system

Abstract

Provide a system. A means for acquiring user profile information; a means for acquiring and transmitting local environmental data; A means for analyzing the received environmental data and generating optimal virtual experience content; means for transmitting the generated content to a user's device; a means for providing a virtual experience on a user's device; means for collecting and transmitting user interaction data during the virtual experience; a means of analyzing interaction data to generate feedback in real time; A system including:

Description

[Technical Field]

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

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

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

[0004] The elderly and physically disabled face the challenge of having limited opportunities to enjoy mental and sensory pleasure due to the difficulty of actually traveling. In addition, advanced, real-time interaction is required to make them feel like they are traveling with their family, but conventional methods have not been able to fully realize this. [Means for solving the problem]

[0005] In order to solve the above problems, the present invention provides the following means.

[0006] The system includes a means for acquiring user profile information, a means for acquiring and transmitting local environmental data, a means for analyzing the received environmental data to generate optimal virtual experience content, a means for transmitting the generated content to the user's device, a means for providing the virtual experience on the user's device, a means for collecting and transmitting user interaction data during the virtual experience, and a means for analyzing the interaction data to generate feedback in real time.

[0007] This allows users to experience the sensation of traveling with their family in real time. Providing multiple types of sensory information (visual, tactile, and audio) creates a more realistic experience. Furthermore, customizing the virtual experience content based on the user's health condition and sensitivity information allows for an optimal experience for each individual user.

[0008] "Means for obtaining user profile information" refers to a function for obtaining personal information such as the user's health condition, sensitivity, preferences, etc. from a database.

[0009] "Means for acquiring and transmitting local environmental data" refers to a function for transmitting visual, audio, tactile, and other environmental data acquired on-site to a server.

[0010] "Means for analyzing received environmental data and generating optimal virtual experience content" refers to the function by which the server analyzes the local environmental data received and generates optimal virtual content based on the user's profile.

[0011] "Means for transmitting generated content to a user's device" refers to a function for transmitting generated virtual experience content from a server to a user's terminal.

[0012] "Means for providing a virtual experience on a user's device" refers to a function for providing a virtual experience to a user through a device worn by the user.

[0013] "Means for collecting and transmitting user interaction data during the virtual experience" refers to a function for detecting the user's conversations and actions, collecting that data, and transmitting it to a server.

[0014] "Means for analyzing interaction data and generating feedback in real time" refers to a function by which the server analyzes user interaction data, generates feedback in real time, and provides it to the user. [Brief explanation of the drawings]

[0015] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0016] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0017] First, the terms used in the following description will be explained.

[0018] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0019] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0020] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0021] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0022] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0023] [First embodiment]

[0024] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0025] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0026] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0027] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0028] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0029] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0030] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0031] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0032] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0033] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0034] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0035] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0036] This is a system that provides a virtual experience for elderly people and people with disabilities, allowing them to feel like they are traveling with their family. This system acquires user profile information and achieves real-time interaction through a series of processes that receive, analyze, generate, and provide local environmental data in real time.

[0037] Natural language explanation of the program's processing

[0038] 1. Obtaining user profile information

[0039] The server retrieves the user's profile information (health status, sensitivity, favorite tourist spots, etc.) from the database.

[0040] The server uses the acquired information to design a virtual experience that suits the user's condition and preferences.

[0041] 2. Acquisition and transmission of local environmental data

[0042] The device collects local environmental data (visual, audio, tactile, etc.).

[0043] The terminal transmits this environmental data to the server in real time.

[0044] The device also obtains location information using GPS and other means and sends this information to the server.

[0045] 3. Analysis of environmental data and generation of virtual experience content

[0046] The server analyzes the received environmental data.

[0047] The server generates virtual experience content tailored to the user's profile information based on the analysis results.

[0048] The server transmits the generated content to the user's terminal.

[0049] 4. Providing virtual experiences

[0050] The user experiences the provided virtual experience content using a dedicated device (such as a VR headset or haptic device).

[0051] Users can experience the experience as if they were actually there through sight, touch, sound, etc.

[0052] 5. Collection and transmission of user interaction data

[0053] The device detects the conversations and actions the user makes during the virtual experience.

[0054] The terminal collects sensed interaction data and transmits it to a server.

[0055] 6. Real-time feedback generation

[0056] The server analyzes the user interaction data.

[0057] The server generates real-time feedback based on the analysis results and sends it to the user's device.

[0058] Feedback includes conversational responses and reactions to actions.

[0059] Specific examples

[0060] For example, consider the case where an elderly person, Mr. A, uses the system at home while his family is on a trip to a seaside resort. The family uses smartphones or dedicated devices at the destination to collect real-time environmental data, such as the sound of the ocean, the scenery, and the feel of the sand. This data is sent to a server, which then generates the most suitable virtual experience content for Mr. A based on his profile information.

[0061] By wearing a dedicated VR headset and haptic device, Mr. A can feel as if he is at a seaside resort in his own home. He can talk to his family and interact with them in real time, giving him the experience of actually traveling.

[0062] The processing flow will be explained below.

[0063] Step 1: Obtaining the user's profile information

[0064] The server queries the database based on the user's ID and obtains the user's profile information (health status, sensitivity, favorite tourist spots, etc.).

[0065] Step 2: Obtaining local environmental data

[0066] The device obtains local GPS location information.

[0067] The device collects environmental data from the local surroundings (visual data from the camera, audio data from the microphone, and tactile data from the tactile sensor).

[0068] Step 3: Sending environment data

[0069] The device compresses the collected environmental data in real time and sends it to the server.

[0070] Step 4: Parse the received data

[0071] The server analyzes the received environmental data.

[0072] The server analyzes the visual data using image processing algorithms and converts it into virtual content.

[0073] The server analyzes the voice data using a voice recognition algorithm and performs voice filtering if necessary.

[0074] The server analyzes the tactile data and converts it into signals for the haptic device.

[0075] Step 5: Generate virtual experience content

[0076] The server generates optimal virtual experience content based on the user's profile information.

[0077] The server applies data filters based on health status and sensitivity, and creates content tailored to the user's condition.

[0078] Step 6: Submit your content

[0079] The server compresses the generated virtual experience content in real time and transmits it to the user's terminal.

[0080] Step 7: Start the user's virtual experience

[0081] Users experience the virtual experience content provided through the device using a VR headset or haptic device.

[0082] The user sees visual information through a VR headset, hears audio information through headphones, and experiences tactile information through a haptic device.

[0083] Step 8: Collect interaction data

[0084] When the user talks or moves during the virtual experience, the device detects this.

[0085] The device collects voice data using a microphone and acquires movement data using a motion sensor.

[0086] Step 9: Sending interaction data

[0087] The terminal transmits the collected interaction data to the server in real time.

[0088] Step 10: Analyze interaction data and generate feedback

[0089] The server analyzes the received interaction data.

[0090] The server analyzes the user's voice data and generates an appropriate response.

[0091] The server analyzes the motion data and generates the necessary virtual interactions.

[0092] The server transmits the generated feedback to the user's terminal in real time.

[0093] Step 11: Provide real-time feedback

[0094] The user receives real-time feedback from the server during the virtual experience.

[0095] The user experiences conversational responses and reactions to actions.

[0096] Example 1

[0097] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0098] Until now, there has been no means available for elderly people and people with physical disabilities to have a real-time virtual experience that makes it seem as if they are traveling with family and friends, even when mobility is difficult. To provide a realistic experience, it is necessary to provide multiple sensory information, such as visual, tactile, and audio, in real time and provide instant feedback on the user's reactions to that information, but the specific system configuration and technical means to achieve this have not yet been established.

[0099] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0100] In this invention, the server includes means for acquiring user profile information, means for collecting local environmental data and transmitting it to the server, means for analyzing the received environmental data, means for generating virtual experience content based on the user profile information, means for transmitting the generated content to the user's device, means for providing the virtual experience on the user's device, means for collecting user interaction data during the virtual experience and transmitting it to the server, and means for analyzing the interaction data and generating feedback in real time, thereby enabling elderly people and people with disabilities to have an experience similar to a real trip in real time and interactively from a safe place such as their own home.

[0101] "Profile information" is information that indicates individual characteristics and conditions such as the user's name, age, health condition, sensitivity, favorite tourist spots, etc.

[0102] "Environmental data" refers to data that includes information about the surroundings, such as visual, audio, and tactile information of the local area.

[0103] "Virtual experience content" refers to content such as images, audio, and haptic feedback that are generated so that users can experience the same environment as they would in a real world.

[0104] "Interaction data" refers to data that indicates a user's reactions and behavior, such as the conversations and actions the user engages in during a virtual experience.

[0105] "Feedback" is data that indicates responses or reactions that are generated based on user interaction data and provided to the user in real time.

[0106] "Device" refers to the equipment used by a user to receive a virtual experience (e.g., VR headset, haptic device, etc.).

[0107] A "server" is a central computer system that receives, analyzes, and processes data sent by users, and generates and sends virtual experience content and feedback to users.

[0108] "Collection" refers to obtaining visual, audio, tactile, and other data on-site.

[0109] "Transmit" means transferring collected data to another device or computer system.

[0110] "Analysis" refers to evaluating collected data and extracting necessary information.

[0111] "Generation" means creating new content or information based on the analysis results.

[0112] This invention is a system that provides a virtual experience for elderly people and people with disabilities, allowing them to feel like they are traveling with their family. This system acquires user profile information and achieves real-time interaction through a series of processes that receive, analyze, generate, and provide local environmental data in real time.

[0113] 1. Profile information acquisition

[0114] The server retrieves the user's profile information from the database, such as the user's name, age, health status, sensitivity, favorite tourist spots, etc. This allows the server to personalize the virtual experience to suit the user's preferences and characteristics.

[0115] 2. Acquisition and transmission of local environmental data

[0116] The device (e.g., a smartphone or dedicated device) collects visual, audio, and tactile data using local environmental data (e.g., a 360-degree camera, field recorder, tactile sensor, etc.). The device transmits the collected data to a server in real time. In addition, the device obtains its location information using GPS and transmits it to the server.

[0117] 3. Analysis of environmental data and generation of virtual experience content

[0118] The server analyzes the received environmental data using data analysis software such as Python libraries (e.g., OpenCV, Librosa) and TENSORFLOW (registered trademark). Based on the analysis results, the server generates virtual experience content optimized for the user's profile information. This content is converted into a format compatible with the device used by the user (e.g., VR headset, haptic device).

[0119] 4. Providing virtual experiences

[0120] Users wear a dedicated device (e.g., Oculus Quest 2, Teslasuit) to enjoy a virtual experience. Users can experience the experience as if they were actually there through sight, touch, and sound, and can converse and interact with family and friends in the location.

[0121] 5. Collection and transmission of interaction data

[0122] The conversations and actions that users make during the virtual experience are detected by the device (e.g., the built-in microphone and motion sensor of the Oculus Quest 2, or the sensor of the Teslasuit). This interaction data is sent to the server in real time.

[0123] 6. Real-time feedback generation

[0124] The server analyzes the received interaction data using natural language processing models and motion analysis algorithms (e.g., OpenAI's (registered trademark) GPT model, PoseNet, etc.). The server generates real-time feedback based on the analysis results and sends it to the user's device. The feedback includes conversational responses and haptic feedback.

[0125] Specific examples

[0126] For example, consider the case where elderly person A uses this system at home while their family travels to a seaside resort. While at the resort, the family uses smartphones or dedicated devices (e.g., 360-degree cameras, ambient sound microphones, tactile sensors, etc.) to collect real-time environmental data, such as the sound of the ocean, the scenery, and the feel of the sand. This data is sent to a server, which then generates virtual experience content that is optimal for A based on his or her profile information.

[0127] By wearing a dedicated VR headset and haptic device, Mr. A can feel as if he is at a seaside resort in his own home. He can talk to his family and interact with them in real time, giving him the experience of actually traveling.

[0128] Prompt Sentence Examples

[0129] Below are some example prompts to input to a generative AI model (e.g., GPT-3®):

[0130] Please explain a system that provides a virtual experience that allows elderly people and people with disabilities to feel like they are traveling with their families. This system acquires user profile information and performs a series of processes to receive, analyze, generate, and provide local environmental data in real time. Please explain in detail what specific hardware and software are used, how the data is processed, and how the virtual experience is provided.

[0131] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0132] Step 1:

[0133] The server retrieves the user's profile information from the database.

[0134] Specifically, the server issues SQL queries to the database to retrieve information such as the user's name, age, health status, sensitivity, and favorite tourist spots. This retrieved profile information becomes the input data for the next processing step. The output is the user's detailed information.

[0135] Step 2:

[0136] The device collects local environmental data and transmits it to a server in real time.

[0137] The terminal collects visual, audio, and tactile data using devices such as a 360-degree camera, field recorder, and tactile sensor. It also acquires location information using GPS. The input is local environmental data and location information. The acquired data is uploaded to a server via a communication line. The output is the environmental data and location information sent to the server.

[0138] Step 3:

[0139] The server analyzes the received environmental data.

[0140] Visual, audio, and haptic data is analyzed using Python libraries (e.g., OpenCV, Librosa) and TensorFlow. The results of this analysis are the basis for generating the user's virtual experience content. The input is the local environment data received by the server. The output is the analyzed environment data.

[0141] Step 4:

[0142] The server generates virtual experience content based on the analysis results.

[0143] The server creates personalized virtual experience content based on the user's profile information and analyzed environmental data. A generative AI model (e.g., TensorFlow, GANs, etc.) is used for generation. The input is the user's profile information and analyzed environmental data. The output is the virtual experience content.

[0144] Step 5:

[0145] The server transmits the generated virtual experience content to the user's device.

[0146] The generated content is converted into a format compatible with the user's VR headset or haptic device and sent to the user's device via a communication line. The input is the generated virtual experience content. The output is the content sent to the user's device.

[0147] Step 6:

[0148] Users get a virtual experience using a dedicated device.

[0149] A user wears a VR headset (e.g., Oculus Quest 2) and a haptic device (e.g., Teslasuit) to play virtual experience content. The input is the received virtual experience content. The output is feedback of the user's virtual experience.

[0150] Step 7:

[0151] The device collects local interaction data and sends it to a server.

[0152] The conversations and actions that users make during the virtual experience are collected through the built-in microphones, motion sensors, and sensors in the haptic device of the VR headset. The input is the user's interaction. The collected data is sent to the server in real time. The output is the interaction data sent to the server.

[0153] Step 8:

[0154] The server analyzes the interaction data and generates feedback in real time.

[0155] The server analyzes the interaction data using a natural language processing model (e.g., GPT model) or a motion analysis algorithm (e.g., PoseNet). The input is the transmitted interaction data. Based on the analysis results, the server generates feedback data to respond to the user in real time. The output is the generated feedback.

[0156] Step 9:

[0157] The server generates feedback and sends it to the user's device.

[0158] The feedback data is transmitted to the user's device via a communication line and provided to the user in real time. The input is the generated feedback data. The output is the real-time feedback provided to the user.

[0159] (Application example 1)

[0160] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0161] With conventional virtual experience systems, it was difficult for elderly people and people with physical disabilities to enjoy a rich shopping experience without actually going to the location. It was also difficult to provide a personalized experience that matched each user's preferences and health condition. This made it difficult to provide a satisfying virtual experience, especially for users with specific needs.

[0162] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0163] In this invention, the server includes means for acquiring user profile information, means for acquiring and transmitting local environmental data, means for analyzing the received environmental data to generate optimal virtual experience content, means for transmitting the generated content to the user's device, means for providing the virtual experience on the user's device, means for collecting and transmitting user interaction data during the virtual experience, means for analyzing the collected interaction data to generate feedback in real time, and means for customizing the shopping experience based on the user's past purchasing history, thereby enabling even elderly people and people with disabilities to enjoy a customized shopping experience in real time without having to go to the site.

[0164] The "means for acquiring user profile information" has a function for acquiring personal information such as the user's health condition, preferences, and past purchase history from a storage device such as a database.

[0165] The "means for acquiring and transmitting local environmental data" is a function that collects data necessary for the user to feel as if they are in the local area, such as local video, audio, and tactile information, and transmits this data to a server.

[0166] The "means for analyzing received environmental data and generating optimal virtual experience content" has the function of analyzing received local environmental data and generating optimized virtual experience content based on the user's profile information.

[0167] "Means for transmitting generated content to a user's device" means a function that transmits the generated virtual experience content to a user's device, such as a VR headset or smart glasses.

[0168] "Means for providing a virtual experience on a user's device" means a function that provides the generated virtual experience content to the user through the user's device, allowing the user to experience it through sight, touch, sound, etc.

[0169] "Means for collecting and transmitting user interaction data during a virtual experience" refers to a device that has the function of collecting interaction data such as the user's actions and conversations during the virtual experience and transmitting it to a server.

[0170] The "means for analyzing collected interaction data and generating feedback in real time" has the function of analyzing collected user interaction data and generating feedback on user actions in real time.

[0171] "Means for customizing a shopping experience based on a user's past purchasing history" refers to a function that customizes virtual experience content based on the user's past purchasing history information in order to provide the optimal shopping experience tailored to the user's preferences.

[0172] This invention provides a virtual experience system that allows elderly people and people with physical disabilities to enjoy a rich shopping experience from home. The system is configured to provide a personalized experience by utilizing the user's personal information, preferences, and past purchasing history.

[0173] 1. Obtaining user profile information

[0174] The server retrieves the user's profile information (health status, preferences, past purchase history, etc.) from the database, which is then used to optimize the virtual shopping experience for the individual user.

[0175] 2. Acquisition and transmission of local environmental data

[0176] Devices (e.g., smartphones or smart glasses) collect environmental data such as video, audio, and detailed product information in real time within a local store. This data is then sent from the local store to a server. The devices are equipped with cameras, microphones, sensors, etc., and have a communication module for transmitting this data in real time.

[0177] 3. Analysis of environmental data and generation of virtual experience content

[0178] The server analyzes the received environmental data and, in cooperation with a generative AI model, generates optimal virtual shopping experience content based on the user's profile information. This analysis utilizes cloud services such as computer vision APIs (e.g., Amazon Rekognition) and natural language processing models (e.g., Google® Cloud Speech-to-Text).

[0179] 4. Providing virtual experiences

[0180] The generated virtual experience content is sent to the user's device (e.g., VR headset or smart glasses). By wearing these devices, the user can experience walking through the virtual store and picking up products through sight, touch, and sound.

[0181] 5. Collection and transmission of user interaction data

[0182] Interaction data, such as conversations and actions that users make during the virtual experience, is sensed and collected by the device, and the collected data is sent to a server.

[0183] 6. Real-time feedback generation

[0184] The server analyzes the collected interaction data, generates feedback in real time, and sends it to the user's device, providing instant feedback on the user's actions and providing a simulated experience that makes the user feel as if they are actually in the store.

[0185] Specific examples

[0186] For example, an elderly user can use the system at home, while a local store staff member uses a terminal to transmit video and audio from the store in real time. The user can then enjoy a personalized shopping experience based on their profile information and past purchase history through a VR headset or smart glasses.

[0187] Examples of prompt statements

[0188] "Generate a virtual store experience tailored to the user's preferences. User information: {Name: 'Jiro Taguchi', Age: 75, Preferences: ['Clothing', 'Electronics']}, Current Store Labels: ['Laptop', 'Smartphone']"

[0189] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0190] Step 1:

[0191] The server retrieves the user's profile information from the database. The retrieved information includes the user's health condition, preferences, past purchase history, etc. The input is identification information such as the user ID, and the output is the user's detailed profile information. This information is retrieved using a database access API.

[0192] Step 2:

[0193] The terminal acquires local environmental data in real time and sends it to the server. The environmental data includes video, audio, and detailed product information from within the store. The terminal collects data using cameras and microphones and sends it through a communications module. The input is sensor data from the cameras and microphones, and the output is data sent to the server.

[0194] Step 3:

[0195] The server analyzes the received local environmental data and generates virtual experience content. The server processes the data using computer vision APIs (e.g., Amazon Rekognition) and natural language processing models (e.g., Google Cloud Speech-to-Text). The input is the received environmental data and user profile information, and the output is the generated virtual experience content.

[0196] Step 4:

[0197] The server generates virtual experience content and sends it to the user's device, which can be a VR headset or smart glasses. The input is the generated virtual experience content, and the output is the data sent to the user's device.

[0198] Step 5:

[0199] The user's device plays the virtual experience content and provides the user with the experience through sight, touch, and sound. The device can be a VR headset or smart glasses, with the input being the transmitted virtual experience content and the output being the user's virtual experience.

[0200] Step 6:

[0201] The device collects interaction data of the user during the virtual experience and sends it to the server. The interaction data includes the user's actions and conversations. The input is the data of the user's actions and speech, and the output is the data sent to the server.

[0202] Step 7:

[0203] The server analyzes the collected interaction data and generates feedback in real time. The server uses a generative AI model to analyze and generate feedback according to the user's actions. The input is the sent interaction data, and the output is the generated feedback data.

[0204] Step 8:

[0205] The server generates feedback and sends it to the user's device, providing it to the user in real time. The feedback includes immediate reactions to the product and additional information. The input is the generated feedback data, and the output is the data sent to the user's device.

[0206] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0207] This system provides a virtual experience for elderly people and people with disabilities, allowing them to feel like they are traveling with their families. This system acquires user profile information and processes a series of processes that receive, analyze, generate, and provide local environmental data in real time. It also includes an emotion engine that recognizes user emotions and adjusts content and provides feedback based on those emotions.

[0208] Natural language explanation of the program's processing

[0209] 1. Obtaining user profile information

[0210] The server queries the database based on the user's ID and obtains the user's profile information (health status, sensitivity, favorite tourist spots, etc.).

[0211] The server uses the acquired information to design a virtual experience that suits the user's condition and preferences.

[0212] 2. Acquisition and transmission of local environmental data

[0213] The device obtains local GPS location information.

[0214] The device collects environmental data from the local surroundings (visual data from the camera, audio data from the microphone, and tactile data from the tactile sensor).

[0215] 3. Sending environmental data

[0216] The device compresses the collected environmental data in real time and sends it to the server.

[0217] 4. Analysis of received data

[0218] The server analyzes the received environmental data.

[0219] The server analyzes the visual data using image processing algorithms and converts it into virtual content.

[0220] The server analyzes the voice data using a voice recognition algorithm and performs voice filtering if necessary.

[0221] The server analyzes the tactile data and converts it into signals for the haptic device.

[0222] 5. Creation of virtual experience content

[0223] The server generates optimal virtual experience content based on the user's profile information.

[0224] The server applies data filters based on health status and sensitivity, and creates content tailored to the user's condition.

[0225] 6. Operation of the Emotion Engine

[0226] The server uses an emotion engine to recognize emotions from the user's facial expressions and voice analysis.

[0227] The server uses an emotion engine to adjust the content of the virtual experience based on the user's emotions.

[0228] 7. Submission of Content

[0229] The server compresses the generated virtual experience content in real time and transmits it to the user's terminal.

[0230] 8. User begins virtual experience

[0231] Users experience the virtual experience content provided through the device using a VR headset or haptic device.

[0232] Users can experience the experience as if they were actually there through sight, touch, sound, etc.

[0233] 9. Collection and transmission of user interaction data

[0234] When the user talks or moves during the virtual experience, the device detects this.

[0235] The device collects voice data using a microphone and acquires movement data using a motion sensor.

[0236] The emotion engine extracts the user's emotions from these data.

[0237] 10. Transmission of Interaction and Emotion Data

[0238] The device transmits the collected interaction data and emotion data to a server in real time.

[0239] 11. Analysis of interaction and emotion data and feedback generation

[0240] The server analyzes the received interaction data and emotion data.

[0241] The server generates feedback in real time based on the user's emotions and transmits it to the user's terminal.

[0242] Feedback includes conversational responses and behavioral reactions, with appropriate emotional adjustments.

[0243] Specific examples

[0244] For example, consider the case where an elderly person, Mr. A, uses the system at home while his family is on a trip to a seaside resort. The family uses smartphones or dedicated devices at the destination to collect real-time environmental data, such as the sound of the ocean, the scenery, and the feel of the sand. This data is sent to a server, which then generates the most suitable virtual experience content for Mr. A based on his profile information.

[0245] By wearing a dedicated VR headset and haptic devices, Mr. A can feel as if he is at a seaside resort in his own home. He can converse with his family and interact with them in real time, giving him the experience of actually traveling. Furthermore, the emotion engine recognizes Mr. A's emotions and adjusts the content and feedback in real time, giving him a deeper sense of satisfaction.

[0246] The processing flow will be explained below.

[0247] Step 1: Obtaining the user's profile information

[0248] The server queries the database based on the user's ID and obtains the user's profile information (health status, sensitivity, favorite tourist spots, etc.).

[0249] Step 2: Obtaining local environmental data

[0250] The device obtains local GPS location information.

[0251] The device collects environmental data from the local surroundings (visual data from the camera, audio data from the microphone, and tactile data from the tactile sensor).

[0252] Step 3: Sending environment data

[0253] The device compresses the collected environmental data in real time and sends it to the server.

[0254] Step 4: Parse the received data

[0255] The server analyzes the received environmental data.

[0256] The server analyzes the visual data using image processing algorithms and converts it into virtual content.

[0257] The server analyzes the voice data using a voice recognition algorithm and performs voice filtering if necessary.

[0258] The server analyzes the tactile data and converts it into signals for the haptic device.

[0259] Step 5: Generate virtual experience content

[0260] The server generates optimal virtual experience content based on the user's profile information.

[0261] The server applies data filters based on health status and sensitivity, and creates content tailored to the user's condition.

[0262] Step 6: Emotion Engine in Action

[0263] The server uses an emotion engine to recognize emotions from the user's facial expressions and voice analysis.

[0264] The server uses an emotion engine to adjust the content of the virtual experience based on the user's emotions.

[0265] Step 7: Submit your content

[0266] The server compresses the generated virtual experience content in real time and transmits it to the user's terminal.

[0267] Step 8: Start the user's virtual experience

[0268] Users experience the virtual experience content provided through the device using a VR headset or haptic device.

[0269] Users can experience the experience as if they were actually there through sight, touch, sound, etc.

[0270] Step 9: Collecting and sending user interaction data

[0271] When the user talks or moves during the virtual experience, the device detects this.

[0272] The device collects voice data using a microphone and acquires movement data using a motion sensor.

[0273] The emotion engine extracts the user's emotions from these data.

[0274] Step 10: Sending interaction and emotion data

[0275] The device transmits the collected interaction data and emotion data to a server in real time.

[0276] Step 11: Analyze interaction and emotion data and generate feedback

[0277] The server analyzes the received interaction data and emotion data.

[0278] The server analyzes the user's voice data and generates an appropriate response.

[0279] The server analyzes the motion data and generates the necessary virtual interactions.

[0280] The server analyzes the emotion data and generates feedback based on the user's emotion.

[0281] Step 12: Provide real-time feedback

[0282] The user receives real-time feedback from the server during the virtual experience.

[0283] The user experiences reactions to conversational responses and actions, and appropriate adjustments are made to match their emotions.

[0284] Example 2

[0285] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0286] The purpose of this invention is to provide optimal content in real time that is tailored to the health and emotions of each individual user, especially when elderly people and people with physical disabilities experience local travel through virtual reality. Conventional systems have had problems such as difficulty in generating virtual experience content that takes into account the individual emotions and health of the user, and a lack of emotional feedback.

[0287] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0288] a means for obtaining user profile information;

[0289] means for acquiring and transmitting local environmental data (visual, audio, tactile);

[0290] A means for analyzing the received environmental data and generating optimal virtual experience content;

[0291] means for transmitting the generated content to a user's device;

[0292] means for recognizing a user's emotion and adjusting the virtual experience content accordingly;

[0293] This enables an optimal virtual local travel experience that takes into account the user's health condition and emotions in real time.

[0294] "User profile information" is information that indicates the user's individual attributes and preferences, such as their health condition, sensitivity, and favorite tourist spots.

[0295] "Local environment data" refers to local visual data, audio data, and tactile data, which is real-time environmental information for the user to experience.

[0296] "Visual data" refers to on-site video information captured by a camera.

[0297] "Audio data" refers to local acoustic information collected by microphones.

[0298] "Tactile data" refers to local texture and vibration information obtained by tactile sensors.

[0299] "Interaction Data" refers to data about the conversations and actions a user makes during a virtual experience.

[0300] "Emotion" is information that represents the mental state of the user, which is recognized by analyzing the user's facial expressions, voice, and the like.

[0301] "Feedback" refers to responses and adjustments generated in real time based on user interaction data and emotions.

[0302] "Virtual experience content" refers to virtual reality content that combines visual, audio, and tactile information generated for a user to experience.

[0303] An "emotion engine" is an algorithm and software that analyzes a user's facial expressions and voice to recognize emotions and adjust the experience.

[0304] "Health condition" is information indicating the physical health condition of the user, and may include symptoms such as high blood pressure and diabetes.

[0305] "Data filter" refers to the algorithms and processes used to adjust collected environmental data according to the user's condition and sensitivity.

[0306] "Virtual experience" refers to a virtual reality experience that a user experiences using a VR headset or haptic device.

[0307] This system provides a virtual experience for elderly people and people with disabilities, allowing them to feel like they are traveling with their families. This system acquires user profile information and performs a series of processes to receive, analyze, generate, and provide local environmental data in real time. It also includes an emotion engine that recognizes user emotions and adjusts content and provides feedback based on those emotions.

[0308] The system consists of a database that records user profile information, a terminal for acquiring local environmental data, a server that analyzes the data and generates virtual experience content, a communication means for sending the generated content to the user's device, and devices such as a VR headset and haptic device that allow the user to experience the experience.

[0309] Program processing explanation

[0310] The program processing of this system will be specifically explained below.

[0311] First, the server queries the database based on the user's ID to obtain the user's profile information (e.g., health status, sensitivity, favorite tourist spots, etc.) The database that can be used may be, for example, an SQL-based database or a NoSQL type.

[0312] The device then uses a smartphone or dedicated device on-site to acquire GPS location information, and uses a camera on-site to collect visual data, a microphone to collect audio data, and a tactile sensor to record tactile data.

[0313] These environmental data are compressed in real time on the device and sent to the server using commonly used compression algorithms (e.g., Gzip, LZ4, etc.).

[0314] The server analyzes the received environmental data. Visual data is analyzed using image processing libraries such as OpenCV and converted into virtual content. Audio data is analyzed using speech recognition algorithms such as the Google Speech-to-Text API, and noise reduction and filtering are performed as needed. Haptic data is converted into signals for haptic feedback devices.

[0315] The server generates optimal virtual experience content based on the user's profile information, applying data filters based on health conditions and sensitivities (e.g., adjusting the tempo of the music to provide a gentler experience for a user with high blood pressure).

[0316] The server's emotion engine then recognizes the user's emotions from facial and voice analysis. This emotion engine uses machine learning models trained with TensorFlow or PyTorch, for example. The server then adjusts the content of the virtual experience in real time based on the user's emotions. This could include adding relaxing elements if the user is excited.

[0317] The generated virtual experience content is compressed and sent from the server to the user's device, where the user can use a VR headset or haptic device to experience the experience through sight, touch, sound, and more, as if they were actually there.

[0318] The conversations and actions that users make during the virtual experience are detected by the device, with voice data collected by a microphone and movement data captured by a motion sensor. This interaction data is sent to the server in real time, where the server's emotion engine analyzes the data and extracts the user's emotions.

[0319] The server analyzes the received interaction data and emotion data and generates feedback based on the user's emotion, which is sent to the user's device and displayed, for example, as a voice response or appropriate adjustment to behavior.

[0320] Specific examples

[0321] For example, consider the case where an elderly person, Mr. A, uses the system at home while his family is on a trip to a seaside resort. The family uses smartphones or dedicated devices at the destination to collect environmental data in real time, such as the sound of the ocean, the scenery, and the feel of the sand, and sends this data to the server. The server then generates virtual experience content that is optimal for Mr. A based on his profile information.

[0322] By wearing a dedicated VR headset and haptic device, A can feel as if he is at a seaside resort from the comfort of his own home. He can hear the sound of the ocean waves, enjoy the scenery with his eyes, and feel the texture of the sand with his hands. Furthermore, the emotion engine recognizes A's emotions and adjusts the content and feedback in real time, giving him a deeper sense of satisfaction.

[0323] Prompt Sentence Examples

[0324] Here are some examples of prompts for generative AI models:

[0325] Describe a scenario in detail where an elderly user would use a virtual experience system at home. Explain how the system connects with tourist attractions the family member is actually visiting and provides the user with the most appropriate virtual experience based on their profile information. This process includes real-time feedback from an emotion engine.

[0326] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0327] Step 1:

[0328] Obtaining user profile information

[0329] Server: Queries the database based on the user's ID and obtains the user's profile information (health status, sensitivity, favorite tourist spots, etc.).

[0330] Input: User ID.

[0331] Data processing: Profile information was obtained through database queries.

[0332] Output: User profile information (e.g., A's health condition, high blood pressure, favorite tourist destination is Kyoto).

[0333] Step 2:

[0334] Acquisition of local environmental data

[0335] Device: Use a smartphone or dedicated device on-site to obtain GPS location information.

[0336] Input: GPS signal.

[0337] Data processing: Obtain GPS location information.

[0338] Output: GPS location (e.g. Gion, Kyoto).

[0339] Step 3:

[0340] Environmental data collection

[0341] Device: The camera captures the scenery, the microphone collects surrounding sounds, and the tactile sensor records the feel of the sand on the beach.

[0342] Input: Local environment.

[0343] Data processing: visual data (camera footage), audio data (microphone recording), tactile data (sensor recording).

[0344] Output: Local environment data (e.g., Gion landscape images, audio, tactile data).

[0345] Step 4:

[0346] Sending environmental data

[0347] Terminal: Compresses collected environmental data in real time and sends it to the server.

[0348] Input: Local environmental data (visual, audio, tactile).

[0349] Data processing: Compressing data using a compression algorithm (e.g. Gzip).

[0350] Output: Compressed environment data.

[0351] Step 5:

[0352] Analyzing received data

[0353] Server: Analyzes the received environmental data.

[0354] Input: Compressed environment data.

[0355] Data processing: Decompressing compressed data, analyzing visual data with an image processing library (e.g., OpenCV), analyzing audio data with a speech recognition algorithm (e.g., Google Speech-to-Text), and converting haptic data for use with the feedback device.

[0356] Output: Parsed environmental data.

[0357] Step 6:

[0358] Creation of virtual experience content

[0359] Server: Generates optimal virtual experience content based on the user's profile information.

[0360] Input: Parsed environmental data, user profile information.

[0361] Data processing: Applying data filters tailored to profile information (e.g., providing a gentler experience for users with high blood pressure).

[0362] Output: Virtual experience content.

[0363] Step 7:

[0364] Emotion Engine Operation

[0365] Server: Recognizes emotions from the user's facial expressions and voice analysis using an emotion engine.

[0366] Input: User's facial expression data, voice data.

[0367] Data processing: Analyze sentiment using machine learning models (e.g., TensorFlow, PyTorch).

[0368] Output: Recognized emotion data.

[0369] Step 8:

[0370] Emotion-based content adjustment

[0371] Server: Adjusts the virtual experience content in real time based on the user's emotions.

[0372] Input: Recognized emotion data, virtual experience content.

[0373] Data manipulation: Adjusting content (e.g., if the user is excited, adding elements that have a calming effect).

[0374] Output: Tailored virtual experience content.

[0375] Step 9:

[0376] Submitting content

[0377] Server: Compresses the tailored virtual experience content in real time and sends it to the user's device.

[0378] Input: Tailored virtual experience content.

[0379] Data processing: Data compression using compression algorithms.

[0380] Output: Compressed virtual experience content.

[0381] Step 10:

[0382] User virtual experience begins

[0383] User: Puts on the VR headset and haptic device and starts the virtual tour.

[0384] Input: Compressed virtual experience content.

[0385] Data processing: decompression and playback.

[0386] Output: Visual, tactile and audio virtual experience.

[0387] Step 11:

[0388] Collecting user interaction data

[0389] Device: Senses what the user says and does during the experience.

[0390] Input: User gestures, voice.

[0391] Data processing: Voice data is collected by a microphone, and movement data is acquired by a motion sensor.

[0392] Output: Interaction data.

[0393] Step 12:

[0394] Transmission of interaction data and emotion data

[0395] Terminal: Collected interaction data and emotion data are sent to the server in real time.

[0396] Input: interaction data, emotion data.

[0397] Data processing: data compression and transmission.

[0398] Output: Interaction and emotion data sent to the server.

[0399] Step 13:

[0400] Analysis of interaction data and emotion data and feedback generation

[0401] Server: Analyzes the received interaction data and emotion data.

[0402] Input: Submitted interaction and sentiment data.

[0403] Data processing: Real-time feedback generation based on user behavior.

[0404] Output: Feedback data sent to the user device.

[0405] (Application example 2)

[0406] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0407] While conventional virtual experience systems offer the elderly and physically challenged people the surprise and fun of traveling and shopping without leaving their homes, they have limitations in providing detailed in-store guidance and promotional information. Furthermore, they are unable to adjust content in real time based on the user's emotional state, making it difficult to improve user satisfaction and the quality of the experience.

[0408] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for acquiring user profile information, means for using sensors to collect user position information and environmental data within the physical store, and means including an emotion engine for analyzing user emotion data. This makes it possible to provide an optimal virtual guidance experience in real time based on the user's position information and emotion data, thereby improving user satisfaction.

[0409] "User profile information" is detailed personal information about the user, such as the user's health condition, sensitivities, and favorite tourist spots.

[0410] "Local environment data" refers to surrounding information such as visual data, audio data, and tactile data that exists in the actual location.

[0411] "Means for analyzing received environmental data" refers to a device or program capable of analyzing environmental data transmitted from the site and converting it into virtual experience content.

[0412] "Generated content" refers to the content of a virtual experience created for a user.

[0413] "User Device" refers to the equipment (e.g., smartphone, smart glasses, head-mounted display) used by a user to engage in a virtual experience.

[0414] "Means for providing a virtual experience" refers to technologies and devices that provide virtual experience content to users in the form of sight, touch, sound, etc.

[0415] "Interaction data" refers to information such as the actions and conversations a user makes during a virtual experience.

[0416] A "sensor" is a device for acquiring environmental data. This includes cameras, microphones, tactile sensors, etc.

[0417] An "emotion engine" is a program that recognizes and analyzes emotions from a user's facial expressions and voice.

[0418] "Promotion information" refers to information about sales and special offers taking place in stores.

[0419] "Emotion data" is data that indicates the user's emotional state analyzed by the emotion engine.

[0420] This invention is a system that allows elderly people and people with physical disabilities to virtually experience the sensation of visiting a store. The system acquires user profile information and local environmental data, analyzes the user's emotional state using an emotion engine, and customizes the virtual experience content in real time based on the analysis.

[0421] Specific processing of the program

[0422] 1. Obtaining user profile information

[0423] The server queries the database based on the user's ID and obtains the user's profile information (health status, sensitivity, favorite product categories, etc.) and uses this information to design an optimal virtual experience.

[0424] 2. Acquiring environmental data within physical stores

[0425] The device (smart glasses) collects environmental data (location information, product information, promotion information) from sensors installed in the store, including cameras, microphones, and tactile sensors.

[0426] 3. Emotion analysis using an emotion engine

[0427] The server uses the camera and microphone built into the smart glasses to analyze the user's facial expressions and voice data, which allows the emotion engine to recognize the user's emotions and capture the data in real time.

[0428] 4. Creation and transmission of virtual experience content

[0429] The server generates virtual experience content based on the acquired environmental data, the user's profile information, and emotional data, and the generated content is compressed and sent to the user's smart glasses.

[0430] 5. User Virtual Experience

[0431] While wearing the smart glasses, users can explore the physical store through virtual experience content, which includes not only sight and sound but also touch, giving them the feeling of actually visiting the store.

[0432] Hardware and software used

[0433] Hardware used

[0434] Smart glasses (general smart devices)

[0435] In-store sensors (beacons that acquire location information, cameras and microphones that collect environmental data)

[0436] Software used

[0437] Emotion engine (e.g. Emotion API)

[0438] Speech recognition algorithms (e.g., Google Cloud Speech-to-Text)

[0439] Image processing algorithms (e.g., OpenCV)

[0440] Specific Examples

[0441] For example, consider the case where an elderly person named B uses a virtual experience system without visiting a physical store. B puts on smart glasses at home and launches the corresponding application. The smart glasses receive and analyze location information, product information, and promotion information collected by sensors in the store in real time. Furthermore, emotional data from B's facial expressions and voice is analyzed, and content is customized based on the products and promotions that B is interested in.

[0442] Prompt Sentence Examples

[0443] User Profile Information:

[0444] ID: user1234

[0445] Likes: Food

[0446] Health status: No problems

[0447] Sensitivity: High

[0448] Environmental data:

[0449] Store name: Supermarket

[0450] Location: Food section

[0451] Products: Apples, bananas, oranges

[0452] Promotion: Buy one apple, get one free

[0453] Emotional Data:

[0454] Expression: Smiling

[0455] Audio: Sounds fun

[0456] By inputting such prompt sentences into a generative AI model, it is possible to generate and provide content for a virtual guidance experience that is optimal for the user.

[0457] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0458] Step 1:

[0459] The server queries the database based on the user's ID and obtains the user's profile information (health status, sensitivity, favorite product categories, etc.) and uses this information to design a virtual experience that is optimal for the user.

[0460] Input: User ID

[0461] Output: User profile information

[0462] Specific Operation: The server communicates with a database server to query for profile information associated with the user ID and stores the resulting information in an internal data store.

[0463] Step 2:

[0464] The device (smart glasses) collects environmental data (location information, product information, promotion information) from sensors installed in the store, including cameras, microphones, and tactile sensors.

[0465] Input: Local environmental data (sensor data)

[0466] Output: Collected environmental data

[0467] Specific operation: The terminal accesses the sensor network, collects data obtained from each sensor, processes it, and prepares it to be sent to the server.

[0468] Step 3:

[0469] The server receives and analyzes the environmental data sent from the device, using image processing algorithms (OpenCV) and speech recognition algorithms (Google Cloud Speech-to-Text) to analyze the data and generate virtual experience content.

[0470] Input: Collected environmental data

[0471] Output: Analysis results, virtual experience content

[0472] Specific operation: The server runs image processing algorithms and voice recognition algorithms to analyze the environmental data, and then generates virtual experience content based on it, customizing it taking into account the user's profile information.

[0473] Step 4:

[0474] The smart glasses use a built-in camera and microphone to collect facial and voice data, which is then used by the emotion engine to recognize the user's emotions.

[0475] Input: User's facial expression data, voice data

[0476] Output: Emotion data

[0477] Specific operation: The device captures the user's facial expressions and voice in real time using a camera and microphone, and sends the data to the server. The server then uses an emotion engine to analyze the data and recognize the user's emotions.

[0478] Step 5:

[0479] The server generates optimal virtual experience content based on the user's profile information, environmental data, and emotional data, compresses it, and sends it to the user's smart glasses.

[0480] Input: Profile information, environmental data, emotional data

[0481] Output: Virtual experience content

[0482] How it works: The server aggregates all data and generates optimized virtual experience content, which is then compressed and instantly sent to the device.

[0483] Step 6:

[0484] By wearing smart glasses, users can explore the store through virtual experience content, and experience the store in a realistic way through sight, sound, and touch. Interaction data collected during the experience is also sent to the server.

[0485] Input: Virtual experience content

[0486] Output: User interaction data

[0487] Specific Actions: Users use smart glasses to initiate a real-time virtual experience, and interaction data such as movements and sounds while exploring are collected and sent to the server.

[0488] Step 7:

[0489] The server analyzes the received interaction data and generates real-time feedback, which is tailored appropriately based on the user's emotions.

[0490] Input: Interaction data

[0491] Output: Feedback

[0492] Specific operation: The server analyzes the interaction data and generates feedback appropriate to the user's behavior and emotions. This feedback is sent back to the device in real time and presented to the user in an appropriate format.

[0493] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0494] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0495] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0496] [Second embodiment]

[0497] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0498] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0499] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0500] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0501] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0502] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0503] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0504] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0505] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0506] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0507] In the smart glasses 214, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0508] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0509] This is a system that provides a virtual experience for elderly people and people with disabilities, allowing them to feel like they are traveling with their family. This system acquires user profile information and achieves real-time interaction through a series of processes that receive, analyze, generate, and provide local environmental data in real time.

[0510] Natural language explanation of the program's processing

[0511] 1. Obtaining user profile information

[0512] The server retrieves the user's profile information (health status, sensitivity, favorite tourist spots, etc.) from the database.

[0513] The server uses the acquired information to design a virtual experience that suits the user's condition and preferences.

[0514] 2. Acquisition and transmission of local environmental data

[0515] The device collects local environmental data (visual, audio, tactile, etc.).

[0516] The terminal transmits this environmental data to the server in real time.

[0517] The device also obtains location information using GPS and other means and sends this information to the server.

[0518] 3. Analysis of environmental data and generation of virtual experience content

[0519] The server analyzes the received environmental data.

[0520] The server generates virtual experience content tailored to the user's profile information based on the analysis results.

[0521] The server transmits the generated content to the user's terminal.

[0522] 4. Providing virtual experiences

[0523] The user experiences the provided virtual experience content using a dedicated device (such as a VR headset or haptic device).

[0524] Users can experience the experience as if they were actually there through sight, touch, sound, etc.

[0525] 5. Collection and transmission of user interaction data

[0526] The device detects the conversations and actions the user makes during the virtual experience.

[0527] The terminal collects sensed interaction data and transmits it to a server.

[0528] 6. Real-time feedback generation

[0529] The server analyzes the user interaction data.

[0530] The server generates real-time feedback based on the analysis results and sends it to the user's device.

[0531] Feedback includes conversational responses and reactions to actions.

[0532] Specific examples

[0533] For example, consider the case where an elderly person, Mr. A, uses the system at home while his family is on a trip to a seaside resort. The family uses smartphones or dedicated devices at the destination to collect real-time environmental data, such as the sound of the ocean, the scenery, and the feel of the sand. This data is sent to a server, which then generates the most suitable virtual experience content for Mr. A based on his profile information.

[0534] By wearing a dedicated VR headset and haptic device, Mr. A can feel as if he is at a seaside resort in his own home. He can talk to his family and interact with them in real time, giving him the experience of actually traveling.

[0535] The processing flow will be explained below.

[0536] Step 1: Obtaining the user's profile information

[0537] The server queries the database based on the user's ID and obtains the user's profile information (health status, sensitivity, favorite tourist spots, etc.).

[0538] Step 2: Obtaining local environmental data

[0539] The device obtains local GPS location information.

[0540] The device collects environmental data from the local surroundings (visual data from the camera, audio data from the microphone, and tactile data from the tactile sensor).

[0541] Step 3: Sending environment data

[0542] The device compresses the collected environmental data in real time and sends it to the server.

[0543] Step 4: Parse the received data

[0544] The server analyzes the received environmental data.

[0545] The server analyzes the visual data using image processing algorithms and converts it into virtual content.

[0546] The server analyzes the voice data using a voice recognition algorithm and performs voice filtering if necessary.

[0547] The server analyzes the tactile data and converts it into signals for the haptic device.

[0548] Step 5: Generate virtual experience content

[0549] The server generates optimal virtual experience content based on the user's profile information.

[0550] The server applies data filters based on health status and sensitivity, and creates content tailored to the user's condition.

[0551] Step 6: Submit your content

[0552] The server compresses the generated virtual experience content in real time and transmits it to the user's terminal.

[0553] Step 7: Start the user's virtual experience

[0554] Users experience the virtual experience content provided through the device using a VR headset or haptic device.

[0555] The user sees visual information through a VR headset, hears audio information through headphones, and experiences tactile information through a haptic device.

[0556] Step 8: Collect interaction data

[0557] When the user talks or moves during the virtual experience, the device detects this.

[0558] The device collects voice data using a microphone and acquires movement data using a motion sensor.

[0559] Step 9: Sending interaction data

[0560] The terminal transmits the collected interaction data to the server in real time.

[0561] Step 10: Analyze interaction data and generate feedback

[0562] The server analyzes the received interaction data.

[0563] The server analyzes the user's voice data and generates an appropriate response.

[0564] The server analyzes the motion data and generates the necessary virtual interactions.

[0565] The server transmits the generated feedback to the user's terminal in real time.

[0566] Step 11: Provide real-time feedback

[0567] The user receives real-time feedback from the server during the virtual experience.

[0568] The user experiences conversational responses and reactions to actions.

[0569] Example 1

[0570] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0571] Until now, there has been no means available for elderly people and people with physical disabilities to have a real-time virtual experience that makes it seem as if they are traveling with family and friends, even when mobility is difficult. To provide a realistic experience, it is necessary to provide multiple sensory information, such as visual, tactile, and audio, in real time and provide instant feedback on the user's reactions to that information, but the specific system configuration and technical means to achieve this have not yet been established.

[0572] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0573] In this invention, the server includes means for acquiring user profile information, means for collecting local environmental data and transmitting it to the server, means for analyzing the received environmental data, means for generating virtual experience content based on the user profile information, means for transmitting the generated content to the user's device, means for providing the virtual experience on the user's device, means for collecting user interaction data during the virtual experience and transmitting it to the server, and means for analyzing the interaction data and generating feedback in real time, thereby enabling elderly people and people with disabilities to have an experience similar to a real trip in real time and interactively from a safe place such as their own home.

[0574] "Profile information" is information that indicates individual characteristics and conditions such as the user's name, age, health condition, sensitivity, favorite tourist spots, etc.

[0575] "Environmental data" refers to data that includes information about the surroundings, such as visual, audio, and tactile information of the local area.

[0576] "Virtual experience content" refers to content such as images, audio, and haptic feedback that are generated so that users can experience the same environment as they would in a real world.

[0577] "Interaction data" refers to data that indicates a user's reactions and behavior, such as the conversations and actions the user engages in during a virtual experience.

[0578] "Feedback" is data that indicates responses or reactions that are generated based on user interaction data and provided to the user in real time.

[0579] "Device" refers to the equipment used by a user to receive a virtual experience (e.g., VR headset, haptic device, etc.).

[0580] A "server" is a central computer system that receives, analyzes, and processes data sent by users, and generates and sends virtual experience content and feedback to users.

[0581] "Collection" refers to obtaining visual, audio, tactile, and other data on-site.

[0582] "Transmit" means transferring collected data to another device or computer system.

[0583] "Analysis" refers to evaluating collected data and extracting necessary information.

[0584] "Generation" means creating new content or information based on the analysis results.

[0585] This invention is a system that provides a virtual experience for elderly people and people with disabilities, allowing them to feel like they are traveling with their family. This system acquires user profile information and achieves real-time interaction through a series of processes that receive, analyze, generate, and provide local environmental data in real time.

[0586] 1. Profile information acquisition

[0587] The server retrieves the user's profile information from the database, such as the user's name, age, health status, sensitivity, favorite tourist spots, etc. This allows the server to personalize the virtual experience to suit the user's preferences and characteristics.

[0588] 2. Acquisition and transmission of local environmental data

[0589] The device (e.g., a smartphone or dedicated device) collects visual, audio, and tactile data using local environmental data (e.g., a 360-degree camera, field recorder, tactile sensor, etc.). The device transmits the collected data to a server in real time. In addition, the device obtains its location information using GPS and transmits it to the server.

[0590] 3. Analysis of environmental data and generation of virtual experience content

[0591] The server analyzes the received environmental data using data analysis software such as Python libraries (e.g., OpenCV, Librosa) and TensorFlow. Based on the analysis results, the server generates virtual experience content optimized for the user's profile information. This content is then converted into a format compatible with the user's device (e.g., VR headset, haptic device).

[0592] 4. Providing virtual experiences

[0593] Users wear a dedicated device (e.g., Oculus Quest 2, Teslasuit) to enjoy a virtual experience. Users can experience the experience as if they were actually there through sight, touch, and sound, and can converse and interact with family and friends in the location.

[0594] 5. Collection and transmission of interaction data

[0595] The conversations and actions that users make during the virtual experience are detected by the device (e.g., the built-in microphone and motion sensor of the Oculus Quest 2, or the sensor of the Teslasuit). This interaction data is sent to the server in real time.

[0596] 6. Real-time feedback generation

[0597] The server analyzes the received interaction data using natural language processing models and motion analysis algorithms (e.g., OpenAI's GPT model, PoseNet, etc.). The server generates real-time feedback based on the analysis results and sends it to the user's device. The feedback includes conversational responses and haptic feedback.

[0598] Specific examples

[0599] For example, consider the case where elderly person A uses this system at home while their family travels to a seaside resort. While at the resort, the family uses smartphones or dedicated devices (e.g., 360-degree cameras, ambient sound microphones, tactile sensors, etc.) to collect real-time environmental data, such as the sound of the ocean, the scenery, and the feel of the sand. This data is sent to a server, which then generates virtual experience content that is optimal for A based on his or her profile information.

[0600] By wearing a dedicated VR headset and haptic device, Mr. A can feel as if he is at a seaside resort in his own home. He can talk to his family and interact with them in real time, giving him the experience of actually traveling.

[0601] Prompt Sentence Examples

[0602] Below are some example prompts to give to a generative AI model (e.g., GPT-3):

[0603] Please explain a system that provides a virtual experience that allows elderly people and people with disabilities to feel like they are traveling with their families. This system acquires user profile information and performs a series of processes to receive, analyze, generate, and provide local environmental data in real time. Please explain in detail what specific hardware and software are used, how the data is processed, and how the virtual experience is provided.

[0604] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0605] Step 1:

[0606] The server retrieves the user's profile information from the database.

[0607] Specifically, the server issues SQL queries to the database to retrieve information such as the user's name, age, health status, sensitivity, and favorite tourist spots. This retrieved profile information becomes the input data for the next processing step. The output is the user's detailed information.

[0608] Step 2:

[0609] The device collects local environmental data and transmits it to a server in real time.

[0610] The terminal collects visual, audio, and tactile data using devices such as a 360-degree camera, field recorder, and tactile sensor. It also acquires location information using GPS. The input is local environmental data and location information. The acquired data is uploaded to a server via a communication line. The output is the environmental data and location information sent to the server.

[0611] Step 3:

[0612] The server analyzes the received environmental data.

[0613] Visual, audio, and haptic data is analyzed using Python libraries (e.g., OpenCV, Librosa) and TensorFlow. The results of this analysis are the basis for generating the user's virtual experience content. The input is the local environment data received by the server. The output is the analyzed environment data.

[0614] Step 4:

[0615] The server generates virtual experience content based on the analysis results.

[0616] The server creates personalized virtual experience content based on the user's profile information and analyzed environmental data. A generative AI model (e.g., TensorFlow, GANs, etc.) is used for generation. The input is the user's profile information and analyzed environmental data. The output is the virtual experience content.

[0617] Step 5:

[0618] The server transmits the generated virtual experience content to the user's device.

[0619] The generated content is converted into a format compatible with the user's VR headset or haptic device and sent to the user's device via a communication line. The input is the generated virtual experience content. The output is the content sent to the user's device.

[0620] Step 6:

[0621] Users get a virtual experience using a dedicated device.

[0622] A user wears a VR headset (e.g., Oculus Quest 2) and a haptic device (e.g., Teslasuit) to play virtual experience content. The input is the received virtual experience content. The output is feedback of the user's virtual experience.

[0623] Step 7:

[0624] The device collects local interaction data and sends it to a server.

[0625] The conversations and actions that users make during the virtual experience are collected through the built-in microphones, motion sensors, and sensors in the haptic device of the VR headset. The input is the user's interaction. The collected data is sent to the server in real time. The output is the interaction data sent to the server.

[0626] Step 8:

[0627] The server analyzes the interaction data and generates feedback in real time.

[0628] The server analyzes the interaction data using a natural language processing model (e.g., GPT model) or a motion analysis algorithm (e.g., PoseNet). The input is the transmitted interaction data. Based on the analysis results, the server generates feedback data to respond to the user in real time. The output is the generated feedback.

[0629] Step 9:

[0630] The server generates feedback and sends it to the user's device.

[0631] The feedback data is transmitted to the user's device via a communication line and provided to the user in real time. The input is the generated feedback data. The output is the real-time feedback provided to the user.

[0632] (Application example 1)

[0633] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0634] With conventional virtual experience systems, it was difficult for elderly people and people with physical disabilities to enjoy a rich shopping experience without actually going to the location. It was also difficult to provide a personalized experience that matched each user's preferences and health condition. This made it difficult to provide a satisfying virtual experience, especially for users with specific needs.

[0635] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0636] In this invention, the server includes means for acquiring user profile information, means for acquiring and transmitting local environmental data, means for analyzing the received environmental data to generate optimal virtual experience content, means for transmitting the generated content to the user's device, means for providing the virtual experience on the user's device, means for collecting and transmitting user interaction data during the virtual experience, means for analyzing the collected interaction data to generate feedback in real time, and means for customizing the shopping experience based on the user's past purchasing history, thereby enabling even elderly people and people with disabilities to enjoy a customized shopping experience in real time without having to go to the site.

[0637] The "means for acquiring user profile information" has a function for acquiring personal information such as the user's health condition, preferences, and past purchase history from a storage device such as a database.

[0638] The "means for acquiring and transmitting local environmental data" is a function that collects data necessary for the user to feel as if they are in the local area, such as local video, audio, and tactile information, and transmits this data to a server.

[0639] The "means for analyzing received environmental data and generating optimal virtual experience content" has the function of analyzing received local environmental data and generating optimized virtual experience content based on the user's profile information.

[0640] "Means for transmitting generated content to a user's device" means a function that transmits the generated virtual experience content to a user's device, such as a VR headset or smart glasses.

[0641] "Means for providing a virtual experience on a user's device" means a function that provides the generated virtual experience content to the user through the user's device, allowing the user to experience it through sight, touch, sound, etc.

[0642] "Means for collecting and transmitting user interaction data during a virtual experience" refers to a device that has the function of collecting interaction data such as the user's actions and conversations during the virtual experience and transmitting it to a server.

[0643] The "means for analyzing collected interaction data and generating feedback in real time" has the function of analyzing collected user interaction data and generating feedback on user actions in real time.

[0644] "Means for customizing a shopping experience based on a user's past purchasing history" refers to a function that customizes virtual experience content based on the user's past purchasing history information in order to provide the optimal shopping experience tailored to the user's preferences.

[0645] This invention provides a virtual experience system that allows elderly people and people with physical disabilities to enjoy a rich shopping experience from home. The system is configured to provide a personalized experience by utilizing the user's personal information, preferences, and past purchasing history.

[0646] 1. Obtaining user profile information

[0647] The server retrieves the user's profile information (health status, preferences, past purchase history, etc.) from the database, which is then used to optimize the virtual shopping experience for the individual user.

[0648] 2. Acquisition and transmission of local environmental data

[0649] Devices (e.g., smartphones or smart glasses) collect environmental data such as video, audio, and detailed product information in real time within a local store. This data is then sent from the local store to a server. The devices are equipped with cameras, microphones, sensors, etc., and have a communication module for transmitting this data in real time.

[0650] 3. Analysis of environmental data and generation of virtual experience content

[0651] The server analyzes the received environmental data and works with a generative AI model to generate optimal virtual shopping experience content based on the user's profile information. This analysis utilizes cloud services such as computer vision APIs (e.g., Amazon Rekognition) and natural language processing models (e.g., Google Cloud Speech-to-Text).

[0652] 4. Providing virtual experiences

[0653] The generated virtual experience content is sent to the user's device (e.g., VR headset or smart glasses). By wearing these devices, the user can experience walking through the virtual store and picking up products through sight, touch, and sound.

[0654] 5. Collection and transmission of user interaction data

[0655] Interaction data, such as conversations and actions that users make during the virtual experience, is sensed and collected by the device, and the collected data is sent to a server.

[0656] 6. Real-time feedback generation

[0657] The server analyzes the collected interaction data, generates feedback in real time, and sends it to the user's device, providing instant feedback on the user's actions and providing a simulated experience that makes the user feel as if they are actually in the store.

[0658] Specific examples

[0659] For example, an elderly user can use the system at home, while a local store staff member uses a terminal to transmit video and audio from the store in real time. The user can then enjoy a personalized shopping experience based on their profile information and past purchase history through a VR headset or smart glasses.

[0660] Examples of prompt statements

[0661] "Generate a virtual store experience tailored to the user's preferences. User information: {Name: 'Jiro Taguchi', Age: 75, Preferences: ['Clothing', 'Electronics']}, Current Store Labels: ['Laptop', 'Smartphone']"

[0662] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0663] Step 1:

[0664] The server retrieves the user's profile information from the database. The retrieved information includes the user's health condition, preferences, past purchase history, etc. The input is identification information such as the user ID, and the output is the user's detailed profile information. This information is retrieved using a database access API.

[0665] Step 2:

[0666] The terminal acquires local environmental data in real time and sends it to the server. The environmental data includes video, audio, and detailed product information from within the store. The terminal collects data using cameras and microphones and sends it through a communications module. The input is sensor data from the cameras and microphones, and the output is data sent to the server.

[0667] Step 3:

[0668] The server analyzes the received local environmental data and generates virtual experience content. The server processes the data using computer vision APIs (e.g., Amazon Rekognition) and natural language processing models (e.g., Google Cloud Speech-to-Text). The input is the received environmental data and user profile information, and the output is the generated virtual experience content.

[0669] Step 4:

[0670] The server generates virtual experience content and sends it to the user's device, which can be a VR headset or smart glasses. The input is the generated virtual experience content, and the output is the data sent to the user's device.

[0671] Step 5:

[0672] The user's device plays the virtual experience content and provides the user with the experience through sight, touch, and sound. The device can be a VR headset or smart glasses, with the input being the transmitted virtual experience content and the output being the user's virtual experience.

[0673] Step 6:

[0674] The device collects interaction data of the user during the virtual experience and sends it to the server. The interaction data includes the user's actions and conversations. The input is the data of the user's actions and speech, and the output is the data sent to the server.

[0675] Step 7:

[0676] The server analyzes the collected interaction data and generates feedback in real time. The server uses a generative AI model to analyze and generate feedback according to the user's actions. The input is the sent interaction data, and the output is the generated feedback data.

[0677] Step 8:

[0678] The server generates feedback and sends it to the user's device, providing it to the user in real time. The feedback includes immediate reactions to the product and additional information. The input is the generated feedback data, and the output is the data sent to the user's device.

[0679] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0680] This system provides a virtual experience for elderly people and people with disabilities, allowing them to feel like they are traveling with their families. This system acquires user profile information and processes a series of processes that receive, analyze, generate, and provide local environmental data in real time. It also includes an emotion engine that recognizes user emotions and adjusts content and provides feedback based on those emotions.

[0681] Natural language explanation of the program's processing

[0682] 1. Obtaining user profile information

[0683] The server queries the database based on the user's ID and obtains the user's profile information (health status, sensitivity, favorite tourist spots, etc.).

[0684] The server uses the acquired information to design a virtual experience that suits the user's condition and preferences.

[0685] 2. Acquisition and transmission of local environmental data

[0686] The device obtains local GPS location information.

[0687] The device collects environmental data from the local surroundings (visual data from the camera, audio data from the microphone, and tactile data from the tactile sensor).

[0688] 3. Sending environmental data

[0689] The device compresses the collected environmental data in real time and sends it to the server.

[0690] 4. Analysis of received data

[0691] The server analyzes the received environmental data.

[0692] The server analyzes the visual data using image processing algorithms and converts it into virtual content.

[0693] The server analyzes the voice data using a voice recognition algorithm and performs voice filtering if necessary.

[0694] The server analyzes the tactile data and converts it into signals for the haptic device.

[0695] 5. Creation of virtual experience content

[0696] The server generates optimal virtual experience content based on the user's profile information.

[0697] The server applies data filters based on health status and sensitivity, and creates content tailored to the user's condition.

[0698] 6. Operation of the Emotion Engine

[0699] The server uses an emotion engine to recognize emotions from the user's facial expressions and voice analysis.

[0700] The server uses an emotion engine to adjust the content of the virtual experience based on the user's emotions.

[0701] 7. Submission of Content

[0702] The server compresses the generated virtual experience content in real time and transmits it to the user's terminal.

[0703] 8. User begins virtual experience

[0704] Users experience the virtual experience content provided through the device using a VR headset or haptic device.

[0705] Users can experience the experience as if they were actually there through sight, touch, sound, etc.

[0706] 9. Collection and transmission of user interaction data

[0707] When the user talks or moves during the virtual experience, the device detects this.

[0708] The device collects voice data using a microphone and acquires movement data using a motion sensor.

[0709] The emotion engine extracts the user's emotions from these data.

[0710] 10. Transmission of Interaction and Emotion Data

[0711] The device transmits the collected interaction data and emotion data to a server in real time.

[0712] 11. Analysis of interaction and emotion data and feedback generation

[0713] The server analyzes the received interaction data and emotion data.

[0714] The server generates feedback in real time based on the user's emotions and transmits it to the user's terminal.

[0715] Feedback includes conversational responses and behavioral reactions, with appropriate emotional adjustments.

[0716] Specific examples

[0717] For example, consider the case where an elderly person, Mr. A, uses the system at home while his family is on a trip to a seaside resort. The family uses smartphones or dedicated devices at the destination to collect real-time environmental data, such as the sound of the ocean, the scenery, and the feel of the sand. This data is sent to a server, which then generates the most suitable virtual experience content for Mr. A based on his profile information.

[0718] By wearing a dedicated VR headset and haptic devices, Mr. A can feel as if he is at a seaside resort in his own home. He can converse with his family and interact with them in real time, giving him the experience of actually traveling. Furthermore, the emotion engine recognizes Mr. A's emotions and adjusts the content and feedback in real time, giving him a deeper sense of satisfaction.

[0719] The processing flow will be explained below.

[0720] Step 1: Obtaining the user's profile information

[0721] The server queries the database based on the user's ID and obtains the user's profile information (health status, sensitivity, favorite tourist spots, etc.).

[0722] Step 2: Obtaining local environmental data

[0723] The device obtains local GPS location information.

[0724] The device collects environmental data from the local surroundings (visual data from the camera, audio data from the microphone, and tactile data from the tactile sensor).

[0725] Step 3: Sending environment data

[0726] The device compresses the collected environmental data in real time and sends it to the server.

[0727] Step 4: Parse the received data

[0728] The server analyzes the received environmental data.

[0729] The server analyzes the visual data using image processing algorithms and converts it into virtual content.

[0730] The server analyzes the voice data using a voice recognition algorithm and performs voice filtering if necessary.

[0731] The server analyzes the tactile data and converts it into signals for the haptic device.

[0732] Step 5: Generate virtual experience content

[0733] The server generates optimal virtual experience content based on the user's profile information.

[0734] The server applies data filters based on health status and sensitivity, and creates content tailored to the user's condition.

[0735] Step 6: Emotion Engine in Action

[0736] The server uses an emotion engine to recognize emotions from the user's facial expressions and voice analysis.

[0737] The server uses an emotion engine to adjust the content of the virtual experience based on the user's emotions.

[0738] Step 7: Submit your content

[0739] The server compresses the generated virtual experience content in real time and transmits it to the user's terminal.

[0740] Step 8: Start the user's virtual experience

[0741] Users experience the virtual experience content provided through the device using a VR headset or haptic device.

[0742] Users can experience the experience as if they were actually there through sight, touch, sound, etc.

[0743] Step 9: Collecting and sending user interaction data

[0744] When the user talks or moves during the virtual experience, the device detects this.

[0745] The device collects voice data using a microphone and acquires movement data using a motion sensor.

[0746] The emotion engine extracts the user's emotions from these data.

[0747] Step 10: Sending interaction and emotion data

[0748] The device transmits the collected interaction data and emotion data to a server in real time.

[0749] Step 11: Analyze interaction and emotion data and generate feedback

[0750] The server analyzes the received interaction data and emotion data.

[0751] The server analyzes the user's voice data and generates an appropriate response.

[0752] The server analyzes the motion data and generates the necessary virtual interactions.

[0753] The server analyzes the emotion data and generates feedback based on the user's emotion.

[0754] Step 12: Provide real-time feedback

[0755] The user receives real-time feedback from the server during the virtual experience.

[0756] The user experiences reactions to conversational responses and actions, and appropriate adjustments are made to match their emotions.

[0757] Example 2

[0758] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0759] The purpose of this invention is to provide optimal content in real time that is tailored to the health and emotions of each individual user, especially when elderly people and people with physical disabilities experience local travel through virtual reality. Conventional systems have had problems such as difficulty in generating virtual experience content that takes into account the individual emotions and health of the user, and a lack of emotional feedback.

[0760] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0761] a means for obtaining user profile information;

[0762] means for acquiring and transmitting local environmental data (visual, audio, tactile);

[0763] A means for analyzing the received environmental data and generating optimal virtual experience content;

[0764] means for transmitting the generated content to a user's device;

[0765] means for recognizing a user's emotion and adjusting the virtual experience content accordingly;

[0766] This enables an optimal virtual local travel experience that takes into account the user's health condition and emotions in real time.

[0767] "User profile information" is information that indicates the user's individual attributes and preferences, such as their health condition, sensitivity, and favorite tourist spots.

[0768] "Local environment data" refers to local visual data, audio data, and tactile data, which is real-time environmental information for the user to experience.

[0769] "Visual data" refers to on-site video information captured by a camera.

[0770] "Audio data" refers to local acoustic information collected by microphones.

[0771] "Tactile data" refers to local texture and vibration information obtained by tactile sensors.

[0772] "Interaction Data" refers to data about the conversations and actions a user makes during a virtual experience.

[0773] "Emotion" is information that represents the mental state of the user, which is recognized by analyzing the user's facial expressions, voice, and the like.

[0774] "Feedback" refers to responses and adjustments generated in real time based on user interaction data and emotions.

[0775] "Virtual experience content" refers to virtual reality content that combines visual, audio, and tactile information generated for a user to experience.

[0776] An "emotion engine" is an algorithm and software that analyzes a user's facial expressions and voice to recognize emotions and adjust the experience.

[0777] "Health condition" is information indicating the physical health condition of the user, and may include symptoms such as high blood pressure and diabetes.

[0778] "Data filter" refers to the algorithms and processes used to adjust collected environmental data according to the user's condition and sensitivity.

[0779] "Virtual experience" refers to a virtual reality experience that a user experiences using a VR headset or haptic device.

[0780] This system provides a virtual experience for elderly people and people with disabilities, allowing them to feel like they are traveling with their families. This system acquires user profile information and performs a series of processes to receive, analyze, generate, and provide local environmental data in real time. It also includes an emotion engine that recognizes user emotions and adjusts content and provides feedback based on those emotions.

[0781] The system consists of a database that records user profile information, a terminal for acquiring local environmental data, a server that analyzes the data and generates virtual experience content, a communication means for sending the generated content to the user's device, and devices such as a VR headset and haptic device that allow the user to experience the experience.

[0782] Program processing explanation

[0783] The program processing of this system will be specifically explained below.

[0784] First, the server queries the database based on the user's ID to obtain the user's profile information (e.g., health status, sensitivity, favorite tourist spots, etc.) The database that can be used may be, for example, an SQL-based database or a NoSQL type.

[0785] The device then uses a smartphone or dedicated device on-site to acquire GPS location information, and uses a camera on-site to collect visual data, a microphone to collect audio data, and a tactile sensor to record tactile data.

[0786] These environmental data are compressed in real time on the device and sent to the server using commonly used compression algorithms (e.g., Gzip, LZ4, etc.).

[0787] The server analyzes the received environmental data. Visual data is analyzed using image processing libraries such as OpenCV and converted into virtual content. Audio data is analyzed using speech recognition algorithms such as the Google Speech-to-Text API, and noise reduction and filtering are performed as needed. Haptic data is converted into signals for haptic feedback devices.

[0788] The server generates optimal virtual experience content based on the user's profile information, applying data filters based on health conditions and sensitivities (e.g., adjusting the tempo of the music to provide a gentler experience for a user with high blood pressure).

[0789] The server's emotion engine then recognizes the user's emotions from facial and voice analysis. This emotion engine uses machine learning models trained with TensorFlow or PyTorch, for example. The server then adjusts the content of the virtual experience in real time based on the user's emotions. This could include adding relaxing elements if the user is excited.

[0790] The generated virtual experience content is compressed and sent from the server to the user's device, where the user can use a VR headset or haptic device to experience the experience through sight, touch, sound, and more, as if they were actually there.

[0791] The conversations and actions that users make during the virtual experience are detected by the device, with voice data collected by a microphone and movement data captured by a motion sensor. This interaction data is sent to the server in real time, where the server's emotion engine analyzes the data and extracts the user's emotions.

[0792] The server analyzes the received interaction data and emotion data and generates feedback based on the user's emotion, which is sent to the user's device and displayed, for example, as a voice response or appropriate adjustment to behavior.

[0793] Specific examples

[0794] For example, consider the case where an elderly person, Mr. A, uses the system at home while his family is on a trip to a seaside resort. The family uses smartphones or dedicated devices at the destination to collect environmental data in real time, such as the sound of the ocean, the scenery, and the feel of the sand, and sends this data to the server. The server then generates virtual experience content that is optimal for Mr. A based on his profile information.

[0795] By wearing a dedicated VR headset and haptic device, A can feel as if he is at a seaside resort from the comfort of his own home. He can hear the sound of the ocean waves, enjoy the scenery with his eyes, and feel the texture of the sand with his hands. Furthermore, the emotion engine recognizes A's emotions and adjusts the content and feedback in real time, giving him a deeper sense of satisfaction.

[0796] Prompt Sentence Examples

[0797] Here are some examples of prompts for generative AI models:

[0798] Describe a scenario in detail where an elderly user would use a virtual experience system at home. Explain how the system connects with tourist attractions the family member is actually visiting and provides the user with the most appropriate virtual experience based on their profile information. This process includes real-time feedback from an emotion engine.

[0799] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0800] Step 1:

[0801] Obtaining user profile information

[0802] Server: Queries the database based on the user's ID and obtains the user's profile information (health status, sensitivity, favorite tourist spots, etc.).

[0803] Input: User ID.

[0804] Data processing: Profile information was obtained through database queries.

[0805] Output: User profile information (e.g., A's health condition, high blood pressure, favorite tourist destination is Kyoto).

[0806] Step 2:

[0807] Acquisition of local environmental data

[0808] Device: Use a smartphone or dedicated device on-site to obtain GPS location information.

[0809] Input: GPS signal.

[0810] Data processing: Obtain GPS location information.

[0811] Output: GPS location (e.g. Gion, Kyoto).

[0812] Step 3:

[0813] Environmental data collection

[0814] Device: The camera captures the scenery, the microphone collects surrounding sounds, and the tactile sensor records the feel of the sand on the beach.

[0815] Input: Local environment.

[0816] Data processing: visual data (camera footage), audio data (microphone recording), tactile data (sensor recording).

[0817] Output: Local environment data (e.g., Gion landscape images, audio, tactile data).

[0818] Step 4:

[0819] Sending environmental data

[0820] Terminal: Compresses collected environmental data in real time and sends it to the server.

[0821] Input: Local environmental data (visual, audio, tactile).

[0822] Data processing: Compressing data using a compression algorithm (e.g. Gzip).

[0823] Output: Compressed environment data.

[0824] Step 5:

[0825] Analyzing received data

[0826] Server: Analyzes the received environmental data.

[0827] Input: Compressed environment data.

[0828] Data processing: Decompressing compressed data, analyzing visual data with an image processing library (e.g., OpenCV), analyzing audio data with a speech recognition algorithm (e.g., Google Speech-to-Text), and converting haptic data for use with the feedback device.

[0829] Output: Parsed environmental data.

[0830] Step 6:

[0831] Creation of virtual experience content

[0832] Server: Generates optimal virtual experience content based on the user's profile information.

[0833] Input: Parsed environmental data, user profile information.

[0834] Data processing: Applying data filters tailored to profile information (e.g., providing a gentler experience for users with high blood pressure).

[0835] Output: Virtual experience content.

[0836] Step 7:

[0837] Emotion Engine Operation

[0838] Server: Recognizes emotions from the user's facial expressions and voice analysis using an emotion engine.

[0839] Input: User's facial expression data, voice data.

[0840] Data processing: Analyze sentiment using machine learning models (e.g., TensorFlow, PyTorch).

[0841] Output: Recognized emotion data.

[0842] Step 8:

[0843] Emotion-based content adjustment

[0844] Server: Adjusts the virtual experience content in real time based on the user's emotions.

[0845] Input: Recognized emotion data, virtual experience content.

[0846] Data manipulation: Adjusting content (e.g., if the user is excited, adding elements that have a calming effect).

[0847] Output: Tailored virtual experience content.

[0848] Step 9:

[0849] Submitting content

[0850] Server: Compresses the tailored virtual experience content in real time and sends it to the user's device.

[0851] Input: Tailored virtual experience content.

[0852] Data processing: Data compression using compression algorithms.

[0853] Output: Compressed virtual experience content.

[0854] Step 10:

[0855] User virtual experience begins

[0856] User: Puts on the VR headset and haptic device and starts the virtual tour.

[0857] Input: Compressed virtual experience content.

[0858] Data processing: decompression and playback.

[0859] Output: Visual, tactile and audio virtual experience.

[0860] Step 11:

[0861] Collecting user interaction data

[0862] Device: Senses what the user says and does during the experience.

[0863] Input: User gestures, voice.

[0864] Data processing: Voice data is collected by a microphone, and movement data is acquired by a motion sensor.

[0865] Output: Interaction data.

[0866] Step 12:

[0867] Transmission of interaction data and emotion data

[0868] Terminal: Collected interaction data and emotion data are sent to the server in real time.

[0869] Input: interaction data, emotion data.

[0870] Data processing: data compression and transmission.

[0871] Output: Interaction and emotion data sent to the server.

[0872] Step 13:

[0873] Analysis of interaction data and emotion data and feedback generation

[0874] Server: Analyzes the received interaction data and emotion data.

[0875] Input: Submitted interaction and sentiment data.

[0876] Data processing: Real-time feedback generation based on user behavior.

[0877] Output: Feedback data sent to the user device.

[0878] (Application example 2)

[0879] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0880] While conventional virtual experience systems offer the elderly and physically challenged people the surprise and fun of traveling and shopping without leaving their homes, they have limitations in providing detailed in-store guidance and promotional information. Furthermore, they are unable to adjust content in real time based on the user's emotional state, making it difficult to improve user satisfaction and the quality of the experience.

[0881] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for acquiring user profile information, means for using sensors to collect user position information and environmental data within the physical store, and means including an emotion engine for analyzing user emotion data. This makes it possible to provide an optimal virtual guidance experience in real time based on the user's position information and emotion data, thereby improving user satisfaction.

[0882] "User profile information" is detailed personal information about the user, such as the user's health condition, sensitivities, and favorite tourist spots.

[0883] "Local environment data" refers to surrounding information such as visual data, audio data, and tactile data that exists in the actual location.

[0884] "Means for analyzing received environmental data" refers to a device or program capable of analyzing environmental data transmitted from the site and converting it into virtual experience content.

[0885] "Generated content" refers to the content of a virtual experience created for a user.

[0886] "User Device" refers to the equipment (e.g., smartphone, smart glasses, head-mounted display) used by a user to engage in a virtual experience.

[0887] "Means for providing a virtual experience" refers to technologies and devices that provide virtual experience content to users in the form of sight, touch, sound, etc.

[0888] "Interaction data" refers to information such as the actions and conversations a user makes during a virtual experience.

[0889] A "sensor" is a device for acquiring environmental data. This includes cameras, microphones, tactile sensors, etc.

[0890] An "emotion engine" is a program that recognizes and analyzes emotions from a user's facial expressions and voice.

[0891] "Promotion information" refers to information about sales and special offers taking place in stores.

[0892] "Emotion data" is data that indicates the user's emotional state analyzed by the emotion engine.

[0893] This invention is a system that allows elderly people and people with physical disabilities to virtually experience the sensation of visiting a store. The system acquires user profile information and local environmental data, analyzes the user's emotional state using an emotion engine, and customizes the virtual experience content in real time based on the analysis.

[0894] Specific processing of the program

[0895] 1. Obtaining user profile information

[0896] The server queries the database based on the user's ID and obtains the user's profile information (health status, sensitivity, favorite product categories, etc.) and uses this information to design an optimal virtual experience.

[0897] 2. Acquiring environmental data within physical stores

[0898] The device (smart glasses) collects environmental data (location information, product information, promotion information) from sensors installed in the store, including cameras, microphones, and tactile sensors.

[0899] 3. Emotion analysis using an emotion engine

[0900] The server uses the camera and microphone built into the smart glasses to analyze the user's facial expressions and voice data, which allows the emotion engine to recognize the user's emotions and capture the data in real time.

[0901] 4. Creation and transmission of virtual experience content

[0902] The server generates virtual experience content based on the acquired environmental data, the user's profile information, and emotional data, and the generated content is compressed and sent to the user's smart glasses.

[0903] 5. User Virtual Experience

[0904] While wearing the smart glasses, users can explore the physical store through virtual experience content, which includes not only sight and sound but also touch, giving them the feeling of actually visiting the store.

[0905] Hardware and software used

[0906] Hardware used

[0907] Smart glasses (general smart devices)

[0908] In-store sensors (beacons that acquire location information, cameras and microphones that collect environmental data)

[0909] Software used

[0910] Emotion engine (e.g. Emotion API)

[0911] Speech recognition algorithms (e.g., Google Cloud Speech-to-Text)

[0912] Image processing algorithms (e.g., OpenCV)

[0913] Specific Examples

[0914] For example, consider the case where an elderly person named B uses a virtual experience system without visiting a physical store. B puts on smart glasses at home and launches the corresponding application. The smart glasses receive and analyze location information, product information, and promotion information collected by sensors in the store in real time. Furthermore, emotional data from B's facial expressions and voice is analyzed, and content is customized based on the products and promotions that B is interested in.

[0915] Prompt Sentence Examples

[0916] User Profile Information:

[0917] ID: user1234

[0918] Likes: Food

[0919] Health status: No problems

[0920] Sensitivity: High

[0921] Environmental data:

[0922] Store name: Supermarket

[0923] Location: Food section

[0924] Products: Apples, bananas, oranges

[0925] Promotion: Buy one apple, get one free

[0926] Emotional Data:

[0927] Expression: Smiling

[0928] Audio: Sounds fun

[0929] By inputting such prompt sentences into a generative AI model, it is possible to generate and provide content for a virtual guidance experience that is optimal for the user.

[0930] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0931] Step 1:

[0932] The server queries the database based on the user's ID and obtains the user's profile information (health status, sensitivity, favorite product categories, etc.) and uses this information to design a virtual experience that is optimal for the user.

[0933] Input: User ID

[0934] Output: User profile information

[0935] Specific Operation: The server communicates with a database server to query for profile information associated with the user ID and stores the resulting information in an internal data store.

[0936] Step 2:

[0937] The device (smart glasses) collects environmental data (location information, product information, promotion information) from sensors installed in the store, including cameras, microphones, and tactile sensors.

[0938] Input: Local environmental data (sensor data)

[0939] Output: Collected environmental data

[0940] Specific operation: The terminal accesses the sensor network, collects data obtained from each sensor, processes it, and prepares it to be sent to the server.

[0941] Step 3:

[0942] The server receives and analyzes the environmental data sent from the device, using image processing algorithms (OpenCV) and speech recognition algorithms (Google Cloud Speech-to-Text) to analyze the data and generate virtual experience content.

[0943] Input: Collected environmental data

[0944] Output: Analysis results, virtual experience content

[0945] Specific operation: The server runs image processing algorithms and voice recognition algorithms to analyze the environmental data, and then generates virtual experience content based on it, customizing it taking into account the user's profile information.

[0946] Step 4:

[0947] The smart glasses use a built-in camera and microphone to collect facial and voice data, which is then used by the emotion engine to recognize the user's emotions.

[0948] Input: User's facial expression data, voice data

[0949] Output: Emotion data

[0950] Specific operation: The device captures the user's facial expressions and voice in real time using a camera and microphone, and sends the data to the server. The server then uses an emotion engine to analyze the data and recognize the user's emotions.

[0951] Step 5:

[0952] The server generates optimal virtual experience content based on the user's profile information, environmental data, and emotional data, compresses it, and sends it to the user's smart glasses.

[0953] Input: Profile information, environmental data, emotional data

[0954] Output: Virtual experience content

[0955] How it works: The server aggregates all data and generates optimized virtual experience content, which is then compressed and instantly sent to the device.

[0956] Step 6:

[0957] By wearing smart glasses, users can explore the store through virtual experience content, and experience the store in a realistic way through sight, sound, and touch. Interaction data collected during the experience is also sent to the server.

[0958] Input: Virtual experience content

[0959] Output: User interaction data

[0960] Specific Actions: Users use smart glasses to initiate a real-time virtual experience, and interaction data such as movements and sounds while exploring are collected and sent to the server.

[0961] Step 7:

[0962] The server analyzes the received interaction data and generates real-time feedback, which is tailored appropriately based on the user's emotions.

[0963] Input: Interaction data

[0964] Output: Feedback

[0965] Specific operation: The server analyzes the interaction data and generates feedback appropriate to the user's behavior and emotions. This feedback is sent back to the device in real time and presented to the user in an appropriate format.

[0966] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0967] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0968] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0969] [Third embodiment]

[0970] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0971] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0972] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0973] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0974] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0975] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0976] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0977] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0978] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0979] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0980] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0981] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[0982] This is a system that provides a virtual experience for elderly people and people with disabilities, allowing them to feel like they are traveling with their family. This system acquires user profile information and achieves real-time interaction through a series of processes that receive, analyze, generate, and provide local environmental data in real time.

[0983] Natural language explanation of the program's processing

[0984] 1. Obtaining user profile information

[0985] The server retrieves the user's profile information (health status, sensitivity, favorite tourist spots, etc.) from the database.

[0986] The server uses the acquired information to design a virtual experience that suits the user's condition and preferences.

[0987] 2. Acquisition and transmission of local environmental data

[0988] The device collects local environmental data (visual, audio, tactile, etc.).

[0989] The terminal transmits this environmental data to the server in real time.

[0990] The device also obtains location information using GPS and other means and sends this information to the server.

[0991] 3. Analysis of environmental data and generation of virtual experience content

[0992] The server analyzes the received environmental data.

[0993] The server generates virtual experience content tailored to the user's profile information based on the analysis results.

[0994] The server transmits the generated content to the user's terminal.

[0995] 4. Providing virtual experiences

[0996] The user experiences the provided virtual experience content using a dedicated device (such as a VR headset or haptic device).

[0997] Users can experience the experience as if they were actually there through sight, touch, sound, etc.

[0998] 5. Collection and transmission of user interaction data

[0999] The device detects the conversations and actions the user makes during the virtual experience.

[1000] The terminal collects sensed interaction data and transmits it to a server.

[1001] 6. Real-time feedback generation

[1002] The server analyzes the user interaction data.

[1003] The server generates real-time feedback based on the analysis results and sends it to the user's device.

[1004] Feedback includes conversational responses and reactions to actions.

[1005] Specific examples

[1006] For example, consider the case where an elderly person, Mr. A, uses the system at home while his family is on a trip to a seaside resort. The family uses smartphones or dedicated devices at the destination to collect real-time environmental data, such as the sound of the ocean, the scenery, and the feel of the sand. This data is sent to a server, which then generates the most suitable virtual experience content for Mr. A based on his profile information.

[1007] By wearing a dedicated VR headset and haptic device, Mr. A can feel as if he is at a seaside resort in his own home. He can talk to his family and interact with them in real time, giving him the experience of actually traveling.

[1008] The processing flow will be explained below.

[1009] Step 1: Obtaining the user's profile information

[1010] The server queries the database based on the user's ID and obtains the user's profile information (health status, sensitivity, favorite tourist spots, etc.).

[1011] Step 2: Obtaining local environmental data

[1012] The device obtains local GPS location information.

[1013] The device collects environmental data from the local surroundings (visual data from the camera, audio data from the microphone, and tactile data from the tactile sensor).

[1014] Step 3: Sending environment data

[1015] The device compresses the collected environmental data in real time and sends it to the server.

[1016] Step 4: Parse the received data

[1017] The server analyzes the received environmental data.

[1018] The server analyzes the visual data using image processing algorithms and converts it into virtual content.

[1019] The server analyzes the voice data using a voice recognition algorithm and performs voice filtering if necessary.

[1020] The server analyzes the tactile data and converts it into signals for the haptic device.

[1021] Step 5: Generate virtual experience content

[1022] The server generates optimal virtual experience content based on the user's profile information.

[1023] The server applies data filters based on health status and sensitivity, and creates content tailored to the user's condition.

[1024] Step 6: Submit your content

[1025] The server compresses the generated virtual experience content in real time and transmits it to the user's terminal.

[1026] Step 7: Start the user's virtual experience

[1027] Users experience the virtual experience content provided through the device using a VR headset or haptic device.

[1028] The user sees visual information through a VR headset, hears audio information through headphones, and experiences tactile information through a haptic device.

[1029] Step 8: Collect interaction data

[1030] When the user talks or moves during the virtual experience, the device detects this.

[1031] The device collects voice data using a microphone and acquires movement data using a motion sensor.

[1032] Step 9: Sending interaction data

[1033] The terminal transmits the collected interaction data to the server in real time.

[1034] Step 10: Analyze interaction data and generate feedback

[1035] The server analyzes the received interaction data.

[1036] The server analyzes the user's voice data and generates an appropriate response.

[1037] The server analyzes the motion data and generates the necessary virtual interactions.

[1038] The server transmits the generated feedback to the user's terminal in real time.

[1039] Step 11: Provide real-time feedback

[1040] The user receives real-time feedback from the server during the virtual experience.

[1041] The user experiences conversational responses and reactions to actions.

[1042] Example 1

[1043] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1044] Until now, there has been no means available for elderly people and people with physical disabilities to have a real-time virtual experience that makes it seem as if they are traveling with family and friends, even when mobility is difficult. To provide a realistic experience, it is necessary to provide multiple sensory information, such as visual, tactile, and audio, in real time and provide instant feedback on the user's reactions to that information, but the specific system configuration and technical means to achieve this have not yet been established.

[1045] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1046] In this invention, the server includes means for acquiring user profile information, means for collecting local environmental data and transmitting it to the server, means for analyzing the received environmental data, means for generating virtual experience content based on the user profile information, means for transmitting the generated content to the user's device, means for providing the virtual experience on the user's device, means for collecting user interaction data during the virtual experience and transmitting it to the server, and means for analyzing the interaction data and generating feedback in real time, thereby enabling elderly people and people with disabilities to have an experience similar to a real trip in real time and interactively from a safe place such as their own home.

[1047] "Profile information" is information that indicates individual characteristics and conditions such as the user's name, age, health condition, sensitivity, favorite tourist spots, etc.

[1048] "Environmental data" refers to data that includes information about the surroundings, such as visual, audio, and tactile information of the local area.

[1049] "Virtual experience content" refers to content such as images, audio, and haptic feedback that are generated so that users can experience the same environment as they would in a real world.

[1050] "Interaction data" refers to data that indicates a user's reactions and behavior, such as the conversations and actions the user engages in during a virtual experience.

[1051] "Feedback" is data that indicates responses or reactions that are generated based on user interaction data and provided to the user in real time.

[1052] "Device" refers to the equipment used by a user to receive a virtual experience (e.g., VR headset, haptic device, etc.).

[1053] A "server" is a central computer system that receives, analyzes, and processes data sent by users, and generates and sends virtual experience content and feedback to users.

[1054] "Collection" refers to obtaining visual, audio, tactile, and other data on-site.

[1055] "Transmit" means transferring collected data to another device or computer system.

[1056] "Analysis" refers to evaluating collected data and extracting necessary information.

[1057] "Generation" means creating new content or information based on the analysis results.

[1058] This invention is a system that provides a virtual experience for elderly people and people with disabilities, allowing them to feel like they are traveling with their family. This system acquires user profile information and achieves real-time interaction through a series of processes that receive, analyze, generate, and provide local environmental data in real time.

[1059] 1. Profile information acquisition

[1060] The server retrieves the user's profile information from the database, such as the user's name, age, health status, sensitivity, favorite tourist spots, etc. This allows the server to personalize the virtual experience to suit the user's preferences and characteristics.

[1061] 2. Acquisition and transmission of local environmental data

[1062] The device (e.g., a smartphone or dedicated device) collects visual, audio, and tactile data using local environmental data (e.g., a 360-degree camera, field recorder, tactile sensor, etc.). The device transmits the collected data to a server in real time. In addition, the device obtains its location information using GPS and transmits it to the server.

[1063] 3. Analysis of environmental data and generation of virtual experience content

[1064] The server analyzes the received environmental data using data analysis software such as Python libraries (e.g., OpenCV, Librosa) and TensorFlow. Based on the analysis results, the server generates virtual experience content optimized for the user's profile information. This content is then converted into a format compatible with the user's device (e.g., VR headset, haptic device).

[1065] 4. Providing virtual experiences

[1066] Users wear a dedicated device (e.g., Oculus Quest 2, Teslasuit) to enjoy a virtual experience. Users can experience the experience as if they were actually there through sight, touch, and sound, and can converse and interact with family and friends in the location.

[1067] 5. Collection and transmission of interaction data

[1068] The conversations and actions that users make during the virtual experience are detected by the device (e.g., the built-in microphone and motion sensor of the Oculus Quest 2, or the sensor of the Teslasuit). This interaction data is sent to the server in real time.

[1069] 6. Real-time feedback generation

[1070] The server analyzes the received interaction data using natural language processing models and motion analysis algorithms (e.g., OpenAI's GPT model, PoseNet, etc.). The server generates real-time feedback based on the analysis results and sends it to the user's device. The feedback includes conversational responses and haptic feedback.

[1071] Specific examples

[1072] For example, consider the case where elderly person A uses this system at home while their family travels to a seaside resort. While at the resort, the family uses smartphones or dedicated devices (e.g., 360-degree cameras, ambient sound microphones, tactile sensors, etc.) to collect real-time environmental data, such as the sound of the ocean, the scenery, and the feel of the sand. This data is sent to a server, which then generates virtual experience content that is optimal for A based on his or her profile information.

[1073] By wearing a dedicated VR headset and haptic device, Mr. A can feel as if he is at a seaside resort in his own home. He can talk to his family and interact with them in real time, giving him the experience of actually traveling.

[1074] Prompt Sentence Examples

[1075] Below are some example prompts to give to a generative AI model (e.g., GPT-3):

[1076] Please explain a system that provides a virtual experience that allows elderly people and people with disabilities to feel like they are traveling with their families. This system acquires user profile information and performs a series of processes to receive, analyze, generate, and provide local environmental data in real time. Please explain in detail what specific hardware and software are used, how the data is processed, and how the virtual experience is provided.

[1077] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1078] Step 1:

[1079] The server retrieves the user's profile information from the database.

[1080] Specifically, the server issues SQL queries to the database to retrieve information such as the user's name, age, health status, sensitivity, and favorite tourist spots. This retrieved profile information becomes the input data for the next processing step. The output is the user's detailed information.

[1081] Step 2:

[1082] The device collects local environmental data and transmits it to a server in real time.

[1083] The terminal collects visual, audio, and tactile data using devices such as a 360-degree camera, field recorder, and tactile sensor. It also acquires location information using GPS. The input is local environmental data and location information. The acquired data is uploaded to a server via a communication line. The output is the environmental data and location information sent to the server.

[1084] Step 3:

[1085] The server analyzes the received environmental data.

[1086] Visual, audio, and haptic data is analyzed using Python libraries (e.g., OpenCV, Librosa) and TensorFlow. The results of this analysis are the basis for generating the user's virtual experience content. The input is the local environment data received by the server. The output is the analyzed environment data.

[1087] Step 4:

[1088] The server generates virtual experience content based on the analysis results.

[1089] The server creates personalized virtual experience content based on the user's profile information and analyzed environmental data. A generative AI model (e.g., TensorFlow, GANs, etc.) is used for generation. The input is the user's profile information and analyzed environmental data. The output is the virtual experience content.

[1090] Step 5:

[1091] The server transmits the generated virtual experience content to the user's device.

[1092] The generated content is converted into a format compatible with the user's VR headset or haptic device and sent to the user's device via a communication line. The input is the generated virtual experience content. The output is the content sent to the user's device.

[1093] Step 6:

[1094] Users get a virtual experience using a dedicated device.

[1095] A user wears a VR headset (e.g., Oculus Quest 2) and a haptic device (e.g., Teslasuit) to play virtual experience content. The input is the received virtual experience content. The output is feedback of the user's virtual experience.

[1096] Step 7:

[1097] The device collects local interaction data and sends it to a server.

[1098] The conversations and actions that users make during the virtual experience are collected through the built-in microphones, motion sensors, and sensors in the haptic device of the VR headset. The input is the user's interaction. The collected data is sent to the server in real time. The output is the interaction data sent to the server.

[1099] Step 8:

[1100] The server analyzes the interaction data and generates feedback in real time.

[1101] The server analyzes the interaction data using a natural language processing model (e.g., GPT model) or a motion analysis algorithm (e.g., PoseNet). The input is the transmitted interaction data. Based on the analysis results, the server generates feedback data to respond to the user in real time. The output is the generated feedback.

[1102] Step 9:

[1103] The server generates feedback and sends it to the user's device.

[1104] The feedback data is transmitted to the user's device via a communication line and provided to the user in real time. The input is the generated feedback data. The output is the real-time feedback provided to the user.

[1105] (Application example 1)

[1106] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1107] With conventional virtual experience systems, it was difficult for elderly people and people with physical disabilities to enjoy a rich shopping experience without actually going to the location. It was also difficult to provide a personalized experience that matched each user's preferences and health condition. This made it difficult to provide a satisfying virtual experience, especially for users with specific needs.

[1108] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1109] In this invention, the server includes means for acquiring user profile information, means for acquiring and transmitting local environmental data, means for analyzing the received environmental data to generate optimal virtual experience content, means for transmitting the generated content to the user's device, means for providing the virtual experience on the user's device, means for collecting and transmitting user interaction data during the virtual experience, means for analyzing the collected interaction data to generate feedback in real time, and means for customizing the shopping experience based on the user's past purchasing history, thereby enabling even elderly people and people with disabilities to enjoy a customized shopping experience in real time without having to go to the site.

[1110] The "means for acquiring user profile information" has a function for acquiring personal information such as the user's health condition, preferences, and past purchase history from a storage device such as a database.

[1111] The "means for acquiring and transmitting local environmental data" is a function that collects data necessary for the user to feel as if they are in the local area, such as local video, audio, and tactile information, and transmits this data to a server.

[1112] The "means for analyzing received environmental data and generating optimal virtual experience content" has the function of analyzing received local environmental data and generating optimized virtual experience content based on the user's profile information.

[1113] "Means for transmitting generated content to a user's device" means a function that transmits the generated virtual experience content to a user's device, such as a VR headset or smart glasses.

[1114] "Means for providing a virtual experience on a user's device" means a function that provides the generated virtual experience content to the user through the user's device, allowing the user to experience it through sight, touch, sound, etc.

[1115] "Means for collecting and transmitting user interaction data during a virtual experience" refers to a device that has the function of collecting interaction data such as the user's actions and conversations during the virtual experience and transmitting it to a server.

[1116] The "means for analyzing collected interaction data and generating feedback in real time" has the function of analyzing collected user interaction data and generating feedback on user actions in real time.

[1117] "Means for customizing a shopping experience based on a user's past purchasing history" refers to a function that customizes virtual experience content based on the user's past purchasing history information in order to provide the optimal shopping experience tailored to the user's preferences.

[1118] This invention provides a virtual experience system that allows elderly people and people with physical disabilities to enjoy a rich shopping experience from home. The system is configured to provide a personalized experience by utilizing the user's personal information, preferences, and past purchasing history.

[1119] 1. Obtaining user profile information

[1120] The server retrieves the user's profile information (health status, preferences, past purchase history, etc.) from the database, which is then used to optimize the virtual shopping experience for the individual user.

[1121] 2. Acquisition and transmission of local environmental data

[1122] Devices (e.g., smartphones or smart glasses) collect environmental data such as video, audio, and detailed product information in real time within a local store. This data is then sent from the local store to a server. The devices are equipped with cameras, microphones, sensors, etc., and have a communication module for transmitting this data in real time.

[1123] 3. Analysis of environmental data and generation of virtual experience content

[1124] The server analyzes the received environmental data and works with a generative AI model to generate optimal virtual shopping experience content based on the user's profile information. This analysis utilizes cloud services such as computer vision APIs (e.g., Amazon Rekognition) and natural language processing models (e.g., Google Cloud Speech-to-Text).

[1125] 4. Providing virtual experiences

[1126] The generated virtual experience content is sent to the user's device (e.g., VR headset or smart glasses). By wearing these devices, the user can experience walking through the virtual store and picking up products through sight, touch, and sound.

[1127] 5. Collection and transmission of user interaction data

[1128] Interaction data, such as conversations and actions that users make during the virtual experience, is sensed and collected by the device, and the collected data is sent to a server.

[1129] 6. Real-time feedback generation

[1130] The server analyzes the collected interaction data, generates feedback in real time, and sends it to the user's device, providing instant feedback on the user's actions and providing a simulated experience that makes the user feel as if they are actually in the store.

[1131] Specific examples

[1132] For example, an elderly user can use the system at home, while a local store staff member uses a terminal to transmit video and audio from the store in real time. The user can then enjoy a personalized shopping experience based on their profile information and past purchase history through a VR headset or smart glasses.

[1133] Examples of prompt statements

[1134] "Generate a virtual store experience tailored to the user's preferences. User information: {Name: 'Jiro Taguchi', Age: 75, Preferences: ['Clothing', 'Electronics']}, Current Store Labels: ['Laptop', 'Smartphone']"

[1135] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1136] Step 1:

[1137] The server retrieves the user's profile information from the database. The retrieved information includes the user's health condition, preferences, past purchase history, etc. The input is identification information such as the user ID, and the output is the user's detailed profile information. This information is retrieved using a database access API.

[1138] Step 2:

[1139] The terminal acquires local environmental data in real time and sends it to the server. The environmental data includes video, audio, and detailed product information from within the store. The terminal collects data using cameras and microphones and sends it through a communications module. The input is sensor data from the cameras and microphones, and the output is data sent to the server.

[1140] Step 3:

[1141] The server analyzes the received local environmental data and generates virtual experience content. The server processes the data using computer vision APIs (e.g., Amazon Rekognition) and natural language processing models (e.g., Google Cloud Speech-to-Text). The input is the received environmental data and user profile information, and the output is the generated virtual experience content.

[1142] Step 4:

[1143] The server generates virtual experience content and sends it to the user's device, which can be a VR headset or smart glasses. The input is the generated virtual experience content, and the output is the data sent to the user's device.

[1144] Step 5:

[1145] The user's device plays the virtual experience content and provides the user with the experience through sight, touch, and sound. The device can be a VR headset or smart glasses, with the input being the transmitted virtual experience content and the output being the user's virtual experience.

[1146] Step 6:

[1147] The device collects interaction data of the user during the virtual experience and sends it to the server. The interaction data includes the user's actions and conversations. The input is the data of the user's actions and speech, and the output is the data sent to the server.

[1148] Step 7:

[1149] The server analyzes the collected interaction data and generates feedback in real time. The server uses a generative AI model to analyze and generate feedback according to the user's actions. The input is the sent interaction data, and the output is the generated feedback data.

[1150] Step 8:

[1151] The server generates feedback and sends it to the user's device, providing it to the user in real time. The feedback includes immediate reactions to the product and additional information. The input is the generated feedback data, and the output is the data sent to the user's device.

[1152] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1153] This system provides a virtual experience for elderly people and people with disabilities, allowing them to feel like they are traveling with their families. This system acquires user profile information and processes a series of processes that receive, analyze, generate, and provide local environmental data in real time. It also includes an emotion engine that recognizes user emotions and adjusts content and provides feedback based on those emotions.

[1154] Natural language explanation of the program's processing

[1155] 1. Obtaining user profile information

[1156] The server queries the database based on the user's ID and obtains the user's profile information (health status, sensitivity, favorite tourist spots, etc.).

[1157] The server uses the acquired information to design a virtual experience that suits the user's condition and preferences.

[1158] 2. Acquisition and transmission of local environmental data

[1159] The device obtains local GPS location information.

[1160] The device collects environmental data from the local surroundings (visual data from the camera, audio data from the microphone, and tactile data from the tactile sensor).

[1161] 3. Sending environmental data

[1162] The device compresses the collected environmental data in real time and sends it to the server.

[1163] 4. Analysis of received data

[1164] The server analyzes the received environmental data.

[1165] The server analyzes the visual data using image processing algorithms and converts it into virtual content.

[1166] The server analyzes the voice data using a voice recognition algorithm and performs voice filtering if necessary.

[1167] The server analyzes the tactile data and converts it into signals for the haptic device.

[1168] 5. Creation of virtual experience content

[1169] The server generates optimal virtual experience content based on the user's profile information.

[1170] The server applies data filters based on health status and sensitivity, and creates content tailored to the user's condition.

[1171] 6. Operation of the Emotion Engine

[1172] The server uses an emotion engine to recognize emotions from the user's facial expressions and voice analysis.

[1173] The server uses an emotion engine to adjust the content of the virtual experience based on the user's emotions.

[1174] 7. Submission of Content

[1175] The server compresses the generated virtual experience content in real time and transmits it to the user's terminal.

[1176] 8. User begins virtual experience

[1177] Users experience the virtual experience content provided through the device using a VR headset or haptic device.

[1178] Users can experience the experience as if they were actually there through sight, touch, sound, etc.

[1179] 9. Collection and transmission of user interaction data

[1180] When the user talks or moves during the virtual experience, the device detects this.

[1181] The device collects voice data using a microphone and acquires movement data using a motion sensor.

[1182] The emotion engine extracts the user's emotions from these data.

[1183] 10. Transmission of Interaction and Emotion Data

[1184] The device transmits the collected interaction data and emotion data to a server in real time.

[1185] 11. Analysis of interaction and emotion data and feedback generation

[1186] The server analyzes the received interaction data and emotion data.

[1187] The server generates feedback in real time based on the user's emotions and transmits it to the user's terminal.

[1188] Feedback includes conversational responses and behavioral reactions, with appropriate emotional adjustments.

[1189] Specific examples

[1190] For example, consider the case where an elderly person, Mr. A, uses the system at home while his family is on a trip to a seaside resort. The family uses smartphones or dedicated devices at the destination to collect real-time environmental data, such as the sound of the ocean, the scenery, and the feel of the sand. This data is sent to a server, which then generates the most suitable virtual experience content for Mr. A based on his profile information.

[1191] By wearing a dedicated VR headset and haptic devices, Mr. A can feel as if he is at a seaside resort in his own home. He can converse with his family and interact with them in real time, giving him the experience of actually traveling. Furthermore, the emotion engine recognizes Mr. A's emotions and adjusts the content and feedback in real time, giving him a deeper sense of satisfaction.

[1192] The processing flow will be explained below.

[1193] Step 1: Obtaining the user's profile information

[1194] The server queries the database based on the user's ID and obtains the user's profile information (health status, sensitivity, favorite tourist spots, etc.).

[1195] Step 2: Obtaining local environmental data

[1196] The device obtains local GPS location information.

[1197] The device collects environmental data from the local surroundings (visual data from the camera, audio data from the microphone, and tactile data from the tactile sensor).

[1198] Step 3: Sending environment data

[1199] The device compresses the collected environmental data in real time and sends it to the server.

[1200] Step 4: Parse the received data

[1201] The server analyzes the received environmental data.

[1202] The server analyzes the visual data using image processing algorithms and converts it into virtual content.

[1203] The server analyzes the voice data using a voice recognition algorithm and performs voice filtering if necessary.

[1204] The server analyzes the tactile data and converts it into signals for the haptic device.

[1205] Step 5: Generate virtual experience content

[1206] The server generates optimal virtual experience content based on the user's profile information.

[1207] The server applies data filters based on health status and sensitivity, and creates content tailored to the user's condition.

[1208] Step 6: Emotion Engine in Action

[1209] The server uses an emotion engine to recognize emotions from the user's facial expressions and voice analysis.

[1210] The server uses an emotion engine to adjust the content of the virtual experience based on the user's emotions.

[1211] Step 7: Submit your content

[1212] The server compresses the generated virtual experience content in real time and transmits it to the user's terminal.

[1213] Step 8: Start the user's virtual experience

[1214] Users experience the virtual experience content provided through the device using a VR headset or haptic device.

[1215] Users can experience the experience as if they were actually there through sight, touch, sound, etc.

[1216] Step 9: Collecting and sending user interaction data

[1217] When the user talks or moves during the virtual experience, the device detects this.

[1218] The device collects voice data using a microphone and acquires movement data using a motion sensor.

[1219] The emotion engine extracts the user's emotions from these data.

[1220] Step 10: Sending interaction and emotion data

[1221] The device transmits the collected interaction data and emotion data to a server in real time.

[1222] Step 11: Analyze interaction and emotion data and generate feedback

[1223] The server analyzes the received interaction data and emotion data.

[1224] The server analyzes the user's voice data and generates an appropriate response.

[1225] The server analyzes the motion data and generates the necessary virtual interactions.

[1226] The server analyzes the emotion data and generates feedback based on the user's emotion.

[1227] Step 12: Provide real-time feedback

[1228] The user receives real-time feedback from the server during the virtual experience.

[1229] The user experiences reactions to conversational responses and actions, and appropriate adjustments are made to match their emotions.

[1230] Example 2

[1231] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1232] The purpose of this invention is to provide optimal content in real time that is tailored to the health and emotions of each individual user, especially when elderly people and people with physical disabilities experience local travel through virtual reality. Conventional systems have had problems such as difficulty in generating virtual experience content that takes into account the individual emotions and health of the user, and a lack of emotional feedback.

[1233] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1234] a means for obtaining user profile information;

[1235] means for acquiring and transmitting local environmental data (visual, audio, tactile);

[1236] A means for analyzing the received environmental data and generating optimal virtual experience content;

[1237] means for transmitting the generated content to a user's device;

[1238] means for recognizing a user's emotion and adjusting the virtual experience content accordingly;

[1239] This enables an optimal virtual local travel experience that takes into account the user's health condition and emotions in real time.

[1240] "User profile information" is information that indicates the user's individual attributes and preferences, such as their health condition, sensitivity, and favorite tourist spots.

[1241] "Local environment data" refers to local visual data, audio data, and tactile data, which is real-time environmental information for the user to experience.

[1242] "Visual data" refers to on-site video information captured by a camera.

[1243] "Audio data" refers to local acoustic information collected by microphones.

[1244] "Tactile data" refers to local texture and vibration information obtained by tactile sensors.

[1245] "Interaction Data" refers to data about the conversations and actions a user makes during a virtual experience.

[1246] "Emotion" is information that represents the mental state of the user, which is recognized by analyzing the user's facial expressions, voice, and the like.

[1247] "Feedback" refers to responses and adjustments generated in real time based on user interaction data and emotions.

[1248] "Virtual experience content" refers to virtual reality content that combines visual, audio, and tactile information generated for a user to experience.

[1249] An "emotion engine" is an algorithm and software that analyzes a user's facial expressions and voice to recognize emotions and adjust the experience.

[1250] "Health condition" is information indicating the physical health condition of the user, and may include symptoms such as high blood pressure and diabetes.

[1251] "Data filter" refers to the algorithms and processes used to adjust collected environmental data according to the user's condition and sensitivity.

[1252] "Virtual experience" refers to a virtual reality experience that a user experiences using a VR headset or haptic device.

[1253] This system provides a virtual experience for elderly people and people with disabilities, allowing them to feel like they are traveling with their families. This system acquires user profile information and performs a series of processes to receive, analyze, generate, and provide local environmental data in real time. It also includes an emotion engine that recognizes user emotions and adjusts content and provides feedback based on those emotions.

[1254] The system consists of a database that records user profile information, a terminal for acquiring local environmental data, a server that analyzes the data and generates virtual experience content, a communication means for sending the generated content to the user's device, and devices such as a VR headset and haptic device that allow the user to experience the experience.

[1255] Program processing explanation

[1256] The program processing of this system will be specifically explained below.

[1257] First, the server queries the database based on the user's ID to obtain the user's profile information (e.g., health status, sensitivity, favorite tourist spots, etc.) The database that can be used may be, for example, an SQL-based database or a NoSQL type.

[1258] The device then uses a smartphone or dedicated device on-site to acquire GPS location information, and uses a camera on-site to collect visual data, a microphone to collect audio data, and a tactile sensor to record tactile data.

[1259] These environmental data are compressed in real time on the device and sent to the server using commonly used compression algorithms (e.g., Gzip, LZ4, etc.).

[1260] The server analyzes the received environmental data. Visual data is analyzed using image processing libraries such as OpenCV and converted into virtual content. Audio data is analyzed using speech recognition algorithms such as the Google Speech-to-Text API, and noise reduction and filtering are performed as needed. Haptic data is converted into signals for haptic feedback devices.

[1261] The server generates optimal virtual experience content based on the user's profile information, applying data filters based on health conditions and sensitivities (e.g., adjusting the tempo of the music to provide a gentler experience for a user with high blood pressure).

[1262] The server's emotion engine then recognizes the user's emotions from facial and voice analysis. This emotion engine uses machine learning models trained with TensorFlow or PyTorch, for example. The server then adjusts the content of the virtual experience in real time based on the user's emotions. This could include adding relaxing elements if the user is excited.

[1263] The generated virtual experience content is compressed and sent from the server to the user's device, where the user can use a VR headset or haptic device to experience the experience through sight, touch, sound, and more, as if they were actually there.

[1264] The conversations and actions that users make during the virtual experience are detected by the device, with voice data collected by a microphone and movement data captured by a motion sensor. This interaction data is sent to the server in real time, where the server's emotion engine analyzes the data and extracts the user's emotions.

[1265] The server analyzes the received interaction data and emotion data and generates feedback based on the user's emotion, which is sent to the user's device and displayed, for example, as a voice response or appropriate adjustment to behavior.

[1266] Specific examples

[1267] For example, consider the case where an elderly person, Mr. A, uses the system at home while his family is on a trip to a seaside resort. The family uses smartphones or dedicated devices at the destination to collect environmental data in real time, such as the sound of the ocean, the scenery, and the feel of the sand, and sends this data to the server. The server then generates virtual experience content that is optimal for Mr. A based on his profile information.

[1268] By wearing a dedicated VR headset and haptic device, A can feel as if he is at a seaside resort from the comfort of his own home. He can hear the sound of the ocean waves, enjoy the scenery with his eyes, and feel the texture of the sand with his hands. Furthermore, the emotion engine recognizes A's emotions and adjusts the content and feedback in real time, giving him a deeper sense of satisfaction.

[1269] Prompt Sentence Examples

[1270] Here are some examples of prompts for generative AI models:

[1271] Describe a scenario in detail where an elderly user would use a virtual experience system at home. Explain how the system connects with tourist attractions the family member is actually visiting and provides the user with the most appropriate virtual experience based on their profile information. This process includes real-time feedback from an emotion engine.

[1272] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1273] Step 1:

[1274] Obtaining user profile information

[1275] Server: Queries the database based on the user's ID and obtains the user's profile information (health status, sensitivity, favorite tourist spots, etc.).

[1276] Input: User ID.

[1277] Data processing: Profile information was obtained through database queries.

[1278] Output: User profile information (e.g., A's health condition, high blood pressure, favorite tourist destination is Kyoto).

[1279] Step 2:

[1280] Acquisition of local environmental data

[1281] Device: Use a smartphone or dedicated device on-site to obtain GPS location information.

[1282] Input: GPS signal.

[1283] Data processing: Obtain GPS location information.

[1284] Output: GPS location (e.g. Gion, Kyoto).

[1285] Step 3:

[1286] Environmental data collection

[1287] Device: The camera captures the scenery, the microphone collects surrounding sounds, and the tactile sensor records the feel of the sand on the beach.

[1288] Input: Local environment.

[1289] Data processing: visual data (camera footage), audio data (microphone recording), tactile data (sensor recording).

[1290] Output: Local environment data (e.g., Gion landscape images, audio, tactile data).

[1291] Step 4:

[1292] Sending environmental data

[1293] Terminal: Compresses collected environmental data in real time and sends it to the server.

[1294] Input: Local environmental data (visual, audio, tactile).

[1295] Data processing: Compressing data using a compression algorithm (e.g. Gzip).

[1296] Output: Compressed environment data.

[1297] Step 5:

[1298] Analyzing received data

[1299] Server: Analyzes the received environmental data.

[1300] Input: Compressed environment data.

[1301] Data processing: Decompressing compressed data, analyzing visual data with an image processing library (e.g., OpenCV), analyzing audio data with a speech recognition algorithm (e.g., Google Speech-to-Text), and converting haptic data for use with the feedback device.

[1302] Output: Parsed environmental data.

[1303] Step 6:

[1304] Creation of virtual experience content

[1305] Server: Generates optimal virtual experience content based on the user's profile information.

[1306] Input: Parsed environmental data, user profile information.

[1307] Data processing: Applying data filters tailored to profile information (e.g., providing a gentler experience for users with high blood pressure).

[1308] Output: Virtual experience content.

[1309] Step 7:

[1310] Emotion Engine Operation

[1311] Server: Recognizes emotions from the user's facial expressions and voice analysis using an emotion engine.

[1312] Input: User's facial expression data, voice data.

[1313] Data processing: Analyze sentiment using machine learning models (e.g., TensorFlow, PyTorch).

[1314] Output: Recognized emotion data.

[1315] Step 8:

[1316] Emotion-based content adjustment

[1317] Server: Adjusts the virtual experience content in real time based on the user's emotions.

[1318] Input: Recognized emotion data, virtual experience content.

[1319] Data manipulation: Adjusting content (e.g., if the user is excited, adding elements that have a calming effect).

[1320] Output: Tailored virtual experience content.

[1321] Step 9:

[1322] Submitting content

[1323] Server: Compresses the tailored virtual experience content in real time and sends it to the user's device.

[1324] Input: Tailored virtual experience content.

[1325] Data processing: Data compression using compression algorithms.

[1326] Output: Compressed virtual experience content.

[1327] Step 10:

[1328] User virtual experience begins

[1329] User: Puts on the VR headset and haptic device and starts the virtual tour.

[1330] Input: Compressed virtual experience content.

[1331] Data processing: decompression and playback.

[1332] Output: Visual, tactile and audio virtual experience.

[1333] Step 11:

[1334] Collecting user interaction data

[1335] Device: Senses what the user says and does during the experience.

[1336] Input: User gestures, voice.

[1337] Data processing: Voice data is collected by a microphone, and movement data is acquired by a motion sensor.

[1338] Output: Interaction data.

[1339] Step 12:

[1340] Transmission of interaction data and emotion data

[1341] Terminal: Collected interaction data and emotion data are sent to the server in real time.

[1342] Input: interaction data, emotion data.

[1343] Data processing: data compression and transmission.

[1344] Output: Interaction and emotion data sent to the server.

[1345] Step 13:

[1346] Analysis of interaction data and emotion data and feedback generation

[1347] Server: Analyzes the received interaction data and emotion data.

[1348] Input: Submitted interaction and sentiment data.

[1349] Data processing: Real-time feedback generation based on user behavior.

[1350] Output: Feedback data sent to the user device.

[1351] (Application example 2)

[1352] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1353] While conventional virtual experience systems offer the elderly and physically challenged people the surprise and fun of traveling and shopping without leaving their homes, they have limitations in providing detailed in-store guidance and promotional information. Furthermore, they are unable to adjust content in real time based on the user's emotional state, making it difficult to improve user satisfaction and the quality of the experience.

[1354] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for acquiring user profile information, means for using sensors to collect user position information and environmental data within the physical store, and means including an emotion engine for analyzing user emotion data. This makes it possible to provide an optimal virtual guidance experience in real time based on the user's position information and emotion data, thereby improving user satisfaction.

[1355] "User profile information" is detailed personal information about the user, such as the user's health condition, sensitivities, and favorite tourist spots.

[1356] "Local environment data" refers to surrounding information such as visual data, audio data, and tactile data that exists in the actual location.

[1357] "Means for analyzing received environmental data" refers to a device or program capable of analyzing environmental data transmitted from the site and converting it into virtual experience content.

[1358] "Generated content" refers to the content of a virtual experience created for a user.

[1359] "User Device" refers to the equipment (e.g., smartphone, smart glasses, head-mounted display) used by a user to engage in a virtual experience.

[1360] "Means for providing a virtual experience" refers to technologies and devices that provide virtual experience content to users in the form of sight, touch, sound, etc.

[1361] "Interaction data" refers to information such as the actions and conversations a user makes during a virtual experience.

[1362] A "sensor" is a device for acquiring environmental data. This includes cameras, microphones, tactile sensors, etc.

[1363] An "emotion engine" is a program that recognizes and analyzes emotions from a user's facial expressions and voice.

[1364] "Promotion information" refers to information about sales and special offers taking place in stores.

[1365] "Emotion data" is data that indicates the user's emotional state analyzed by the emotion engine.

[1366] This invention is a system that allows elderly people and people with physical disabilities to virtually experience the sensation of visiting a store. The system acquires user profile information and local environmental data, analyzes the user's emotional state using an emotion engine, and customizes the virtual experience content in real time based on the analysis.

[1367] Specific processing of the program

[1368] 1. Obtaining user profile information

[1369] The server queries the database based on the user's ID and obtains the user's profile information (health status, sensitivity, favorite product categories, etc.) and uses this information to design an optimal virtual experience.

[1370] 2. Acquiring environmental data within physical stores

[1371] The device (smart glasses) collects environmental data (location information, product information, promotion information) from sensors installed in the store, including cameras, microphones, and tactile sensors.

[1372] 3. Emotion analysis using an emotion engine

[1373] The server uses the camera and microphone built into the smart glasses to analyze the user's facial expressions and voice data, which allows the emotion engine to recognize the user's emotions and capture the data in real time.

[1374] 4. Creation and transmission of virtual experience content

[1375] The server generates virtual experience content based on the acquired environmental data, the user's profile information, and emotional data, and the generated content is compressed and sent to the user's smart glasses.

[1376] 5. User Virtual Experience

[1377] While wearing the smart glasses, users can explore the physical store through virtual experience content, which includes not only sight and sound but also touch, giving them the feeling of actually visiting the store.

[1378] Hardware and software used

[1379] Hardware used

[1380] Smart glasses (general smart devices)

[1381] In-store sensors (beacons that acquire location information, cameras and microphones that collect environmental data)

[1382] Software used

[1383] Emotion engine (e.g. Emotion API)

[1384] Speech recognition algorithms (e.g., Google Cloud Speech-to-Text)

[1385] Image processing algorithms (e.g., OpenCV)

[1386] Specific Examples

[1387] For example, consider the case where an elderly person named B uses a virtual experience system without visiting a physical store. B puts on smart glasses at home and launches the corresponding application. The smart glasses receive and analyze location information, product information, and promotion information collected by sensors in the store in real time. Furthermore, emotional data from B's facial expressions and voice is analyzed, and content is customized based on the products and promotions that B is interested in.

[1388] Prompt Sentence Examples

[1389] User Profile Information:

[1390] ID: user1234

[1391] Likes: Food

[1392] Health status: No problems

[1393] Sensitivity: High

[1394] Environmental data:

[1395] Store name: Supermarket

[1396] Location: Food section

[1397] Products: Apples, bananas, oranges

[1398] Promotion: Buy one apple, get one free

[1399] Emotional Data:

[1400] Expression: Smiling

[1401] Audio: Sounds fun

[1402] By inputting such prompt sentences into a generative AI model, it is possible to generate and provide content for a virtual guidance experience that is optimal for the user.

[1403] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1404] Step 1:

[1405] The server queries the database based on the user's ID and obtains the user's profile information (health status, sensitivity, favorite product categories, etc.) and uses this information to design a virtual experience that is optimal for the user.

[1406] Input: User ID

[1407] Output: User profile information

[1408] Specific Operation: The server communicates with a database server to query for profile information associated with the user ID and stores the resulting information in an internal data store.

[1409] Step 2:

[1410] The device (smart glasses) collects environmental data (location information, product information, promotion information) from sensors installed in the store, including cameras, microphones, and tactile sensors.

[1411] Input: Local environmental data (sensor data)

[1412] Output: Collected environmental data

[1413] Specific operation: The terminal accesses the sensor network, collects data obtained from each sensor, processes it, and prepares it to be sent to the server.

[1414] Step 3:

[1415] The server receives and analyzes the environmental data sent from the device, using image processing algorithms (OpenCV) and speech recognition algorithms (Google Cloud Speech-to-Text) to analyze the data and generate virtual experience content.

[1416] Input: Collected environmental data

[1417] Output: Analysis results, virtual experience content

[1418] Specific operation: The server runs image processing algorithms and voice recognition algorithms to analyze the environmental data, and then generates virtual experience content based on it, customizing it taking into account the user's profile information.

[1419] Step 4:

[1420] The smart glasses use a built-in camera and microphone to collect facial and voice data, which is then used by the emotion engine to recognize the user's emotions.

[1421] Input: User's facial expression data, voice data

[1422] Output: Emotion data

[1423] Specific operation: The device captures the user's facial expressions and voice in real time using a camera and microphone, and sends the data to the server. The server then uses an emotion engine to analyze the data and recognize the user's emotions.

[1424] Step 5:

[1425] The server generates optimal virtual experience content based on the user's profile information, environmental data, and emotional data, compresses it, and sends it to the user's smart glasses.

[1426] Input: Profile information, environmental data, emotional data

[1427] Output: Virtual experience content

[1428] How it works: The server aggregates all data and generates optimized virtual experience content, which is then compressed and instantly sent to the device.

[1429] Step 6:

[1430] By wearing smart glasses, users can explore the store through virtual experience content, and experience the store in a realistic way through sight, sound, and touch. Interaction data collected during the experience is also sent to the server.

[1431] Input: Virtual experience content

[1432] Output: User interaction data

[1433] Specific Actions: Users use smart glasses to initiate a real-time virtual experience, and interaction data such as movements and sounds while exploring are collected and sent to the server.

[1434] Step 7:

[1435] The server analyzes the received interaction data and generates real-time feedback, which is tailored appropriately based on the user's emotions.

[1436] Input: Interaction data

[1437] Output: Feedback

[1438] Specific operation: The server analyzes the interaction data and generates feedback appropriate to the user's behavior and emotions. This feedback is sent back to the device in real time and presented to the user in an appropriate format.

[1439] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1440] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1441] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1442] [Fourth embodiment]

[1443] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1444] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1445] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1446] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1447] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1448] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1449] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1450] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1451] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1452] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1453] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1454] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1455] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1456] This is a system that provides a virtual experience for elderly people and people with disabilities, allowing them to feel like they are traveling with their family. This system acquires user profile information and achieves real-time interaction through a series of processes that receive, analyze, generate, and provide local environmental data in real time.

[1457] Natural language explanation of the program's processing

[1458] 1. Obtaining user profile information

[1459] The server retrieves the user's profile information (health status, sensitivity, favorite tourist spots, etc.) from the database.

[1460] The server uses the acquired information to design a virtual experience that suits the user's condition and preferences.

[1461] 2. Acquisition and transmission of local environmental data

[1462] The device collects local environmental data (visual, audio, tactile, etc.).

[1463] The terminal transmits this environmental data to the server in real time.

[1464] The device also obtains location information using GPS and other means and sends this information to the server.

[1465] 3. Analysis of environmental data and generation of virtual experience content

[1466] The server analyzes the received environmental data.

[1467] The server generates virtual experience content tailored to the user's profile information based on the analysis results.

[1468] The server transmits the generated content to the user's terminal.

[1469] 4. Providing virtual experiences

[1470] The user experiences the provided virtual experience content using a dedicated device (such as a VR headset or haptic device).

[1471] Users can experience the experience as if they were actually there through sight, touch, sound, etc.

[1472] 5. Collection and transmission of user interaction data

[1473] The device detects the conversations and actions the user makes during the virtual experience.

[1474] The terminal collects sensed interaction data and transmits it to a server.

[1475] 6. Real-time feedback generation

[1476] The server analyzes the user interaction data.

[1477] The server generates real-time feedback based on the analysis results and sends it to the user's device.

[1478] Feedback includes conversational responses and reactions to actions.

[1479] Specific examples

[1480] For example, consider the case where an elderly person, Mr. A, uses the system at home while his family is on a trip to a seaside resort. The family uses smartphones or dedicated devices at the destination to collect real-time environmental data, such as the sound of the ocean, the scenery, and the feel of the sand. This data is sent to a server, which then generates the most suitable virtual experience content for Mr. A based on his profile information.

[1481] By wearing a dedicated VR headset and haptic device, Mr. A can feel as if he is at a seaside resort in his own home. He can talk to his family and interact with them in real time, giving him the experience of actually traveling.

[1482] The processing flow will be explained below.

[1483] Step 1: Obtaining the user's profile information

[1484] The server queries the database based on the user's ID and obtains the user's profile information (health status, sensitivity, favorite tourist spots, etc.).

[1485] Step 2: Obtaining local environmental data

[1486] The device obtains local GPS location information.

[1487] The device collects environmental data from the local surroundings (visual data from the camera, audio data from the microphone, and tactile data from the tactile sensor).

[1488] Step 3: Sending environment data

[1489] The device compresses the collected environmental data in real time and sends it to the server.

[1490] Step 4: Parse the received data

[1491] The server analyzes the received environmental data.

[1492] The server analyzes the visual data using image processing algorithms and converts it into virtual content.

[1493] The server analyzes the voice data using a voice recognition algorithm and performs voice filtering if necessary.

[1494] The server analyzes the tactile data and converts it into signals for the haptic device.

[1495] Step 5: Generate virtual experience content

[1496] The server generates optimal virtual experience content based on the user's profile information.

[1497] The server applies data filters based on health status and sensitivity, and creates content tailored to the user's condition.

[1498] Step 6: Submit your content

[1499] The server compresses the generated virtual experience content in real time and transmits it to the user's terminal.

[1500] Step 7: Start the user's virtual experience

[1501] Users experience the virtual experience content provided through the device using a VR headset or haptic device.

[1502] The user sees visual information through a VR headset, hears audio information through headphones, and experiences tactile information through a haptic device.

[1503] Step 8: Collect interaction data

[1504] When the user talks or moves during the virtual experience, the device detects this.

[1505] The device collects voice data using a microphone and acquires movement data using a motion sensor.

[1506] Step 9: Sending interaction data

[1507] The terminal transmits the collected interaction data to the server in real time.

[1508] Step 10: Analyze interaction data and generate feedback

[1509] The server analyzes the received interaction data.

[1510] The server analyzes the user's voice data and generates an appropriate response.

[1511] The server analyzes the motion data and generates the necessary virtual interactions.

[1512] The server transmits the generated feedback to the user's terminal in real time.

[1513] Step 11: Provide real-time feedback

[1514] The user receives real-time feedback from the server during the virtual experience.

[1515] The user experiences conversational responses and reactions to actions.

[1516] Example 1

[1517] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1518] Until now, there has been no means available for elderly people and people with physical disabilities to have a real-time virtual experience that makes it seem as if they are traveling with family and friends, even when mobility is difficult. To provide a realistic experience, it is necessary to provide multiple sensory information, such as visual, tactile, and audio, in real time and provide instant feedback on the user's reactions to that information, but the specific system configuration and technical means to achieve this have not yet been established.

[1519] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1520] In this invention, the server includes means for acquiring user profile information, means for collecting local environmental data and transmitting it to the server, means for analyzing the received environmental data, means for generating virtual experience content based on the user profile information, means for transmitting the generated content to the user's device, means for providing the virtual experience on the user's device, means for collecting user interaction data during the virtual experience and transmitting it to the server, and means for analyzing the interaction data and generating feedback in real time, thereby enabling elderly people and people with disabilities to have an experience similar to a real trip in real time and interactively from a safe place such as their own home.

[1521] "Profile information" is information that indicates individual characteristics and conditions such as the user's name, age, health condition, sensitivity, favorite tourist spots, etc.

[1522] "Environmental data" refers to data that includes information about the surroundings, such as visual, audio, and tactile information of the local area.

[1523] "Virtual experience content" refers to content such as images, audio, and haptic feedback that are generated so that users can experience the same environment as they would in a real world.

[1524] "Interaction data" refers to data that indicates a user's reactions and behavior, such as the conversations and actions the user engages in during a virtual experience.

[1525] "Feedback" is data that indicates responses or reactions that are generated based on user interaction data and provided to the user in real time.

[1526] "Device" refers to the equipment used by a user to receive a virtual experience (e.g., VR headset, haptic device, etc.).

[1527] A "server" is a central computer system that receives, analyzes, and processes data sent by users, and generates and sends virtual experience content and feedback to users.

[1528] "Collection" refers to obtaining visual, audio, tactile, and other data on-site.

[1529] "Transmit" means transferring collected data to another device or computer system.

[1530] "Analysis" refers to evaluating collected data and extracting necessary information.

[1531] "Generation" means creating new content or information based on the analysis results.

[1532] This invention is a system that provides a virtual experience for elderly people and people with disabilities, allowing them to feel like they are traveling with their family. This system acquires user profile information and achieves real-time interaction through a series of processes that receive, analyze, generate, and provide local environmental data in real time.

[1533] 1. Profile information acquisition

[1534] The server retrieves the user's profile information from the database, such as the user's name, age, health status, sensitivity, favorite tourist spots, etc. This allows the server to personalize the virtual experience to suit the user's preferences and characteristics.

[1535] 2. Acquisition and transmission of local environmental data

[1536] The device (e.g., a smartphone or dedicated device) collects visual, audio, and tactile data using local environmental data (e.g., a 360-degree camera, field recorder, tactile sensor, etc.). The device transmits the collected data to a server in real time. In addition, the device obtains its location information using GPS and transmits it to the server.

[1537] 3. Analysis of environmental data and generation of virtual experience content

[1538] The server analyzes the received environmental data using data analysis software such as Python libraries (e.g., OpenCV, Librosa) and TensorFlow. Based on the analysis results, the server generates virtual experience content optimized for the user's profile information. This content is then converted into a format compatible with the user's device (e.g., VR headset, haptic device).

[1539] 4. Providing virtual experiences

[1540] Users wear a dedicated device (e.g., Oculus Quest 2, Teslasuit) to enjoy a virtual experience. Users can experience the experience as if they were actually there through sight, touch, and sound, and can converse and interact with family and friends in the location.

[1541] 5. Collection and transmission of interaction data

[1542] The conversations and actions that users make during the virtual experience are detected by the device (e.g., the built-in microphone and motion sensor of the Oculus Quest 2, or the sensor of the Teslasuit). This interaction data is sent to the server in real time.

[1543] 6. Real-time feedback generation

[1544] The server analyzes the received interaction data using natural language processing models and motion analysis algorithms (e.g., OpenAI's GPT model, PoseNet, etc.). The server generates real-time feedback based on the analysis results and sends it to the user's device. The feedback includes conversational responses and haptic feedback.

[1545] Specific examples

[1546] For example, consider the case where elderly person A uses this system at home while their family travels to a seaside resort. While at the resort, the family uses smartphones or dedicated devices (e.g., 360-degree cameras, ambient sound microphones, tactile sensors, etc.) to collect real-time environmental data, such as the sound of the ocean, the scenery, and the feel of the sand. This data is sent to a server, which then generates virtual experience content that is optimal for A based on his or her profile information.

[1547] By wearing a dedicated VR headset and haptic device, Mr. A can feel as if he is at a seaside resort in his own home. He can talk to his family and interact with them in real time, giving him the experience of actually traveling.

[1548] Prompt Sentence Examples

[1549] Below are some example prompts to give to a generative AI model (e.g., GPT-3):

[1550] Please explain a system that provides a virtual experience that allows elderly people and people with disabilities to feel like they are traveling with their families. This system acquires user profile information and performs a series of processes to receive, analyze, generate, and provide local environmental data in real time. Please explain in detail what specific hardware and software are used, how the data is processed, and how the virtual experience is provided.

[1551] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1552] Step 1:

[1553] The server retrieves the user's profile information from the database.

[1554] Specifically, the server issues SQL queries to the database to retrieve information such as the user's name, age, health status, sensitivity, and favorite tourist spots. This retrieved profile information becomes the input data for the next processing step. The output is the user's detailed information.

[1555] Step 2:

[1556] The device collects local environmental data and transmits it to a server in real time.

[1557] The terminal collects visual, audio, and tactile data using devices such as a 360-degree camera, field recorder, and tactile sensor. It also acquires location information using GPS. The input is local environmental data and location information. The acquired data is uploaded to a server via a communication line. The output is the environmental data and location information sent to the server.

[1558] Step 3:

[1559] The server analyzes the received environmental data.

[1560] Visual, audio, and haptic data is analyzed using Python libraries (e.g., OpenCV, Librosa) and TensorFlow. The results of this analysis are the basis for generating the user's virtual experience content. The input is the local environment data received by the server. The output is the analyzed environment data.

[1561] Step 4:

[1562] The server generates virtual experience content based on the analysis results.

[1563] The server creates personalized virtual experience content based on the user's profile information and analyzed environmental data. A generative AI model (e.g., TensorFlow, GANs, etc.) is used for generation. The input is the user's profile information and analyzed environmental data. The output is the virtual experience content.

[1564] Step 5:

[1565] The server transmits the generated virtual experience content to the user's device.

[1566] The generated content is converted into a format compatible with the user's VR headset or haptic device and sent to the user's device via a communication line. The input is the generated virtual experience content. The output is the content sent to the user's device.

[1567] Step 6:

[1568] Users get a virtual experience using a dedicated device.

[1569] A user wears a VR headset (e.g., Oculus Quest 2) and a haptic device (e.g., Teslasuit) to play virtual experience content. The input is the received virtual experience content. The output is feedback of the user's virtual experience.

[1570] Step 7:

[1571] The device collects local interaction data and sends it to a server.

[1572] The conversations and actions that users make during the virtual experience are collected through the built-in microphones, motion sensors, and sensors in the haptic device of the VR headset. The input is the user's interaction. The collected data is sent to the server in real time. The output is the interaction data sent to the server.

[1573] Step 8:

[1574] The server analyzes the interaction data and generates feedback in real time.

[1575] The server analyzes the interaction data using a natural language processing model (e.g., GPT model) or a motion analysis algorithm (e.g., PoseNet). The input is the transmitted interaction data. Based on the analysis results, the server generates feedback data to respond to the user in real time. The output is the generated feedback.

[1576] Step 9:

[1577] The server generates feedback and sends it to the user's device.

[1578] The feedback data is transmitted to the user's device via a communication line and provided to the user in real time. The input is the generated feedback data. The output is the real-time feedback provided to the user.

[1579] (Application example 1)

[1580] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1581] With conventional virtual experience systems, it was difficult for elderly people and people with physical disabilities to enjoy a rich shopping experience without actually going to the location. It was also difficult to provide a personalized experience that matched each user's preferences and health condition. This made it difficult to provide a satisfying virtual experience, especially for users with specific needs.

[1582] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1583] In this invention, the server includes means for acquiring user profile information, means for acquiring and transmitting local environmental data, means for analyzing the received environmental data to generate optimal virtual experience content, means for transmitting the generated content to the user's device, means for providing the virtual experience on the user's device, means for collecting and transmitting user interaction data during the virtual experience, means for analyzing the collected interaction data to generate feedback in real time, and means for customizing the shopping experience based on the user's past purchasing history, thereby enabling even elderly people and people with disabilities to enjoy a customized shopping experience in real time without having to go to the site.

[1584] The "means for acquiring user profile information" has a function for acquiring personal information such as the user's health condition, preferences, and past purchase history from a storage device such as a database.

[1585] The "means for acquiring and transmitting local environmental data" is a function that collects data necessary for the user to feel as if they are in the local area, such as local video, audio, and tactile information, and transmits this data to a server.

[1586] The "means for analyzing received environmental data and generating optimal virtual experience content" has the function of analyzing received local environmental data and generating optimized virtual experience content based on the user's profile information.

[1587] "Means for transmitting generated content to a user's device" means a function that transmits the generated virtual experience content to a user's device, such as a VR headset or smart glasses.

[1588] "Means for providing a virtual experience on a user's device" means a function that provides the generated virtual experience content to the user through the user's device, allowing the user to experience it through sight, touch, sound, etc.

[1589] "Means for collecting and transmitting user interaction data during a virtual experience" refers to a device that has the function of collecting interaction data such as the user's actions and conversations during the virtual experience and transmitting it to a server.

[1590] The "means for analyzing collected interaction data and generating feedback in real time" has the function of analyzing collected user interaction data and generating feedback on user actions in real time.

[1591] "Means for customizing a shopping experience based on a user's past purchasing history" refers to a function that customizes virtual experience content based on the user's past purchasing history information in order to provide the optimal shopping experience tailored to the user's preferences.

[1592] This invention provides a virtual experience system that allows elderly people and people with physical disabilities to enjoy a rich shopping experience from home. The system is configured to provide a personalized experience by utilizing the user's personal information, preferences, and past purchasing history.

[1593] 1. Obtaining user profile information

[1594] The server retrieves the user's profile information (health status, preferences, past purchase history, etc.) from the database, which is then used to optimize the virtual shopping experience for the individual user.

[1595] 2. Acquisition and transmission of local environmental data

[1596] Devices (e.g., smartphones or smart glasses) collect environmental data such as video, audio, and detailed product information in real time within a local store. This data is then sent from the local store to a server. The devices are equipped with cameras, microphones, sensors, etc., and have a communication module for transmitting this data in real time.

[1597] 3. Analysis of environmental data and generation of virtual experience content

[1598] The server analyzes the received environmental data and works with a generative AI model to generate optimal virtual shopping experience content based on the user's profile information. This analysis utilizes cloud services such as computer vision APIs (e.g., Amazon Rekognition) and natural language processing models (e.g., Google Cloud Speech-to-Text).

[1599] 4. Providing virtual experiences

[1600] The generated virtual experience content is sent to the user's device (e.g., VR headset or smart glasses). By wearing these devices, the user can experience walking through the virtual store and picking up products through sight, touch, and sound.

[1601] 5. Collection and transmission of user interaction data

[1602] Interaction data, such as conversations and actions that users make during the virtual experience, is sensed and collected by the device, and the collected data is sent to a server.

[1603] 6. Real-time feedback generation

[1604] The server analyzes the collected interaction data, generates feedback in real time, and sends it to the user's device, providing instant feedback on the user's actions and providing a simulated experience that makes the user feel as if they are actually in the store.

[1605] Specific examples

[1606] For example, an elderly user can use the system at home, while a local store staff member uses a terminal to transmit video and audio from the store in real time. The user can then enjoy a personalized shopping experience based on their profile information and past purchase history through a VR headset or smart glasses.

[1607] Examples of prompt statements

[1608] "Generate a virtual store experience tailored to the user's preferences. User information: {Name: 'Jiro Taguchi', Age: 75, Preferences: ['Clothing', 'Electronics']}, Current Store Labels: ['Laptop', 'Smartphone']"

[1609] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1610] Step 1:

[1611] The server retrieves the user's profile information from the database. The retrieved information includes the user's health condition, preferences, past purchase history, etc. The input is identification information such as the user ID, and the output is the user's detailed profile information. This information is retrieved using a database access API.

[1612] Step 2:

[1613] The terminal acquires local environmental data in real time and sends it to the server. The environmental data includes video, audio, and detailed product information from within the store. The terminal collects data using cameras and microphones and sends it through a communications module. The input is sensor data from the cameras and microphones, and the output is data sent to the server.

[1614] Step 3:

[1615] The server analyzes the received local environmental data and generates virtual experience content. The server processes the data using computer vision APIs (e.g., Amazon Rekognition) and natural language processing models (e.g., Google Cloud Speech-to-Text). The input is the received environmental data and user profile information, and the output is the generated virtual experience content.

[1616] Step 4:

[1617] The server generates virtual experience content and sends it to the user's device, which can be a VR headset or smart glasses. The input is the generated virtual experience content, and the output is the data sent to the user's device.

[1618] Step 5:

[1619] The user's device plays the virtual experience content and provides the user with the experience through sight, touch, and sound. The device can be a VR headset or smart glasses, with the input being the transmitted virtual experience content and the output being the user's virtual experience.

[1620] Step 6:

[1621] The device collects interaction data of the user during the virtual experience and sends it to the server. The interaction data includes the user's actions and conversations. The input is the data of the user's actions and speech, and the output is the data sent to the server.

[1622] Step 7:

[1623] The server analyzes the collected interaction data and generates feedback in real time. The server uses a generative AI model to analyze and generate feedback according to the user's actions. The input is the sent interaction data, and the output is the generated feedback data.

[1624] Step 8:

[1625] The server generates feedback and sends it to the user's device, providing it to the user in real time. The feedback includes immediate reactions to the product and additional information. The input is the generated feedback data, and the output is the data sent to the user's device.

[1626] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1627] This system provides a virtual experience for elderly people and people with disabilities, allowing them to feel like they are traveling with their families. This system acquires user profile information and processes a series of processes that receive, analyze, generate, and provide local environmental data in real time. It also includes an emotion engine that recognizes user emotions and adjusts content and provides feedback based on those emotions.

[1628] Natural language explanation of the program's processing

[1629] 1. Obtaining user profile information

[1630] The server queries the database based on the user's ID and obtains the user's profile information (health status, sensitivity, favorite tourist spots, etc.).

[1631] The server uses the acquired information to design a virtual experience that suits the user's condition and preferences.

[1632] 2. Acquisition and transmission of local environmental data

[1633] The device obtains local GPS location information.

[1634] The device collects environmental data from the local surroundings (visual data from the camera, audio data from the microphone, and tactile data from the tactile sensor).

[1635] 3. Sending environmental data

[1636] The device compresses the collected environmental data in real time and sends it to the server.

[1637] 4. Analysis of received data

[1638] The server analyzes the received environmental data.

[1639] The server analyzes the visual data using image processing algorithms and converts it into virtual content.

[1640] The server analyzes the voice data using a voice recognition algorithm and performs voice filtering if necessary.

[1641] The server analyzes the tactile data and converts it into signals for the haptic device.

[1642] 5. Creation of virtual experience content

[1643] The server generates optimal virtual experience content based on the user's profile information.

[1644] The server applies data filters based on health status and sensitivity, and creates content tailored to the user's condition.

[1645] 6. Operation of the Emotion Engine

[1646] The server uses an emotion engine to recognize emotions from the user's facial expressions and voice analysis.

[1647] The server uses an emotion engine to adjust the content of the virtual experience based on the user's emotions.

[1648] 7. Submission of Content

[1649] The server compresses the generated virtual experience content in real time and transmits it to the user's terminal.

[1650] 8. User begins virtual experience

[1651] Users experience the virtual experience content provided through the device using a VR headset or haptic device.

[1652] Users can experience the experience as if they were actually there through sight, touch, sound, etc.

[1653] 9. Collection and transmission of user interaction data

[1654] When the user talks or moves during the virtual experience, the device detects this.

[1655] The device collects voice data using a microphone and acquires movement data using a motion sensor.

[1656] The emotion engine extracts the user's emotions from these data.

[1657] 10. Transmission of Interaction and Emotion Data

[1658] The device transmits the collected interaction data and emotion data to a server in real time.

[1659] 11. Analysis of interaction and emotion data and feedback generation

[1660] The server analyzes the received interaction data and emotion data.

[1661] The server generates feedback in real time based on the user's emotions and transmits it to the user's terminal.

[1662] Feedback includes conversational responses and behavioral reactions, with appropriate emotional adjustments.

[1663] Specific examples

[1664] For example, consider the case where an elderly person, Mr. A, uses the system at home while his family is on a trip to a seaside resort. The family uses smartphones or dedicated devices at the destination to collect real-time environmental data, such as the sound of the ocean, the scenery, and the feel of the sand. This data is sent to a server, which then generates the most suitable virtual experience content for Mr. A based on his profile information.

[1665] By wearing a dedicated VR headset and haptic devices, Mr. A can feel as if he is at a seaside resort in his own home. He can converse with his family and interact with them in real time, giving him the experience of actually traveling. Furthermore, the emotion engine recognizes Mr. A's emotions and adjusts the content and feedback in real time, giving him a deeper sense of satisfaction.

[1666] The processing flow will be explained below.

[1667] Step 1: Obtaining the user's profile information

[1668] The server queries the database based on the user's ID and obtains the user's profile information (health status, sensitivity, favorite tourist spots, etc.).

[1669] Step 2: Obtaining local environmental data

[1670] The device obtains local GPS location information.

[1671] The device collects environmental data from the local surroundings (visual data from the camera, audio data from the microphone, and tactile data from the tactile sensor).

[1672] Step 3: Sending environment data

[1673] The device compresses the collected environmental data in real time and sends it to the server.

[1674] Step 4: Parse the received data

[1675] The server analyzes the received environmental data.

[1676] The server analyzes the visual data using image processing algorithms and converts it into virtual content.

[1677] The server analyzes the voice data using a voice recognition algorithm and performs voice filtering if necessary.

[1678] The server analyzes the tactile data and converts it into signals for the haptic device.

[1679] Step 5: Generate virtual experience content

[1680] The server generates optimal virtual experience content based on the user's profile information.

[1681] The server applies data filters based on health status and sensitivity, and creates content tailored to the user's condition.

[1682] Step 6: Emotion Engine in Action

[1683] The server uses an emotion engine to recognize emotions from the user's facial expressions and voice analysis.

[1684] The server uses an emotion engine to adjust the content of the virtual experience based on the user's emotions.

[1685] Step 7: Submit your content

[1686] The server compresses the generated virtual experience content in real time and transmits it to the user's terminal.

[1687] Step 8: Start the user's virtual experience

[1688] Users experience the virtual experience content provided through the device using a VR headset or haptic device.

[1689] Users can experience the experience as if they were actually there through sight, touch, sound, etc.

[1690] Step 9: Collecting and sending user interaction data

[1691] When the user talks or moves during the virtual experience, the device detects this.

[1692] The device collects voice data using a microphone and acquires movement data using a motion sensor.

[1693] The emotion engine extracts the user's emotions from these data.

[1694] Step 10: Sending interaction and emotion data

[1695] The device transmits the collected interaction data and emotion data to a server in real time.

[1696] Step 11: Analyze interaction and emotion data and generate feedback

[1697] The server analyzes the received interaction data and emotion data.

[1698] The server analyzes the user's voice data and generates an appropriate response.

[1699] The server analyzes the motion data and generates the necessary virtual interactions.

[1700] The server analyzes the emotion data and generates feedback based on the user's emotion.

[1701] Step 12: Provide real-time feedback

[1702] The user receives real-time feedback from the server during the virtual experience.

[1703] The user experiences reactions to conversational responses and actions, and appropriate adjustments are made to match their emotions.

[1704] Example 2

[1705] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1706] The purpose of this invention is to provide optimal content in real time that is tailored to the health and emotions of each individual user, especially when elderly people and people with physical disabilities experience local travel through virtual reality. Conventional systems have had problems such as difficulty in generating virtual experience content that takes into account the individual emotions and health of the user, and a lack of emotional feedback.

[1707] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1708] a means for obtaining user profile information;

[1709] means for acquiring and transmitting local environmental data (visual, audio, tactile);

[1710] A means for analyzing the received environmental data and generating optimal virtual experience content;

[1711] means for transmitting the generated content to a user's device;

[1712] means for recognizing a user's emotion and adjusting the virtual experience content accordingly;

[1713] This enables an optimal virtual local travel experience that takes into account the user's health condition and emotions in real time.

[1714] "User profile information" is information that indicates the user's individual attributes and preferences, such as their health condition, sensitivity, and favorite tourist spots.

[1715] "Local environment data" refers to local visual data, audio data, and tactile data, which is real-time environmental information for the user to experience.

[1716] "Visual data" refers to on-site video information captured by a camera.

[1717] "Audio data" refers to local acoustic information collected by microphones.

[1718] "Tactile data" refers to local texture and vibration information obtained by tactile sensors.

[1719] "Interaction Data" refers to data about the conversations and actions a user makes during a virtual experience.

[1720] "Emotion" is information that represents the mental state of the user, which is recognized by analyzing the user's facial expressions, voice, and the like.

[1721] "Feedback" refers to responses and adjustments generated in real time based on user interaction data and emotions.

[1722] "Virtual experience content" refers to virtual reality content that combines visual, audio, and tactile information generated for a user to experience.

[1723] An "emotion engine" is an algorithm and software that analyzes a user's facial expressions and voice to recognize emotions and adjust the experience.

[1724] "Health condition" is information indicating the physical health condition of the user, and may include symptoms such as high blood pressure and diabetes.

[1725] "Data filter" refers to the algorithms and processes used to adjust collected environmental data according to the user's condition and sensitivity.

[1726] "Virtual experience" refers to a virtual reality experience that a user experiences using a VR headset or haptic device.

[1727] This system provides a virtual experience for elderly people and people with disabilities, allowing them to feel like they are traveling with their families. This system acquires user profile information and performs a series of processes to receive, analyze, generate, and provide local environmental data in real time. It also includes an emotion engine that recognizes user emotions and adjusts content and provides feedback based on those emotions.

[1728] The system consists of a database that records user profile information, a terminal for acquiring local environmental data, a server that analyzes the data and generates virtual experience content, a communication means for sending the generated content to the user's device, and devices such as a VR headset and haptic device that allow the user to experience the experience.

[1729] Program processing explanation

[1730] The program processing of this system will be specifically explained below.

[1731] First, the server queries the database based on the user's ID to obtain the user's profile information (e.g., health status, sensitivity, favorite tourist spots, etc.) The database that can be used may be, for example, an SQL-based database or a NoSQL type.

[1732] The device then uses a smartphone or dedicated device on-site to acquire GPS location information, and uses a camera on-site to collect visual data, a microphone to collect audio data, and a tactile sensor to record tactile data.

[1733] These environmental data are compressed in real time on the device and sent to the server using commonly used compression algorithms (e.g., Gzip, LZ4, etc.).

[1734] The server analyzes the received environmental data. Visual data is analyzed using image processing libraries such as OpenCV and converted into virtual content. Audio data is analyzed using speech recognition algorithms such as the Google Speech-to-Text API, and noise reduction and filtering are performed as needed. Haptic data is converted into signals for haptic feedback devices.

[1735] The server generates optimal virtual experience content based on the user's profile information, applying data filters based on health conditions and sensitivities (e.g., adjusting the tempo of the music to provide a gentler experience for a user with high blood pressure).

[1736] The server's emotion engine then recognizes the user's emotions from facial and voice analysis. This emotion engine uses machine learning models trained with TensorFlow or PyTorch, for example. The server then adjusts the content of the virtual experience in real time based on the user's emotions. This could include adding relaxing elements if the user is excited.

[1737] The generated virtual experience content is compressed and sent from the server to the user's device, where the user can use a VR headset or haptic device to experience the experience through sight, touch, sound, and more, as if they were actually there.

[1738] The conversations and actions that users make during the virtual experience are detected by the device, with voice data collected by a microphone and movement data captured by a motion sensor. This interaction data is sent to the server in real time, where the server's emotion engine analyzes the data and extracts the user's emotions.

[1739] The server analyzes the received interaction data and emotion data and generates feedback based on the user's emotion, which is sent to the user's device and displayed, for example, as a voice response or appropriate adjustment to behavior.

[1740] Specific examples

[1741] For example, consider the case where an elderly person, Mr. A, uses the system at home while his family is on a trip to a seaside resort. The family uses smartphones or dedicated devices at the destination to collect environmental data in real time, such as the sound of the ocean, the scenery, and the feel of the sand, and sends this data to the server. The server then generates virtual experience content that is optimal for Mr. A based on his profile information.

[1742] By wearing a dedicated VR headset and haptic device, A can feel as if he is at a seaside resort from the comfort of his own home. He can hear the sound of the ocean waves, enjoy the scenery with his eyes, and feel the texture of the sand with his hands. Furthermore, the emotion engine recognizes A's emotions and adjusts the content and feedback in real time, giving him a deeper sense of satisfaction.

[1743] Prompt Sentence Examples

[1744] Here are some examples of prompts for generative AI models:

[1745] Describe a scenario in detail where an elderly user would use a virtual experience system at home. Explain how the system connects with tourist attractions the family member is actually visiting and provides the user with the most appropriate virtual experience based on their profile information. This process includes real-time feedback from an emotion engine.

[1746] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1747] Step 1:

[1748] Obtaining user profile information

[1749] Server: Queries the database based on the user's ID and obtains the user's profile information (health status, sensitivity, favorite tourist spots, etc.).

[1750] Input: User ID.

[1751] Data processing: Profile information was obtained through database queries.

[1752] Output: User profile information (e.g., A's health condition, high blood pressure, favorite tourist destination is Kyoto).

[1753] Step 2:

[1754] Acquisition of local environmental data

[1755] Device: Use a smartphone or dedicated device on-site to obtain GPS location information.

[1756] Input: GPS signal.

[1757] Data processing: Obtain GPS location information.

[1758] Output: GPS location (e.g. Gion, Kyoto).

[1759] Step 3:

[1760] Environmental data collection

[1761] Device: The camera captures the scenery, the microphone collects surrounding sounds, and the tactile sensor records the feel of the sand on the beach.

[1762] Input: Local environment.

[1763] Data processing: visual data (camera footage), audio data (microphone recording), tactile data (sensor recording).

[1764] Output: Local environment data (e.g., Gion landscape images, audio, tactile data).

[1765] Step 4:

[1766] Sending environmental data

[1767] Terminal: Compresses collected environmental data in real time and sends it to the server.

[1768] Input: Local environmental data (visual, audio, tactile).

[1769] Data processing: Compressing data using a compression algorithm (e.g. Gzip).

[1770] Output: Compressed environment data.

[1771] Step 5:

[1772] Analyzing received data

[1773] Server: Analyzes the received environmental data.

[1774] Input: Compressed environment data.

[1775] Data processing: Decompressing compressed data, analyzing visual data with an image processing library (e.g., OpenCV), analyzing audio data with a speech recognition algorithm (e.g., Google Speech-to-Text), and converting haptic data for use with the feedback device.

[1776] Output: Parsed environmental data.

[1777] Step 6:

[1778] Creation of virtual experience content

[1779] Server: Generates optimal virtual experience content based on the user's profile information.

[1780] Input: Parsed environmental data, user profile information.

[1781] Data processing: Applying data filters tailored to profile information (e.g., providing a gentler experience for users with high blood pressure).

[1782] Output: Virtual experience content.

[1783] Step 7:

[1784] Emotion Engine Operation

[1785] Server: Recognizes emotions from the user's facial expressions and voice analysis using an emotion engine.

[1786] Input: User's facial expression data, voice data.

[1787] Data processing: Analyze sentiment using machine learning models (e.g., TensorFlow, PyTorch).

[1788] Output: Recognized emotion data.

[1789] Step 8:

[1790] Emotion-based content adjustment

[1791] Server: Adjusts the virtual experience content in real time based on the user's emotions.

[1792] Input: Recognized emotion data, virtual experience content.

[1793] Data manipulation: Adjusting content (e.g., if the user is excited, adding elements that have a calming effect).

[1794] Output: Tailored virtual experience content.

[1795] Step 9:

[1796] Submitting content

[1797] Server: Compresses the tailored virtual experience content in real time and sends it to the user's device.

[1798] Input: Tailored virtual experience content.

[1799] Data processing: Data compression using compression algorithms.

[1800] Output: Compressed virtual experience content.

[1801] Step 10:

[1802] User virtual experience begins

[1803] User: Puts on the VR headset and haptic device and starts the virtual tour.

[1804] Input: Compressed virtual experience content.

[1805] Data processing: decompression and playback.

[1806] Output: Visual, tactile and audio virtual experience.

[1807] Step 11:

[1808] Collecting user interaction data

[1809] Device: Senses what the user says and does during the experience.

[1810] Input: User gestures, voice.

[1811] Data processing: Voice data is collected by a microphone, and movement data is acquired by a motion sensor.

[1812] Output: Interaction data.

[1813] Step 12:

[1814] Transmission of interaction data and emotion data

[1815] Terminal: Collected interaction data and emotion data are sent to the server in real time.

[1816] Input: interaction data, emotion data.

[1817] Data processing: data compression and transmission.

[1818] Output: Interaction and emotion data sent to the server.

[1819] Step 13:

[1820] Analysis of interaction data and emotion data and feedback generation

[1821] Server: Analyzes the received interaction data and emotion data.

[1822] Input: Submitted interaction and sentiment data.

[1823] Data processing: Real-time feedback generation based on user behavior.

[1824] Output: Feedback data sent to the user device.

[1825] (Application example 2)

[1826] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1827] While conventional virtual experience systems offer the elderly and physically challenged people the surprise and fun of traveling and shopping without leaving their homes, they have limitations in providing detailed in-store guidance and promotional information. Furthermore, they are unable to adjust content in real time based on the user's emotional state, making it difficult to improve user satisfaction and the quality of the experience.

[1828] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for acquiring user profile information, means for using sensors to collect user position information and environmental data within the physical store, and means including an emotion engine for analyzing user emotion data. This makes it possible to provide an optimal virtual guidance experience in real time based on the user's position information and emotion data, thereby improving user satisfaction.

[1829] "User profile information" is detailed personal information about the user, such as the user's health condition, sensitivities, and favorite tourist spots.

[1830] "Local environment data" refers to surrounding information such as visual data, audio data, and tactile data that exists in the actual location.

[1831] "Means for analyzing received environmental data" refers to a device or program capable of analyzing environmental data transmitted from the site and converting it into virtual experience content.

[1832] "Generated content" refers to the content of a virtual experience created for a user.

[1833] "User Device" refers to the equipment (e.g., smartphone, smart glasses, head-mounted display) used by a user to engage in a virtual experience.

[1834] "Means for providing a virtual experience" refers to technologies and devices that provide virtual experience content to users in the form of sight, touch, sound, etc.

[1835] "Interaction data" refers to information such as the actions and conversations a user makes during a virtual experience.

[1836] A "sensor" is a device for acquiring environmental data. This includes cameras, microphones, tactile sensors, etc.

[1837] An "emotion engine" is a program that recognizes and analyzes emotions from a user's facial expressions and voice.

[1838] "Promotion information" refers to information about sales and special offers taking place in stores.

[1839] "Emotion data" is data that indicates the user's emotional state analyzed by the emotion engine.

[1840] This invention is a system that allows elderly people and people with physical disabilities to virtually experience the sensation of visiting a store. The system acquires user profile information and local environmental data, analyzes the user's emotional state using an emotion engine, and customizes the virtual experience content in real time based on the analysis.

[1841] Specific processing of the program

[1842] 1. Obtaining user profile information

[1843] The server queries the database based on the user's ID and obtains the user's profile information (health status, sensitivity, favorite product categories, etc.) and uses this information to design an optimal virtual experience.

[1844] 2. Acquiring environmental data within physical stores

[1845] The device (smart glasses) collects environmental data (location information, product information, promotion information) from sensors installed in the store, including cameras, microphones, and tactile sensors.

[1846] 3. Emotion analysis using an emotion engine

[1847] The server uses the camera and microphone built into the smart glasses to analyze the user's facial expressions and voice data, which allows the emotion engine to recognize the user's emotions and capture the data in real time.

[1848] 4. Creation and transmission of virtual experience content

[1849] The server generates virtual experience content based on the acquired environmental data, the user's profile information, and emotional data, and the generated content is compressed and sent to the user's smart glasses.

[1850] 5. User Virtual Experience

[1851] While wearing the smart glasses, users can explore the physical store through virtual experience content, which includes not only sight and sound but also touch, giving them the feeling of actually visiting the store.

[1852] Hardware and software used

[1853] Hardware used

[1854] Smart glasses (general smart devices)

[1855] In-store sensors (beacons that acquire location information, cameras and microphones that collect environmental data)

[1856] Software used

[1857] Emotion engine (e.g. Emotion API)

[1858] Speech recognition algorithms (e.g., Google Cloud Speech-to-Text)

[1859] Image processing algorithms (e.g., OpenCV)

[1860] Specific Examples

[1861] For example, consider the case where an elderly person named B uses a virtual experience system without visiting a physical store. B puts on smart glasses at home and launches the corresponding application. The smart glasses receive and analyze location information, product information, and promotion information collected by sensors in the store in real time. Furthermore, emotional data from B's facial expressions and voice is analyzed, and content is customized based on the products and promotions that B is interested in.

[1862] Prompt Sentence Examples

[1863] User Profile Information:

[1864] ID: user1234

[1865] Likes: Food

[1866] Health status: No problems

[1867] Sensitivity: High

[1868] Environmental data:

[1869] Store name: Supermarket

[1870] Location: Food section

[1871] Products: Apples, bananas, oranges

[1872] Promotion: Buy one apple, get one free

[1873] Emotional Data:

[1874] Expression: Smiling

[1875] Audio: Sounds fun

[1876] By inputting such prompt sentences into a generative AI model, it is possible to generate and provide content for a virtual guidance experience that is optimal for the user.

[1877] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1878] Step 1:

[1879] The server queries the database based on the user's ID and obtains the user's profile information (health status, sensitivity, favorite product categories, etc.) and uses this information to design a virtual experience that is optimal for the user.

[1880] Input: User ID

[1881] Output: User profile information

[1882] Specific Operation: The server communicates with a database server to query for profile information associated with the user ID and stores the resulting information in an internal data store.

[1883] Step 2:

[1884] The device (smart glasses) collects environmental data (location information, product information, promotion information) from sensors installed in the store, including cameras, microphones, and tactile sensors.

[1885] Input: Local environmental data (sensor data)

[1886] Output: Collected environmental data

[1887] Specific operation: The terminal accesses the sensor network, collects data obtained from each sensor, processes it, and prepares it to be sent to the server.

[1888] Step 3:

[1889] The server receives and analyzes the environmental data sent from the device, using image processing algorithms (OpenCV) and speech recognition algorithms (Google Cloud Speech-to-Text) to analyze the data and generate virtual experience content.

[1890] Input: Collected environmental data

[1891] Output: Analysis results, virtual experience content

[1892] Specific operation: The server runs image processing algorithms and voice recognition algorithms to analyze the environmental data, and then generates virtual experience content based on it, customizing it taking into account the user's profile information.

[1893] Step 4:

[1894] The smart glasses use a built-in camera and microphone to collect facial and voice data, which is then used by the emotion engine to recognize the user's emotions.

[1895] Input: User's facial expression data, voice data

[1896] Output: Emotion data

[1897] Specific operation: The device captures the user's facial expressions and voice in real time using a camera and microphone, and sends the data to the server. The server then uses an emotion engine to analyze the data and recognize the user's emotions.

[1898] Step 5:

[1899] The server generates optimal virtual experience content based on the user's profile information, environmental data, and emotional data, compresses it, and sends it to the user's smart glasses.

[1900] Input: Profile information, environmental data, emotional data

[1901] Output: Virtual experience content

[1902] How it works: The server aggregates all data and generates optimized virtual experience content, which is then compressed and instantly sent to the device.

[1903] Step 6:

[1904] By wearing smart glasses, users can explore the store through virtual experience content, and experience the store in a realistic way through sight, sound, and touch. Interaction data collected during the experience is also sent to the server.

[1905] Input: Virtual experience content

[1906] Output: User interaction data

[1907] Specific Actions: Users use smart glasses to initiate a real-time virtual experience, and interaction data such as movements and sounds while exploring are collected and sent to the server.

[1908] Step 7:

[1909] The server analyzes the received interaction data and generates real-time feedback, which is tailored appropriately based on the user's emotions.

[1910] Input: Interaction data

[1911] Output: Feedback

[1912] Specific operation: The server analyzes the interaction data and generates feedback appropriate to the user's behavior and emotions. This feedback is sent back to the device in real time and presented to the user in an appropriate format.

[1913] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1914] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1915] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1916] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1917] FIG. 9 illustrates an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and behaviors arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1918] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1919] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1920] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1921] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1922] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1923] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1924] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1925] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1926] 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.

[1927] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1928] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1929] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1930] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1931] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1932] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1933] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1934] The following is further disclosed regarding the above embodiment.

[1935] (Claim 1)

[1936] a means for obtaining user profile information;

[1937] a means for acquiring and transmitting local environmental data;

[1938] A means for analyzing the received environmental data and generating optimal virtual experience content;

[1939] means for transmitting the generated content to a user's device;

[1940] a means for providing a virtual experience on a user's device;

[1941] means for collecting and transmitting user interaction data during the virtual experience;

[1942] A means of analyzing interaction data to generate feedback in real time;

[1943] A system including:

[1944] (Claim 2)

[1945] 10. The system of claim 1, further comprising means for providing the user with multiple types of sensory information (visual, tactile, audio).

[1946] (Claim 3)

[1947] 10. The system of claim 1, further comprising means for customizing virtual experience content based on a user's health and sensitivity information.

[1948] "Example 1"

[1949] (Claim 1)

[1950] a means for obtaining user profile information;

[1951] means for collecting local environmental data and transmitting the data to a server;

[1952] means for analyzing the received environmental data;

[1953] means for generating virtual experience content based on the user's profile information;

[1954] means for transmitting the generated content to a user's device;

[1955] a means for providing a virtual experience on a user's device;

[1956] means for collecting and transmitting user interaction data during the virtual experience to a server;

[1957] A means of analyzing interaction data to generate feedback in real time;

[1958] A system including:

[1959] (Claim 2)

[1960] 10. The system of claim 1, further comprising means for providing the user with multiple types of sensory information (visual, tactile, audio).

[1961] (Claim 3)

[1962] 10. The system of claim 1, further comprising means for customizing virtual experience content based on a user's health and sensitivity information.

[1963] "Application Example 1"

[1964] (Claim 1)

[1965] a means for obtaining user profile information;

[1966] a means for acquiring and transmitting local environmental data;

[1967] A means for analyzing the received environmental data and generating optimal virtual experience content;

[1968] means for transmitting the generated content to a user's device;

[1969] a means for providing a virtual experience on a user's device;

[1970] means for collecting and transmitting user interaction data during the virtual experience;

[1971] A means of analyzing the collected interaction data to generate feedback in real time;

[1972] A means to customize the shopping experience based on a user's past purchasing history;

[1973] A system including:

[1974] (Claim 2)

[1975] 10. The system of claim 1, further comprising means for providing the user with multiple types of sensory information (visual, tactile, audio).

[1976] (Claim 3)

[1977] 10. The system of claim 1, further comprising means for customizing virtual experience content based on a user's health status and sensitivity information and past purchasing history.

[1978] "Example 2: Combining Emotion Engines"

[1979] (Claim 1)

[1980] a means for obtaining user profile information;

[1981] means for acquiring and transmitting local environmental data (visual, audio, tactile);

[1982] A means for analyzing the received environmental data and generating optimal virtual experience content;

[1983] means for transmitting the generated content to a user's device;

[1984] a means for providing a virtual experience on a user's device;

[1985] means for collecting and transmitting user interaction data during the virtual experience;

[1986] a means of analyzing interaction data to generate feedback in real time;

[1987] means for recognizing a user's emotion and adjusting the virtual experience content accordingly;

[1988] A system including:

[1989] (Claim 2)

[1990] 10. The system of claim 1, further comprising means for providing the user with multiple types of sensory information (visual, tactile, audio).

[1991] (Claim 3)

[1992] 10. The system of claim 1, further comprising means for customizing virtual experience content based on a user's health and sensitivity information.

[1993] "Application example 2 when combining emotion engines"

[1994] (Claim 1)

[1995] a means for obtaining user profile information;

[1996] a means for acquiring and transmitting local environmental data;

[1997] A means for analyzing the received environmental data and generating optimal virtual experience content;

[1998] means for transmitting the generated content to a user's device;

[1999] a means for providing a virtual experience on a user's device;

[2000] means for collecting and transmitting user interaction data during the virtual experience;

[2001] a means of analyzing interaction data to generate feedback in real time;

[2002] A means of using sensors to collect user location and environmental data within a physical store;

[2003] means including an emotion engine for analyzing emotion data of a user;

[2004] A system including:

[2005] (Claim 2)

[2006] means for providing the user with multiple sensory information (visual, tactile, audio);

[2007] 10. The system of claim 1, further comprising means for adjusting content in real time based on user emotion data.

[2008] (Claim 3)

[2009] a means for customizing the virtual experience content based on the user's health status and sensitivity information;

[2010] 10. The system of claim 1, further comprising means for displaying in-store promotional information in real time. [Explanation of symbols]

[2011] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. a means for obtaining user profile information; a means for acquiring and transmitting local environmental data; A means for analyzing the received environmental data and generating optimal virtual experience content; means for transmitting the generated content to a user's device; a means for providing a virtual experience on a user's device; means for collecting and transmitting user interaction data during the virtual experience; a means of analyzing interaction data to generate feedback in real time; A system including:

2. 10. The system of claim 1, further comprising means for providing multiple types of sensory information to the user.

3. The system of claim 1 , further comprising means for customizing virtual experience content based on the user's health and sensitivity information.

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