system

Abstract

We provide the system. [Solution] A data collection means for receiving environmental and biometric information obtained from the user, An analysis means analyzes the data received from the data collection means and determines the user's state, Content generation means that generates virtual reality content based on the user's state determined by the analysis means, A means for transmitting generated virtual reality content to users, An adaptive mechanism that receives user interaction and dynamically adjusts content based on it, A means that enables the generation of virtual reality content related to the surrounding physical environment based on location information, A system that includes this.

Description

Technical Field

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

Background Art

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

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] By effectively integrating the real world and the virtual world, it is required to provide users with a seamless and personalized immersive experience. Such integration is a very difficult technical problem because it is necessary to collect and analyze information in real time from multiple data sources. In addition, the generation of adaptive virtual reality content that responds immediately to the user's state is not sufficiently provided by the current technology. Against this background, there is a need to develop a system that provides a flexible and real-time virtual reality experience according to the needs and states of individual users.

Means for Solving the Problems

[0005] This invention provides a system that accurately determines the user's state by utilizing and analyzing environmental and biometric information acquired from the user. Specifically, it includes data collection means that collect environmental and biometric data in real time using sensors and transfer it to a server. The server then analyzes the data and generates virtual reality content tailored to the user's state. The generated content is delivered to the user's terminal via a transmission means. Furthermore, this system includes adaptive means that receive interaction information from the user and dynamically adjust the content based on it. This makes it possible to provide the user with an optimal virtual reality experience.

[0006] "Data collection means" refers to equipment and technologies used to acquire environmental and biometric information from users.

[0007] "Analysis means" refers to algorithms and processing equipment used to determine the user's state and needs based on collected data.

[0008] "Content generation means" refers to systems and technologies that create virtual reality content optimized for a user based on an analyzed user state.

[0009] "Transmission means" refers to the communication protocols and equipment used to deliver generated virtual reality content to the user's device.

[0010] "Adaptive measures" refer to technologies and systems for dynamically adjusting and modifying virtual reality content in response to user interaction.

[0011] "Environmental data" refers to data about external conditions, including information such as the user's geographical location, sound, and light.

[0012] "Biometric information" refers to data about the user's physical condition, including heart rate, gaze, and facial orientation.

[0013] "Interaction" refers to the actions and behaviors that a user performs within a virtual reality environment, and the feedback that the system receives as a result. [Brief explanation of the drawing]

[0014] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] This is a sequence diagram showing the processing flow of the data processing system in Example 2, when an emotion engine is combined. [Figure 14]It is a sequence diagram showing the processing flow of a data processing system in Application Example 2 when a sentiment engine is combined.

Embodiments for Carrying Out the Invention

[0015] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0016] First, the terms used in the following description will be explained.

[0017] In the following embodiments, a processor with a reference number (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0018] In the following embodiments, a RAM (Random Access Memory) with a reference number is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0019] In the following embodiments, a storage with a reference number is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, and the like.

[0020] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0021] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0022] [First Embodiment]

[0023] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0024] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0025] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0026] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0027] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0028] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0029] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0030] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0031] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0032] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0033] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0034] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0035] This invention relates to a system that provides a virtual reality (VR) experience using smart glasses. The user wears smart glasses and collects environmental data and biometric information through sensors built into the device. This includes environmental data such as location information, sound, and lighting conditions, as well as biometric information such as heart rate, gaze, and face orientation.

[0036] The device sends this information to the server. The server analyzes the user's stress level and interests based on the received data. Next, based on the analysis results, it generates virtual reality content to optimize the user's state. For example, if the user is feeling stressed, it generates content that includes relaxing natural scenery and music.

[0037] The server sends the generated content to the device, which then displays it on the user's smart glasses. This allows the user to easily and seamlessly transition from the physical world to a virtual environment, enjoying a personalized experience. Furthermore, the user's gaze and gestures within the virtual environment enable an even more interactive experience.

[0038] A concrete example is in an educational setting, where users (for example, students) can virtually visit historical sites. In this case, they can move their gaze to display detailed information or use gestures to zoom in on specific areas. Such interactions are realized through adaptive mechanisms where the server receives user interaction information and dynamically adjusts the content based on that information.

[0039] As a result, the present invention provides users with a highly personalized and immersive virtual reality experience, demonstrating its usefulness in a variety of situations.

[0040] The following describes the processing flow.

[0041] Step 1:

[0042] The user puts on smart glasses and begins operating the device. The device activates sensors and collects environmental data (location, sound, lighting conditions) and biometric information (heart rate, gaze, face orientation) in real time.

[0043] Step 2:

[0044] The device transmits collected environmental data and biometric information to the server. Secure communication protocols are used to ensure data security during transmission.

[0045] Step 3:

[0046] The server analyzes the received data to determine the user's state. At this stage, a learning algorithm is used to evaluate, for example, the user's stress level and areas of interest.

[0047] Step 4:

[0048] Based on the analysis results, the server generates virtual reality content suitable for the user's state. If the goal is relaxation, it selects content depicting calming natural scenery; if the goal is learning, it generates relevant educational content.

[0049] Step 5:

[0050] The server sends the generated virtual reality content to the terminal. Here too, data compression and stream formats are used to improve communication efficiency.

[0051] Step 6:

[0052] The device displays the transmitted content on the user's smart glasses, allowing the user to immerse themselves in a virtual world. The user can interact within this virtual reality space using gaze and gestures.

[0053] Step 7:

[0054] User interaction information is retransmitted to the server via the device, and the server analyzes this information to dynamically adapt the content. This makes it possible to continuously improve the quality of the user experience.

[0055] (Example 1)

[0056] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0057] Current virtual reality systems offer a limited user experience and fail to adequately personalize the experience based on stress levels and interests. As a result, users struggle to become immersed, and the effectiveness of interactions within virtual reality is limited. This challenge stems from a lack of real-time data analysis and dynamic adjustments through interaction.

[0058] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0059] In this invention, the server includes data collection means for receiving environmental information, including location, acoustic and light information, and biometric information, including heart rate, gaze and face orientation information, data collection means for receiving environmental information and biometric information received from the data collection means and determining the user's stress level and interests using a generating AI model, and content generation means for generating virtual reality content, including natural scenery and music, based on the user's stress level and interests determined by the analysis means. This makes it possible to provide a personalized virtual reality experience that is tailored to the individual state of the user.

[0060] "Data collection means" refers to a function for receiving environmental information, including location, acoustic and light information, and biometric information, including heart rate, gaze, and facial orientation information, acquired from the user.

[0061] The "analysis means" refers to a function that uses a generated AI model, based on received environmental and biometric information, to determine the user's stress level and areas of interest.

[0062] The "content generation means" is a function that generates virtual reality content, including natural scenery and music, based on the user's stress level and interests determined by the analysis means.

[0063] "Transmission means" refers to the functionality for delivering generated virtual reality content to users using encryption protocols.

[0064] "Adaptive measures" refer to functions that receive user interactions, including gaze and gestures, and dynamically adjust content using a generative AI model based on that information.

[0065] A "generative AI model" refers to a model that uses artificial intelligence to analyze data and make decisions or generate specific information.

[0066] A "prompt sentence" is a sentence that is input into a generative AI model to instruct it to perform a specific analysis or generation.

[0067] The embodiments for carrying out this invention are as follows.

[0068] The user wears smart glasses and uses a terminal to collect environmental and biometric information. The terminal incorporates a GPS-enabled location device, microphone sensor, light sensor, and built-in heart rate sensor, eye tracking sensor, accelerometer, and gyroscope, which are used to acquire data in real time. This data includes environmental information such as location, sound, and light, as well as biometric information such as heart rate, gaze, and facial orientation.

[0069] The device sends the collected data to the server. The server analyzes the data using a generative AI model to determine the user's stress level and interests. The analysis is performed using prompts to instruct the server on the environments in which the user experiences stress. For example, the prompt might be "Generate content that calms the user." This allows the AI ​​model to estimate the user's state and obtain information to generate appropriate virtual reality content.

[0070] Based on the analysis results, the server constructs virtual reality content tailored to the user's state. This content generation uses techniques that combine natural scenery and relaxing sounds. The generated content is then transmitted to the terminal using an encryption protocol.

[0071] The device displays the received content on the smart glasses, allowing the user to begin an immersive experience. For example, to alleviate stress, the user's field of vision could be filled with images of a clear blue sky or a tranquil seaside landscape. Furthermore, the user can interact with the virtual environment using eye movements and gestures. For instance, moving their gaze could display information, or specific movements could zoom in on the scene.

[0072] This system allows users to experience comfort and interest through personalized virtual reality experiences. The aim of this invention is to enable users to enjoy a richer experience.

[0073] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0074] Step 1:

[0075] The device acquires information about the user's surroundings using a location tracking device, microphone sensor, and light sensor built into the smart glasses. This information includes the user's current location, ambient sound, and light intensity. Furthermore, it collects biometric information such as heart rate, gaze, and face orientation using a heart rate sensor, eye tracking sensor, accelerometer, and gyroscope. This provides a detailed dataset in real time, preparing for the next steps.

[0076] Step 2:

[0077] The device encrypts the environmental and biometric information collected in Step 1 and sends it to the server. Encryption uses protocols to ensure the security of the communication. The server decodes the received data and converts it into a format suitable for analysis. This prepares the server to evaluate the user's state based on a high-quality, reliable dataset.

[0078] Step 3:

[0079] The server uses a generative AI model to analyze the data received in step 2. Based on environmental and biometric information as input, it estimates the user's stress level and areas of interest. During this process, the prompt "Generate content that calms the user" is used to instruct the AI ​​model. As an output of the analysis, hypotheses about the user's mental state are obtained, forming insights necessary for generating the next content.

[0080] Step 4:

[0081] Based on the analysis results obtained in Step 3, the server generates virtual reality content tailored to the user's state. This process involves selecting natural scenery and relaxing music, constructing scenes, and integrating sound data. The generated content is meticulously designed to provide the user with the utmost comfort and peace of mind.

[0082] Step 5:

[0083] The server sends the generated content back to the device. The device receives this content and displays it in the appropriate format on the smart glasses. This leads the user into an immersive virtual environment, allowing them to enjoy a new experience adapted to their mental state.

[0084] Step 6:

[0085] Users interact within a virtual environment, manipulating the scene by making eye contact and using gestures. The device sends these actions to the server in real time, which uses an AI model to perform additional analysis and dynamically adjust the content to provide the user with an even more personalized experience.

[0086] (Application Example 1)

[0087] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0088] In the real world, there is a challenge in that it is difficult for users to individually experience information related to specific places or environments. Typically, users need to research many sources themselves to obtain educational or cultural information. However, if they can intuitively and interactively experience information relevant to their situation in real time, educational efficiency and information accessibility will improve.

[0089] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0090] In this invention, the server includes data collection means for receiving environmental and biometric information acquired from the user, analysis means for analyzing the data and determining the user's state, and means for generating virtual reality content related to the surrounding physical environment based on location information. As a result, the user can receive relevant information as a VR experience at each location, enabling real-time interactive learning and information acquisition.

[0091] "Data collection means" refers to means for acquiring environmental and biometric information from users and transmitting it to a server or similar device.

[0092] "Analysis means" refers to a process or system that evaluates and determines the user's psychological or physiological state based on received environmental and biological information.

[0093] "Content generation means" refers to a process or device that creates virtual reality content based on analysis results such as the user's state and location information.

[0094] "Transmission means" refers to the infrastructure that sends generated virtual reality content to a user's terminal and allows the user to view or experience that content.

[0095] "Adaptive means" refers to a process or device for dynamically changing content in real time based on user interaction to optimize the user experience.

[0096] "Means for generating virtual reality content related to the surrounding physical environment based on location information" refers to a method or apparatus that utilizes the user's geographical location and surrounding environment data to create and provide virtual content related to that location to the user.

[0097] The system for realizing this invention collects the user's environment and biometric information and provides a personalized virtual reality experience based on that information. Details are described below.

[0098] Smart glasses are equipped with a variety of sensors to collect environmental data such as the user's location, sound, and lighting conditions, as well as biometric information such as heart rate, gaze, and facial orientation. This data is temporarily processed within the device and then transmitted to a server via a high-speed network.

[0099] The server executes an analysis algorithm written in a programming language such as Python to analyze the received information. In this process, the user's stress level and areas of interest are determined. Based on the analysis results, the server generates user-specific virtual reality content using a generative AI model (e.g., ChatGPT® API).

[0100] The content integrates elements related to the user's current geographical location and surrounding environment, thereby providing historical events and educational information relevant to the user's real-world location. The generated content is transmitted to the user's smart glasses using VR content development platforms such as Unity or Unreal Engine.

[0101] A concrete example of content generation in this process is providing a 30-second video explaining the history of a place when a user visits a historical landmark. An example of a prompt to the generation AI model is, "Generate a video of 30 seconds or less explaining the historical background of the user's current location."

[0102] This allows users to enjoy interactive and educational experiences tailored to their location.

[0103] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0104] Step 1:

[0105] The device collects the user's environmental and biometric information through the sensors in the smart glasses. This includes environmental data such as location, sound, and lighting conditions, and biometric information such as heart rate, gaze, and face orientation. This data is first temporarily stored on the device (input). The device then transmits this data to a server via a high-speed network (output).

[0106] Step 2:

[0107] The server uses a programming language such as Python to analyze the received data (input). The analysis process combines gaze direction and heart rate data to evaluate the user's stress level and areas of interest (data calculation). Based on these results, the server determines the user's current psychological and physiological state (output).

[0108] Step 3:

[0109] The server generates virtual reality content using a generative AI model based on the analysis results (input). It prompts the generative AI model (e.g., ChatGPT API) to design content that matches the user's interests and stress levels (data processing). For example, it might use a prompt like, "Generate a video of 30 seconds or less showing the historical background of the user's current location" (prompt statement). As a result, customized content for the user is output.

[0110] Step 4:

[0111] The generated content is converted to a format suitable for the user's smart glasses using VR content development platforms such as Unity or Unreal Engine (input). During this conversion process, the content is adjusted to maximize the visual and auditory experience in virtual reality (specific actions). The converted content is then sent to the device (output).

[0112] Step 5:

[0113] The device displays the received virtual reality content on the smart glasses (input). The user can view this content and interact with it using gaze and gestures (specific actions). User interactions are recorded in real time on the device and fed back to the server as needed, which then adjusts the content (output).

[0114] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0115] This invention relates to a system that recognizes a user's emotions and dynamically adjusts the virtual reality experience based on them. The user wears smart glasses, and a terminal collects environmental data and biometric information in real time. During this process, sensors detect location, sound, and lighting conditions, and acquire data such as heart rate, gaze, and face orientation.

[0116] The device sends this information to the server. On the server, an emotion engine analyzes the user's emotions based on the received data. This analysis is performed by using a specific algorithm to classify the user's emotional state as, for example, "relaxed," "stressed," or "excited."

[0117] Based on the analysis results, the server generates appropriate virtual reality content according to the situation. For example, if the user's emotion is determined to be "stress," the server prepares a relaxing virtual environment and generates content that includes calming music and scenery.

[0118] The generated content is sent from the server to the device, which displays it on the user's smart glasses. The user interacts with the system through actions and gaze within the virtual reality environment. The device then sends data about these interactions back to the server, which analyzes the data and dynamically adjusts the content. This allows the user to obtain an optimal virtual reality experience that matches their emotional state at the time.

[0119] As a concrete example, let's consider its application in an educational setting. If a user (for example, a student) enters a virtual library to prepare for an exam and feels stressed by the situation, the emotion engine will analyze this as "stress." The server will immediately switch to a relaxing virtual landscape, providing the user with an environment where they can concentrate on learning. This process enables a flexible and customized experience that can respond to the user's emotional state.

[0120] The following describes the processing flow.

[0121] Step 1:

[0122] The user puts on smart glasses and activates the virtual reality system. The device collects environmental data and biometric information in real time through its built-in sensors. Environmental data includes location information, ambient sound, and light intensity, while biometric information includes heart rate, gaze direction, and facial expressions.

[0123] Step 2:

[0124] The device sends the collected data to the server. A secure communication protocol is used for transmission, ensuring data integrity and privacy.

[0125] Step 3:

[0126] The server analyzes the received data. The emotion engine evaluates the user's emotions based on the user's biometric information, determining, for example, whether the user is feeling "relaxed" or "stressed."

[0127] Step 4:

[0128] The server uses the results of the emotion engine's analysis to generate virtual reality content best suited to the user's current emotional state. If the server determines that the user is stressed, it will generate content that includes relaxing natural scenery and calming music.

[0129] Step 5:

[0130] The server sends the generated content to the device, which then displays it on the user's smart glasses. During this process, the video and audio are played smoothly to ensure a seamless and immersive experience for the user.

[0131] Step 6:

[0132] Users interact within the displayed virtual environment using gaze and gestures. For example, they can select specific objects using their gaze or manipulate them with gestures.

[0133] Step 7:

[0134] User interaction data is sent back to the server via the device, where it is analyzed and the content is dynamically adjusted as needed. This ensures that the user's emotional state and needs are continuously met, providing a truly responsive experience.

[0135] (Example 2)

[0136] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0137] In the modern era, virtual experiences in digital environments are becoming increasingly diverse, and there is a demand for customized experiences tailored to the individual user's state. However, conventional virtual experience systems have the problem of difficulty in dynamically adjusting content to adequately reflect the user's real-time emotions and biometric information. This invention aims to solve this problem and provide a system that allows users to obtain the optimal experience at that moment.

[0138] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0139] In this invention, the server includes information gathering means for receiving environmental and biometric information acquired from the user, state analysis means for analyzing the information received from the information gathering means and determining the user's state, and experience generation means for generating virtual experience content based on the user's state determined by the state analysis means. This makes it possible to dynamically provide an experience that is suitable for the user's real-time state.

[0140] "Information gathering means" refers to a device or software that has the function of acquiring environmental and biometric information from a user.

[0141] "State analysis means" refers to a device or software that has the function of analyzing collected information and determining the user's emotions and biological state.

[0142] "Experience generation means" refers to a device or software that has the function of constructing virtual experience content based on the results of user state analysis.

[0143] "Display means" refers to a device or software that has the function of presenting generated virtual experience content to a user.

[0144] "Adjustment means" refers to a device or software that has the function of receiving responses from users and dynamically adjusting the virtual experience based on those responses.

[0145] A "detection device" is a device that includes sensors and other components for collecting environmental and biological information in real time.

[0146] A "virtual experience" refers to a simulated environment or situation created for a user using a computer system.

[0147] This invention is a system that recognizes the user's emotions in real time and dynamically adjusts the virtual experience based on those emotions. The user uses a smart device, and various sensors built into the device collect environmental and biometric information. This includes location information, sound environment, lighting conditions, heart rate, gaze, and facial orientation.

[0148] The terminal is responsible for immediately transmitting this information to the server. The server analyzes the received data and classifies the user's emotions using an emotion engine with a generative AI model. Emotion analysis is performed by classifying the user's emotions into states such as "relaxed," "stressed," and "excited."

[0149] Based on the analysis results, the server generates content to adjust the virtual experience. For example, if stress is detected, it might create a virtual space that includes relaxing ambient sounds and scenery. This allows the system to quickly adapt to the user's desired experience.

[0150] The generated virtual experience content is displayed on the user's smart device via a terminal. The user interacts with the system through their gaze and movements within the virtual space. This movement information is collected again and sent to the server to be used to dynamically adjust the virtual experience.

[0151] A concrete example is its use in educational settings. If a user experiences stress while preparing for an exam in a virtual library, the system can instantly switch to a calm and quiet environment, providing a state conducive to focused learning. This allows for flexible responses tailored to individual emotional states.

[0152] Example of a prompt:

[0153] "When students feel stressed in the virtual library, how do you transform the environment into a more relaxing one?"

[0154] This system is a modern approach that utilizes generative AI models to provide users with the optimal virtual experience in real time.

[0155] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0156] Step 1:

[0157] The user wears a smart device and begins the virtual experience. The device uses built-in sensors to collect environmental information and biometric information in real time, including the user's location, sound environment, lighting conditions, heart rate, gaze, and face orientation. The input is the user's environmental data and biometric information, and the output is this collected data. Specifically, the gaze tracking sensor captures the user's gaze direction, and the heart rate sensor measures the heart rate.

[0158] Step 2:

[0159] The device transmits the collected data to the server. The input is a set of collected environmental and biometric data, and the output is this data converted into transmission data packets. Specifically, the device uploads the data to the server via high-speed Wi-Fi, minimizing data transfer delays.

[0160] Step 3:

[0161] The server analyzes the received data and estimates the user's emotions using a generative AI model. This process utilizes an emotion engine. The input consists of transmitted environmental data and biometric information, and the output is the estimated emotional state of the user. Specifically, the emotion engine analyzes heart rate and eye movement patterns and classifies the emotional state into one of three categories: "relaxed," "stressed," or "excited."

[0162] Step 4:

[0163] The server generates virtual experience content based on the user's emotional state. The input is the estimated emotional state, and the output is the corresponding virtual experience content. Specifically, if a stressed state is detected, the server synthesizes content including relaxing music and scenery to adjust the virtual space.

[0164] Step 5:

[0165] The server sends the generated virtual experience content to the terminal. The input is the generated virtual experience content, and the output is the content converted into display data. Specifically, the server sends the content data to the terminal, which then prepares to display it on a smart device.

[0166] Step 6:

[0167] Users interact within a virtual space. Input is the displayed virtual content, and output is interaction data based on the user's gaze and movements. Specific actions include the user selecting a particular virtual object using their gaze.

[0168] Step 7:

[0169] The terminal collects user interaction data and sends it to the server. The input is user interaction data, and the output is data packets for transmission. Specifically, the terminal detects user movements and changes in gaze, organizes the data based on these, and sends it to the server.

[0170] Step 8:

[0171] The server dynamically adjusts the virtual experience content based on user interaction. The input is user interaction data, and the output is the updated virtual experience content. Specifically, if the server determines that the user has entered a relaxed state, it switches to content containing a wider variety of stimuli.

[0172] (Application Example 2)

[0173] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0174] Current in-home service robots struggle to flexibly adapt their actions to the user's emotional state. Therefore, it's difficult to provide services appropriate to a user's state, such as when they are stressed or seeking relaxation. Consequently, there is a need to develop a system that can recognize the user's emotional state in real time and dynamically adjust the in-home environment and services accordingly.

[0175] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0176] In this invention, the server includes data collection means for receiving environmental and biometric information acquired from the user, analysis means for analyzing the data received from the data collection means and determining the user's state, and content generation means for generating and dynamically adjusting virtual reality content based on the user's state determined by the analysis means. This enables dynamic adjustment of the home environment in accordance with the user's emotional state and the provision of appropriate services.

[0177] "Data collection means" refers to a device or function for receiving environmental information and biometric information acquired from users.

[0178] "Analysis means" refers to a function or program that determines the user's emotions or state based on data obtained from data collection means.

[0179] "Content generation means" refers to a device or function that generates virtual reality content suitable for the user's state based on analysis results, and further dynamically adjusts it.

[0180] "Transmission means" refers to a device or function for delivering generated virtual reality content to a user's device.

[0181] "Behavior control means" refers to a device or function that controls the home environment or the provision of services based on the user's emotional state.

[0182] The system implementing this invention mainly consists of data collection means, analysis means, content generation means, transmission means, and behavior control means. Specifically, a robot installed in a home is central to this system.

[0183] The system program operates as follows: As a data collection method, smart glasses acquire the user's environmental information (sound and lighting) and biometric information (heart rate, gaze, face orientation) in real time. This data is received by a robot and analyzed to determine the user's emotional state (e.g., relaxed, stressed, excited).

[0184] The analyzed information is formed into virtual reality content tailored to the user's state by a content generation means. The generated content is delivered to a robot via a transmission means, and the user experiences virtual reality through smart glasses.

[0185] Furthermore, the behavioral control system enables the robot to provide in-home services based on the user's emotional state. If the user shows signs of stress, the robot can play calming music or change the lighting to create a relaxing environment.

[0186] The operation of this system is realized by a generating AI model in the form of specific prompt statements, such as, "Please provide specific suggestions on how the robot can create a relaxing environment when the user is feeling stressed." This allows for flexible responses that are tailored to the user's emotions.

[0187] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0188] Step 1:

[0189] The device acquires user environmental information (sound, lighting) and biometric information (heart rate, gaze, face orientation) through smart glasses. The input is real-time data from sensors, and the output is aggregated raw data. This data is transferred to a server for later analysis.

[0190] Step 2:

[0191] The server processes the raw data received by the data collection means using the analysis means. The input data consists of environmental and biometric information aggregated in step 1, and by applying this to the analysis algorithm, the user's emotional state (relaxed, stressed, excited, etc.) is obtained as output. This analysis process is performed in real time, and the user's state is continuously monitored.

[0192] Step 3:

[0193] The server generates appropriate virtual reality content using content generation means based on the user's emotional state obtained by the analysis means. The input is the user's emotional state, and the output is a virtual environment (such as calming music or scenery) that is suitable for that state. This generation is performed dynamically to optimize the user experience.

[0194] Step 4:

[0195] The generated virtual reality content is returned to the terminal via a transmission method and displayed on the user's smart glasses. The input is the virtual reality content generated in step 3, and the output is the content that the user visually experiences. This allows the user to experience a virtual reality space that matches their emotional state.

[0196] Step 5:

[0197] The user interacts through actions and gaze within the virtual reality environment, and the device sends this new data back to the server. The input here is the user's interaction data, and the output is received by the server again as data for analysis in the next processing step.

[0198] Step 6:

[0199] The server uses behavioral control means to control the robot so that it provides in-home services that correspond to the user's emotional state. The inputs are the emotional state data analyzed in step 2 and the interaction data obtained in step 5, and the output is the robot's specific actions (e.g., playing music, adjusting the lighting). This enables the provision of services that are in line with the user's emotional state.

[0200] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0201] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0202] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0203] [Second Embodiment]

[0204] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0205] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0206] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0207] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0208] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0209] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0210] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0211] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0212] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0213] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0214] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0215] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0216] This invention relates to a system that provides a virtual reality (VR) experience using smart glasses. The user wears smart glasses and collects environmental data and biometric information through sensors built into the device. This includes environmental data such as location information, sound, and lighting conditions, as well as biometric information such as heart rate, gaze, and face orientation.

[0217] The device sends this information to the server. The server analyzes the user's stress level and interests based on the received data. Next, based on the analysis results, it generates virtual reality content to optimize the user's state. For example, if the user is feeling stressed, it generates content that includes relaxing natural scenery and music.

[0218] The server sends the generated content to the device, which then displays it on the user's smart glasses. This allows the user to easily and seamlessly transition from the physical world to a virtual environment, enjoying a personalized experience. Furthermore, the user's gaze and gestures within the virtual environment enable an even more interactive experience.

[0219] A concrete example is in an educational setting, where users (for example, students) can virtually visit historical sites. In this case, they can move their gaze to display detailed information or use gestures to zoom in on specific areas. Such interactions are realized through adaptive mechanisms where the server receives user interaction information and dynamically adjusts the content based on that information.

[0220] As a result, the present invention provides users with a highly personalized and immersive virtual reality experience, demonstrating its usefulness in a variety of situations.

[0221] The following describes the processing flow.

[0222] Step 1:

[0223] The user puts on smart glasses and begins operating the device. The device activates sensors and collects environmental data (location, sound, lighting conditions) and biometric information (heart rate, gaze, face orientation) in real time.

[0224] Step 2:

[0225] The device transmits collected environmental data and biometric information to the server. Secure communication protocols are used to ensure data security during transmission.

[0226] Step 3:

[0227] The server analyzes the received data to determine the user's state. At this stage, a learning algorithm is used to evaluate, for example, the user's stress level and areas of interest.

[0228] Step 4:

[0229] Based on the analysis results, the server generates virtual reality content suitable for the user's state. If the goal is relaxation, it selects content depicting calming natural scenery; if the goal is learning, it generates relevant educational content.

[0230] Step 5:

[0231] The server sends the generated virtual reality content to the terminal. Here too, data compression and stream formats are used to improve communication efficiency.

[0232] Step 6:

[0233] The device displays the transmitted content on the user's smart glasses, allowing the user to immerse themselves in a virtual world. The user can interact within this virtual reality space using gaze and gestures.

[0234] Step 7:

[0235] User interaction information is retransmitted to the server via the device, and the server analyzes this information to dynamically adapt the content. This makes it possible to continuously improve the quality of the user experience.

[0236] (Example 1)

[0237] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0238] Current virtual reality systems offer a limited user experience and fail to adequately personalize the experience based on stress levels and interests. As a result, users struggle to become immersed, and the effectiveness of interactions within virtual reality is limited. This challenge stems from a lack of real-time data analysis and dynamic adjustments through interaction.

[0239] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0240] In this invention, the server includes data collection means for receiving environmental information, including location, acoustic and light information, and biometric information, including heart rate, gaze and face orientation information, data collection means for receiving environmental information and biometric information received from the data collection means and determining the user's stress level and interests using a generating AI model, and content generation means for generating virtual reality content, including natural scenery and music, based on the user's stress level and interests determined by the analysis means. This makes it possible to provide a personalized virtual reality experience that is tailored to the individual state of the user.

[0241] "Data collection means" refers to a function for receiving environmental information, including location, acoustic and light information, and biometric information, including heart rate, gaze, and facial orientation information, acquired from the user.

[0242] The "analysis means" refers to a function that uses a generated AI model, based on received environmental and biometric information, to determine the user's stress level and areas of interest.

[0243] The "content generation means" is a function that generates virtual reality content, including natural scenery and music, based on the user's stress level and interests determined by the analysis means.

[0244] "Transmission means" refers to the functionality for delivering generated virtual reality content to users using encryption protocols.

[0245] "Adaptive measures" refer to functions that receive user interactions, including gaze and gestures, and dynamically adjust content using a generative AI model based on that information.

[0246] A "generative AI model" refers to a model that uses artificial intelligence to analyze data and make decisions or generate specific information.

[0247] A "prompt sentence" is a sentence that is input into a generative AI model to instruct it to perform a specific analysis or generation.

[0248] The embodiments for carrying out this invention are as follows.

[0249] The user wears smart glasses and uses a terminal to collect environmental and biometric information. The terminal incorporates a GPS-enabled location device, microphone sensor, light sensor, and built-in heart rate sensor, eye tracking sensor, accelerometer, and gyroscope, which are used to acquire data in real time. This data includes environmental information such as location, sound, and light, as well as biometric information such as heart rate, gaze, and facial orientation.

[0250] The device sends the collected data to the server. The server analyzes the data using a generative AI model to determine the user's stress level and interests. The analysis is performed using prompts to instruct the server on the environments in which the user experiences stress. For example, the prompt might be "Generate content that calms the user." This allows the AI ​​model to estimate the user's state and obtain information to generate appropriate virtual reality content.

[0251] Based on the analysis results, the server constructs virtual reality content tailored to the user's state. This content generation uses techniques that combine natural scenery and relaxing sounds. The generated content is then transmitted to the terminal using an encryption protocol.

[0252] The device displays the received content on the smart glasses, allowing the user to begin an immersive experience. For example, to alleviate stress, the user's field of vision could be filled with images of a clear blue sky or a tranquil seaside landscape. Furthermore, the user can interact with the virtual environment using eye movements and gestures. For instance, moving their gaze could display information, or specific movements could zoom in on the scene.

[0253] This system allows users to experience comfort and interest through personalized virtual reality experiences. The aim of this invention is to enable users to enjoy a richer experience.

[0254] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0255] Step 1:

[0256] The device acquires information about the user's surroundings using a location tracking device, microphone sensor, and light sensor built into the smart glasses. This information includes the user's current location, ambient sound, and light intensity. Furthermore, it collects biometric information such as heart rate, gaze, and face orientation using a heart rate sensor, eye tracking sensor, accelerometer, and gyroscope. This provides a detailed dataset in real time, preparing for the next steps.

[0257] Step 2:

[0258] The device encrypts the environmental and biometric information collected in Step 1 and sends it to the server. Encryption uses protocols to ensure the security of the communication. The server decodes the received data and converts it into a format suitable for analysis. This prepares the server to evaluate the user's state based on a high-quality, reliable dataset.

[0259] Step 3:

[0260] The server uses a generative AI model to analyze the data received in step 2. Based on environmental and biometric information as input, it estimates the user's stress level and areas of interest. During this process, the prompt "Generate content that calms the user" is used to instruct the AI ​​model. As an output of the analysis, hypotheses about the user's mental state are obtained, forming insights necessary for generating the next content.

[0261] Step 4:

[0262] Based on the analysis results obtained in Step 3, the server generates virtual reality content tailored to the user's state. This process involves selecting natural scenery and relaxing music, constructing scenes, and integrating sound data. The generated content is meticulously designed to provide the user with the utmost comfort and peace of mind.

[0263] Step 5:

[0264] The server sends the generated content back to the device. The device receives this content and displays it in the appropriate format on the smart glasses. This leads the user into an immersive virtual environment, allowing them to enjoy a new experience adapted to their mental state.

[0265] Step 6:

[0266] Users interact within a virtual environment, manipulating the scene by making eye contact and using gestures. The device sends these actions to the server in real time, which uses an AI model to perform additional analysis and dynamically adjust the content to provide the user with an even more personalized experience.

[0267] (Application Example 1)

[0268] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0269] In the real world, there is a challenge in that it is difficult for users to individually experience information related to specific places or environments. Typically, users need to research many sources themselves to obtain educational or cultural information. However, if they can intuitively and interactively experience information relevant to their situation in real time, educational efficiency and information accessibility will improve.

[0270] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0271] In this invention, the server includes data collection means for receiving environmental and biometric information acquired from the user, analysis means for analyzing the data and determining the user's state, and means for generating virtual reality content related to the surrounding physical environment based on location information. As a result, the user can receive relevant information as a VR experience at each location, enabling real-time interactive learning and information acquisition.

[0272] "Data collection means" refers to means for acquiring environmental and biometric information from users and transmitting it to a server or similar device.

[0273] "Analysis means" refers to a process or system that evaluates and determines the user's psychological or physiological state based on received environmental and biological information.

[0274] "Content generation means" refers to a process or device that creates virtual reality content based on analysis results such as the user's state and location information.

[0275] "Transmission means" refers to the infrastructure that sends generated virtual reality content to a user's terminal and allows the user to view or experience that content.

[0276] "Adaptive means" refers to a process or device for dynamically changing content in real time based on user interaction to optimize the user experience.

[0277] "Means for generating virtual reality content related to the surrounding physical environment based on location information" refers to a method or apparatus that utilizes the user's geographical location and surrounding environment data to create and provide virtual content related to that location to the user.

[0278] The system for realizing this invention collects the user's environment and biometric information and provides a personalized virtual reality experience based on that information. Details are described below.

[0279] Smart glasses are equipped with a variety of sensors to collect environmental data such as the user's location, sound, and lighting conditions, as well as biometric information such as heart rate, gaze, and facial orientation. This data is temporarily processed within the device and then transmitted to a server via a high-speed network.

[0280] The server executes an analysis algorithm written in a programming language such as Python to analyze the received information. In this process, the user's stress level and the objects that attract interest are determined. Based on the analysis results, the server uses a generative AI model (e.g., ChatGPT API) to generate virtual reality content dedicated to the user.

[0281] The content integrates elements related to the user's current geographical location and the surrounding environment, thereby providing historical events and educational information related to the user's actual location. The generated content is transmitted to the user's smart glasses using a VR content development platform such as Unity or Unreal Engine.

[0282] As a specific example of content generation in this process, when the user visits a historical site, providing 30-second video-form content explaining the history of that place can be cited. An example of a prompt sentence for the generative AI model is "Please generate the historical background at the location where the user is in a 30-second video format."

[0283] This enables the user to enjoy an interactive and educational experience according to the location.

[0284] The flow of the specific process in Application Example 1 will be described using FIG. 12.

[0285] Step 1:

[0286] The terminal collects the user's environment and biometric information through the sensors of the smart glasses. At this time, the environmental data includes location information, sound, lighting conditions, and the biometric information includes heart rate, line of sight, and face orientation. These data are first temporarily stored on the terminal side (input). The terminal transmits this data to the server via a high-speed network (output).

[0287] Step 2:

[0288] The server uses a programming language such as Python to analyze the received data (input). The analysis process combines gaze direction and heart rate data to evaluate the user's stress level and areas of interest (data calculation). Based on these results, the server determines the user's current psychological and physiological state (output).

[0289] Step 3:

[0290] The server generates virtual reality content using a generative AI model based on the analysis results (input). It prompts the generative AI model (e.g., ChatGPT API) to design content that matches the user's interests and stress levels (data processing). For example, it might use a prompt like, "Generate a video of 30 seconds or less showing the historical background of the user's current location" (prompt statement). As a result, customized content for the user is output.

[0291] Step 4:

[0292] The generated content is converted to a format suitable for the user's smart glasses using VR content development platforms such as Unity or Unreal Engine (input). During this conversion process, the content is adjusted to maximize the visual and auditory experience in virtual reality (specific actions). The converted content is then sent to the device (output).

[0293] Step 5:

[0294] The device displays the received virtual reality content on the smart glasses (input). The user can view this content and interact with it using gaze and gestures (specific actions). User interactions are recorded in real time on the device and fed back to the server as needed, which then adjusts the content (output).

[0295] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0296] This invention relates to a system that recognizes a user's emotions and dynamically adjusts the virtual reality experience based on them. The user wears smart glasses, and a terminal collects environmental data and biometric information in real time. During this process, sensors detect location, sound, and lighting conditions, and acquire data such as heart rate, gaze, and face orientation.

[0297] The device sends this information to the server. On the server, an emotion engine analyzes the user's emotions based on the received data. This analysis is performed by using a specific algorithm to classify the user's emotional state as, for example, "relaxed," "stressed," or "excited."

[0298] Based on the analysis results, the server generates appropriate virtual reality content according to the situation. For example, if the user's emotion is determined to be "stress," the server prepares a relaxing virtual environment and generates content that includes calming music and scenery.

[0299] The generated content is sent from the server to the device, which displays it on the user's smart glasses. The user interacts with the system through actions and gaze within the virtual reality environment. The device then sends data about these interactions back to the server, which analyzes the data and dynamically adjusts the content. This allows the user to obtain an optimal virtual reality experience that matches their emotional state at the time.

[0300] As a specific example, consider the application in an educational scenario. When a user (e.g., a student) enters a virtual library for exam preparation and feels stressed in that situation, the emotion engine analyzes this as "stress". The server immediately switches to a virtual landscape with a relaxing effect and provides an environment where the user can study intensively. Through such a process, a flexible and customized experience that can adapt to the user's emotional state is realized.

[0301] The following describes the processing flow.

[0302] Step 1:

[0303] The user wears smart glasses and activates the virtual reality system. The terminal collects environmental data and biometric information around the user in real time through built-in sensors. The environmental data includes location information, surrounding sounds, light intensity, etc., and the biometric information includes heart rate, direction of gaze, facial expressions.

[0304] Step 2:

[0305] The terminal sends the collected data to the server. A communication protocol with security ensured is used for transmission. This ensures the integrity and privacy of the data.

[0306] Step 3:

[0307] The server analyzes the received data. The emotion engine evaluates the user's emotion based on the user's biometric information and determines, for example, whether the user is feeling "relaxed" or "stressed".

[0308] Step 4:

[0309] Based on the analysis result of the emotion engine, the server generates virtual reality content optimal for the current user's emotional state. If it is determined that the user is feeling stressed, content including a natural landscape with a relaxing effect and quiet and calming music is generated.

[0310] Step 5:

[0311] The server sends the generated content to the device, which then displays it on the user's smart glasses. During this process, the video and audio are played smoothly to ensure a seamless and immersive experience for the user.

[0312] Step 6:

[0313] Users interact within the displayed virtual environment using gaze and gestures. For example, they can select specific objects using their gaze or manipulate them with gestures.

[0314] Step 7:

[0315] User interaction data is sent back to the server via the device, where it is analyzed and the content is dynamically adjusted as needed. This ensures that the user's emotional state and needs are continuously met, providing a truly responsive experience.

[0316] (Example 2)

[0317] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0318] In the modern era, virtual experiences in digital environments are becoming increasingly diverse, and there is a demand for customized experiences tailored to the individual user's state. However, conventional virtual experience systems have the problem of difficulty in dynamically adjusting content to adequately reflect the user's real-time emotions and biometric information. This invention aims to solve this problem and provide a system that allows users to obtain the optimal experience at that moment.

[0319] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0320] In this invention, the server includes information gathering means for receiving environmental and biometric information acquired from the user, state analysis means for analyzing the information received from the information gathering means and determining the user's state, and experience generation means for generating virtual experience content based on the user's state determined by the state analysis means. This makes it possible to dynamically provide an experience that is suitable for the user's real-time state.

[0321] "Information gathering means" refers to a device or software that has the function of acquiring environmental and biometric information from a user.

[0322] "State analysis means" refers to a device or software that has the function of analyzing collected information and determining the user's emotions and biological state.

[0323] "Experience generation means" refers to a device or software that has the function of constructing virtual experience content based on the results of user state analysis.

[0324] "Display means" refers to a device or software that has the function of presenting generated virtual experience content to a user.

[0325] "Adjustment means" refers to a device or software that has the function of receiving responses from users and dynamically adjusting the virtual experience based on those responses.

[0326] A "detection device" is a device that includes sensors and other components for collecting environmental and biological information in real time.

[0327] A "virtual experience" refers to a simulated environment or situation created for a user using a computer system.

[0328] This invention is a system that recognizes the user's emotions in real time and dynamically adjusts the virtual experience based on those emotions. The user uses a smart device, and various sensors built into the device collect environmental and biometric information. This includes location information, sound environment, lighting conditions, heart rate, gaze, and facial orientation.

[0329] The terminal is responsible for immediately transmitting this information to the server. The server analyzes the received data and classifies the user's emotions using an emotion engine with a generative AI model. Emotion analysis is performed by classifying the user's emotions into states such as "relaxed," "stressed," and "excited."

[0330] Based on the analysis results, the server generates content to adjust the virtual experience. For example, if stress is detected, it might create a virtual space that includes relaxing ambient sounds and scenery. This allows the system to quickly adapt to the user's desired experience.

[0331] The generated virtual experience content is displayed on the user's smart device via a terminal. The user interacts with the system through their gaze and movements within the virtual space. This movement information is collected again and sent to the server to be used to dynamically adjust the virtual experience.

[0332] A concrete example is its use in educational settings. If a user experiences stress while preparing for an exam in a virtual library, the system can instantly switch to a calm and quiet environment, providing a state conducive to focused learning. This allows for flexible responses tailored to individual emotional states.

[0333] Example of a prompt:

[0334] "When students feel stressed in the virtual library, how do you transform the environment into a more relaxing one?"

[0335] This system is a modern approach that utilizes generative AI models to provide users with the optimal virtual experience in real time.

[0336] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0337] Step 1:

[0338] The user wears a smart device and begins the virtual experience. The device uses built-in sensors to collect environmental information and biometric information in real time, including the user's location, sound environment, lighting conditions, heart rate, gaze, and face orientation. The input is the user's environmental data and biometric information, and the output is this collected data. Specifically, the gaze tracking sensor captures the user's gaze direction, and the heart rate sensor measures the heart rate.

[0339] Step 2:

[0340] The device transmits the collected data to the server. The input is a set of collected environmental and biometric data, and the output is this data converted into transmission data packets. Specifically, the device uploads the data to the server via high-speed Wi-Fi, minimizing data transfer delays.

[0341] Step 3:

[0342] The server analyzes the received data and estimates the user's emotions using a generative AI model. This process utilizes an emotion engine. The input consists of transmitted environmental data and biometric information, and the output is the estimated emotional state of the user. Specifically, the emotion engine analyzes heart rate and eye movement patterns and classifies the emotional state into one of three categories: "relaxed," "stressed," or "excited."

[0343] Step 4:

[0344] The server generates virtual experience content based on the user's emotional state. The input is the estimated emotional state, and the output is the corresponding virtual experience content. Specifically, if a stressed state is detected, the server synthesizes content including relaxing music and scenery to adjust the virtual space.

[0345] Step 5:

[0346] The server sends the generated virtual experience content to the terminal. The input is the generated virtual experience content, and the output is the content converted into display data. Specifically, the server sends the content data to the terminal, which then prepares to display it on a smart device.

[0347] Step 6:

[0348] Users interact within a virtual space. Input is the displayed virtual content, and output is interaction data based on the user's gaze and movements. Specific actions include the user selecting a particular virtual object using their gaze.

[0349] Step 7:

[0350] The terminal collects user interaction data and sends it to the server. The input is user interaction data, and the output is data packets for transmission. Specifically, the terminal detects user movements and changes in gaze, organizes the data based on these, and sends it to the server.

[0351] Step 8:

[0352] The server dynamically adjusts the virtual experience content based on user interaction. The input is user interaction data, and the output is the updated virtual experience content. Specifically, if the server determines that the user has entered a relaxed state, it switches to content containing a wider variety of stimuli.

[0353] (Application Example 2)

[0354] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0355] Current in-home service robots struggle to flexibly adapt their actions to the user's emotional state. Therefore, it's difficult to provide services appropriate to a user's state, such as when they are stressed or seeking relaxation. Consequently, there is a need to develop a system that can recognize the user's emotional state in real time and dynamically adjust the in-home environment and services accordingly.

[0356] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0357] In this invention, the server includes data collection means for receiving environmental and biometric information acquired from the user, analysis means for analyzing the data received from the data collection means and determining the user's state, and content generation means for generating and dynamically adjusting virtual reality content based on the user's state determined by the analysis means. This enables dynamic adjustment of the home environment in accordance with the user's emotional state and the provision of appropriate services.

[0358] "Data collection means" refers to a device or function for receiving environmental information and biometric information acquired from users.

[0359] "Analysis means" refers to a function or program that determines the user's emotions or state based on data obtained from data collection means.

[0360] "Content generation means" refers to a device or function that generates virtual reality content suitable for the user's state based on analysis results, and further dynamically adjusts it.

[0361] "Transmission means" refers to a device or function for delivering generated virtual reality content to a user's device.

[0362] "Behavior control means" refers to a device or function that controls the home environment or the provision of services based on the user's emotional state.

[0363] The system implementing this invention mainly consists of data collection means, analysis means, content generation means, transmission means, and behavior control means. Specifically, a robot installed in a home is central to this system.

[0364] The system program operates as follows: As a data collection method, smart glasses acquire the user's environmental information (sound and lighting) and biometric information (heart rate, gaze, face orientation) in real time. This data is received by a robot and analyzed to determine the user's emotional state (e.g., relaxed, stressed, excited).

[0365] The analyzed information is formed into virtual reality content tailored to the user's state by a content generation means. The generated content is delivered to a robot via a transmission means, and the user experiences virtual reality through smart glasses.

[0366] Furthermore, the behavioral control system enables the robot to provide in-home services based on the user's emotional state. If the user shows signs of stress, the robot can play calming music or change the lighting to create a relaxing environment.

[0367] The operation of this system is realized by a generating AI model in the form of specific prompt statements, such as, "Please provide specific suggestions on how the robot can create a relaxing environment when the user is feeling stressed." This allows for flexible responses that are tailored to the user's emotions.

[0368] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0369] Step 1:

[0370] The device acquires user environmental information (sound, lighting) and biometric information (heart rate, gaze, face orientation) through smart glasses. The input is real-time data from sensors, and the output is aggregated raw data. This data is transferred to a server for later analysis.

[0371] Step 2:

[0372] The server processes the raw data received by the data collection means using the analysis means. The input data consists of environmental and biometric information aggregated in step 1, and by applying this to the analysis algorithm, the user's emotional state (relaxed, stressed, excited, etc.) is obtained as output. This analysis process is performed in real time, and the user's state is continuously monitored.

[0373] Step 3:

[0374] The server generates appropriate virtual reality content using content generation means based on the user's emotional state obtained by the analysis means. The input is the user's emotional state, and the output is a virtual environment (such as calming music or scenery) that is suitable for that state. This generation is performed dynamically to optimize the user experience.

[0375] Step 4:

[0376] The generated virtual reality content is returned to the terminal via a transmission method and displayed on the user's smart glasses. The input is the virtual reality content generated in step 3, and the output is the content that the user visually experiences. This allows the user to experience a virtual reality space that matches their emotional state.

[0377] Step 5:

[0378] The user interacts through actions and gaze within the virtual reality environment, and the device sends this new data back to the server. The input here is the user's interaction data, and the output is received by the server again as data for analysis in the next processing step.

[0379] Step 6:

[0380] The server uses behavioral control means to control the robot so that it provides in-home services that correspond to the user's emotional state. The inputs are the emotional state data analyzed in step 2 and the interaction data obtained in step 5, and the output is the robot's specific actions (e.g., playing music, adjusting the lighting). This enables the provision of services that are in line with the user's emotional state.

[0381] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0382] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0383] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0384] [Third Embodiment]

[0385] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0386] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0387] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0388] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0389] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0390] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0391] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0392] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0393] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0394] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0395] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0396] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0397] This invention relates to a system that provides a virtual reality (VR) experience using smart glasses. The user wears smart glasses and collects environmental data and biometric information through sensors built into the device. This includes environmental data such as location information, sound, and lighting conditions, as well as biometric information such as heart rate, gaze, and face orientation.

[0398] The device sends this information to the server. The server analyzes the user's stress level and interests based on the received data. Next, based on the analysis results, it generates virtual reality content to optimize the user's state. For example, if the user is feeling stressed, it generates content that includes relaxing natural scenery and music.

[0399] The server sends the generated content to the device, which then displays it on the user's smart glasses. This allows the user to easily and seamlessly transition from the physical world to a virtual environment, enjoying a personalized experience. Furthermore, the user's gaze and gestures within the virtual environment enable an even more interactive experience.

[0400] A concrete example is in an educational setting, where users (for example, students) can virtually visit historical sites. In this case, they can move their gaze to display detailed information or use gestures to zoom in on specific areas. Such interactions are realized through adaptive mechanisms where the server receives user interaction information and dynamically adjusts the content based on that information.

[0401] As a result, the present invention provides users with a highly personalized and immersive virtual reality experience, demonstrating its usefulness in a variety of situations.

[0402] The following describes the processing flow.

[0403] Step 1:

[0404] The user puts on smart glasses and begins operating the device. The device activates sensors and collects environmental data (location, sound, lighting conditions) and biometric information (heart rate, gaze, face orientation) in real time.

[0405] Step 2:

[0406] The device transmits collected environmental data and biometric information to the server. Secure communication protocols are used to ensure data security during transmission.

[0407] Step 3:

[0408] The server analyzes the received data to determine the user's state. At this stage, a learning algorithm is used to evaluate, for example, the user's stress level and areas of interest.

[0409] Step 4:

[0410] Based on the analysis results, the server generates virtual reality content suitable for the user's state. If the goal is relaxation, it selects content depicting calming natural scenery; if the goal is learning, it generates relevant educational content.

[0411] Step 5:

[0412] The server sends the generated virtual reality content to the terminal. Here too, data compression and stream formats are used to improve communication efficiency.

[0413] Step 6:

[0414] The device displays the transmitted content on the user's smart glasses, allowing the user to immerse themselves in a virtual world. The user can interact within this virtual reality space using gaze and gestures.

[0415] Step 7:

[0416] User interaction information is retransmitted to the server via the device, and the server analyzes this information to dynamically adapt the content. This makes it possible to continuously improve the quality of the user experience.

[0417] (Example 1)

[0418] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0419] Current virtual reality systems offer a limited user experience and fail to adequately personalize the experience based on stress levels and interests. As a result, users struggle to become immersed, and the effectiveness of interactions within virtual reality is limited. This challenge stems from a lack of real-time data analysis and dynamic adjustments through interaction.

[0420] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0421] In this invention, the server includes data collection means for receiving environmental information, including location, acoustic and light information, and biometric information, including heart rate, gaze and face orientation information, data collection means for receiving environmental information and biometric information received from the data collection means and determining the user's stress level and interests using a generating AI model, and content generation means for generating virtual reality content, including natural scenery and music, based on the user's stress level and interests determined by the analysis means. This makes it possible to provide a personalized virtual reality experience that is tailored to the individual state of the user.

[0422] "Data collection means" refers to a function for receiving environmental information, including location, acoustic and light information, and biometric information, including heart rate, gaze, and facial orientation information, acquired from the user.

[0423] The "analysis means" refers to a function that uses a generated AI model, based on received environmental and biometric information, to determine the user's stress level and areas of interest.

[0424] The "content generation means" is a function that generates virtual reality content, including natural scenery and music, based on the user's stress level and interests determined by the analysis means.

[0425] "Transmission means" refers to the functionality for delivering generated virtual reality content to users using encryption protocols.

[0426] "Adaptive measures" refer to functions that receive user interactions, including gaze and gestures, and dynamically adjust content using a generative AI model based on that information.

[0427] A "generative AI model" refers to a model that uses artificial intelligence to analyze data and make decisions or generate specific information.

[0428] A "prompt sentence" is a sentence that is input into a generative AI model to instruct it to perform a specific analysis or generation.

[0429] The embodiments for carrying out this invention are as follows.

[0430] The user wears smart glasses and uses a terminal to collect environmental and biometric information. The terminal incorporates a GPS-enabled location device, microphone sensor, light sensor, and built-in heart rate sensor, eye tracking sensor, accelerometer, and gyroscope, which are used to acquire data in real time. This data includes environmental information such as location, sound, and light, as well as biometric information such as heart rate, gaze, and facial orientation.

[0431] The device sends the collected data to the server. The server analyzes the data using a generative AI model to determine the user's stress level and interests. The analysis is performed using prompts to instruct the server on the environments in which the user experiences stress. For example, the prompt might be "Generate content that calms the user." This allows the AI ​​model to estimate the user's state and obtain information to generate appropriate virtual reality content.

[0432] Based on the analysis results, the server constructs virtual reality content tailored to the user's state. This content generation uses techniques that combine natural scenery and relaxing sounds. The generated content is then transmitted to the terminal using an encryption protocol.

[0433] The device displays the received content on the smart glasses, allowing the user to begin an immersive experience. For example, to alleviate stress, the user's field of vision could be filled with images of a clear blue sky or a tranquil seaside landscape. Furthermore, the user can interact with the virtual environment using eye movements and gestures. For instance, moving their gaze could display information, or specific movements could zoom in on the scene.

[0434] This system allows users to experience comfort and interest through personalized virtual reality experiences. The aim of this invention is to enable users to enjoy a richer experience.

[0435] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0436] Step 1:

[0437] The device acquires information about the user's surroundings using a location tracking device, microphone sensor, and light sensor built into the smart glasses. This information includes the user's current location, ambient sound, and light intensity. Furthermore, it collects biometric information such as heart rate, gaze, and face orientation using a heart rate sensor, eye tracking sensor, accelerometer, and gyroscope. This provides a detailed dataset in real time, preparing for the next steps.

[0438] Step 2:

[0439] The device encrypts the environmental and biometric information collected in Step 1 and sends it to the server. Encryption uses protocols to ensure the security of the communication. The server decodes the received data and converts it into a format suitable for analysis. This prepares the server to evaluate the user's state based on a high-quality, reliable dataset.

[0440] Step 3:

[0441] The server uses a generative AI model to analyze the data received in step 2. Based on environmental and biometric information as input, it estimates the user's stress level and areas of interest. During this process, the prompt "Generate content that calms the user" is used to instruct the AI ​​model. As an output of the analysis, hypotheses about the user's mental state are obtained, forming insights necessary for generating the next content.

[0442] Step 4:

[0443] Based on the analysis results obtained in Step 3, the server generates virtual reality content tailored to the user's state. This process involves selecting natural scenery and relaxing music, constructing scenes, and integrating sound data. The generated content is meticulously designed to provide the user with the utmost comfort and peace of mind.

[0444] Step 5:

[0445] The server sends the generated content back to the device. The device receives this content and displays it in the appropriate format on the smart glasses. This leads the user into an immersive virtual environment, allowing them to enjoy a new experience adapted to their mental state.

[0446] Step 6:

[0447] Users interact within a virtual environment, manipulating the scene by making eye contact and using gestures. The device sends these actions to the server in real time, which uses an AI model to perform additional analysis and dynamically adjust the content to provide the user with an even more personalized experience.

[0448] (Application Example 1)

[0449] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0450] In the real world, there is a challenge in that it is difficult for users to individually experience information related to specific places or environments. Typically, users need to research many sources themselves to obtain educational or cultural information. However, if they can intuitively and interactively experience information relevant to their situation in real time, educational efficiency and information accessibility will improve.

[0451] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0452] In this invention, the server includes data collection means for receiving environmental and biometric information acquired from the user, analysis means for analyzing the data and determining the user's state, and means for generating virtual reality content related to the surrounding physical environment based on location information. As a result, the user can receive relevant information as a VR experience at each location, enabling real-time interactive learning and information acquisition.

[0453] "Data collection means" refers to means for acquiring environmental and biometric information from users and transmitting it to a server or similar device.

[0454] "Analysis means" refers to a process or system that evaluates and determines the user's psychological or physiological state based on received environmental and biological information.

[0455] "Content generation means" refers to a process or device that creates virtual reality content based on analysis results such as the user's state and location information.

[0456] "Transmission means" refers to the infrastructure that sends generated virtual reality content to a user's terminal and allows the user to view or experience that content.

[0457] "Adaptive means" refers to a process or device for dynamically changing content in real time based on user interaction to optimize the user experience.

[0458] "Means for generating virtual reality content related to the surrounding physical environment based on location information" refers to a method or apparatus that utilizes the user's geographical location and surrounding environment data to create and provide virtual content related to that location to the user.

[0459] The system for realizing this invention collects the user's environment and biometric information and provides a personalized virtual reality experience based on that information. Details are described below.

[0460] Smart glasses are equipped with a variety of sensors to collect environmental data such as the user's location, sound, and lighting conditions, as well as biometric information such as heart rate, gaze, and facial orientation. This data is temporarily processed within the device and then transmitted to a server via a high-speed network.

[0461] The server executes analysis algorithms written in programming languages ​​such as Python to analyze the received information. In this process, the user's stress level and areas of interest are determined. Based on the analysis results, the server generates user-specific virtual reality content using a generative AI model (e.g., ChatGPT API).

[0462] The content integrates elements related to the user's current geographical location and surrounding environment, thereby providing historical events and educational information relevant to the user's real-world location. The generated content is transmitted to the user's smart glasses using VR content development platforms such as Unity or Unreal Engine.

[0463] A concrete example of content generation in this process is providing a 30-second video explaining the history of a place when a user visits a historical landmark. An example of a prompt to the generation AI model is, "Generate a video of 30 seconds or less explaining the historical background of the user's current location."

[0464] This allows users to enjoy interactive and educational experiences tailored to their location.

[0465] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0466] Step 1:

[0467] The device collects the user's environmental and biometric information through the sensors in the smart glasses. This includes environmental data such as location, sound, and lighting conditions, and biometric information such as heart rate, gaze, and face orientation. This data is first temporarily stored on the device (input). The device then transmits this data to a server via a high-speed network (output).

[0468] Step 2:

[0469] The server uses a programming language such as Python to analyze the received data (input). The analysis process combines gaze direction and heart rate data to evaluate the user's stress level and areas of interest (data calculation). Based on these results, the server determines the user's current psychological and physiological state (output).

[0470] Step 3:

[0471] The server generates virtual reality content using a generative AI model based on the analysis results (input). It prompts the generative AI model (e.g., ChatGPT API) to design content that matches the user's interests and stress levels (data processing). For example, it might use a prompt like, "Generate a video of 30 seconds or less showing the historical background of the user's current location" (prompt statement). As a result, customized content for the user is output.

[0472] Step 4:

[0473] The generated content is converted to a format suitable for the user's smart glasses using VR content development platforms such as Unity or Unreal Engine (input). During this conversion process, the content is adjusted to maximize the visual and auditory experience in virtual reality (specific actions). The converted content is then sent to the device (output).

[0474] Step 5:

[0475] The device displays the received virtual reality content on the smart glasses (input). The user can view this content and interact with it using gaze and gestures (specific actions). User interactions are recorded in real time on the device and fed back to the server as needed, which then adjusts the content (output).

[0476] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0477] This invention relates to a system that recognizes a user's emotions and dynamically adjusts the virtual reality experience based on them. The user wears smart glasses, and a terminal collects environmental data and biometric information in real time. During this process, sensors detect location, sound, and lighting conditions, and acquire data such as heart rate, gaze, and face orientation.

[0478] The device sends this information to the server. On the server, an emotion engine analyzes the user's emotions based on the received data. This analysis is performed by using a specific algorithm to classify the user's emotional state as, for example, "relaxed," "stressed," or "excited."

[0479] Based on the analysis results, the server generates appropriate virtual reality content according to the situation. For example, if the user's emotion is determined to be "stress," the server prepares a relaxing virtual environment and generates content that includes calming music and scenery.

[0480] The generated content is sent from the server to the device, which displays it on the user's smart glasses. The user interacts with the system through actions and gaze within the virtual reality environment. The device then sends data about these interactions back to the server, which analyzes the data and dynamically adjusts the content. This allows the user to obtain an optimal virtual reality experience that matches their emotional state at the time.

[0481] As a concrete example, let's consider its application in an educational setting. If a user (for example, a student) enters a virtual library to prepare for an exam and feels stressed by the situation, the emotion engine will analyze this as "stress." The server will immediately switch to a relaxing virtual landscape, providing the user with an environment where they can concentrate on learning. This process enables a flexible and customized experience that can respond to the user's emotional state.

[0482] The following describes the processing flow.

[0483] Step 1:

[0484] The user puts on smart glasses and activates the virtual reality system. The device collects environmental data and biometric information in real time through its built-in sensors. Environmental data includes location information, ambient sound, and light intensity, while biometric information includes heart rate, gaze direction, and facial expressions.

[0485] Step 2:

[0486] The device sends the collected data to the server. A secure communication protocol is used for transmission, ensuring data integrity and privacy.

[0487] Step 3:

[0488] The server analyzes the received data. The emotion engine evaluates the user's emotions based on the user's biometric information, determining, for example, whether the user is feeling "relaxed" or "stressed."

[0489] Step 4:

[0490] The server uses the results of the emotion engine's analysis to generate virtual reality content best suited to the user's current emotional state. If the server determines that the user is stressed, it will generate content that includes relaxing natural scenery and calming music.

[0491] Step 5:

[0492] The server sends the generated content to the device, which then displays it on the user's smart glasses. During this process, the video and audio are played smoothly to ensure a seamless and immersive experience for the user.

[0493] Step 6:

[0494] Users interact within the displayed virtual environment using gaze and gestures. For example, they can select specific objects using their gaze or manipulate them with gestures.

[0495] Step 7:

[0496] User interaction data is sent back to the server via the device, where it is analyzed and the content is dynamically adjusted as needed. This ensures that the user's emotional state and needs are continuously met, providing a truly responsive experience.

[0497] (Example 2)

[0498] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0499] In the modern era, virtual experiences in digital environments are becoming increasingly diverse, and there is a demand for customized experiences tailored to the individual user's state. However, conventional virtual experience systems have the problem of difficulty in dynamically adjusting content to adequately reflect the user's real-time emotions and biometric information. This invention aims to solve this problem and provide a system that allows users to obtain the optimal experience at that moment.

[0500] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0501] In this invention, the server includes information gathering means for receiving environmental and biometric information acquired from the user, state analysis means for analyzing the information received from the information gathering means and determining the user's state, and experience generation means for generating virtual experience content based on the user's state determined by the state analysis means. This makes it possible to dynamically provide an experience that is suitable for the user's real-time state.

[0502] "Information gathering means" refers to a device or software that has the function of acquiring environmental and biometric information from a user.

[0503] "State analysis means" refers to a device or software that has the function of analyzing collected information and determining the user's emotions and biological state.

[0504] "Experience generation means" refers to a device or software that has the function of constructing virtual experience content based on the results of user state analysis.

[0505] "Display means" refers to a device or software that has the function of presenting generated virtual experience content to a user.

[0506] "Adjustment means" refers to a device or software that has the function of receiving responses from users and dynamically adjusting the virtual experience based on those responses.

[0507] A "detection device" is a device that includes sensors and other components for collecting environmental and biological information in real time.

[0508] A "virtual experience" refers to a simulated environment or situation created for a user using a computer system.

[0509] This invention is a system that recognizes the user's emotions in real time and dynamically adjusts the virtual experience based on those emotions. The user uses a smart device, and various sensors built into the device collect environmental and biometric information. This includes location information, sound environment, lighting conditions, heart rate, gaze, and facial orientation.

[0510] The terminal is responsible for immediately transmitting this information to the server. The server analyzes the received data and classifies the user's emotions using an emotion engine with a generative AI model. Emotion analysis is performed by classifying the user's emotions into states such as "relaxed," "stressed," and "excited."

[0511] Based on the analysis results, the server generates content to adjust the virtual experience. For example, if stress is detected, it might create a virtual space that includes relaxing ambient sounds and scenery. This allows the system to quickly adapt to the user's desired experience.

[0512] The generated virtual experience content is displayed on the user's smart device via a terminal. The user interacts with the system through their gaze and movements within the virtual space. This movement information is collected again and sent to the server to be used to dynamically adjust the virtual experience.

[0513] A concrete example is its use in educational settings. If a user experiences stress while preparing for an exam in a virtual library, the system can instantly switch to a calm and quiet environment, providing a state conducive to focused learning. This allows for flexible responses tailored to individual emotional states.

[0514] Example of a prompt:

[0515] "When students feel stressed in the virtual library, how do you transform the environment into a more relaxing one?"

[0516] This system is a modern approach that utilizes generative AI models to provide users with the optimal virtual experience in real time.

[0517] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0518] Step 1:

[0519] The user wears a smart device and begins the virtual experience. The device uses built-in sensors to collect environmental information and biometric information in real time, including the user's location, sound environment, lighting conditions, heart rate, gaze, and face orientation. The input is the user's environmental data and biometric information, and the output is this collected data. Specifically, the gaze tracking sensor captures the user's gaze direction, and the heart rate sensor measures the heart rate.

[0520] Step 2:

[0521] The device transmits the collected data to the server. The input is a set of collected environmental and biometric data, and the output is this data converted into transmission data packets. Specifically, the device uploads the data to the server via high-speed Wi-Fi, minimizing data transfer delays.

[0522] Step 3:

[0523] The server analyzes the received data and estimates the user's emotions using a generative AI model. This process utilizes an emotion engine. The input consists of transmitted environmental data and biometric information, and the output is the estimated emotional state of the user. Specifically, the emotion engine analyzes heart rate and eye movement patterns and classifies the emotional state into one of three categories: "relaxed," "stressed," or "excited."

[0524] Step 4:

[0525] The server generates virtual experience content based on the user's emotional state. The input is the estimated emotional state, and the output is the corresponding virtual experience content. Specifically, if a stressed state is detected, the server synthesizes content including relaxing music and scenery to adjust the virtual space.

[0526] Step 5:

[0527] The server sends the generated virtual experience content to the terminal. The input is the generated virtual experience content, and the output is the content converted into display data. Specifically, the server sends the content data to the terminal, which then prepares to display it on a smart device.

[0528] Step 6:

[0529] Users interact within a virtual space. Input is the displayed virtual content, and output is interaction data based on the user's gaze and movements. Specific actions include the user selecting a particular virtual object using their gaze.

[0530] Step 7:

[0531] The terminal collects user interaction data and sends it to the server. The input is user interaction data, and the output is data packets for transmission. Specifically, the terminal detects user movements and changes in gaze, organizes the data based on these, and sends it to the server.

[0532] Step 8:

[0533] The server dynamically adjusts the virtual experience content based on user interaction. The input is user interaction data, and the output is the updated virtual experience content. Specifically, if the server determines that the user has entered a relaxed state, it switches to content containing a wider variety of stimuli.

[0534] (Application Example 2)

[0535] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0536] Current in-home service robots struggle to flexibly adapt their actions to the user's emotional state. Therefore, it's difficult to provide services appropriate to a user's state, such as when they are stressed or seeking relaxation. Consequently, there is a need to develop a system that can recognize the user's emotional state in real time and dynamically adjust the in-home environment and services accordingly.

[0537] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0538] In this invention, the server includes data collection means for receiving environmental and biometric information acquired from the user, analysis means for analyzing the data received from the data collection means and determining the user's state, and content generation means for generating and dynamically adjusting virtual reality content based on the user's state determined by the analysis means. This enables dynamic adjustment of the home environment in accordance with the user's emotional state and the provision of appropriate services.

[0539] "Data collection means" refers to a device or function for receiving environmental information and biometric information acquired from users.

[0540] "Analysis means" refers to a function or program that determines the user's emotions or state based on data obtained from data collection means.

[0541] "Content generation means" refers to a device or function that generates virtual reality content suitable for the user's state based on analysis results, and further dynamically adjusts it.

[0542] "Transmission means" refers to a device or function for delivering generated virtual reality content to a user's device.

[0543] "Behavior control means" refers to a device or function that controls the home environment or the provision of services based on the user's emotional state.

[0544] The system implementing this invention mainly consists of data collection means, analysis means, content generation means, transmission means, and behavior control means. Specifically, a robot installed in a home is central to this system.

[0545] The system program operates as follows: As a data collection method, smart glasses acquire the user's environmental information (sound and lighting) and biometric information (heart rate, gaze, face orientation) in real time. This data is received by a robot and analyzed to determine the user's emotional state (e.g., relaxed, stressed, excited).

[0546] The analyzed information is formed into virtual reality content tailored to the user's state by a content generation means. The generated content is delivered to a robot via a transmission means, and the user experiences virtual reality through smart glasses.

[0547] Furthermore, the behavioral control system enables the robot to provide in-home services based on the user's emotional state. If the user shows signs of stress, the robot can play calming music or change the lighting to create a relaxing environment.

[0548] The operation of this system is realized by a generating AI model in the form of specific prompt statements, such as, "Please provide specific suggestions on how the robot can create a relaxing environment when the user is feeling stressed." This allows for flexible responses that are tailored to the user's emotions.

[0549] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0550] Step 1:

[0551] The device acquires user environmental information (sound, lighting) and biometric information (heart rate, gaze, face orientation) through smart glasses. The input is real-time data from sensors, and the output is aggregated raw data. This data is transferred to a server for later analysis.

[0552] Step 2:

[0553] The server processes the raw data received by the data collection means using the analysis means. The input data consists of environmental and biometric information aggregated in step 1, and by applying this to the analysis algorithm, the user's emotional state (relaxed, stressed, excited, etc.) is obtained as output. This analysis process is performed in real time, and the user's state is continuously monitored.

[0554] Step 3:

[0555] The server generates appropriate virtual reality content using content generation means based on the user's emotional state obtained by the analysis means. The input is the user's emotional state, and the output is a virtual environment (such as calming music or scenery) that is suitable for that state. This generation is performed dynamically to optimize the user experience.

[0556] Step 4:

[0557] The generated virtual reality content is returned to the terminal via a transmission method and displayed on the user's smart glasses. The input is the virtual reality content generated in step 3, and the output is the content that the user visually experiences. This allows the user to experience a virtual reality space that matches their emotional state.

[0558] Step 5:

[0559] The user interacts through actions and gaze within the virtual reality environment, and the device sends this new data back to the server. The input here is the user's interaction data, and the output is received by the server again as data for analysis in the next processing step.

[0560] Step 6:

[0561] The server uses behavioral control means to control the robot so that it provides in-home services that correspond to the user's emotional state. The inputs are the emotional state data analyzed in step 2 and the interaction data obtained in step 5, and the output is the robot's specific actions (e.g., playing music, adjusting the lighting). This enables the provision of services that are in line with the user's emotional state.

[0562] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0563] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0564] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0565] [Fourth Embodiment]

[0566] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0567] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0568] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0569] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0570] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0571] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0572] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0573] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0574] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0575] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0576] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0577] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0578] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0579] This invention relates to a system that provides a virtual reality (VR) experience using smart glasses. The user wears smart glasses and collects environmental data and biometric information through sensors built into the device. This includes environmental data such as location information, sound, and lighting conditions, as well as biometric information such as heart rate, gaze, and face orientation.

[0580] The device sends this information to the server. The server analyzes the user's stress level and interests based on the received data. Next, based on the analysis results, it generates virtual reality content to optimize the user's state. For example, if the user is feeling stressed, it generates content that includes relaxing natural scenery and music.

[0581] The server sends the generated content to the device, which then displays it on the user's smart glasses. This allows the user to easily and seamlessly transition from the physical world to a virtual environment, enjoying a personalized experience. Furthermore, the user's gaze and gestures within the virtual environment enable an even more interactive experience.

[0582] A concrete example is in an educational setting, where users (for example, students) can virtually visit historical sites. In this case, they can move their gaze to display detailed information or use gestures to zoom in on specific areas. Such interactions are realized through adaptive mechanisms where the server receives user interaction information and dynamically adjusts the content based on that information.

[0583] As a result, the present invention provides users with a highly personalized and immersive virtual reality experience, demonstrating its usefulness in a variety of situations.

[0584] The following describes the processing flow.

[0585] Step 1:

[0586] The user puts on smart glasses and begins operating the device. The device activates sensors and collects environmental data (location, sound, lighting conditions) and biometric information (heart rate, gaze, face orientation) in real time.

[0587] Step 2:

[0588] The device transmits collected environmental data and biometric information to the server. Secure communication protocols are used to ensure data security during transmission.

[0589] Step 3:

[0590] The server analyzes the received data to determine the user's state. At this stage, a learning algorithm is used to evaluate, for example, the user's stress level and areas of interest.

[0591] Step 4:

[0592] Based on the analysis results, the server generates virtual reality content suitable for the user's state. If the goal is relaxation, it selects content depicting calming natural scenery; if the goal is learning, it generates relevant educational content.

[0593] Step 5:

[0594] The server sends the generated virtual reality content to the terminal. Here too, data compression and stream formats are used to improve communication efficiency.

[0595] Step 6:

[0596] The device displays the transmitted content on the user's smart glasses, allowing the user to immerse themselves in a virtual world. The user can interact within this virtual reality space using gaze and gestures.

[0597] Step 7:

[0598] User interaction information is retransmitted to the server via the device, and the server analyzes this information to dynamically adapt the content. This makes it possible to continuously improve the quality of the user experience.

[0599] (Example 1)

[0600] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0601] Current virtual reality systems offer a limited user experience and fail to adequately personalize the experience based on stress levels and interests. As a result, users struggle to become immersed, and the effectiveness of interactions within virtual reality is limited. This challenge stems from a lack of real-time data analysis and dynamic adjustments through interaction.

[0602] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0603] In this invention, the server includes data collection means for receiving environmental information, including location, acoustic and light information, and biometric information, including heart rate, gaze and face orientation information, data collection means for receiving environmental information and biometric information received from the data collection means and determining the user's stress level and interests using a generating AI model, and content generation means for generating virtual reality content, including natural scenery and music, based on the user's stress level and interests determined by the analysis means. This makes it possible to provide a personalized virtual reality experience that is tailored to the individual state of the user.

[0604] "Data collection means" refers to a function for receiving environmental information, including location, acoustic and light information, and biometric information, including heart rate, gaze, and facial orientation information, acquired from the user.

[0605] The "analysis means" refers to a function that uses a generated AI model, based on received environmental and biometric information, to determine the user's stress level and areas of interest.

[0606] The "content generation means" is a function that generates virtual reality content, including natural scenery and music, based on the user's stress level and interests determined by the analysis means.

[0607] "Transmission means" refers to the functionality for delivering generated virtual reality content to users using encryption protocols.

[0608] "Adaptive measures" refer to functions that receive user interactions, including gaze and gestures, and dynamically adjust content using a generative AI model based on that information.

[0609] A "generative AI model" refers to a model that uses artificial intelligence to analyze data and make decisions or generate specific information.

[0610] A "prompt sentence" is a sentence that is input into a generative AI model to instruct it to perform a specific analysis or generation.

[0611] The embodiments for carrying out this invention are as follows.

[0612] The user wears smart glasses and uses a terminal to collect environmental and biometric information. The terminal incorporates a GPS-enabled location device, microphone sensor, light sensor, and built-in heart rate sensor, eye tracking sensor, accelerometer, and gyroscope, which are used to acquire data in real time. This data includes environmental information such as location, sound, and light, as well as biometric information such as heart rate, gaze, and facial orientation.

[0613] The device sends the collected data to the server. The server analyzes the data using a generative AI model to determine the user's stress level and interests. The analysis is performed using prompts to instruct the server on the environments in which the user experiences stress. For example, the prompt might be "Generate content that calms the user." This allows the AI ​​model to estimate the user's state and obtain information to generate appropriate virtual reality content.

[0614] Based on the analysis results, the server constructs virtual reality content tailored to the user's state. This content generation uses techniques that combine natural scenery and relaxing sounds. The generated content is then transmitted to the terminal using an encryption protocol.

[0615] The device displays the received content on the smart glasses, allowing the user to begin an immersive experience. For example, to alleviate stress, the user's field of vision could be filled with images of a clear blue sky or a tranquil seaside landscape. Furthermore, the user can interact with the virtual environment using eye movements and gestures. For instance, moving their gaze could display information, or specific movements could zoom in on the scene.

[0616] This system allows users to experience comfort and interest through personalized virtual reality experiences. The aim of this invention is to enable users to enjoy a richer experience.

[0617] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0618] Step 1:

[0619] The device acquires information about the user's surroundings using a location tracking device, microphone sensor, and light sensor built into the smart glasses. This information includes the user's current location, ambient sound, and light intensity. Furthermore, it collects biometric information such as heart rate, gaze, and face orientation using a heart rate sensor, eye tracking sensor, accelerometer, and gyroscope. This provides a detailed dataset in real time, preparing for the next steps.

[0620] Step 2:

[0621] The device encrypts the environmental and biometric information collected in Step 1 and sends it to the server. Encryption uses protocols to ensure the security of the communication. The server decodes the received data and converts it into a format suitable for analysis. This prepares the server to evaluate the user's state based on a high-quality, reliable dataset.

[0622] Step 3:

[0623] The server uses a generative AI model to analyze the data received in step 2. Based on environmental and biometric information as input, it estimates the user's stress level and areas of interest. During this process, the prompt "Generate content that calms the user" is used to instruct the AI ​​model. As an output of the analysis, hypotheses about the user's mental state are obtained, forming insights necessary for generating the next content.

[0624] Step 4:

[0625] Based on the analysis results obtained in Step 3, the server generates virtual reality content tailored to the user's state. This process involves selecting natural scenery and relaxing music, constructing scenes, and integrating sound data. The generated content is meticulously designed to provide the user with the utmost comfort and peace of mind.

[0626] Step 5:

[0627] The server sends the generated content back to the device. The device receives this content and displays it in the appropriate format on the smart glasses. This leads the user into an immersive virtual environment, allowing them to enjoy a new experience adapted to their mental state.

[0628] Step 6:

[0629] Users interact within a virtual environment, manipulating the scene by making eye contact and using gestures. The device sends these actions to the server in real time, which uses an AI model to perform additional analysis and dynamically adjust the content to provide the user with an even more personalized experience.

[0630] (Application Example 1)

[0631] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0632] In the real world, there is a challenge in that it is difficult for users to individually experience information related to specific places or environments. Typically, users need to research many sources themselves to obtain educational or cultural information. However, if they can intuitively and interactively experience information relevant to their situation in real time, educational efficiency and information accessibility will improve.

[0633] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0634] In this invention, the server includes data collection means for receiving environmental and biometric information acquired from the user, analysis means for analyzing the data and determining the user's state, and means for generating virtual reality content related to the surrounding physical environment based on location information. As a result, the user can receive relevant information as a VR experience at each location, enabling real-time interactive learning and information acquisition.

[0635] "Data collection means" refers to means for acquiring environmental and biometric information from users and transmitting it to a server or similar device.

[0636] "Analysis means" refers to a process or system that evaluates and determines the user's psychological or physiological state based on received environmental and biological information.

[0637] "Content generation means" refers to a process or device that creates virtual reality content based on analysis results such as the user's state and location information.

[0638] "Transmission means" refers to the infrastructure that sends generated virtual reality content to a user's terminal and allows the user to view or experience that content.

[0639] "Adaptive means" refers to a process or device for dynamically changing content in real time based on user interaction to optimize the user experience.

[0640] "Means for generating virtual reality content related to the surrounding physical environment based on location information" refers to a method or apparatus that utilizes the user's geographical location and surrounding environment data to create and provide virtual content related to that location to the user.

[0641] The system for realizing this invention collects the user's environment and biometric information and provides a personalized virtual reality experience based on that information. Details are described below.

[0642] Smart glasses are equipped with a variety of sensors to collect environmental data such as the user's location, sound, and lighting conditions, as well as biometric information such as heart rate, gaze, and facial orientation. This data is temporarily processed within the device and then transmitted to a server via a high-speed network.

[0643] The server executes analysis algorithms written in programming languages ​​such as Python to analyze the received information. In this process, the user's stress level and areas of interest are determined. Based on the analysis results, the server generates user-specific virtual reality content using a generative AI model (e.g., ChatGPT API).

[0644] The content integrates elements related to the user's current geographical location and surrounding environment, thereby providing historical events and educational information relevant to the user's real-world location. The generated content is transmitted to the user's smart glasses using VR content development platforms such as Unity or Unreal Engine.

[0645] A concrete example of content generation in this process is providing a 30-second video explaining the history of a place when a user visits a historical landmark. An example of a prompt to the generation AI model is, "Generate a video of 30 seconds or less explaining the historical background of the user's current location."

[0646] This allows users to enjoy interactive and educational experiences tailored to their location.

[0647] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0648] Step 1:

[0649] The device collects the user's environmental and biometric information through the sensors in the smart glasses. This includes environmental data such as location, sound, and lighting conditions, and biometric information such as heart rate, gaze, and face orientation. This data is first temporarily stored on the device (input). The device then transmits this data to a server via a high-speed network (output).

[0650] Step 2:

[0651] The server uses a programming language such as Python to analyze the received data (input). The analysis process combines gaze direction and heart rate data to evaluate the user's stress level and areas of interest (data calculation). Based on these results, the server determines the user's current psychological and physiological state (output).

[0652] Step 3:

[0653] The server generates virtual reality content using a generative AI model based on the analysis results (input). It prompts the generative AI model (e.g., ChatGPT API) to design content that matches the user's interests and stress levels (data processing). For example, it might use a prompt like, "Generate a video of 30 seconds or less showing the historical background of the user's current location" (prompt statement). As a result, customized content for the user is output.

[0654] Step 4:

[0655] The generated content is converted to a format suitable for the user's smart glasses using VR content development platforms such as Unity or Unreal Engine (input). During this conversion process, the content is adjusted to maximize the visual and auditory experience in virtual reality (specific actions). The converted content is then sent to the device (output).

[0656] Step 5:

[0657] The device displays the received virtual reality content on the smart glasses (input). The user can view this content and interact with it using gaze and gestures (specific actions). User interactions are recorded in real time on the device and fed back to the server as needed, which then adjusts the content (output).

[0658] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0659] This invention relates to a system that recognizes a user's emotions and dynamically adjusts the virtual reality experience based on them. The user wears smart glasses, and a terminal collects environmental data and biometric information in real time. During this process, sensors detect location, sound, and lighting conditions, and acquire data such as heart rate, gaze, and face orientation.

[0660] The device sends this information to the server. On the server, an emotion engine analyzes the user's emotions based on the received data. This analysis is performed by using a specific algorithm to classify the user's emotional state as, for example, "relaxed," "stressed," or "excited."

[0661] Based on the analysis results, the server generates appropriate virtual reality content according to the situation. For example, if the user's emotion is determined to be "stress," the server prepares a relaxing virtual environment and generates content that includes calming music and scenery.

[0662] The generated content is sent from the server to the device, which displays it on the user's smart glasses. The user interacts with the system through actions and gaze within the virtual reality environment. The device then sends data about these interactions back to the server, which analyzes the data and dynamically adjusts the content. This allows the user to obtain an optimal virtual reality experience that matches their emotional state at the time.

[0663] As a concrete example, let's consider its application in an educational setting. If a user (for example, a student) enters a virtual library to prepare for an exam and feels stressed by the situation, the emotion engine will analyze this as "stress." The server will immediately switch to a relaxing virtual landscape, providing the user with an environment where they can concentrate on learning. This process enables a flexible and customized experience that can respond to the user's emotional state.

[0664] The following describes the processing flow.

[0665] Step 1:

[0666] The user puts on smart glasses and activates the virtual reality system. The device collects environmental data and biometric information in real time through its built-in sensors. Environmental data includes location information, ambient sound, and light intensity, while biometric information includes heart rate, gaze direction, and facial expressions.

[0667] Step 2:

[0668] The device sends the collected data to the server. A secure communication protocol is used for transmission, ensuring data integrity and privacy.

[0669] Step 3:

[0670] The server analyzes the received data. The emotion engine evaluates the user's emotions based on the user's biometric information, determining, for example, whether the user is feeling "relaxed" or "stressed."

[0671] Step 4:

[0672] The server uses the results of the emotion engine's analysis to generate virtual reality content best suited to the user's current emotional state. If the server determines that the user is stressed, it will generate content that includes relaxing natural scenery and calming music.

[0673] Step 5:

[0674] The server sends the generated content to the device, which then displays it on the user's smart glasses. During this process, the video and audio are played smoothly to ensure a seamless and immersive experience for the user.

[0675] Step 6:

[0676] Users interact within the displayed virtual environment using gaze and gestures. For example, they can select specific objects using their gaze or manipulate them with gestures.

[0677] Step 7:

[0678] User interaction data is sent back to the server via the device, where it is analyzed and the content is dynamically adjusted as needed. This ensures that the user's emotional state and needs are continuously met, providing a truly responsive experience.

[0679] (Example 2)

[0680] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0681] In the modern era, virtual experiences in digital environments are becoming increasingly diverse, and there is a demand for customized experiences tailored to the individual user's state. However, conventional virtual experience systems have the problem of difficulty in dynamically adjusting content to adequately reflect the user's real-time emotions and biometric information. This invention aims to solve this problem and provide a system that allows users to obtain the optimal experience at that moment.

[0682] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0683] In this invention, the server includes information gathering means for receiving environmental and biometric information acquired from the user, state analysis means for analyzing the information received from the information gathering means and determining the user's state, and experience generation means for generating virtual experience content based on the user's state determined by the state analysis means. This makes it possible to dynamically provide an experience that is suitable for the user's real-time state.

[0684] "Information gathering means" refers to a device or software that has the function of acquiring environmental and biometric information from a user.

[0685] "State analysis means" refers to a device or software that has the function of analyzing collected information and determining the user's emotions and biological state.

[0686] "Experience generation means" refers to a device or software that has the function of constructing virtual experience content based on the results of user state analysis.

[0687] "Display means" refers to a device or software that has the function of presenting generated virtual experience content to a user.

[0688] "Adjustment means" refers to a device or software that has the function of receiving responses from users and dynamically adjusting the virtual experience based on those responses.

[0689] A "detection device" is a device that includes sensors and other components for collecting environmental and biological information in real time.

[0690] A "virtual experience" refers to a simulated environment or situation created for a user using a computer system.

[0691] This invention is a system that recognizes the user's emotions in real time and dynamically adjusts the virtual experience based on those emotions. The user uses a smart device, and various sensors built into the device collect environmental and biometric information. This includes location information, sound environment, lighting conditions, heart rate, gaze, and facial orientation.

[0692] The terminal is responsible for immediately transmitting this information to the server. The server analyzes the received data and classifies the user's emotions using an emotion engine with a generative AI model. Emotion analysis is performed by classifying the user's emotions into states such as "relaxed," "stressed," and "excited."

[0693] Based on the analysis results, the server generates content to adjust the virtual experience. For example, if stress is detected, it might create a virtual space that includes relaxing ambient sounds and scenery. This allows the system to quickly adapt to the user's desired experience.

[0694] The generated virtual experience content is displayed on the user's smart device via a terminal. The user interacts with the system through their gaze and movements within the virtual space. This movement information is collected again and sent to the server to be used to dynamically adjust the virtual experience.

[0695] A concrete example is its use in educational settings. If a user experiences stress while preparing for an exam in a virtual library, the system can instantly switch to a calm and quiet environment, providing a state conducive to focused learning. This allows for flexible responses tailored to individual emotional states.

[0696] Example of a prompt:

[0697] "When students feel stressed in the virtual library, how do you transform the environment into a more relaxing one?"

[0698] This system is a modern approach that utilizes generative AI models to provide users with the optimal virtual experience in real time.

[0699] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0700] Step 1:

[0701] The user wears a smart device and begins the virtual experience. The device uses built-in sensors to collect environmental information and biometric information in real time, including the user's location, sound environment, lighting conditions, heart rate, gaze, and face orientation. The input is the user's environmental data and biometric information, and the output is this collected data. Specifically, the gaze tracking sensor captures the user's gaze direction, and the heart rate sensor measures the heart rate.

[0702] Step 2:

[0703] The device transmits the collected data to the server. The input is a set of collected environmental and biometric data, and the output is this data converted into transmission data packets. Specifically, the device uploads the data to the server via high-speed Wi-Fi, minimizing data transfer delays.

[0704] Step 3:

[0705] The server analyzes the received data and estimates the user's emotions using a generative AI model. This process utilizes an emotion engine. The input consists of transmitted environmental data and biometric information, and the output is the estimated emotional state of the user. Specifically, the emotion engine analyzes heart rate and eye movement patterns and classifies the emotional state into one of three categories: "relaxed," "stressed," or "excited."

[0706] Step 4:

[0707] The server generates virtual experience content based on the user's emotional state. The input is the estimated emotional state, and the output is the corresponding virtual experience content. Specifically, if a stressed state is detected, the server synthesizes content including relaxing music and scenery to adjust the virtual space.

[0708] Step 5:

[0709] The server sends the generated virtual experience content to the terminal. The input is the generated virtual experience content, and the output is the content converted into display data. Specifically, the server sends the content data to the terminal, which then prepares to display it on a smart device.

[0710] Step 6:

[0711] Users interact within a virtual space. Input is the displayed virtual content, and output is interaction data based on the user's gaze and movements. Specific actions include the user selecting a particular virtual object using their gaze.

[0712] Step 7:

[0713] The terminal collects user interaction data and sends it to the server. The input is user interaction data, and the output is data packets for transmission. Specifically, the terminal detects user movements and changes in gaze, organizes the data based on these, and sends it to the server.

[0714] Step 8:

[0715] The server dynamically adjusts the virtual experience content based on user interaction. The input is user interaction data, and the output is the updated virtual experience content. Specifically, if the server determines that the user has entered a relaxed state, it switches to content containing a wider variety of stimuli.

[0716] (Application Example 2)

[0717] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0718] Current in-home service robots struggle to flexibly adapt their actions to the user's emotional state. Therefore, it's difficult to provide services appropriate to a user's state, such as when they are stressed or seeking relaxation. Consequently, there is a need to develop a system that can recognize the user's emotional state in real time and dynamically adjust the in-home environment and services accordingly.

[0719] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0720] In this invention, the server includes data collection means for receiving environmental and biometric information acquired from the user, analysis means for analyzing the data received from the data collection means and determining the user's state, and content generation means for generating and dynamically adjusting virtual reality content based on the user's state determined by the analysis means. This enables dynamic adjustment of the home environment in accordance with the user's emotional state and the provision of appropriate services.

[0721] "Data collection means" refers to a device or function for receiving environmental information and biometric information acquired from users.

[0722] "Analysis means" refers to a function or program that determines the user's emotions or state based on data obtained from data collection means.

[0723] "Content generation means" refers to a device or function that generates virtual reality content suitable for the user's state based on analysis results, and further dynamically adjusts it.

[0724] "Transmission means" refers to a device or function for delivering generated virtual reality content to a user's device.

[0725] "Behavior control means" refers to a device or function that controls the home environment or the provision of services based on the user's emotional state.

[0726] The system implementing this invention mainly consists of data collection means, analysis means, content generation means, transmission means, and behavior control means. Specifically, a robot installed in a home is central to this system.

[0727] The system program operates as follows: As a data collection method, smart glasses acquire the user's environmental information (sound and lighting) and biometric information (heart rate, gaze, face orientation) in real time. This data is received by a robot and analyzed to determine the user's emotional state (e.g., relaxed, stressed, excited).

[0728] The analyzed information is formed into virtual reality content tailored to the user's state by a content generation means. The generated content is delivered to a robot via a transmission means, and the user experiences virtual reality through smart glasses.

[0729] Furthermore, the behavioral control system enables the robot to provide in-home services based on the user's emotional state. If the user shows signs of stress, the robot can play calming music or change the lighting to create a relaxing environment.

[0730] The operation of this system is realized by a generating AI model in the form of specific prompt statements, such as, "Please provide specific suggestions on how the robot can create a relaxing environment when the user is feeling stressed." This allows for flexible responses that are tailored to the user's emotions.

[0731] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0732] Step 1:

[0733] The device acquires user environmental information (sound, lighting) and biometric information (heart rate, gaze, face orientation) through smart glasses. The input is real-time data from sensors, and the output is aggregated raw data. This data is transferred to a server for later analysis.

[0734] Step 2:

[0735] The server processes the raw data received by the data collection means using the analysis means. The input data consists of environmental and biometric information aggregated in step 1, and by applying this to the analysis algorithm, the user's emotional state (relaxed, stressed, excited, etc.) is obtained as output. This analysis process is performed in real time, and the user's state is continuously monitored.

[0736] Step 3:

[0737] The server generates appropriate virtual reality content using content generation means based on the user's emotional state obtained by the analysis means. The input is the user's emotional state, and the output is a virtual environment (such as calming music or scenery) that is suitable for that state. This generation is performed dynamically to optimize the user experience.

[0738] Step 4:

[0739] The generated virtual reality content is returned to the terminal via a transmission method and displayed on the user's smart glasses. The input is the virtual reality content generated in step 3, and the output is the content that the user visually experiences. This allows the user to experience a virtual reality space that matches their emotional state.

[0740] Step 5:

[0741] The user interacts through actions and gaze within the virtual reality environment, and the device sends this new data back to the server. The input here is the user's interaction data, and the output is received by the server again as data for analysis in the next processing step.

[0742] Step 6:

[0743] The server uses behavioral control means to control the robot so that it provides in-home services that correspond to the user's emotional state. The inputs are the emotional state data analyzed in step 2 and the interaction data obtained in step 5, and the output is the robot's specific actions (e.g., playing music, adjusting the lighting). This enables the provision of services that are in line with the user's emotional state.

[0744] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0745] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0746] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0747] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0748] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0749] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0750] The inside of the Emotion Map 400 represents what's in your mind, while the outside represents what you're doing. Therefore, the further you go out the 400-coordinate scale, the more visible your emotions become (the more they manifest in your actions).

[0751] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0752] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0753] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0754] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0755] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0756] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0757] 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.

[0758] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0759] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0760] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0761] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0762] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0763] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0764] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0765] The following is further disclosed regarding the embodiments described above.

[0766] (Claim 1)

[0767] A data collection means for receiving environmental and biometric information obtained from the user,

[0768] An analysis means analyzes the data received from the data collection means and determines the user's state,

[0769] Content generation means that generates virtual reality content based on the user's state determined by the analysis means,

[0770] A means for transmitting generated virtual reality content to users,

[0771] An adaptive mechanism that receives user interaction and dynamically adjusts content based on it,

[0772] A system that includes this.

[0773] (Claim 2)

[0774] The system according to claim 1, further comprising sensors for collecting environmental data and biometric information in real time.

[0775] (Claim 3)

[0776] The system according to claim 1, characterized in that it dynamically changes objects and scenes in virtual reality based on user interaction.

[0777] "Example 1"

[0778] (Claim 1)

[0779] A data collection means for receiving environmental information including location, acoustic and light information acquired from the user, and biometric information including heart rate, gaze and face orientation information,

[0780] An analysis means that uses environmental information and biometric information received from the data collection means to determine the user's stress level and areas of interest using a generated AI model,

[0781] A content generation means that generates virtual reality content, including natural scenery and music, based on the user's stress level and interests determined by the analysis means,

[0782] A means for transmitting generated virtual reality content to a user using an encryption protocol,

[0783] An adaptive means that receives user interaction, including gaze and gestures, and dynamically adjusts content using a generative AI model based on that interaction.

[0784] A system that includes this.

[0785] (Claim 2)

[0786] The system according to claim 1, further comprising sensors for collecting environmental information and biological information in real time.

[0787] (Claim 3)

[0788] The system according to claim 1, characterized in that it dynamically changes objects and scenes in virtual reality based on the user's gaze and gesture interactions.

[0789] "Application Example 1"

[0790] (Claim 1)

[0791] A data collection means for receiving environmental and biometric information obtained from the user,

[0792] An analysis means analyzes the data received from the data collection means and determines the user's state,

[0793] Content generation means that generates virtual reality content based on the user's state determined by the analysis means,

[0794] A means for transmitting generated virtual reality content to users,

[0795] An adaptive mechanism that receives user interaction and dynamically adjusts content based on it,

[0796] A means that enables the generation of virtual reality content related to the surrounding physical environment based on location information,

[0797] A system that includes this.

[0798] (Claim 2)

[0799] The system according to claim 1, further comprising sensors for collecting environmental data and biometric information in real time.

[0800] (Claim 3)

[0801] The system according to claim 1, characterized in that it dynamically changes objects and scenes in virtual reality based on user interaction.

[0802] "Example 2 of combining an emotion engine"

[0803] (Claim 1)

[0804] Information collection means for receiving environmental and biometric information acquired from the user,

[0805] A state analysis means analyzes the information received from the aforementioned information collection means and determines the user's state,

[0806] An experience generation means that generates virtual experience content based on the user's state determined by the state analysis means,

[0807] A display means for presenting generated virtual experience content to the user,

[0808] An adjustment mechanism that receives a response from the user and dynamically adjusts the experience based on it,

[0809] A system that includes this.

[0810] (Claim 2)

[0811] The system according to claim 1, further comprising a detection device for immediately collecting environmental information and biological information.

[0812] (Claim 3)

[0813] The system according to claim 1, characterized in that it dynamically changes elements and scenes within a virtual experience based on user responses.

[0814] "Application example 2 when combining with an emotional engine"

[0815] (Claim 1)

[0816] A data collection means for receiving environmental and biometric information obtained from the user,

[0817] An analysis means analyzes the data received from the data collection means and determines the user's state,

[0818] Content generation means that generates and dynamically adjusts virtual reality content based on the user's state determined by the analysis means,

[0819] A means for transmitting generated virtual reality content to users,

[0820] A means of controlling behavior to provide in-home services in response to the user's emotional state,

[0821] A system that includes this.

[0822] (Claim 2)

[0823] The system according to claim 1, further comprising sensors for collecting environmental data and biometric information in real time.

[0824] (Claim 3)

[0825] The system according to claim 1, characterized in that it dynamically changes the home environment based on user interaction and emotional state. [Explanation of symbols]

[0826] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A data collection means for receiving environmental and biometric information obtained from the user, An analysis means analyzes the data received from the data collection means and determines the user's state, Content generation means that generates virtual reality content based on the user's state determined by the analysis means, A means for transmitting generated virtual reality content to users, An adaptive mechanism that receives user interaction and dynamically adjusts content based on it, A means that enables the generation of virtual reality content related to the surrounding physical environment based on location information, A system that includes this.

2. The system according to claim 1, further comprising sensors for collecting environmental data and biological information in real time.

3. The system according to claim 1, characterized in that it dynamically changes objects and scenes in virtual reality based on user interaction.

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