performed using AI, or may be performed without using AI. For example, the reception unit may input user emotion data into the AI ​​and have the AI ​​suggest the optimal voice assistant.

[0135] The analysis unit can also estimate the user's emotions and adjust the visual presentation of the analysis results based on the user's emotions. For example, if the user is relaxed, the analysis results can be displayed using calm colors and smooth animations. The analysis unit captures the user's facial expressions with a camera and estimates their emotions using an emotion estimation algorithm. For example, it calculates an emotion score based on changes in facial expressions. If the user is excited, the analysis results can be displayed using vivid colors and dynamic animations. The analysis unit records the user's voice and estimates their emotions using voice analysis technology. For example, it analyzes the tone and speed of the voice to calculate an emotion score. If the user is stressed, the analysis results can be displayed using calm colors and quiet animations. The analysis unit collects the user's biometric data (heart rate and electrodermal activity) using a sensor and estimates their emotions using an emotion estimation algorithm. For example, it calculates an emotion score based on heart rate fluctuations. This allows the system to provide visual analysis results that correspond to the user's emotions. Emotion estimation is achieved using an emotion estimation function, for example, an emotion engine or generative AI. The generation AI may be, but is not limited to, a text generation AI (e.g., LLM) or a multimodal generation AI. Some or all of the above-described processing in the analysis unit may be performed using AI, or may be performed without using AI. For example, the analysis unit may input user emotion data into the AI ​​and have the AI ​​propose the optimal visual representation.

[0136] The providing unit can also adjust the generated digital universe based on the user's health condition. For example, if the user needs relaxation, it can provide a universe with calm colors and quiet movements. Alternatively, if the user needs energy, it can provide a universe with vivid colors and dynamic movements. Furthermore, if the user is feeling stressed, it can provide a universe that combines music or natural sounds with a relaxing effect. This allows the user to have an optimal space experience according to their health condition. Some or all of the above-mentioned processing in the providing unit may be performed using AI, or may be performed without using AI. For example, the providing unit can input the user's health data into AI and have the AI ​​suggest the optimal space experience.

[0137] The reception unit can also provide relevant astronomical news and the latest information based on the user's input. For example, if the user selects a particular constellation, the latest observation results and research results related to that constellation are displayed. If the user selects a planet, the latest exploration missions and discoveries related to that planet can be provided. Furthermore, if the user inputs the shape of a galaxy, the latest research papers and observation data related to that galaxy can be provided. This allows the user to always be aware of the latest astronomical information. Some or all of the above-mentioned processing in the reception unit may be performed using AI, or may be performed without using AI. For example, the reception unit can input the user's input data into AI and have the AI ​​suggest the most appropriate news and the latest information.

[0138] The analysis unit can estimate the user's emotions and adjust the display method of the analysis results based on the emotions. For example, if the user is relaxed, detailed analysis results are displayed. The analysis unit captures the user's facial expressions with a camera and estimates the emotions using an emotion estimation algorithm. For example, an emotion score is calculated based on changes in facial expressions. If the user is in a hurry, a concise analysis result can be displayed. The analysis unit records the user's voice and estimates the emotions using voice analysis technology. For example, the tone and speed of the voice are analyzed to calculate an emotion score. If the user is excited, a visually appealing analysis result can be displayed. The analysis unit collects the user's biometric data (heart rate and electrodermal activity) using a sensor and estimates the emotions using an emotion estimation algorithm. For example, an emotion score is calculated based on heart rate fluctuations. This allows for a display method of the analysis results that corresponds to the user's emotions. Emotion estimation is achieved using an emotion estimation function, for example, an emotion engine or a generation AI. The generation AI can be, but is not limited to, a text generation AI (e.g., LLM) or a multimodal generation AI. Some or all of the above-described processing in the analysis unit may be performed using AI, or may be performed without using AI. For example, the analysis unit may input user emotion data into AI and have the AI ​​suggest the optimal display method.

[0139] The providing unit can also adjust the generated digital universe based on the user's health condition. For example, if the user needs relaxation, it can provide a universe with calm colors and quiet movements. Alternatively, if the user needs energy, it can provide a universe with vivid colors and dynamic movements. Furthermore, if the user is feeling stressed, it can provide a universe that combines music or natural sounds with a relaxing effect. This allows the user to have an optimal space experience according to their health condition. Some or all of the above-mentioned processing in the providing unit may be performed using AI, or may be performed without using AI. For example, the providing unit can input the user's health data into AI and have the AI ​​suggest the optimal space experience.

[0140] The reception unit can also provide relevant astronomical news and the latest information based on the user's input. For example, if the user selects a particular constellation, the latest observation results and research results related to that constellation are displayed. If the user selects a planet, the latest exploration missions and discoveries related to that planet can be provided. Furthermore, if the user inputs the shape of a galaxy, the latest research papers and observation data related to that galaxy can be provided. This allows the user to always be aware of the latest astronomical information. Some or all of the above-mentioned processing in the reception unit may be performed using AI, or may be performed without using AI. For example, the reception unit can input the user's input data into AI and have the AI ​​suggest the most appropriate news and the latest information.

[0141] The analysis unit can estimate the user's emotions and adjust the display method of the analysis results based on the emotions. For example, if the user is relaxed, detailed analysis results are displayed. The analysis unit captures the user's facial expressions with a camera and estimates the emotions using an emotion estimation algorithm. For example, an emotion score is calculated based on changes in facial expressions. If the user is in a hurry, a concise analysis result can be displayed. The analysis unit records the user's voice and estimates the emotions using voice analysis technology. For example, the tone and speed of the voice are analyzed to calculate an emotion score. If the user is excited, a visually appealing analysis result can be displayed. The analysis unit collects the user's biometric data (heart rate and electrodermal activity) using a sensor and estimates the emotions using an emotion estimation algorithm. For example, an emotion score is calculated based on heart rate fluctuations. This allows for a display method of the analysis results that corresponds to the user's emotions. Emotion estimation is achieved using an emotion estimation function, for example, an emotion engine or a generation AI. The generation AI can be, but is not limited to, a text generation AI (e.g., LLM) or a multimodal generation AI. Some or all of the above-described processing in the analysis unit may be performed using AI, or may be performed without using AI. For example, the analysis unit may input user emotion data into AI and have the AI ​​suggest the optimal display method.

[0142] The providing unit can also adjust the generated digital universe based on the user's health condition. For example, if the user needs relaxation, it can provide a universe with calm colors and quiet movements. Alternatively, if the user needs energy, it can provide a universe with vivid colors and dynamic movements. Furthermore, if the user is feeling stressed, it can provide a universe that combines music or natural sounds with a relaxing effect. This allows the user to have an optimal space experience according to their health condition. Some or all of the above-mentioned processing in the providing unit may be performed using AI, or may be performed without using AI. For example, the providing unit can input the user's health data into AI and have the AI ​​suggest the optimal space experience.

[0143] The reception unit can also provide relevant astronomical news and the latest information based on the user's input. For example, if the user selects a particular constellation, the latest observation results and research results related to that constellation are displayed. If the user selects a planet, the latest exploration missions and discoveries related to that planet can be provided. Furthermore, if the user inputs the shape of a galaxy, the latest research papers and observation data related to that galaxy can be provided. This allows the user to always be aware of the latest astronomical information. Some or all of the above-mentioned processing in the reception unit may be performed using AI, or may be performed without using AI. For example, the reception unit can input the user's input data into AI and have the AI ​​suggest the most appropriate news and the latest information.

[0144] The analysis unit can estimate the user's emotions and adjust the display method of the analysis results based on the emotions. For example, if the user is relaxed, detailed analysis results are displayed. The analysis unit captures the user's facial expressions with a camera and estimates the emotions using an emotion estimation algorithm. For example, an emotion score is calculated based on changes in facial expressions. If the user is in a hurry, a concise analysis result can be displayed. The analysis unit records the user's voice and estimates the emotions using voice analysis technology. For example, the tone and speed of the voice are analyzed to calculate an emotion score. If the user is excited, a visually appealing analysis result can be displayed. The analysis unit collects the user's biometric data (heart rate and electrodermal activity) using a sensor and estimates the emotions using an emotion estimation algorithm. For example, an emotion score is calculated based on heart rate fluctuations. This allows for a display method of the analysis results that corresponds to the user's emotions. Emotion estimation is achieved using an emotion estimation function, for example, an emotion engine or a generation AI. The generation AI can be, but is not limited to, a text generation AI (e.g., LLM) or a multimodal generation AI. Some or all of the above-described processing in the analysis unit may be performed using AI, or may be performed without using AI. For example, the analysis unit may input user emotion data into AI and have the AI ​​suggest the optimal display method.

[0145] The providing unit can also adjust the generated digital universe based on the user's health condition. For example, if the user needs relaxation, it can provide a universe with calm colors and quiet movements. Alternatively, if the user needs energy, it can provide a universe with vivid colors and dynamic movements. Furthermore, if the user is feeling stressed, it can provide a universe that combines music or natural sounds with a relaxing effect. This allows the user to have an optimal space experience according to their health condition. Some or all of the above-mentioned processing in the providing unit may be performed using AI, or may be performed without using AI. For example, the providing unit can input the user's health data into AI and have the AI ​​suggest the optimal space experience.

[0146] The reception unit can also provide relevant astronomical news and the latest information based on the user's input. For example, if the user selects a particular constellation, the latest observation results and research results related to that constellation are displayed. If the user selects a planet, the latest exploration missions and discoveries related to that planet can be provided. Furthermore, if the user inputs the shape of a galaxy, the latest research papers and observation data related to that galaxy can be provided. This allows the user to always be aware of the latest astronomical information. Some or all of the above-mentioned processing in the reception unit may be performed using AI, or may be performed without using AI. For example, the reception unit can input the user's input data into AI and have the AI ​​suggest the most appropriate news and the latest information.

[0147] The analysis unit can estimate the user's emotions and adjust the display method of the analysis results based on the emotions. For example, if the user is relaxed, detailed analysis results are displayed. The analysis unit captures the user's facial expressions with a camera and estimates the emotions using an emotion estimation algorithm. For example, an emotion score is calculated based on changes in facial expressions. If the user is in a hurry, a concise analysis result can be displayed. The analysis unit records the user's voice and estimates the emotions using voice analysis technology. For example, the tone and speed of the voice are analyzed to calculate an emotion score. If the user is excited, a visually appealing analysis result can be displayed. The analysis unit collects the user's biometric data (heart rate and electrodermal activity) using a sensor and estimates the emotions using an emotion estimation algorithm. For example, an emotion score is calculated based on heart rate fluctuations. This allows for a display method of the analysis results that corresponds to the user's emotions. Emotion estimation is achieved using an emotion estimation function, for example, an emotion engine or a generation AI. The generation AI can be, but is not limited to, a text generation AI (e.g., LLM) or a multimodal generation AI. Some or all of the above-described processing in the analysis unit may be performed using AI, or may be performed without using AI. For example, the analysis unit may input user emotion data into AI and have the AI ​​suggest the optimal display method.

[0148] The providing unit can also adjust the generated digital universe based on the user's health condition. For example, if the user needs relaxation, it can provide a universe with calm colors and quiet movements. Alternatively, if the user needs energy, it can provide a universe with vivid colors and dynamic movements. Furthermore, if the user is feeling stressed, it can provide a universe that combines music or natural sounds with a relaxing effect. This allows the user to have an optimal space experience according to their health condition. Some or all of the above-mentioned processing in the providing unit may be performed using AI, or may be performed without using AI. For example, the providing unit can input the user's health data into AI and have the AI ​​suggest the optimal space experience.

[0149] The reception unit can also provide relevant astronomical news and the latest information based on the user's input. For example, if the user selects a particular constellation, the latest observation results and research results related to that constellation are displayed. If the user selects a planet, the latest exploration missions and discoveries related to that planet can be provided. Furthermore, if the user inputs the shape of a galaxy, the latest research papers and observation data related to that galaxy can be provided. This allows the user to always be aware of the latest astronomical information. Some or all of the above-mentioned processing in the reception unit may be performed using AI, or may be performed without using AI. For example, the reception unit can input the user's input data into AI and have the AI ​​suggest the most appropriate news and the latest information.

[0150] The analysis unit can estimate the user's emotions and adjust the display method of the analysis results based on the emotions. For example, if the user is relaxed, detailed analysis results are displayed. The analysis unit captures the user's facial expressions with a camera and estimates the emotions using an emotion estimation algorithm. For example, an emotion score is calculated based on changes in facial expressions. If the user is in a hurry, a concise analysis result can be displayed. The analysis unit records the user's voice and estimates the emotions using voice analysis technology. For example, the tone and speed of the voice are analyzed to calculate an emotion score. If the user is excited, a visually appealing analysis result can be displayed. The analysis unit collects the user's biometric data (heart rate and electrodermal activity) using a sensor and estimates the emotions using an emotion estimation algorithm. For example, an emotion score is calculated based on heart rate fluctuations. This allows for a display method of the analysis results that corresponds to the user's emotions. Emotion estimation is achieved using an emotion estimation function, for example, an emotion engine or a generation AI. The generation AI can be, but is not limited to, a text generation AI (e.g., LLM) or a multimodal generation AI. Some or all of the above-described processing in the analysis unit may be performed using AI, or may be performed without using AI. For example, the analysis unit may input user emotion data into AI and have the AI ​​suggest the optimal display method.

[0151] The providing unit can also adjust the generated digital universe based on the user's health condition. For example, if the user needs relaxation, it can provide a universe with calm colors and quiet movements. Alternatively, if the user needs energy, it can provide a universe with vivid colors and dynamic movements. Furthermore, if the user is feeling stressed, it can provide a universe that combines music or natural sounds with a relaxing effect. This allows the user to have an optimal space experience according to their health condition. Some or all of the above-mentioned processing in the providing unit may be performed using AI, or may be performed without using AI. For example, the providing unit can input the user's health data into AI and have the AI ​​suggest the optimal space experience.

[0152] The reception unit can also provide relevant astronomical news and the latest information based on the user's input. For example, if the user selects a particular constellation, the latest observation results and research results related to that constellation are displayed. If the user selects a planet, the latest exploration missions and discoveries related to that planet can be provided. Furthermore, if the user inputs the shape of a galaxy, the latest research papers and observation data related to that galaxy can be provided. This allows the user to always be aware of the latest astronomical information. Some or all of the above-mentioned processing in the reception unit may be performed using AI, or may be performed without using AI. For example, the reception unit can input the user's input data into AI and have the AI ​​suggest the most appropriate news and the latest information.

[0153] The analysis unit can estimate the user's emotions and adjust the display method of the analysis results based on the emotions. For example, if the user is relaxed, detailed analysis results are displayed. The analysis unit captures the user's facial expressions with a camera and estimates the emotions using an emotion estimation algorithm. For example, an emotion score is calculated based on changes in facial expressions. If the user is in a hurry, a concise analysis result can be displayed. The analysis unit records the user's voice and estimates the emotions using voice analysis technology. For example, the tone and speed of the voice are analyzed to calculate an emotion score. If the user is excited, a visually appealing analysis result can be displayed. The analysis unit collects the user's biometric data (heart rate and electrodermal activity) using a sensor and estimates the emotions using an emotion estimation algorithm. For example, an emotion score is calculated based on heart rate fluctuations. This allows for a display method of the analysis results that corresponds to the user's emotions. Emotion estimation is achieved using an emotion estimation function, for example, an emotion engine or a generation AI. The generation AI can be, but is not limited to, a text generation AI (e.g., LLM) or a multimodal generation AI. Some or all of the above-described processing in the analysis unit may be performed using AI, or may be performed without using AI. For example, the analysis unit may input user emotion data into AI and have the AI ​​suggest the optimal display method.

[0154] The providing unit can also adjust the generated digital universe based on the user's health condition. For example, if the user needs relaxation, it can provide a universe with calm colors and quiet movements. Alternatively, if the user needs energy, it can provide a universe with vivid colors and dynamic movements. Furthermore, if the user is feeling stressed, it can provide a universe that combines music or natural sounds with a relaxing effect. This allows the user to have an optimal space experience according to their health condition. Some or all of the above-mentioned processing in the providing unit may be performed using AI, or may be performed without using AI. For example, the providing unit can input the user's health data into AI and have the AI ​​suggest the optimal space experience.

[0155] The reception unit can also provide relevant astronomical news and the latest information based on the user's input. For example, if the user selects a particular constellation, the latest observation results and research results related to that constellation are displayed. If the user selects a planet, the latest exploration missions and discoveries related to that planet can be provided. Furthermore, if the user inputs the shape of a galaxy, the latest research papers and observation data related to that galaxy can be provided. This allows the user to always be aware of the latest astronomical information. Some or all of the above-mentioned processing in the reception unit may be performed using AI, or may be performed without using AI. For example, the reception unit can input the user's input data into AI and have the AI ​​suggest the most appropriate news and the latest information.

[0156] The analysis unit can estimate the user's emotions and adjust the display method of the analysis results based on the emotions. For example, if the user is relaxed, detailed analysis results are displayed. The analysis unit captures the user's facial expressions with a camera and estimates the emotions using an emotion estimation algorithm. For example, an emotion score is calculated based on changes in facial expressions. If the user is in a hurry, a concise analysis result can be displayed. The analysis unit records the user's voice and estimates the emotions using voice analysis technology. For example, the tone and speed of the voice are analyzed to calculate an emotion score. If the user is excited, a visually appealing analysis result can be displayed. The analysis unit collects the user's biometric data (heart rate and electrodermal activity) using a sensor and estimates the emotions using an emotion estimation algorithm. For example, an emotion score is calculated based on heart rate fluctuations. This allows for a display method of the analysis results that corresponds to the user's emotions. Emotion estimation is achieved using an emotion estimation function, for example, an emotion engine or a generation AI. The generation AI can be, but is not limited to, a text generation AI (e.g., LLM) or a multimodal generation AI. Some or all of the above-described processing in the analysis unit may be performed using AI, or may be performed without using AI. For example, the analysis unit may input user emotion data into AI and have the AI ​​suggest the optimal display method.

[0157] The providing unit can also adjust the generated digital universe based on the user's health condition. For example, if the user needs relaxation, it can provide a universe with calm colors and quiet movements. Alternatively, if the user needs energy, it can provide a universe with vivid colors and dynamic movements. Furthermore, if the user is feeling stressed, it can provide a universe that combines music or natural sounds with a relaxing effect. This allows the user to have an optimal space experience according to their health condition. Some or all of the above-mentioned processing in the providing unit may be performed using AI, or may be performed without using AI. For example, the providing unit can input the user's health data into AI and have the AI ​​suggest the optimal space experience.

[0158] The reception unit can also provide relevant astronomical news and the latest information based on the user's input. For example, if the user selects a particular constellation, the latest observation results and research results related to that constellation are displayed. If the user selects a planet, the latest exploration missions and discoveries related to that planet can be provided. Furthermore, if the user inputs the shape of a galaxy, the latest research papers and observation data related to that galaxy can be provided. This allows the user to always be aware of the latest astronomical information. Some or all of the above-mentioned processing in the reception unit may be performed using AI, or may be performed without using AI. For example, the reception unit can input the user's input data into AI and have the AI ​​suggest the most appropriate news and the latest information.

[0159] The analysis unit can estimate the user's emotions and adjust the display method of the analysis results based on the emotions. For example, if the user is relaxed, detailed analysis results are displayed. The analysis unit captures the user's facial expressions with a camera and estimates the emotions using an emotion estimation algorithm. For example, an emotion score is calculated based on changes in facial expressions. If the user is in a hurry, a concise analysis result can be displayed. The analysis unit records the user's voice and estimates the emotions using voice analysis technology. For example, the tone and speed of the voice are analyzed to calculate an emotion score. If the user is excited, a visually appealing analysis result can be displayed. The analysis unit collects the user's biometric data (heart rate and electrodermal activity) using a sensor and estimates the emotions using an emotion estimation algorithm. For example, an emotion score is calculated based on heart rate fluctuations. This allows for a display method of the analysis results that corresponds to the user's emotions. Emotion estimation is achieved using an emotion estimation function, for example, an emotion engine or a generation AI. The generation AI can be, but is not limited to, a text generation AI (e.g., LLM) or a multimodal generation AI. Some or all of the above-described processing in the analysis unit may be performed using AI, or may be performed without using AI. For example, the analysis unit may input user emotion data into AI and have the AI ​​suggest the optimal display method.

[0160] The providing unit can also adjust the generated digital universe based on the user's health condition. For example, if the user needs relaxation, it can provide a universe with calm colors and quiet movements. Alternatively, if the user needs energy, it can provide a universe with vivid colors and dynamic movements. Furthermore, if the user is feeling stressed, it can provide a universe that combines music or natural sounds with a relaxing effect. This allows the user to have an optimal space experience according to their health condition. Some or all of the above-mentioned processing in the providing unit may be performed using AI, or may be performed without using AI. For example, the providing unit can input the user's health data into AI and have the AI ​​suggest the optimal space experience.

[0161] The reception unit can also provide relevant astronomical news and the latest information based on the user's input. For example, if the user selects a particular constellation, the latest observation results and research results related to that constellation are displayed. If the user selects a planet, the latest exploration missions and discoveries related to that planet can be provided. Furthermore, if the user inputs the shape of a galaxy, the latest research papers and observation data related to that galaxy can be provided. This allows the user to always be aware of the latest astronomical information. Some or all of the above-mentioned processing in the reception unit may be performed using AI, or may be performed without using AI. For example, the reception unit can input the user's input data into AI and have the AI ​​suggest the most appropriate news and the latest information.

[0162] The analysis unit can estimate the user's emotions and adjust the display method of the analysis results based on the emotions. For example, if the user is relaxed, detailed analysis results are displayed. The analysis unit captures the user's facial expressions with a camera and estimates the emotions using an emotion estimation algorithm. For example, an emotion score is calculated based on changes in facial expressions. If the user is in a hurry, a concise analysis result can be displayed. The analysis unit records the user's voice and estimates the emotions using voice analysis technology. For example, the tone and speed of the voice are analyzed to calculate an emotion score. If the user is excited, a visually appealing analysis result can be displayed. The analysis unit collects the user's biometric data (heart rate and electrodermal activity) using a sensor and estimates the emotions using an emotion estimation algorithm. For example, an emotion score is calculated based on heart rate fluctuations. This allows for a display method of the analysis results that corresponds to the user's emotions. Emotion estimation is achieved using an emotion estimation function, for example, an emotion engine or a generation AI. The generation AI can be, but is not limited to, a text generation AI (e.g., LLM) or a multimodal generation AI. Some or all of the above-described processing in the analysis unit may be performed using AI, or may be performed without using AI. For example, the analysis unit may input user emotion data into AI and have the AI ​​suggest the optimal display method.

[0163] The providing unit can also adjust the generated digital universe based on the user's health condition. For example, if the user needs relaxation, it can provide a universe with calm colors and quiet movements. Alternatively, if the user needs energy, it can provide a universe with vivid colors and dynamic movements. Furthermore, if the user is feeling stressed, it can provide a universe that combines music or natural sounds with a relaxing effect. This allows the user to have an optimal space experience according to their health condition. Some or all of the above-mentioned processing in the providing unit may be performed using AI, or may be performed without using AI. For example, the providing unit can input the user's health data into AI and have the AI ​​suggest the optimal space experience.

[0164] The reception unit can also provide relevant astronomical news and the latest information based on the user's input. For example, if the user selects a particular constellation, the latest observation results and research results related to that constellation are displayed. If the user selects a planet, the latest exploration missions and discoveries related to that planet can be provided. Furthermore, if the user inputs the shape of a galaxy, the latest research papers and observation data related to that galaxy can be provided. This allows the user to always be aware of the latest astronomical information. Some or all of the above-mentioned processing in the reception unit may be performed using AI, or may be performed without using AI. For example, the reception unit can input the user's input data into AI and have the AI ​​suggest the most appropriate news and the latest information.

[0165] The analysis unit can estimate the user's emotions and adjust the display method of the analysis results based on the emotions. For example, if the user is relaxed, detailed analysis results are displayed. The analysis unit captures the user's facial expressions with a camera and estimates the emotions using an emotion estimation algorithm. For example, an emotion score is calculated based on changes in facial expressions. If the user is in a hurry, a concise analysis result can be displayed. The analysis unit records the user's voice and estimates the emotions using voice analysis technology. For example, the tone and speed of the voice are analyzed to calculate an emotion score. If the user is excited, a visually appealing analysis result can be displayed. The analysis unit collects the user's biometric data (heart rate and electrodermal activity) using a sensor and estimates the emotions using an emotion estimation algorithm. For example, an emotion score is calculated based on heart rate fluctuations. This allows for a display method of the analysis results that corresponds to the user's emotions. Emotion estimation is achieved using an emotion estimation function, for example, an emotion engine or a generation AI. The generation AI can be, but is not limited to, a text generation AI (e.g., LLM) or a multimodal generation AI. Some or all of the above-described processing in the analysis unit may be performed using AI, or may be performed without using AI. For example, the analysis unit may input user emotion data into AI and have the AI ​​suggest the optimal display method.

[0166] The providing unit can also adjust the generated digital universe based on the user's health condition. For example, if the user needs relaxation, it can provide a universe with calm colors and quiet movements. Alternatively, if the user needs energy, it can provide a universe with vivid colors and dynamic movements. Furthermore, if the user is feeling stressed, it can provide a universe that combines music or natural sounds with a relaxing effect. This allows the user to have an optimal space experience according to their health condition. Some or all of the above-mentioned processing in the providing unit may be performed using AI, or may be performed without using AI. For example, the providing unit can input the user's health data into AI and have the AI ​​suggest the optimal space experience.

[0167] The processing flow of the second embodiment will be briefly explained below.

[0168] Step 1: The reception unit inputs the space characteristics desired by the user. The space characteristics desired by the user include, for example, the arrangement of stars, the type of planets, the shape of the galaxy, etc. The reception unit provides an interface for the user to specify the arrangement of stars, an option for selecting the type of planets, and a guide for inputting the shape of the galaxy. Step 2: The analysis unit analyzes the features received by the reception unit. The analysis unit analyzes the star arrangement, planet types, and galaxy shapes entered by the user, and generates data for generating an appropriate digital universe. Step 3: The generator generates a digital universe based on the characteristics analyzed by the analyzer. The generator digitally recreates a realistic universe based on astronomical data, meeting the user's needs. Using generative AI, it recreates the arrangement of stars, the types of planets, the shape of galaxies, and more in detail. Step 4: The providing unit provides the digital universe generated by the generating unit to the user. The providing unit provides the generated digital universe to the user through a planetarium or a VR device, and provides an interface that allows the user to visually experience it.

[0169] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0170] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> Examples of generative AIs include the data generation model 58, such as a neural network model (e.g., a neural network model), and a neural network model (e.g., a neural network model). The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating speech, text data indicating text, and image data indicating an image is also input to the data generation model 58. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specification processing unit 290 performs the above-mentioned specification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0171] Furthermore, the processing by the data processing system 10 described above is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart device 14, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart device 14. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the smart device 14 or an external device, etc., and the smart device 14 acquires or collects information necessary for processing from the data processing device 12 or an external device, etc.

[0172] The correspondence between each part and the device or control part is not limited to the example described above, and various modifications are possible.

[0173] [Second embodiment] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0174] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0175] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0176] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0177] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0178] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0179] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0180] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0181] 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.

[0182] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0183] In the smart glasses 214, the specific processing is performed by the processor 46. A specific processing program 60 is stored in the storage 50. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. The smart glasses 214 also have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0184] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0185] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0186] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AI other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0187] The data processing system 210 according to the second embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 210 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart glasses 214, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart glasses 214. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the smart glasses 214 or an external device, etc., and the smart glasses 214 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0188] The correspondence between each part and the device or control part is not limited to the example described above, and various modifications are possible.

[0189] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0190] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0191] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0192] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0193] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0194] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0195] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0196] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0197] 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.

[0198] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0199] In the headset type terminal 314, the identification process is performed by the processor 46. A identification program 60 is stored in the storage 50. The processor 46 reads the identification program 60 from the storage 50 and executes the read identification program 60 on the RAM 48. The identification process is realized by the processor 46 operating as a control unit 46A in accordance with the identification program 60 executed on the RAM 48. Note that the headset type terminal 314 has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can also perform processing similar to that of the identification processing unit 290 using these models.

[0200] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0201] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0202] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AI other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0203] The data processing system 310 according to the third embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 310 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the headset type terminal 314, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the headset type terminal 314. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the headset type terminal 314 or an external device, etc., and the headset type terminal 314 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0204] The correspondence between each part and the device or control part is not limited to the example described above, and various modifications are possible.

[0205] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0206] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0207] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0208] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[0209] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0210] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS image sensor or a CCD image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0211] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0212] The control 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 emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[0213] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0214] 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.

[0215] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0216] In the robot 414, the processor 46 performs the identification process. The storage 50 stores the identification program 60. The processor 46 reads the identification program 60 from the storage 50 and executes the read identification program 60 on the RAM 48. The identification process is realized by the processor 46 operating as the control unit 46A in accordance with the identification program 60 executed on the RAM 48. The robot 414 also has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can perform the same process as the identification processing unit 290 using these models.

[0217] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0218] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[0219] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AI other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0220] The data processing system 410 according to the fourth embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 410 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the robot 414, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the robot 414. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the robot 414 or an external device, etc., and the robot 414 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0221] The correspondence between each part and the device or control part is not limited to the example described above, and various modifications are possible.

[0222] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0223] FIG. 9 illustrates an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and behaviors arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion encompasses both emotions and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[0224] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[0225] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[0226] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is expressed, and when they approach the ideal, a state of pleasure is expressed. Emotions can also be created for robots, cars, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is expressed, and when they approach the ideal, a state of pleasure is expressed. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on speech emotion recognition and brain physiological signal analysis systems for emotions, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[0227] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[0228] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[0229] In the above embodiment, an example was given in which a specific process is performed by one computer 22, but the technology disclosed herein is not limited to this, and distributed processing of the specific process may be performed by multiple computers including computer 22.

[0230] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[0231] 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.

[0232] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[0233] The hardware resource for executing a specific process can be any of the following types of processors: A processor, for example, is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. A processor also includes a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[0234] The hardware resource that executes the specific process may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific process may be a single processor.

[0235] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[0236] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[0237] In the above example, the first to fourth embodiments have been described separately, but some or all of these embodiments may be combined. The smart device 14, smart glasses 214, headset terminal 314, and robot 414 are merely examples, and they may be combined, or other devices may be used. In the above example, the first and second embodiments have been described separately, but they may be combined.

[0238] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[0239] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[0240] [Explanation of symbols]

[0241] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot

Claims

1. a reception unit for inputting desired space characteristics by a user; an analysis unit that analyzes the features accepted by the acceptance unit; a generation unit that generates a digital universe based on the features analyzed by the analysis unit; a providing unit that provides the digital universe generated by the generating unit to a user. A system characterized by:

2. The generation unit Generating a digital universe based on astronomical data 2. The system of claim 1.

3. The providing unit The generated digital universe will be provided to users through planetariums and VR devices.

2. The system of claim 1.

4. The reception unit The user inputs the star arrangement, planet types, and galaxy shape characteristics.

2. The system of claim 1.

5. The generation unit Digitally recreate a realistic universe that meets the user's needs 2. The system of claim 1.

6. The providing unit The generated digital universe will be used for astronomy education and creating a relaxing space.

2. The system of claim 1.

7. The reception unit Estimate user emotions and adjust the design of the input interface based on the estimated user emotions.

2. The system of claim 1.

8. The reception unit Analyzes the user's past input history and suggests input methods 2. The system of claim 1.

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