System

Abstract

A system is provided.SOLUTION: A wearable device including a camera device, the system including means for capturing image data, means including a position information acquisition device, communication means for transmitting the captured image data and position information to a server, means for analyzing the image data received by the server and recognizing a specific object, means for generating information related to the recognized object, and display means for receiving the generated information and displaying the information superimposed on a field of view of a user.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] Existing wearable devices and AR systems only provide limited means for users to obtain real-time information from objects they see, making it difficult to provide information tailored to individual interests. Furthermore, information acquisition is often done manually, requiring cumbersome operations, resulting in a lack of user convenience. It is particularly difficult to instantly obtain detailed information about unknown locations or new stores, which tends to result in a poor user experience. Even in business settings, it is difficult to efficiently obtain information and carry out work. [Means for solving the problem]

[0005] The present invention provides a wearable device system including a camera device, a means for capturing image data, a means for acquiring location information, a communication means for transmitting the captured image data and location information to a server, a means for analyzing the image data received by the server and recognizing a specific object, a means for generating information related to the recognized object, and a display means for receiving the generated information and displaying it superimposed on the user's field of view. Furthermore, by including a means for storing user profile information, the generated information can be personalized based on the user's profile information, allowing for real-time provision of information tailored to individual interests. This eliminates the complexity of operations, improves the user experience, and enables efficient information acquisition and business operations.

[0006] A "camera device" is an electronic device equipped with an optical sensor for capturing visual data.

[0007] A "wearable device" is an information processing device that is provided in a form that can be worn by a user.

[0008] "Image data" refers to digital data used to electronically store and process visual information.

[0009] A "location information acquisition device" is a device that uses technology such as GPS to identify a physical location.

[0010] A "communication tool" is a technology or device for sending or receiving data to another device or system.

[0011] A "server" is a computer system that provides data storage, management, and processing over a network.

[0012] "Analysis" is the process of interpreting received data and converting it into meaningful information.

[0013] An "object" is a particular subject or region within image data.

[0014] "Recognition" is the process of identifying specific objects from the analyzed data.

[0015] "Generation" is the process of creating or forming new information.

[0016] "Display means" refers to technology such as a screen or projector for visually presenting information.

[0017] "Profile information" is information that includes a user's personal information and past data.

[0018] "Personalization" means customizing to suit the preferences and needs of a particular user. [Brief explanation of the drawings]

[0019] [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

[0020] 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.

[0021] First, the terms used in the following description will be explained.

[0022] 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).

[0023] 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.

[0024] 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.

[0025] 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.

[0026] 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."

[0027] [First embodiment]

[0028] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0029] 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.

[0030] 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).

[0031] 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.

[0032] 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.

[0033] 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.

[0034] 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.

[0035] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0036] 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.

[0037] 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.

[0038] 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.

[0039] 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."

[0040] This invention is a system that uses a wearable device including a camera to analyze image data and location information in real time and provide personalized information to users. This system is mainly composed of three elements: the user, the terminal (wearable device), and the server.

[0041] System Configuration

[0042] 1. Users

[0043] Users wear wearable devices (hereafter referred to as smart glasses) while walking around town or working. User profile information is shared between the smart glasses and a server, and the user's past usage history and interests are stored.

[0044] 2. Device (smart glasses)

[0045] The smart glasses have the following features:

[0046] 1. Camera equipment

[0047] Capture the surrounding scenery and save it as image data.

[0048] 2. Location information acquisition device

[0049] Use GPS to determine the user's current location.

[0050] 3. Means of communication

[0051] Image data and location information are sent to the server.

[0052] 4. Display means

[0053] The information received from the server is displayed superimposed on the user's field of view.

[0054] 3. Server

[0055] The server performs the following process.

[0056] 1. Data Reception

[0057] Receive image data and location information transmitted from the smart glasses.

[0058] 2. Image Analysis

[0059] Use image recognition AI to identify objects in image data.

[0060] 3. Information generation

[0061] Information related to the recognized object is obtained from the LY database and GTP database, and information is generated using generation AI.

[0062] 4. Personalization

[0063] Personalize the generated information based on the user's profile information.

[0064] 5. Data Transmission

[0065] Send personalized information to smart glasses.

[0066] Program processing explanation

[0067] User operations and initial settings

[0068] The user puts on the smart glasses and launches the application.

[0069] Enter your profile settings and interests.

[0070] Image capture and data transmission

[0071] The device (smart glasses) uses a camera device to capture the surrounding scenery and create image data.

[0072] The device uses the GPS module to obtain current location data.

[0073] The device transmits the captured image data and location information to the server.

[0074] Data analysis and information generation

[0075] The server analyzes the image data and location information received from the device.

[0076] The server uses image recognition AI to recognize objects in the image.

[0077] The server retrieves information from the LY and GTP databases related to the recognized object.

[0078] The server uses generation AI to generate detailed information.

[0079] The server personalizes the information based on the user's profile information.

[0080] The server returns the generated information to the terminal.

[0081] Information presentation and user interaction

[0082] The information received by the device (smart glasses) is displayed in the user's field of vision.

[0083] The user reviews the displayed information and requests more details using voice commands or gaze.

[0084] Specific examples

[0085] For example, as a user walks around town, the camera in the smart glasses captures the surrounding scenery. The image data and location information are sent to a server, where image recognition AI identifies specific restaurants. The server retrieves information about the restaurant, such as its menu, reviews, and opening hours, from the LY database and uses generative AI to generate detailed information. This information is personalized based on the user's profile and sent back to the smart glasses.

[0086] Through the smart glasses, users can see whether a particular restaurant suits their tastes, and detailed menu information and reviews are overlaid on the visuals, helping them make an intuitive choice. In this way, users receive personalized, helpful information in real time, facilitating decision-making.

[0087] Smart glasses can also be used in business settings, allowing delivery personnel, for example, to obtain detailed destination information and efficient routes in real time, enabling smoother operations. Even if sudden changes occur, they can be quickly responded to based on shared information.

[0088] The above is an embodiment of the present invention, which significantly improves user convenience and efficiency in obtaining information.

[0089] The processing flow will be explained below.

[0090] Program processing steps

[0091] Step 1:

[0092] The user puts on the smart glasses, turns them on, and launches the application.

[0093] A user enters information about their interests and preferences in a profile setting screen.

[0094] Step 2:

[0095] The device (smart glasses) continuously captures the surrounding scenery using a camera device.

[0096] The device obtains current location information using the GPS module.

[0097] Step 3:

[0098] The image data and location information acquired by the device are temporarily stored and then sent to the server using a communication module.

[0099] Step 4:

[0100] The server receives the image data and location information sent from the terminal.

[0101] The server uses an image analysis module to recognize objects in the image.

[0102] Step 5:

[0103] The server retrieves information related to the recognized object from the LY database and the GTP database.

[0104] The server uses a generation AI to generate detailed information about the recognized object.

[0105] Step 6:

[0106] The server refers to the user's profile information and personalizes the generated information.

[0107] The server sends the personalized information to the device.

[0108] Step 7:

[0109] The terminal analyzes the personalized information received from the server.

[0110] The information analyzed by the device is displayed overlaid on the user's field of vision.

[0111] Step 8:

[0112] When a user checks the information displayed on the smart glasses and wants to know more about a particular piece of information, they can make a request using voice commands or eye movements.

[0113] Step 9:

[0114] The terminal transmits a request from the user to the server through the communication module.

[0115] Step 10:

[0116] The server receives the request, generates additional details and sends them back to the device.

[0117] Step 11:

[0118] The additional information received by the device is displayed in the user's field of view, providing navigation and further details.

[0119] This allows users to obtain detailed information about their surroundings in real time based on visually overlaid information, enabling smooth decision-making.Similarly, in business situations, users can quickly obtain necessary information and carry out their work efficiently.

[0120] Example 1

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

[0122] Conventional wearable device systems have faced the issue of not being able to obtain necessary information in a timely manner due to a lack of real-time information provision and personalization based on user profiles. Furthermore, the generation of specific detailed information based on image data and location information often lacks precision, resulting in reduced user convenience.

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

[0124] In this invention, the server includes a means for analyzing the received image data and recognizing a specific object, a means for acquiring information related to the recognized object from an accumulation database, and a means for generating detailed information using a generative AI model based on the acquired information, thereby enabling real-time generation and personalization of detailed information.

[0125] A "camera device" is a device for photographing surrounding scenery and objects.

[0126] "Wearable device" is a general term for electronic devices that can be worn by the user.

[0127] "Image data" is data that includes visual information captured by a camera device.

[0128] A "location information acquisition device" is a device that uses GPS or other location measurement technology to determine a current location.

[0129] A "communication means" is a device that has the function of transmitting image data and location information to a server.

[0130] A "server" is a high-performance computer that processes and manages data over a network.

[0131] "Image analysis" is a process of analyzing received image data and recognizing objects.

[0132] An "object" refers to a specific object or location that exists within image data.

[0133] An "accumulation database" is a database that stores acquired information and allows it to be searched and used as needed.

[0134] A "generative AI model" is an algorithm or system that uses artificial intelligence to generate detailed information.

[0135] "Detailed information" is specific explanations and recommended information generated based on image data and location information.

[0136] "Personalization" refers to customizing information based on a user's profile information.

[0137] The "display means" is a device for displaying information superimposed on the user's field of vision.

[0138] "Profile information" is information relating to a user's personal interests and history.

[0139] This invention is a system that uses a wearable device including a camera device to analyze image data and location information in real time and provide personalized information to the user. This system mainly consists of three elements: the user, the terminal (wearable device), and the server. Specifically, the system uses the following hardware and software:

[0140] System Configuration

[0141] 1. Users

[0142] Users wear wearable devices (hereafter referred to as smart glasses) while walking around town or working. User profile information is shared between the smart glasses and a server, and the user's past usage history and interests are stored.

[0143] 2. Device (smart glasses)

[0144] The smart glasses have the following features:

[0145] 1. Camera equipment

[0146] Capture the surrounding scenery and save it as image data.

[0147] 2. Location information acquisition device

[0148] Use GPS to determine the user's current location.

[0149] 3. Means of communication

[0150] Image data and location information are sent to the server.

[0151] 4. Display means

[0152] The information received from the server is displayed superimposed on the user's field of view.

[0153] 3. Server

[0154] The server performs the following process.

[0155] 1. Data Reception

[0156] Receive image data and location information transmitted from the smart glasses.

[0157] 2. Image Analysis

[0158] It uses image recognition AI to identify objects in image data, specifically using Google Cloud Vision API, for example.

[0159] 3. Information generation

[0160] Information related to the recognized object is obtained from the accumulated database and external databases, and detailed information is generated using a generative AI model (e.g., OpenAI's GPT-4).

[0161] 4. Personalization

[0162] Personalize the generated information based on the user's profile information.

[0163] 5. Data Transmission

[0164] Send personalized information to smart glasses.

[0165] Specific examples

[0166] For example, as a user walks around town, the camera in the smart glasses captures the surrounding scenery. The image data and location information are sent to a server, where the Google Cloud Vision API identifies specific restaurants. The server retrieves information about the restaurant, such as its menu, reviews, and opening hours, from a database and uses a generative AI model (e.g., GPT-4) to generate detailed information. This information is personalized based on the user's profile and sent back to the smart glasses.

[0167] Through the smart glasses, users can see whether a particular restaurant suits their tastes, and detailed menu information and reviews are overlaid on the visuals, helping them make an intuitive choice. In this way, users receive personalized, helpful information in real time, facilitating decision-making.

[0168] Smart glasses can also be used in business settings, allowing delivery personnel, for example, to obtain detailed destination information and efficient routes in real time, enabling smoother operations. Even if sudden changes occur, they can be quickly responded to based on shared information.

[0169] Prompt Sentence Examples

[0170] If you use a generation AI, the prompt sentence is shown below as an example.

[0171] 1. Prompt to generate restaurant details:

[0172] Input: Restaurant name, menu items, hours, review rating

[0173] Answer: Create the following details: [restaurant name] overview, popular menu items, opening hours, what makes it great, and user review highlights.

[0174] 2. Information generation prompt for delivery agents:

[0175] Input: Delivery address, landmarks along the way, traffic conditions

[0176] Answer: Detailed route directions and landmark information along the way to help couriers reach their destination in the most efficient and smoothest way possible.

[0177] This is expected to significantly improve user convenience and the efficiency of information acquisition.

[0178] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0179] Step 1:

[0180] Initial setup and startup

[0181] The user puts on the smart glasses and launches the application. The user taps the application icon to launch it and enters their profile information and interests. This allows the user's personal setting information to be shared between the smart glasses and the server.

[0182] Input: User profile information, interests

[0183] Output: Save the setting information to the smart glasses.

[0184] Step 2:

[0185] Image capture and location acquisition

[0186] The device (smart glasses) uses a camera device to capture the surrounding scenery and create image data, and also uses a GPS module to obtain current location information.

[0187] Input: Surrounding scenery, current location

[0188] Output: Captured image data, location information

[0189] Step 3:

[0190] Data transmission

[0191] The device sends the captured image data and location information to a server, and the communication module in the smart glasses uploads the data using Wi-Fi or 4G / 5G networks.

[0192] Input: Image data, location information

[0193] Output: Data sent (reaches the server)

[0194] Step 4:

[0195] Data reception and analysis

[0196] The server analyzes the image data and location information received from the device, adds the received data to a dedicated processing queue, and uses image recognition AI (such as Google Cloud Vision API) to identify objects in the image.

[0197] Input: Image data, location information

[0198] Output: Recognized object information

[0199] Step 5:

[0200] information generation

[0201] The server retrieves information related to the recognized object from the stored database and external databases, then generates detailed information using a generative AI model (e.g., OpenAI's GPT-4).

[0202] Input: Recognized object information, accumulated database information

[0203] Output: Detailed information generated

[0204] Step 6:

[0205] Personalizing Information

[0206] The server personalizes the generated information based on the user's profile information, providing information that is relevant to the user's interests and past usage history.

[0207] Input: Generated details, user profile information

[0208] Output: personalized information

[0209] Step 7:

[0210] Data transmission and information display

[0211] The server sends personalized information to the device (smart glasses), which receives the information and displays it over the user's field of vision.

[0212] Input: Personalized Information

[0213] Output: Information displayed in the field of view of the smart glasses

[0214] Step 8:

[0215] User Interaction

[0216] The user can check the displayed information and request more details using voice commands or gaze. Voice commands are given using words such as "Show me more details," and the microphone in the smart glasses recognizes this and takes appropriate action.

[0217] Input: Voice command, gaze information

[0218] Output: Updated display information

[0219] (Application example 1)

[0220] 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."

[0221] Current information provision systems using wearable devices have challenges in that it is difficult for users to obtain detailed product information in real time in physical stores, and they are unable to personalize information based on individual users' preferences and past purchase history. In particular, they lack product recognition and navigation functions in physical stores, which often limit users' shopping experiences. Therefore, the development of a new system that significantly improves user convenience is desirable.

[0222] 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.

[0223] In this invention, the server includes a means for analyzing image data and recognizing specific objects, a means for retrieving information related to the recognized object from a database and generating detailed information using a generative AI model, and a means for personalizing the generated information based on a user's profile information. This allows for real-time provision of detailed information about products in a physical store and personalized information based on the user's profile. Furthermore, by enhancing product recognition and navigation functions, it is possible to support a user's efficient shopping experience.

[0224] A "camera device" is hardware for capturing image data.

[0225] A "wearable device" is a portable device that can be worn and used by a user.

[0226] "Image data" is visual information captured from a camera device.

[0227] A "location information acquisition device" is a device that uses technology such as GPS to identify a user's current location.

[0228] "Communication means" refers to a connection means for transmitting image data and location information to the server.

[0229] A "server" is a computer system that receives, analyzes, and generates data.

[0230] "Image Recognition AI" is an artificial intelligence algorithm that analyzes received image data and recognizes specific objects.

[0231] A "database" is a system for efficiently storing, searching, and managing large amounts of information.

[0232] A "generative AI model" is an artificial intelligence model that generates detailed information based on data.

[0233] "Profile information" is personal information such as a user's past usage history and interests.

[0234] "Personalization" refers to optimizing the information provided based on the user's individual profile information.

[0235] "Display means for displaying information overlaid on the user's field of vision" refers to technology that allows wearable devices such as smart glasses to overlay information on the user's field of vision.

[0236] A "brick and mortar store" is a commercial establishment that exists in a physical location.

[0237] A "navigation feature" is a feature that helps a user locate a particular product within a physical store.

[0238] This invention is a system that uses a wearable device including a camera to analyze image data and location information in real time and provide personalized information to users. This system is mainly composed of three elements: the user, the terminal (wearable device), and the server.

[0239] System Configuration

[0240] 1. Users

[0241] Users wear a wearable device (hereafter referred to as smart glasses) to check products in physical stores and obtain necessary information. User profile information is shared between the smart glasses and a server, and the user's past usage history and interests are stored.

[0242] 2. Device (smart glasses)

[0243] The smart glasses have the following features:

[0244] 1. Camera equipment

[0245] Capture surrounding products and save them as image data.

[0246] 2. Location information acquisition device

[0247] Use GPS to determine the user's current location.

[0248] 3. Means of communication

[0249] Image data and location information are sent to the server.

[0250] 4. Display means

[0251] The information received from the server is displayed superimposed on the user's field of view.

[0252] 3. Server

[0253] The server performs the following process.

[0254] 1. Data Reception

[0255] Receive image data and location information transmitted from the smart glasses.

[0256] 2. Image Analysis

[0257] Use image recognition AI to identify objects in image data.

[0258] 3. Information generation

[0259] Information related to the recognized object is retrieved from a database, and detailed information is generated using a generative AI model.

[0260] 4. Personalization

[0261] Personalize the generated information based on the user's profile information.

[0262] 5. Data Transmission

[0263] Send personalized information to smart glasses.

[0264] Program processing explanation

[0265] User operations and initial settings

[0266] The user puts on the smart glasses, launches a dedicated application, and enters their profile settings and interests to prepare for personalized information provision.

[0267] Image capture and data transmission

[0268] The camera device of the smart glasses captures the surrounding products and creates image data, and the GPS module acquires the current location data, and then transmits the captured image data and location information to the server.

[0269] Data analysis and information generation

[0270] The server analyzes the received image data and location information. It uses image recognition AI (e.g., TensorFlow) to recognize objects in the image. It retrieves information related to the recognized object from a database and generates detailed information using a generative AI model (e.g., GPT-4). The generated information is personalized based on the user's profile information.

[0271] Information presentation and user interaction

[0272] The smart glasses overlay the received information onto the user's field of vision, allowing the user to review the displayed information and request more information via voice commands or eye contact.

[0273] Specific examples

[0274] For example, imagine a user is in the chocolate section of a supermarket. The camera in the smart glasses captures products on the shelf and sends the image data and location information to a server. The server uses image recognition AI to recognize the specific product and retrieves its details from a database. A generative AI model is used to generate product reviews, nutritional information, and pricing information, personalizing it based on the user's profile. The generated information is sent to the smart glasses and displayed in the user's field of view. The user can then view the information and make product selections.

[0275] Prompt Sentence Examples

[0276] "When a user sees a new product in the supermarket, generate personalized details about that product. We'd like a natural language description based on the user's past purchases, allergies, and preferences."

[0277] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0278] Step 1:

[0279] The user puts on the smart glasses and launches the dedicated application. The user's profile information and interests are required as input. This information is stored on the smart glasses and serves as the basis for providing personalized information. As output, the smart glasses prepare the user's profile information and can then connect to the server.

[0280] Step 2:

[0281] The device (smart glasses) uses a camera device to capture surrounding products. The input is visual information (image data) acquired through the camera lens. The output is the acquired image data.

[0282] Step 3:

[0283] The device (smart glasses) uses a GPS location information acquisition device to obtain current location data. The input is a signal from the GPS sensor. The output is current location information.

[0284] Step 4:

[0285] The terminal transmits the captured image data and location information to the server using a communication means. The inputs are the image data and location information generated earlier. The output is transmitted to the server.

[0286] Step 5:

[0287] The server analyzes the received image data and location information. The inputs are the transmitted image data and location information. The server uses image recognition AI (e.g., TensorFlow) to identify objects in the image data. The output is information about the recognized objects.

[0288] Step 6:

[0289] The server retrieves information related to the recognized object from the database and generates detailed information using a generative AI model (e.g., GPT-4). The inputs are information about the object stored in the database and information about the recognized object. The output is the detailed information generated by the generative AI model.

[0290] Step 7:

[0291] The server personalizes the generated information based on the user's profile information. The inputs are the generated details and the user's profile information. The output is personalized details.

[0292] Step 8:

[0293] The server sends personalized information to the smart glasses. As input, there are personalized details. As output, the details are sent to the smart glasses.

[0294] Step 9:

[0295] The device (smart glasses) receives information and displays it over the user's field of view. The input is personalized details sent from the server. The output is the information overlaid on the user's field of view.

[0296] Step 10:

[0297] The user reviews the displayed information and requests more information if necessary. The inputs are the visual information from the smart glasses, as well as the user's voice commands and gaze information. The output is a request for additional information.

[0298] 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.

[0299] This invention is a system that uses a wearable device including a camera to analyze image data and location information in real time and provide personalized information based on the user's emotional data. This system is mainly composed of four elements: the user, the terminal (wearable device), the server, and the emotion engine.

[0300] System Configuration

[0301] 1. Users

[0302] Users wear wearable devices (hereafter referred to as smart glasses) while walking around town or working. User profile information is shared between the smart glasses and a server, and the user's past usage history and interests are stored. In addition, emotion data is collected in real time by an emotion engine.

[0303] 2. Device (smart glasses)

[0304] The smart glasses have the following features:

[0305] 1. Camera equipment

[0306] Capture the surrounding scenery and save it as image data.

[0307] 2. Location information acquisition device

[0308] Use GPS to determine the user's current location.

[0309] 3. Means of communication

[0310] Image data and location information are sent to the server.

[0311] 4. Display means

[0312] The information received from the server is displayed superimposed on the user's field of view.

[0313] 5. Emotion Engine

[0314] The user's voice and facial expressions are analyzed to generate emotional data, which is then sent to the server.

[0315] 3. Server

[0316] The server performs the following process.

[0317] 1. Data Reception

[0318] The image data, location information, and emotion data transmitted from the terminal are received.

[0319] 2. Image Analysis

[0320] Use image recognition AI to recognize objects in image data.

[0321] 3. Information generation

[0322] Information related to the recognized object is obtained from the LY database and GTP database, and information is generated using generation AI.

[0323] 4. Personalization

[0324] The generated information is personalized based on the user's profile information and emotion data obtained from the emotion engine.

[0325] 5. Data Transmission

[0326] Send personalized information to your device.

[0327] Program processing explanation

[0328] User operations and initial settings

[0329] The user puts on the smart glasses and launches the application.

[0330] A user enters information about their interests and preferences in a profile setting screen.

[0331] Image capture and data transmission

[0332] The device (smart glasses) uses a camera device to continuously capture the surrounding scenery and create image data.

[0333] The device uses the GPS module to obtain its current location.

[0334] The emotion engine analyzes the user's voice and facial expressions to generate emotion data.

[0335] The terminal transmits the captured image data, location information, and emotion data to a server.

[0336] Data analysis and information generation

[0337] The server receives the image data, location information, and emotion data transmitted from the terminal.

[0338] The server uses an image analysis module to recognize objects in the image.

[0339] The server retrieves information from the LY and GTP databases related to the recognized object.

[0340] The server uses generation AI to generate detailed information.

[0341] The server personalizes the information based on the user's profile information and emotional data.

[0342] The server returns the generated personalized information to the terminal.

[0343] Information presentation and user interaction

[0344] The information received by the device (smart glasses) is displayed in the user's field of vision.

[0345] The user can review the displayed information and, if they want more details about a particular piece of information, make a request using voice commands or eye control.

[0346] Specific examples

[0347] For example, as a user walks around town, the camera in the smart glasses captures the surrounding scenery. The image data and location information are sent to a server, where image recognition AI identifies specific restaurants. The server retrieves information about the restaurant, such as its menu, reviews, and opening hours, from the LY database and uses generative AI to generate detailed information. This information is personalized based on the user's profile and emotional data and sent back to the smart glasses.

[0348] For example, if the emotion engine recognizes that the user is tired, it will prioritize information about relaxing cafes and rest spots. Conversely, if the user is excited, it will display information about active leisure activities.

[0349] This allows users to obtain the most appropriate information for their situation in real time, allowing them to enjoy walking around town. In business situations, delivery companies can use emotion data to efficiently carry out their work and flexibly respond to sudden changes. The above is an embodiment of the present invention, which provides information according to the user's emotional state and improves the user experience.

[0350] The processing flow will be explained below.

[0351] Program processing steps

[0352] Step 1:

[0353] The user puts on the smart glasses, turns them on, and launches the application.

[0354] A user enters information about their interests and preferences in a profile setting screen.

[0355] Step 2:

[0356] The device (smart glasses) continuously captures the surrounding scenery using a camera device.

[0357] The device obtains current location information using the GPS module.

[0358] Step 3:

[0359] The emotion engine analyzes the user's voice and facial expressions in real time and generates emotion data.

[0360] Voice analysis detects the tone of a user's voice and the rhythm of their speech to identify their emotional state (e.g., joy, anger, sadness, etc.).

[0361] Facial expression analysis involves capturing a user's facial expressions and using emotion analysis algorithms to identify their emotional state.

[0362] Step 4:

[0363] The image data, location information, and emotional data acquired by the device are temporarily stored and transmitted to a server using a communication module.

[0364] Step 5:

[0365] The server receives the image data, location information, and emotion data transmitted from the terminal.

[0366] Step 6:

[0367] The server uses an image analysis module to recognize objects in the image.

[0368] The server retrieves information from the LY and GTP databases related to the recognized object.

[0369] Example: If a specific restaurant is recognized, retrieve its menu, reviews, opening hours, etc.

[0370] Step 7:

[0371] The server uses generation AI to generate detailed information about the recognized objects.

[0372] Step 8:

[0373] The server personalizes the generated details based on the user's profile information and emotion data.

[0374] Example: If the user is tired, provide them with information about cafes and rest spots where they can relax.

[0375] Step 9:

[0376] The server sends the personalized information to the device.

[0377] Step 10:

[0378] The device (smart glasses) analyzes the personalized information received.

[0379] The information analyzed by the device is displayed overlaid on the user's field of vision.

[0380] Step 11:

[0381] If the user checks the displayed information and wants to know more, they can make a request using voice commands or eye movements.

[0382] For example, say the voice command, "Tell me more about this restaurant's menu."

[0383] Step 12:

[0384] The terminal transmits a request from the user to the server through the communication module.

[0385] Step 13:

[0386] The server receives the request, generates additional details and sends them back to the device.

[0387] Step 14:

[0388] The additional information received by the device (smart glasses) is displayed in the user's field of view, providing navigation and further details.

[0389] Examples:

[0390] As a user walks around town, the smartglasses' camera captures the surrounding scenery. The image data and location information are sent to a server, where image recognition AI identifies specific restaurants. The server retrieves information about the restaurant, such as its menu, reviews, and opening hours, from the LY database and uses generative AI to generate detailed information. This information is personalized based on the user's profile and emotional data and sent back to the smartglasses.

[0391] For example, if the emotion engine recognizes that the user is tired, it will prioritize displaying information about relaxing cafes and rest spots. Conversely, if the user is excited, it will display information about active leisure activities. In this way, users can obtain optimal information in real time and enjoy a highly satisfying experience. In business situations, emotional data can also be used to efficiently carry out work and flexibly respond to sudden changes.

[0392] Example 2

[0393] 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."

[0394] Conventional wearable device systems have limited information that users can obtain in real time, making it difficult to provide appropriate information tailored to the user's emotional state and individual interests. Furthermore, due to a lack of personalization of information, it has been difficult to efficiently obtain information that is valuable to the user. Therefore, it is necessary to further improve user convenience and the usefulness of information.

[0395] 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.

[0396] In this invention, the server includes means for analyzing a user's voice and facial expressions to generate emotional data, means for analyzing image data received by the server and recognizing a specific object, means for acquiring information related to the recognized object, means for generating detailed information using a generative AI model, and means for personalizing the generated detailed information based on the user's profile information and emotional data, thereby enabling the provision of appropriate information in real time according to the user's emotional state and individual interests.

[0397] A "camera device" is a device used to capture image data.

[0398] A "wearable device" is an electronic device that can be worn by a user.

[0399] A "location information acquisition device" is a device that acquires information about a user's current location using technology such as GPS.

[0400] "Communication means" refers to a means for transmitting data to other devices or servers.

[0401] "Emotion data" is data relating to the user's emotional state obtained by analyzing the user's voice and facial expressions.

[0402] "Image analysis means" is a means for analyzing captured image data and recognizing specific objects within the image.

[0403] The "information acquisition means" is a means for acquiring information related to a recognized object from a database or the like.

[0404] A "generative AI model" is an algorithm that uses artificial intelligence techniques to generate detailed information based on specific inputs.

[0405] "Personalization means" refers to means for individualizing the generated detailed information based on the user's profile information and emotional data.

[0406] A "display means" is a means for displaying generated or personalized information to the user's view.

[0407] "Profile information" is individual information about a user, such as information about the user's interests and preferences.

[0408] "Voice command" refers to an operation or request made by a user through voice.

[0409] This invention is a system that uses a wearable device including a camera to analyze image data and location information in real time and provide personalized information based on the user's emotional data. This system is mainly composed of four elements: the user, the terminal (wearable device), the server, and the emotion engine.

[0410] System Configuration

[0411] 1. Users

[0412] Users wear wearable devices (hereafter referred to as smart glasses) while walking around town or working. User profile information is shared between the smart glasses and a server, and the user's past usage history and interests are stored. In addition, emotion data is collected in real time by an emotion engine.

[0413] 2. Device (smart glasses)

[0414] The smart glasses have the following features:

[0415] 1. Camera equipment

[0416] Capture the surrounding scenery and save it as image data.

[0417] 2. Location information acquisition device

[0418] Use GPS to determine the user's current location.

[0419] 3. Means of communication

[0420] Image data and location information are sent to the server.

[0421] 4. Display means

[0422] The information received from the server is displayed superimposed on the user's field of view.

[0423] 5. Emotion Engine

[0424] The user's voice and facial expressions are analyzed to generate emotional data, which is then sent to the server.

[0425] 3. Server

[0426] The server performs the following process.

[0427] 1. Data Reception

[0428] The image data, location information, and emotion data transmitted from the terminal are received.

[0429] 2. Image Analysis

[0430] Use image recognition AI to recognize objects in image data.

[0431] 3. Information acquisition

[0432] Information related to the recognized object is retrieved from the database.

[0433] 4. Information generation

[0434] A generative AI model is used to generate detailed information, such as OpenAI's GPT model.

[0435] 5. Personalization

[0436] The generated information is personalized based on the user's profile information and emotion data obtained from the emotion engine.

[0437] 6. Data Transmission

[0438] Send personalized information to your device.

[0439] Program processing explanation

[0440] Image capture and data transmission

[0441] The device (smart glasses) uses a camera device to continuously capture the surrounding scenery and create image data. The device acquires its current location information using a GPS module. The emotion engine analyzes the user's voice and facial expressions to generate emotion data. The device sends the captured image data, location information, and emotion data to a server.

[0442] Data analysis and information generation

[0443] The server receives image data, location information, and emotion data sent from the device. The server uses an image analysis module to recognize objects in the image. The server retrieves information related to the recognized object from a database. The server uses a generative AI model to generate detailed information. The server personalizes the information based on the user's profile information and emotion data. The server sends the generated personalized information to the device.

[0444] Information presentation and user interaction

[0445] The device (smart glasses) displays the received information in the user's field of vision. If the user checks the displayed information and wants more details about a specific piece of information, they can make a request using voice commands or eye movements. In this way, the most appropriate information can be provided based on the user's real-time emotional state and profile information.

[0446] Specific examples

[0447] For example, as a user walks around town, the camera in the smart glasses captures the surrounding scenery and identifies restaurants. The image data and location information are sent to a server, where image recognition AI identifies the specific restaurant. The server retrieves information about the restaurant, such as its menu, reviews, and opening hours, from a database and uses generative AI to generate detailed information. This information is personalized based on the user's profile and emotional data and sent back to the smart glasses.

[0448] For example, if the emotion engine recognizes that the user is tired, it will prioritize information about cafes and rest spots where they can relax. Conversely, if the user is excited, it will display information about active leisure activities. The following is an example of a prompt sentence:

[0449] "Recommend restaurants near my current location"

[0450] "Looking for a relaxing cafe"

[0451] "What live event can I go to tonight?"

[0452] This allows users to obtain the most appropriate information for their situation in real time, allowing them to enjoy walking around town.In business settings, delivery companies can use emotion data to carry out their work efficiently and respond flexibly to sudden changes.

[0453] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0454] System program processing flow

[0455] Step 1: User interaction and initial setup

[0456] Input: The user puts on the smart glasses and launches the application.

[0457] Action: The user powers on the smart glasses and launches the application. The application begins its startup sequence and displays the initial setup screen.

[0458] Output: The smart glasses start up and the profile setting screen is displayed.

[0459] Step 2: Profile Settings

[0460] Input: The user enters information about interests and preferences in a profile setup screen.

[0461] How it works: A user fills out a profile screen that describes their interests, preferences, and general interests. This includes selecting categories and entering text.

[0462] Output: The entered information is sent to the server and a user profile is generated.

[0463] Step 3: Image capture

[0464] Input: A user puts on smart glasses and starts moving.

[0465] Operation: The device (smart glasses) uses a camera device to continuously capture the surrounding scenery and generate image data.

[0466] Output: The generated image data is saved in the internal memory.

[0467] Step 4: Obtaining location information

[0468] Input: A user puts on smart glasses and continues moving.

[0469] Operation: The device (smart glasses) uses the GPS module to obtain current location information. This process is performed automatically at regular intervals.

[0470] Output: The acquired location information is stored in the internal memory.

[0471] Step 5: Emotion data generation

[0472] Input: The user wears the smart glasses and can speak or change their facial expressions.

[0473] How it works: The emotion engine analyzes the user's voice and facial expressions to generate emotion data. Waveform analysis and phoneme analysis are used for voice analysis, and image processing algorithms are used for facial expression analysis.

[0474] Output: The generated emotion data is stored in the internal memory.

[0475] Step 6: Send data

[0476] Input: Generated image data, location information, and emotion data.

[0477] Operation: The device transmits the captured image data, location information, and emotion data to the server. This transmission is performed using wireless communication means.

[0478] Output: The server receives these data.

[0479] Step 7: Receiving Data

[0480] Input: Image data, location information, and emotional data sent from the device.

[0481] Operation: The server receives image data, location information, and emotion data sent from the device.

[0482] Output: The received data is saved in a specific directory on the server.

[0483] Step 8: Image analysis

[0484] Input: Received image data.

[0485] How it works: The server uses an image analysis module to recognize objects in an image, for example using an image recognition algorithm such as YOLO (You Only Look Once).

[0486] Output: Recognized object information is generated.

[0487] Step 9: Information Acquisition

[0488] Input: Recognized object information.

[0489] How it works: The server retrieves information related to the recognized object from a database (e.g., an LY database or a GTP database), typically using an SQL query.

[0490] Output: Relevant information is obtained.

[0491] Step 10: Information Generation

[0492] Input: The relevant information retrieved.

[0493] How it works: The server uses a generative AI model (e.g., OpenAI's GPT model) to generate detailed information. It sends prompts to the model to generate detailed explanations and additional information.

[0494] Output: Detailed information is generated.

[0495] Step 11: Personalize

[0496] Input: Generated details, user profile information, and sentiment data.

[0497] How it works: The server personalizes the generated information based on the user's profile information and emotional data, taking into account the user's current emotional state and past behavioral patterns.

[0498] Output: Personalized information is generated.

[0499] Step 12: Data transmission (retransmission)

[0500] Input: Personalized information.

[0501] Operation: The server transmits the generated personalized information to the terminal. This transmission is also performed using wireless communication means.

[0502] Output: The device receives the personalized information.

[0503] Step 13: Display Information

[0504] Input: Received personalization information.

[0505] How it works: The device (smart glasses) displays the information it receives in the user's field of vision using HUD (head-up display) technology.

[0506] Output: The user sees the personalized information.

[0507] Step 14: User Interaction

[0508] Input: User's reaction to the received personalized information.

[0509] How it works: If the user wants to know more about a particular piece of information, they can make a request using voice commands or eye contact. This request is sent to the server via the device.

[0510] Output: The server receives the new request information and the process repeats, generating the relevant information again.

[0511] Through these steps, this system will be able to provide appropriate information in real time according to the user's emotional state and individual interests.

[0512] (Application example 2)

[0513] 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."

[0514] In today's shopping experience, it is difficult for users to obtain appropriate information in real time based on their interests and emotions. Specifically, it is difficult to instantly find products and services that match their preferences in a store, which reduces shopping satisfaction. Furthermore, when users want to know more about information that interests them, there is a lack of a way to quickly and intuitively obtain detailed information. There is a need for a way to resolve these issues and improve the user experience.

[0515] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0516] In this invention, the server includes an emotion analysis means for analyzing the user's emotion data, a means for generating detailed information using a generative AI model, and a means for personalizing information based on the user's profile information and emotion data, thereby enabling the provision of personalized information based on the user's location information and emotion.

[0517] A "camera device" is a device that is built into a wearable device and captures image data of the surroundings.

[0518] A "location information acquisition device" is a device that identifies the user's current location. It uses GPS or in-store beacons.

[0519] The "communication means" is a means for transmitting captured image data and location information to a server.

[0520] A "server" is a computer system that analyzes received image data and recognizes specific objects.

[0521] A "means for recognizing specific objects" is an algorithm or device that identifies and identifies objects or people based on image data.

[0522] The "means for generating information" is a function that generates information related to a recognized object.

[0523] "Means for generating detailed information using a generative AI model" refers to means for automatically generating detailed information to be provided to a user using an artificial intelligence model.

[0524] The "emotion analysis means that provides user emotion data based on an emotion engine" refers to a device or software that analyzes the user's voice and facial expressions and derives emotion data.

[0525] The "display means" is a device that displays the generated information superimposed on the user's field of vision. It usually includes smart glasses or the like.

[0526] "User profile information" is data including the user's past usage history, interests, personal information, etc.

[0527] "Personalization" means tailoring and individually optimizing the information provided based on each user's individual profile and emotional data.

[0528] "Means for requesting detailed information about specific information using eye movements or voice commands" refers to an operating means for obtaining details about information of interest to the user through eye movements or voice instructions.

[0529] The present invention relates to a system using a wearable device that provides personalized information based on a user's emotional data. This system analyzes image data, location information, and emotional data in real time when the user wears the wearable device, and provides personalized information to the user.

[0530] System Configuration

[0531] User

[0532] A user wears a wearable device (e.g., smart glasses) and uses the device while walking around town or inside a store.

[0533] Device (smart glasses)

[0534] The smart glasses have the following features:

[0535] 1. Camera equipment

[0536] Capture image data of the surroundings in real time.

[0537] 2. Location information acquisition device

[0538] Use GPS or in-store beacons to determine the user's current location.

[0539] 3. Means of communication

[0540] The captured image data, location information, and emotion data are transmitted to a server.

[0541] 4. Display means

[0542] The personalized information received from the server is displayed superimposed on the user's field of view.

[0543] 5. Emotion analysis method

[0544] The system analyzes the user's voice and facial expressions to generate emotional data, which is then sent to the server.

[0545] server

[0546] The server performs the following process.

[0547] 1. Data Reception

[0548] The image data, position information, and emotion data transmitted from the terminal are received.

[0549] 2. Image Analysis

[0550] Image recognition algorithms are used to recognize specific objects within the image data.

[0551] 3. Emotion analysis

[0552] The received emotional data is analyzed to understand the user's emotional state.

[0553] 4. Information generation

[0554] Information related to the recognized object is retrieved from a database and detailed information is generated using a generative AI model.

[0555] 5. Personalization

[0556] The generated information is personalized based on the user's profile information and emotional data.

[0557] 6. Data Transmission

[0558] Send personalized information to your device.

[0559] Program processing explanation

[0560] Hardware

[0561] Camera devices (e.g., cameras built into wearable devices)

[0562] GPS devices (e.g., smartphone GPS modules, in-store beacons)

[0563] Smart glasses (e.g. Google Glass)

[0564] Display device (smart glasses built-in display)

[0565] software

[0566] EmotionRecognizer (emotion analysis library)

[0567] GPS module (location information acquisition library)

[0568] Requests library (HTTP request library)

[0569] Generative AI model (AI model for generating detailed information)

[0570] Data processing and calculation

[0571] 1. Capture image data

[0572] The camera device captures images of the surroundings in real time.

[0573] 2. Obtaining location information

[0574] The user's current location is obtained using a GPS module or beacon.

[0575] 3. Generating Emotion Data

[0576] Emotion data is generated from the user's voice and facial expressions using EmotionRecognizer.

[0577] 4. Data Transmission

[0578] Use the Requests library to send image data, location information, and emotion data to the server.

[0579] 5. Server-side data analysis

[0580] The server analyzes the images based on the received data and recognizes specific objects. It also analyzes the emotional data to understand the user's emotional state.

[0581] 6. Information generation

[0582] Information related to the recognized object is retrieved from a database and detailed information is generated using a generative AI model.

[0583] 7. Personalization

[0584] The generated information is personalized based on the user's profile information and emotional data.

[0585] 8. Information display

[0586] The generated personalized information is displayed on the smart glasses display.

[0587] Specific examples

[0588] Example prompt sentence:

[0589] The user's name is User 1. He is 30 years old and enjoys active shopping. He is currently on the third floor of a department store. He is wearing smart glasses, and the emotion engine recognizes his excitement. Provide him with information that may interest him. His favorite brands are popular, and he is interested in new products.

[0590] Based on these prompts, users can receive information optimized for their emotions and profile in real time. For example, as a user walks through a store, the camera in the smart glasses captures a specific product, and detailed information about that product is instantly displayed on the display. Recommended products and services based on the user's emotional state are also displayed, improving the user's shopping experience.

[0591] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0592] Step 1:

[0593] The user puts on the smart glasses and launches the application.

[0594] Input: User profile information (interests, favorite brands, etc.)

[0595] Output: Profile information is shared between smart glasses and the server.

[0596] Specific operation: The user puts on the smart glasses, launches the app, and enters information on the profile settings screen.

[0597] Step 2:

[0598] The device (smart glasses) uses a camera device to capture image data of the surroundings in real time.

[0599] Input: Surrounding landscape

[0600] Output: Real-time image data

[0601] How it works: The camera built into the smart glasses continuously captures images and stores them in its internal memory.

[0602] Step 3:

[0603] The device uses the GPS module to obtain its current location.

[0604] Input: Current location satellite data

[0605] Output: Current location information

[0606] Specific operation: The GPS module receives satellite data and calculates latitude and longitude.

[0607] Step 4:

[0608] The emotion engine analyzes the user's voice and facial expressions to generate emotion data.

[0609] Input: User's voice and facial expression data

[0610] Output: Emotion data (e.g., joy, anger, surprise, etc.)

[0611] How it works: The smart glasses' microphone and camera capture voice and facial expressions, and the emotion engine analyzes this data to infer emotions.

[0612] Step 5:

[0613] The terminal transmits the captured image data, location information, and emotion data to a server.

[0614] Input: image data, location information, emotion data

[0615] Output: Data sent to the server

[0616] Specific operation: The communication module uploads data to the server using an HTTP request.

[0617] Step 6:

[0618] The server analyzes the received image data and recognizes specific objects.

[0619] Input: Image data

[0620] Output: Recognized object information

[0621] What it does: Image recognition algorithms on the server analyze the image and identify the object.

[0622] Step 7:

[0623] The server analyzes the received emotional data and understands the user's emotional state.

[0624] Input: Emotion data

[0625] Output: Emotional state (e.g., "excited")

[0626] Specific operation: Emotion analysis software on the server analyzes the emotion data and evaluates the user's emotional state.

[0627] Step 8:

[0628] The server retrieves information related to a specific object from a database and generates detailed information using a generative AI model.

[0629] Input: Recognized object information

[0630] Output:Detailed information

[0631] How it works: The server retrieves information related to the object from the database and generates detailed information using a generative AI model.

[0632] Step 9:

[0633] The server personalizes the information based on the user's profile information and emotional data.

[0634] Input: Details, profile information, emotional data

[0635] Output: Personalized information

[0636] Specific operation: The server customizes detailed information to suit the user based on profile information and emotional data.

[0637] Step 10:

[0638] The server sends the personalized information to the device.

[0639] Input: Personalized Information

[0640] Output: Information sent to the terminal

[0641] Specific operation: The server transmits the personalized information to the terminal via the communication module.

[0642] Step 11:

[0643] The information received by the device (smart glasses) is displayed overlaid on the user's field of vision.

[0644] Input: Personalized Information

[0645] Output: Information displayed in the user's field of view

[0646] Specific operation: The smart glasses display device displays the received information as an overlay.

[0647] Step 12:

[0648] The user uses gaze or voice commands to request detailed information about a specific item.

[0649] Input: Voice commands and gaze data

[0650] Output: Request for more information

[0651] Specific actions: The user sends a request by speaking a specific command into the smart glasses or by directing their gaze in a specific location.

[0652] 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.

[0653] 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.

[0654] 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.

[0655] [Second embodiment]

[0656] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0657] 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.

[0658] 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).

[0659] 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.

[0660] 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.

[0661] 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).

[0662] 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.

[0663] 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.

[0664] 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.

[0665] 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.

[0666] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0667] 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."

[0668] This invention is a system that uses a wearable device including a camera to analyze image data and location information in real time and provide personalized information to users. This system is mainly composed of three elements: the user, the terminal (wearable device), and the server.

[0669] System Configuration

[0670] 1. Users

[0671] Users wear wearable devices (hereafter referred to as smart glasses) while walking around town or working. User profile information is shared between the smart glasses and a server, and the user's past usage history and interests are stored.

[0672] 2. Device (smart glasses)

[0673] The smart glasses have the following features:

[0674] 1. Camera equipment

[0675] Capture the surrounding scenery and save it as image data.

[0676] 2. Location information acquisition device

[0677] Use GPS to determine the user's current location.

[0678] 3. Means of communication

[0679] Image data and location information are sent to the server.

[0680] 4. Display means

[0681] The information received from the server is displayed superimposed on the user's field of view.

[0682] 3. Server

[0683] The server performs the following process.

[0684] 1. Data Reception

[0685] Receive image data and location information transmitted from the smart glasses.

[0686] 2. Image Analysis

[0687] Use image recognition AI to identify objects in image data.

[0688] 3. Information generation

[0689] Information related to the recognized object is obtained from the LY database and GTP database, and information is generated using generation AI.

[0690] 4. Personalization

[0691] Personalize the generated information based on the user's profile information.

[0692] 5. Data Transmission

[0693] Send personalized information to smart glasses.

[0694] Program processing explanation

[0695] User operations and initial settings

[0696] The user puts on the smart glasses and launches the application.

[0697] Enter your profile settings and interests.

[0698] Image capture and data transmission

[0699] The device (smart glasses) uses a camera device to capture the surrounding scenery and create image data.

[0700] The device uses the GPS module to obtain current location data.

[0701] The device transmits the captured image data and location information to the server.

[0702] Data analysis and information generation

[0703] The server analyzes the image data and location information received from the device.

[0704] The server uses image recognition AI to recognize objects in the image.

[0705] The server retrieves information from the LY and GTP databases related to the recognized object.

[0706] The server uses generation AI to generate detailed information.

[0707] The server personalizes the information based on the user's profile information.

[0708] The server returns the generated information to the terminal.

[0709] Information presentation and user interaction

[0710] The information received by the device (smart glasses) is displayed in the user's field of vision.

[0711] The user reviews the displayed information and requests more details using voice commands or gaze.

[0712] Specific examples

[0713] For example, as a user walks around town, the camera in the smart glasses captures the surrounding scenery. The image data and location information are sent to a server, where image recognition AI identifies specific restaurants. The server retrieves information about the restaurant, such as its menu, reviews, and opening hours, from the LY database and uses generative AI to generate detailed information. This information is personalized based on the user's profile and sent back to the smart glasses.

[0714] Through the smart glasses, users can see whether a particular restaurant suits their tastes, and detailed menu information and reviews are overlaid on the visuals, helping them make an intuitive choice. In this way, users receive personalized, helpful information in real time, facilitating decision-making.

[0715] Smart glasses can also be used in business settings, allowing delivery personnel, for example, to obtain detailed destination information and efficient routes in real time, enabling smoother operations. Even if sudden changes occur, they can be quickly responded to based on shared information.

[0716] The above is an embodiment of the present invention, which significantly improves user convenience and efficiency in obtaining information.

[0717] The processing flow will be explained below.

[0718] Program processing steps

[0719] Step 1:

[0720] The user puts on the smart glasses, turns them on, and launches the application.

[0721] A user enters information about their interests and preferences in a profile setting screen.

[0722] Step 2:

[0723] The device (smart glasses) continuously captures the surrounding scenery using a camera device.

[0724] The device obtains current location information using the GPS module.

[0725] Step 3:

[0726] The image data and location information acquired by the device are temporarily stored and then sent to the server using a communication module.

[0727] Step 4:

[0728] The server receives the image data and location information sent from the terminal.

[0729] The server uses an image analysis module to recognize objects in the image.

[0730] Step 5:

[0731] The server retrieves information related to the recognized object from the LY database and the GTP database.

[0732] The server uses a generation AI to generate detailed information about the recognized object.

[0733] Step 6:

[0734] The server refers to the user's profile information and personalizes the generated information.

[0735] The server sends the personalized information to the device.

[0736] Step 7:

[0737] The terminal analyzes the personalized information received from the server.

[0738] The information analyzed by the device is displayed overlaid on the user's field of vision.

[0739] Step 8:

[0740] When a user checks the information displayed on the smart glasses and wants to know more about a particular piece of information, they can make a request using voice commands or eye movements.

[0741] Step 9:

[0742] The terminal transmits a request from the user to the server through the communication module.

[0743] Step 10:

[0744] The server receives the request, generates additional details and sends them back to the device.

[0745] Step 11:

[0746] The additional information received by the device is displayed in the user's field of view, providing navigation and further details.

[0747] This allows users to obtain detailed information about their surroundings in real time based on visually overlaid information, enabling smooth decision-making.Similarly, in business situations, users can quickly obtain necessary information and carry out their work efficiently.

[0748] Example 1

[0749] 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."

[0750] Conventional wearable device systems have faced the issue of not being able to obtain necessary information in a timely manner due to a lack of real-time information provision and personalization based on user profiles. Furthermore, the generation of specific detailed information based on image data and location information often lacks precision, resulting in reduced user convenience.

[0751] 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.

[0752] In this invention, the server includes a means for analyzing the received image data and recognizing a specific object, a means for acquiring information related to the recognized object from an accumulation database, and a means for generating detailed information using a generative AI model based on the acquired information, thereby enabling real-time generation and personalization of detailed information.

[0753] A "camera device" is a device for photographing surrounding scenery and objects.

[0754] "Wearable device" is a general term for electronic devices that can be worn by the user.

[0755] "Image data" is data that includes visual information captured by a camera device.

[0756] A "location information acquisition device" is a device that uses GPS or other location measurement technology to determine a current location.

[0757] A "communication means" is a device that has the function of transmitting image data and location information to a server.

[0758] A "server" is a high-performance computer that processes and manages data over a network.

[0759] "Image analysis" is a process of analyzing received image data and recognizing objects.

[0760] An "object" refers to a specific object or location that exists within image data.

[0761] An "accumulation database" is a database that stores acquired information and allows it to be searched and used as needed.

[0762] A "generative AI model" is an algorithm or system that uses artificial intelligence to generate detailed information.

[0763] "Detailed information" is specific explanations and recommended information generated based on image data and location information.

[0764] "Personalization" refers to customizing information based on a user's profile information.

[0765] The "display means" is a device for displaying information superimposed on the user's field of vision.

[0766] "Profile information" is information relating to a user's personal interests and history.

[0767] This invention is a system that uses a wearable device including a camera device to analyze image data and location information in real time and provide personalized information to the user. This system mainly consists of three elements: the user, the terminal (wearable device), and the server. Specifically, the system uses the following hardware and software:

[0768] System Configuration

[0769] 1. Users

[0770] Users wear wearable devices (hereafter referred to as smart glasses) while walking around town or working. User profile information is shared between the smart glasses and a server, and the user's past usage history and interests are stored.

[0771] 2. Device (smart glasses)

[0772] The smart glasses have the following features:

[0773] 1. Camera equipment

[0774] Capture the surrounding scenery and save it as image data.

[0775] 2. Location information acquisition device

[0776] Use GPS to determine the user's current location.

[0777] 3. Means of communication

[0778] Image data and location information are sent to the server.

[0779] 4. Display means

[0780] The information received from the server is displayed superimposed on the user's field of view.

[0781] 3. Server

[0782] The server performs the following process.

[0783] 1. Data Reception

[0784] Receive image data and location information transmitted from the smart glasses.

[0785] 2. Image Analysis

[0786] It uses image recognition AI to identify objects in image data, specifically using Google Cloud Vision API, for example.

[0787] 3. Information generation

[0788] Information related to the recognized object is obtained from the accumulated database and external databases, and detailed information is generated using a generative AI model (e.g., OpenAI's GPT-4).

[0789] 4. Personalization

[0790] Personalize the generated information based on the user's profile information.

[0791] 5. Data Transmission

[0792] Send personalized information to smart glasses.

[0793] Specific examples

[0794] For example, as a user walks around town, the camera in the smart glasses captures the surrounding scenery. The image data and location information are sent to a server, where the Google Cloud Vision API identifies specific restaurants. The server retrieves information about the restaurant, such as its menu, reviews, and opening hours, from a database and uses a generative AI model (e.g., GPT-4) to generate detailed information. This information is personalized based on the user's profile and sent back to the smart glasses.

[0795] Through the smart glasses, users can see whether a particular restaurant suits their tastes, and detailed menu information and reviews are overlaid on the visuals, helping them make an intuitive choice. In this way, users receive personalized, helpful information in real time, facilitating decision-making.

[0796] Smart glasses can also be used in business settings, allowing delivery personnel, for example, to obtain detailed destination information and efficient routes in real time, enabling smoother operations. Even if sudden changes occur, they can be quickly responded to based on shared information.

[0797] Prompt Sentence Examples

[0798] If you use a generation AI, the prompt sentence is shown below as an example.

[0799] 1. Prompt to generate restaurant details:

[0800] Input: Restaurant name, menu items, hours, review rating

[0801] Answer: Create the following details: [restaurant name] overview, popular menu items, opening hours, what makes it great, and user review highlights.

[0802] 2. Information generation prompt for delivery agents:

[0803] Input: Delivery address, landmarks along the way, traffic conditions

[0804] Answer: Detailed route directions and landmark information along the way to help couriers reach their destination in the most efficient and smoothest way possible.

[0805] This is expected to significantly improve user convenience and the efficiency of information acquisition.

[0806] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0807] Step 1:

[0808] Initial setup and startup

[0809] The user puts on the smart glasses and launches the application. The user taps the application icon to launch it and enters their profile information and interests. This allows the user's personal setting information to be shared between the smart glasses and the server.

[0810] Input: User profile information, interests

[0811] Output: Save the setting information to the smart glasses.

[0812] Step 2:

[0813] Image capture and location acquisition

[0814] The device (smart glasses) uses a camera device to capture the surrounding scenery and create image data, and also uses a GPS module to obtain current location information.

[0815] Input: Surrounding scenery, current location

[0816] Output: Captured image data, location information

[0817] Step 3:

[0818] Data transmission

[0819] The device sends the captured image data and location information to a server, and the communication module in the smart glasses uploads the data using Wi-Fi or 4G / 5G networks.

[0820] Input: Image data, location information

[0821] Output: Data sent (reaches the server)

[0822] Step 4:

[0823] Data reception and analysis

[0824] The server analyzes the image data and location information received from the device, adds the received data to a dedicated processing queue, and uses image recognition AI (such as Google Cloud Vision API) to identify objects in the image.

[0825] Input: Image data, location information

[0826] Output: Recognized object information

[0827] Step 5:

[0828] information generation

[0829] The server retrieves information related to the recognized object from the stored database and external databases, then generates detailed information using a generative AI model (e.g., OpenAI's GPT-4).

[0830] Input: Recognized object information, accumulated database information

[0831] Output: Detailed information generated

[0832] Step 6:

[0833] Personalizing Information

[0834] The server personalizes the generated information based on the user's profile information, providing information that is relevant to the user's interests and past usage history.

[0835] Input: Generated details, user profile information

[0836] Output: personalized information

[0837] Step 7:

[0838] Data transmission and information display

[0839] The server sends personalized information to the device (smart glasses), which receives the information and displays it over the user's field of vision.

[0840] Input: Personalized Information

[0841] Output: Information displayed in the field of view of the smart glasses

[0842] Step 8:

[0843] User Interaction

[0844] The user can check the displayed information and request more details using voice commands or gaze. Voice commands are given using words such as "Show me more details," and the microphone in the smart glasses recognizes this and takes appropriate action.

[0845] Input: Voice command, gaze information

[0846] Output: Updated display information

[0847] (Application example 1)

[0848] 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."

[0849] Current information provision systems using wearable devices have challenges in that it is difficult for users to obtain detailed product information in real time in physical stores, and they are unable to personalize information based on individual users' preferences and past purchase history. In particular, they lack product recognition and navigation functions in physical stores, which often limit users' shopping experiences. Therefore, the development of a new system that significantly improves user convenience is desirable.

[0850] 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.

[0851] In this invention, the server includes a means for analyzing image data and recognizing specific objects, a means for retrieving information related to the recognized object from a database and generating detailed information using a generative AI model, and a means for personalizing the generated information based on a user's profile information. This allows for real-time provision of detailed information about products in a physical store and personalized information based on the user's profile. Furthermore, by enhancing product recognition and navigation functions, it is possible to support a user's efficient shopping experience.

[0852] A "camera device" is hardware for capturing image data.

[0853] A "wearable device" is a portable device that can be worn and used by a user.

[0854] "Image data" is visual information captured from a camera device.

[0855] A "location information acquisition device" is a device that uses technology such as GPS to identify a user's current location.

[0856] "Communication means" refers to a connection means for transmitting image data and location information to the server.

[0857] A "server" is a computer system that receives, analyzes, and generates data.

[0858] "Image Recognition AI" is an artificial intelligence algorithm that analyzes received image data and recognizes specific objects.

[0859] A "database" is a system for efficiently storing, searching, and managing large amounts of information.

[0860] A "generative AI model" is an artificial intelligence model that generates detailed information based on data.

[0861] "Profile information" is personal information such as a user's past usage history and interests.

[0862] "Personalization" refers to optimizing the information provided based on the user's individual profile information.

[0863] "Display means for displaying information overlaid on the user's field of vision" refers to technology that allows wearable devices such as smart glasses to overlay information on the user's field of vision.

[0864] A "brick and mortar store" is a commercial establishment that exists in a physical location.

[0865] A "navigation feature" is a feature that helps a user locate a particular product within a physical store.

[0866] This invention is a system that uses a wearable device including a camera to analyze image data and location information in real time and provide personalized information to users. This system is mainly composed of three elements: the user, the terminal (wearable device), and the server.

[0867] System Configuration

[0868] 1. Users

[0869] Users wear a wearable device (hereafter referred to as smart glasses) to check products in physical stores and obtain necessary information. User profile information is shared between the smart glasses and a server, and the user's past usage history and interests are stored.

[0870] 2. Device (smart glasses)

[0871] The smart glasses have the following features:

[0872] 1. Camera equipment

[0873] Capture surrounding products and save them as image data.

[0874] 2. Location information acquisition device

[0875] Use GPS to determine the user's current location.

[0876] 3. Means of communication

[0877] Image data and location information are sent to the server.

[0878] 4. Display means

[0879] The information received from the server is displayed superimposed on the user's field of view.

[0880] 3. Server

[0881] The server performs the following process.

[0882] 1. Data Reception

[0883] Receive image data and location information transmitted from the smart glasses.

[0884] 2. Image Analysis

[0885] Use image recognition AI to identify objects in image data.

[0886] 3. Information generation

[0887] Information related to the recognized object is retrieved from a database, and detailed information is generated using a generative AI model.

[0888] 4. Personalization

[0889] Personalize the generated information based on the user's profile information.

[0890] 5. Data Transmission

[0891] Send personalized information to smart glasses.

[0892] Program processing explanation

[0893] User operations and initial settings

[0894] The user puts on the smart glasses, launches a dedicated application, and enters their profile settings and interests to prepare for personalized information provision.

[0895] Image capture and data transmission

[0896] The camera device of the smart glasses captures the surrounding products and creates image data, and the GPS module acquires the current location data, and then transmits the captured image data and location information to the server.

[0897] Data analysis and information generation

[0898] The server analyzes the received image data and location information. It uses image recognition AI (e.g., TensorFlow) to recognize objects in the image. It retrieves information related to the recognized object from a database and generates detailed information using a generative AI model (e.g., GPT-4). The generated information is personalized based on the user's profile information.

[0899] Information presentation and user interaction

[0900] The smart glasses overlay the received information onto the user's field of vision, allowing the user to review the displayed information and request more information via voice commands or eye contact.

[0901] Specific examples

[0902] For example, imagine a user is in the chocolate section of a supermarket. The camera in the smart glasses captures products on the shelf and sends the image data and location information to a server. The server uses image recognition AI to recognize the specific product and retrieves its details from a database. A generative AI model is used to generate product reviews, nutritional information, and pricing information, personalizing it based on the user's profile. The generated information is sent to the smart glasses and displayed in the user's field of view. The user can then view the information and make product selections.

[0903] Prompt Sentence Examples

[0904] "When a user sees a new product in the supermarket, generate personalized details about that product. We'd like a natural language description based on the user's past purchases, allergies, and preferences."

[0905] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0906] Step 1:

[0907] The user puts on the smart glasses and launches the dedicated application. The user's profile information and interests are required as input. This information is stored on the smart glasses and serves as the basis for providing personalized information. As output, the smart glasses prepare the user's profile information and can then connect to the server.

[0908] Step 2:

[0909] The device (smart glasses) uses a camera device to capture surrounding products. The input is visual information (image data) acquired through the camera lens. The output is the acquired image data.

[0910] Step 3:

[0911] The device (smart glasses) uses a GPS location information acquisition device to obtain current location data. The input is a signal from the GPS sensor. The output is current location information.

[0912] Step 4:

[0913] The terminal transmits the captured image data and location information to the server using a communication means. The inputs are the image data and location information generated earlier. The output is transmitted to the server.

[0914] Step 5:

[0915] The server analyzes the received image data and location information. The inputs are the transmitted image data and location information. The server uses image recognition AI (e.g., TensorFlow) to identify objects in the image data. The output is information about the recognized objects.

[0916] Step 6:

[0917] The server retrieves information related to the recognized object from the database and generates detailed information using a generative AI model (e.g., GPT-4). The inputs are information about the object stored in the database and information about the recognized object. The output is the detailed information generated by the generative AI model.

[0918] Step 7:

[0919] The server personalizes the generated information based on the user's profile information. The inputs are the generated details and the user's profile information. The output is personalized details.

[0920] Step 8:

[0921] The server sends personalized information to the smart glasses. As input, there are personalized details. As output, the details are sent to the smart glasses.

[0922] Step 9:

[0923] The device (smart glasses) receives information and displays it over the user's field of view. The input is personalized details sent from the server. The output is the information overlaid on the user's field of view.

[0924] Step 10:

[0925] The user reviews the displayed information and requests more information if necessary. The inputs are the visual information from the smart glasses, as well as the user's voice commands and gaze information. The output is a request for additional information.

[0926] 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.

[0927] This invention is a system that uses a wearable device including a camera to analyze image data and location information in real time and provide personalized information based on the user's emotional data. This system is mainly composed of four elements: the user, the terminal (wearable device), the server, and the emotion engine.

[0928] System Configuration

[0929] 1. Users

[0930] Users wear wearable devices (hereafter referred to as smart glasses) while walking around town or working. User profile information is shared between the smart glasses and a server, and the user's past usage history and interests are stored. In addition, emotion data is collected in real time by an emotion engine.

[0931] 2. Device (smart glasses)

[0932] The smart glasses have the following features:

[0933] 1. Camera equipment

[0934] Capture the surrounding scenery and save it as image data.

[0935] 2. Location information acquisition device

[0936] Use GPS to determine the user's current location.

[0937] 3. Means of communication

[0938] Image data and location information are sent to the server.

[0939] 4. Display means

[0940] The information received from the server is displayed superimposed on the user's field of view.

[0941] 5. Emotion Engine

[0942] The user's voice and facial expressions are analyzed to generate emotional data, which is then sent to the server.

[0943] 3. Server

[0944] The server performs the following process.

[0945] 1. Data Reception

[0946] The image data, location information, and emotion data transmitted from the terminal are received.

[0947] 2. Image Analysis

[0948] Use image recognition AI to recognize objects in image data.

[0949] 3. Information generation

[0950] Information related to the recognized object is obtained from the LY database and GTP database, and information is generated using generation AI.

[0951] 4. Personalization

[0952] The generated information is personalized based on the user's profile information and emotion data obtained from the emotion engine.

[0953] 5. Data Transmission

[0954] Send personalized information to your device.

[0955] Program processing explanation

[0956] User operations and initial settings

[0957] The user puts on the smart glasses and launches the application.

[0958] A user enters information about their interests and preferences in a profile setting screen.

[0959] Image capture and data transmission

[0960] The device (smart glasses) uses a camera device to continuously capture the surrounding scenery and create image data.

[0961] The device uses the GPS module to obtain its current location.

[0962] The emotion engine analyzes the user's voice and facial expressions to generate emotion data.

[0963] The terminal transmits the captured image data, location information, and emotion data to a server.

[0964] Data analysis and information generation

[0965] The server receives the image data, location information, and emotion data transmitted from the terminal.

[0966] The server uses an image analysis module to recognize objects in the image.

[0967] The server retrieves information from the LY and GTP databases related to the recognized object.

[0968] The server uses generation AI to generate detailed information.

[0969] The server personalizes the information based on the user's profile information and emotional data.

[0970] The server returns the generated personalized information to the terminal.

[0971] Information presentation and user interaction

[0972] The information received by the device (smart glasses) is displayed in the user's field of vision.

[0973] The user can review the displayed information and, if they want more details about a particular piece of information, make a request using voice commands or eye control.

[0974] Specific examples

[0975] For example, as a user walks around town, the camera in the smart glasses captures the surrounding scenery. The image data and location information are sent to a server, where image recognition AI identifies specific restaurants. The server retrieves information about the restaurant, such as its menu, reviews, and opening hours, from the LY database and uses generative AI to generate detailed information. This information is personalized based on the user's profile and emotional data and sent back to the smart glasses.

[0976] For example, if the emotion engine recognizes that the user is tired, it will prioritize information about relaxing cafes and rest spots. Conversely, if the user is excited, it will display information about active leisure activities.

[0977] This allows users to obtain the most appropriate information for their situation in real time, allowing them to enjoy walking around town. In business situations, delivery companies can use emotion data to efficiently carry out their work and flexibly respond to sudden changes. The above is an embodiment of the present invention, which provides information according to the user's emotional state and improves the user experience.

[0978] The processing flow will be explained below.

[0979] Program processing steps

[0980] Step 1:

[0981] The user puts on the smart glasses, turns them on, and launches the application.

[0982] A user enters information about their interests and preferences in a profile setting screen.

[0983] Step 2:

[0984] The device (smart glasses) continuously captures the surrounding scenery using a camera device.

[0985] The device obtains current location information using the GPS module.

[0986] Step 3:

[0987] The emotion engine analyzes the user's voice and facial expressions in real time and generates emotion data.

[0988] Voice analysis detects the tone of a user's voice and the rhythm of their speech to identify their emotional state (e.g., joy, anger, sadness, etc.).

[0989] Facial expression analysis involves capturing a user's facial expressions and using emotion analysis algorithms to identify their emotional state.

[0990] Step 4:

[0991] The image data, location information, and emotional data acquired by the device are temporarily stored and transmitted to a server using a communication module.

[0992] Step 5:

[0993] The server receives the image data, location information, and emotion data transmitted from the terminal.

[0994] Step 6:

[0995] The server uses an image analysis module to recognize objects in the image.

[0996] The server retrieves information from the LY and GTP databases related to the recognized object.

[0997] Example: If a specific restaurant is recognized, retrieve its menu, reviews, opening hours, etc.

[0998] Step 7:

[0999] The server uses generation AI to generate detailed information about the recognized objects.

[1000] Step 8:

[1001] The server personalizes the generated details based on the user's profile information and emotion data.

[1002] Example: If the user is tired, provide them with information about cafes and rest spots where they can relax.

[1003] Step 9:

[1004] The server sends the personalized information to the device.

[1005] Step 10:

[1006] The device (smart glasses) analyzes the personalized information received.

[1007] The information analyzed by the device is displayed overlaid on the user's field of vision.

[1008] Step 11:

[1009] If the user checks the displayed information and wants to know more, they can make a request using voice commands or eye movements.

[1010] For example, say the voice command, "Tell me more about this restaurant's menu."

[1011] Step 12:

[1012] The terminal transmits a request from the user to the server through the communication module.

[1013] Step 13:

[1014] The server receives the request, generates additional details and sends them back to the device.

[1015] Step 14:

[1016] The additional information received by the device (smart glasses) is displayed in the user's field of view, providing navigation and further details.

[1017] Examples:

[1018] As a user walks around town, the smartglasses' camera captures the surrounding scenery. The image data and location information are sent to a server, where image recognition AI identifies specific restaurants. The server retrieves information about the restaurant, such as its menu, reviews, and opening hours, from the LY database and uses generative AI to generate detailed information. This information is personalized based on the user's profile and emotional data and sent back to the smartglasses.

[1019] For example, if the emotion engine recognizes that the user is tired, it will prioritize displaying information about relaxing cafes and rest spots. Conversely, if the user is excited, it will display information about active leisure activities. In this way, users can obtain optimal information in real time and enjoy a highly satisfying experience. In business situations, emotional data can also be used to efficiently carry out work and flexibly respond to sudden changes.

[1020] Example 2

[1021] 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."

[1022] Conventional wearable device systems have limited information that users can obtain in real time, making it difficult to provide appropriate information tailored to the user's emotional state and individual interests. Furthermore, due to a lack of personalization of information, it has been difficult to efficiently obtain information that is valuable to the user. Therefore, it is necessary to further improve user convenience and the usefulness of information.

[1023] 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.

[1024] In this invention, the server includes means for analyzing a user's voice and facial expressions to generate emotional data, means for analyzing image data received by the server and recognizing a specific object, means for acquiring information related to the recognized object, means for generating detailed information using a generative AI model, and means for personalizing the generated detailed information based on the user's profile information and emotional data, thereby enabling the provision of appropriate information in real time according to the user's emotional state and individual interests.

[1025] A "camera device" is a device used to capture image data.

[1026] A "wearable device" is an electronic device that can be worn by a user.

[1027] A "location information acquisition device" is a device that acquires information about a user's current location using technology such as GPS.

[1028] "Communication means" refers to a means for transmitting data to other devices or servers.

[1029] "Emotion data" is data relating to the user's emotional state obtained by analyzing the user's voice and facial expressions.

[1030] "Image analysis means" is a means for analyzing captured image data and recognizing specific objects within the image.

[1031] The "information acquisition means" is a means for acquiring information related to a recognized object from a database or the like.

[1032] A "generative AI model" is an algorithm that uses artificial intelligence techniques to generate detailed information based on specific inputs.

[1033] "Personalization means" refers to means for individualizing the generated detailed information based on the user's profile information and emotional data.

[1034] A "display means" is a means for displaying generated or personalized information to the user's view.

[1035] "Profile information" is individual information about a user, such as information about the user's interests and preferences.

[1036] "Voice command" refers to an operation or request made by a user through voice.

[1037] This invention is a system that uses a wearable device including a camera to analyze image data and location information in real time and provide personalized information based on the user's emotional data. This system is mainly composed of four elements: the user, the terminal (wearable device), the server, and the emotion engine.

[1038] System Configuration

[1039] 1. Users

[1040] Users wear wearable devices (hereafter referred to as smart glasses) while walking around town or working. User profile information is shared between the smart glasses and a server, and the user's past usage history and interests are stored. In addition, emotion data is collected in real time by an emotion engine.

[1041] 2. Device (smart glasses)

[1042] The smart glasses have the following features:

[1043] 1. Camera equipment

[1044] Capture the surrounding scenery and save it as image data.

[1045] 2. Location information acquisition device

[1046] Use GPS to determine the user's current location.

[1047] 3. Means of communication

[1048] Image data and location information are sent to the server.

[1049] 4. Display means

[1050] The information received from the server is displayed superimposed on the user's field of view.

[1051] 5. Emotion Engine

[1052] The user's voice and facial expressions are analyzed to generate emotional data, which is then sent to the server.

[1053] 3. Server

[1054] The server performs the following process.

[1055] 1. Data Reception

[1056] The image data, location information, and emotion data transmitted from the terminal are received.

[1057] 2. Image Analysis

[1058] Use image recognition AI to recognize objects in image data.

[1059] 3. Information acquisition

[1060] Information related to the recognized object is retrieved from the database.

[1061] 4. Information generation

[1062] A generative AI model is used to generate detailed information, such as OpenAI's GPT model.

[1063] 5. Personalization

[1064] The generated information is personalized based on the user's profile information and emotion data obtained from the emotion engine.

[1065] 6. Data Transmission

[1066] Send personalized information to your device.

[1067] Program processing explanation

[1068] Image capture and data transmission

[1069] The device (smart glasses) uses a camera device to continuously capture the surrounding scenery and create image data. The device acquires its current location information using a GPS module. The emotion engine analyzes the user's voice and facial expressions to generate emotion data. The device sends the captured image data, location information, and emotion data to a server.

[1070] Data analysis and information generation

[1071] The server receives image data, location information, and emotion data sent from the device. The server uses an image analysis module to recognize objects in the image. The server retrieves information related to the recognized object from a database. The server uses a generative AI model to generate detailed information. The server personalizes the information based on the user's profile information and emotion data. The server sends the generated personalized information to the device.

[1072] Information presentation and user interaction

[1073] The device (smart glasses) displays the received information in the user's field of vision. If the user checks the displayed information and wants more details about a specific piece of information, they can make a request using voice commands or eye movements. In this way, the most appropriate information can be provided based on the user's real-time emotional state and profile information.

[1074] Specific examples

[1075] For example, as a user walks around town, the camera in the smart glasses captures the surrounding scenery and identifies restaurants. The image data and location information are sent to a server, where image recognition AI identifies the specific restaurant. The server retrieves information about the restaurant, such as its menu, reviews, and opening hours, from a database and uses generative AI to generate detailed information. This information is personalized based on the user's profile and emotional data and sent back to the smart glasses.

[1076] For example, if the emotion engine recognizes that the user is tired, it will prioritize information about cafes and rest spots where they can relax. Conversely, if the user is excited, it will display information about active leisure activities. The following is an example of a prompt sentence:

[1077] "Recommend restaurants near my current location"

[1078] "Looking for a relaxing cafe"

[1079] "What live event can I go to tonight?"

[1080] This allows users to obtain the most appropriate information for their situation in real time, allowing them to enjoy walking around town.In business settings, delivery companies can use emotion data to carry out their work efficiently and respond flexibly to sudden changes.

[1081] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1082] System program processing flow

[1083] Step 1: User interaction and initial setup

[1084] Input: The user puts on the smart glasses and launches the application.

[1085] Action: The user powers on the smart glasses and launches the application. The application begins its startup sequence and displays the initial setup screen.

[1086] Output: The smart glasses start up and the profile setting screen is displayed.

[1087] Step 2: Profile Settings

[1088] Input: The user enters information about interests and preferences in a profile setup screen.

[1089] How it works: A user fills out a profile screen that describes their interests, preferences, and general interests. This includes selecting categories and entering text.

[1090] Output: The entered information is sent to the server and a user profile is generated.

[1091] Step 3: Image capture

[1092] Input: A user puts on smart glasses and starts moving.

[1093] Operation: The device (smart glasses) uses a camera device to continuously capture the surrounding scenery and generate image data.

[1094] Output: The generated image data is saved in the internal memory.

[1095] Step 4: Obtaining location information

[1096] Input: A user puts on smart glasses and continues moving.

[1097] Operation: The device (smart glasses) uses the GPS module to obtain current location information. This process is performed automatically at regular intervals.

[1098] Output: The acquired location information is stored in the internal memory.

[1099] Step 5: Emotion data generation

[1100] Input: The user wears the smart glasses and can speak or change their facial expressions.

[1101] How it works: The emotion engine analyzes the user's voice and facial expressions to generate emotion data. Waveform analysis and phoneme analysis are used for voice analysis, and image processing algorithms are used for facial expression analysis.

[1102] Output: The generated emotion data is stored in the internal memory.

[1103] Step 6: Send data

[1104] Input: Generated image data, location information, and emotion data.

[1105] Operation: The device transmits the captured image data, location information, and emotion data to the server. This transmission is performed using wireless communication means.

[1106] Output: The server receives these data.

[1107] Step 7: Receiving Data

[1108] Input: Image data, location information, and emotional data sent from the device.

[1109] Operation: The server receives image data, location information, and emotion data sent from the device.

[1110] Output: The received data is saved in a specific directory on the server.

[1111] Step 8: Image analysis

[1112] Input: Received image data.

[1113] How it works: The server uses an image analysis module to recognize objects in an image, for example using an image recognition algorithm such as YOLO (You Only Look Once).

[1114] Output: Recognized object information is generated.

[1115] Step 9: Information Acquisition

[1116] Input: Recognized object information.

[1117] How it works: The server retrieves information related to the recognized object from a database (e.g., an LY database or a GTP database), typically using an SQL query.

[1118] Output: Relevant information is obtained.

[1119] Step 10: Information Generation

[1120] Input: The relevant information retrieved.

[1121] How it works: The server uses a generative AI model (e.g., OpenAI's GPT model) to generate detailed information. It sends prompts to the model to generate detailed explanations and additional information.

[1122] Output: Detailed information is generated.

[1123] Step 11: Personalize

[1124] Input: Generated details, user profile information, and sentiment data.

[1125] How it works: The server personalizes the generated information based on the user's profile information and emotional data, taking into account the user's current emotional state and past behavioral patterns.

[1126] Output: Personalized information is generated.

[1127] Step 12: Data transmission (retransmission)

[1128] Input: Personalized information.

[1129] Operation: The server transmits the generated personalized information to the terminal. This transmission is also performed using wireless communication means.

[1130] Output: The device receives the personalized information.

[1131] Step 13: Display Information

[1132] Input: Received personalization information.

[1133] How it works: The device (smart glasses) displays the information it receives in the user's field of vision using HUD (head-up display) technology.

[1134] Output: The user sees the personalized information.

[1135] Step 14: User Interaction

[1136] Input: User's reaction to the received personalized information.

[1137] How it works: If the user wants to know more about a particular piece of information, they can make a request using voice commands or eye contact. This request is sent to the server via the device.

[1138] Output: The server receives the new request information and the process repeats, generating the relevant information again.

[1139] Through these steps, this system will be able to provide appropriate information in real time according to the user's emotional state and individual interests.

[1140] (Application example 2)

[1141] 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."

[1142] In today's shopping experience, it is difficult for users to obtain appropriate information in real time based on their interests and emotions. Specifically, it is difficult to instantly find products and services that match their preferences in a store, which reduces shopping satisfaction. Furthermore, when users want to know more about information that interests them, there is a lack of a way to quickly and intuitively obtain detailed information. There is a need for a way to resolve these issues and improve the user experience.

[1143] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1144] In this invention, the server includes an emotion analysis means for analyzing the user's emotion data, a means for generating detailed information using a generative AI model, and a means for personalizing information based on the user's profile information and emotion data, thereby enabling the provision of personalized information based on the user's location information and emotion.

[1145] A "camera device" is a device that is built into a wearable device and captures image data of the surroundings.

[1146] A "location information acquisition device" is a device that identifies the user's current location. It uses GPS or in-store beacons.

[1147] The "communication means" is a means for transmitting captured image data and location information to a server.

[1148] A "server" is a computer system that analyzes received image data and recognizes specific objects.

[1149] A "means for recognizing specific objects" is an algorithm or device that identifies and identifies objects or people based on image data.

[1150] The "means for generating information" is a function that generates information related to a recognized object.

[1151] "Means for generating detailed information using a generative AI model" refers to means for automatically generating detailed information to be provided to a user using an artificial intelligence model.

[1152] The "emotion analysis means that provides user emotion data based on an emotion engine" refers to a device or software that analyzes the user's voice and facial expressions and derives emotion data.

[1153] The "display means" is a device that displays the generated information superimposed on the user's field of vision. It usually includes smart glasses or the like.

[1154] "User profile information" is data including the user's past usage history, interests, personal information, etc.

[1155] "Personalization" means tailoring and individually optimizing the information provided based on each user's individual profile and emotional data.

[1156] "Means for requesting detailed information about specific information using eye movements or voice commands" refers to an operating means for obtaining details about information of interest to the user through eye movements or voice instructions.

[1157] The present invention relates to a system using a wearable device that provides personalized information based on a user's emotional data. This system analyzes image data, location information, and emotional data in real time when the user wears the wearable device, and provides personalized information to the user.

[1158] System Configuration

[1159] User

[1160] A user wears a wearable device (e.g., smart glasses) and uses the device while walking around town or inside a store.

[1161] Device (smart glasses)

[1162] The smart glasses have the following features:

[1163] 1. Camera equipment

[1164] Capture image data of the surroundings in real time.

[1165] 2. Location information acquisition device

[1166] Use GPS or in-store beacons to determine the user's current location.

[1167] 3. Means of communication

[1168] The captured image data, location information, and emotion data are transmitted to a server.

[1169] 4. Display means

[1170] The personalized information received from the server is displayed superimposed on the user's field of view.

[1171] 5. Emotion analysis method

[1172] The system analyzes the user's voice and facial expressions to generate emotional data, which is then sent to the server.

[1173] server

[1174] The server performs the following process.

[1175] 1. Data Reception

[1176] The image data, position information, and emotion data transmitted from the terminal are received.

[1177] 2. Image Analysis

[1178] Image recognition algorithms are used to recognize specific objects within the image data.

[1179] 3. Emotion analysis

[1180] The received emotional data is analyzed to understand the user's emotional state.

[1181] 4. Information generation

[1182] Information related to the recognized object is retrieved from a database and detailed information is generated using a generative AI model.

[1183] 5. Personalization

[1184] The generated information is personalized based on the user's profile information and emotional data.

[1185] 6. Data Transmission

[1186] Send personalized information to your device.

[1187] Program processing explanation

[1188] Hardware

[1189] Camera devices (e.g., cameras built into wearable devices)

[1190] GPS devices (e.g., smartphone GPS modules, in-store beacons)

[1191] Smart glasses (e.g. Google Glass)

[1192] Display device (smart glasses built-in display)

[1193] software

[1194] EmotionRecognizer (emotion analysis library)

[1195] GPS module (location information acquisition library)

[1196] Requests library (HTTP request library)

[1197] Generative AI model (AI model for generating detailed information)

[1198] Data processing and calculation

[1199] 1. Capture image data

[1200] The camera device captures images of the surroundings in real time.

[1201] 2. Obtaining location information

[1202] The user's current location is obtained using a GPS module or beacon.

[1203] 3. Generating Emotion Data

[1204] Emotion data is generated from the user's voice and facial expressions using EmotionRecognizer.

[1205] 4. Data Transmission

[1206] Use the Requests library to send image data, location information, and emotion data to the server.

[1207] 5. Server-side data analysis

[1208] The server analyzes the images based on the received data and recognizes specific objects. It also analyzes the emotional data to understand the user's emotional state.

[1209] 6. Information generation

[1210] Information related to the recognized object is retrieved from a database and detailed information is generated using a generative AI model.

[1211] 7. Personalization

[1212] The generated information is personalized based on the user's profile information and emotional data.

[1213] 8. Information display

[1214] The generated personalized information is displayed on the smart glasses display.

[1215] Specific examples

[1216] Example prompt sentence:

[1217] The user's name is User 1. He is 30 years old and enjoys active shopping. He is currently on the third floor of a department store. He is wearing smart glasses, and the emotion engine recognizes his excitement. Provide him with information that may interest him. His favorite brands are popular, and he is interested in new products.

[1218] Based on these prompts, users can receive information optimized for their emotions and profile in real time. For example, as a user walks through a store, the camera in the smart glasses captures a specific product, and detailed information about that product is instantly displayed on the display. Recommended products and services based on the user's emotional state are also displayed, improving the user's shopping experience.

[1219] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1220] Step 1:

[1221] The user puts on the smart glasses and launches the application.

[1222] Input: User profile information (interests, favorite brands, etc.)

[1223] Output: Profile information is shared between smart glasses and the server.

[1224] Specific operation: The user puts on the smart glasses, launches the app, and enters information on the profile settings screen.

[1225] Step 2:

[1226] The device (smart glasses) uses a camera device to capture image data of the surroundings in real time.

[1227] Input: Surrounding landscape

[1228] Output: Real-time image data

[1229] How it works: The camera built into the smart glasses continuously captures images and stores them in its internal memory.

[1230] Step 3:

[1231] The device uses the GPS module to obtain its current location.

[1232] Input: Current location satellite data

[1233] Output: Current location information

[1234] Specific operation: The GPS module receives satellite data and calculates latitude and longitude.

[1235] Step 4:

[1236] The emotion engine analyzes the user's voice and facial expressions to generate emotion data.

[1237] Input: User's voice and facial expression data

[1238] Output: Emotion data (e.g., joy, anger, surprise, etc.)

[1239] How it works: The smart glasses' microphone and camera capture voice and facial expressions, and the emotion engine analyzes this data to infer emotions.

[1240] Step 5:

[1241] The terminal transmits the captured image data, location information, and emotion data to a server.

[1242] Input: image data, location information, emotion data

[1243] Output: Data sent to the server

[1244] Specific operation: The communication module uploads data to the server using an HTTP request.

[1245] Step 6:

[1246] The server analyzes the received image data and recognizes specific objects.

[1247] Input: Image data

[1248] Output: Recognized object information

[1249] What it does: Image recognition algorithms on the server analyze the image and identify the object.

[1250] Step 7:

[1251] The server analyzes the received emotional data and understands the user's emotional state.

[1252] Input: Emotion data

[1253] Output: Emotional state (e.g. "Excited")

[1254] Specific operation: Emotion analysis software on the server analyzes the emotion data and evaluates the user's emotional state.

[1255] Step 8:

[1256] The server retrieves information related to a specific object from a database and generates detailed information using a generative AI model.

[1257] Input: Recognized object information

[1258] Output:Detailed information

[1259] How it works: The server retrieves information related to the object from the database and generates detailed information using a generative AI model.

[1260] Step 9:

[1261] The server personalizes the information based on the user's profile information and emotional data.

[1262] Input: Details, profile information, emotional data

[1263] Output: Personalized information

[1264] Specific operation: The server customizes detailed information to suit the user based on profile information and emotional data.

[1265] Step 10:

[1266] The server sends the personalized information to the device.

[1267] Input: Personalized Information

[1268] Output: Information sent to the terminal

[1269] Specific operation: The server transmits the personalized information to the terminal via the communication module.

[1270] Step 11:

[1271] The information received by the device (smart glasses) is displayed overlaid on the user's field of vision.

[1272] Input: Personalized Information

[1273] Output: Information displayed in the user's field of view

[1274] Specific operation: The smart glasses display device displays the received information as an overlay.

[1275] Step 12:

[1276] The user uses gaze or voice commands to request detailed information about a specific item.

[1277] Input: Voice commands and gaze data

[1278] Output: Request for more information

[1279] Specific actions: The user sends a request by speaking a specific command into the smart glasses or by directing their gaze in a specific location.

[1280] 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.

[1281] 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.

[1282] 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.

[1283] [Third embodiment]

[1284] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1285] 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.

[1286] 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).

[1287] 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.

[1288] 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.

[1289] 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).

[1290] 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.

[1291] 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.

[1292] 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.

[1293] 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.

[1294] 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.

[1295] 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."

[1296] This invention is a system that uses a wearable device including a camera to analyze image data and location information in real time and provide personalized information to users. This system is mainly composed of three elements: the user, the terminal (wearable device), and the server.

[1297] System Configuration

[1298] 1. Users

[1299] Users wear wearable devices (hereafter referred to as smart glasses) while walking around town or working. User profile information is shared between the smart glasses and a server, and the user's past usage history and interests are stored.

[1300] 2. Device (smart glasses)

[1301] The smart glasses have the following features:

[1302] 1. Camera equipment

[1303] Capture the surrounding scenery and save it as image data.

[1304] 2. Location information acquisition device

[1305] Use GPS to determine the user's current location.

[1306] 3. Means of communication

[1307] Image data and location information are sent to the server.

[1308] 4. Display means

[1309] The information received from the server is displayed superimposed on the user's field of view.

[1310] 3. Server

[1311] The server performs the following process.

[1312] 1. Data Reception

[1313] Receive image data and location information transmitted from the smart glasses.

[1314] 2. Image Analysis

[1315] Use image recognition AI to identify objects in image data.

[1316] 3. Information generation

[1317] Information related to the recognized object is obtained from the LY database and GTP database, and information is generated using generation AI.

[1318] 4. Personalization

[1319] Personalize the generated information based on the user's profile information.

[1320] 5. Data Transmission

[1321] Send personalized information to smart glasses.

[1322] Program processing explanation

[1323] User operations and initial settings

[1324] The user puts on the smart glasses and launches the application.

[1325] Enter your profile settings and interests.

[1326] Image capture and data transmission

[1327] The device (smart glasses) uses a camera device to capture the surrounding scenery and create image data.

[1328] The device uses the GPS module to obtain current location data.

[1329] The device transmits the captured image data and location information to the server.

[1330] Data analysis and information generation

[1331] The server analyzes the image data and location information received from the device.

[1332] The server uses image recognition AI to recognize objects in the image.

[1333] The server retrieves information from the LY and GTP databases related to the recognized object.

[1334] The server uses generation AI to generate detailed information.

[1335] The server personalizes the information based on the user's profile information.

[1336] The server returns the generated information to the terminal.

[1337] Information presentation and user interaction

[1338] The information received by the device (smart glasses) is displayed in the user's field of vision.

[1339] The user reviews the displayed information and requests more details using voice commands or gaze.

[1340] Specific examples

[1341] For example, as a user walks around town, the camera in the smart glasses captures the surrounding scenery. The image data and location information are sent to a server, where image recognition AI identifies specific restaurants. The server retrieves information about the restaurant, such as its menu, reviews, and opening hours, from the LY database and uses generative AI to generate detailed information. This information is personalized based on the user's profile and sent back to the smart glasses.

[1342] Through the smart glasses, users can see whether a particular restaurant suits their tastes, and detailed menu information and reviews are overlaid on the visuals, helping them make an intuitive choice. In this way, users receive personalized, helpful information in real time, facilitating decision-making.

[1343] Smart glasses can also be used in business settings, allowing delivery personnel, for example, to obtain detailed destination information and efficient routes in real time, enabling smoother operations. Even if sudden changes occur, they can be quickly responded to based on shared information.

[1344] The above is an embodiment of the present invention, which significantly improves user convenience and efficiency in obtaining information.

[1345] The processing flow will be explained below.

[1346] Program processing steps

[1347] Step 1:

[1348] The user puts on the smart glasses, turns them on, and launches the application.

[1349] A user enters information about their interests and preferences in a profile setting screen.

[1350] Step 2:

[1351] The device (smart glasses) continuously captures the surrounding scenery using a camera device.

[1352] The device obtains current location information using the GPS module.

[1353] Step 3:

[1354] The image data and location information acquired by the device are temporarily stored and then sent to the server using a communication module.

[1355] Step 4:

[1356] The server receives the image data and location information sent from the terminal.

[1357] The server uses an image analysis module to recognize objects in the image.

[1358] Step 5:

[1359] The server retrieves information related to the recognized object from the LY database and the GTP database.

[1360] The server uses a generation AI to generate detailed information about the recognized object.

[1361] Step 6:

[1362] The server refers to the user's profile information and personalizes the generated information.

[1363] The server sends the personalized information to the device.

[1364] Step 7:

[1365] The terminal analyzes the personalized information received from the server.

[1366] The information analyzed by the device is displayed overlaid on the user's field of vision.

[1367] Step 8:

[1368] When a user checks the information displayed on the smart glasses and wants to know more about a particular piece of information, they can make a request using voice commands or eye movements.

[1369] Step 9:

[1370] The terminal transmits a request from the user to the server through the communication module.

[1371] Step 10:

[1372] The server receives the request, generates additional details and sends them back to the device.

[1373] Step 11:

[1374] The additional information received by the device is displayed in the user's field of view, providing navigation and further details.

[1375] This allows users to obtain detailed information about their surroundings in real time based on visually overlaid information, enabling smooth decision-making.Similarly, in business situations, users can quickly obtain necessary information and carry out their work efficiently.

[1376] Example 1

[1377] 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."

[1378] Conventional wearable device systems have faced the issue of not being able to obtain necessary information in a timely manner due to a lack of real-time information provision and personalization based on user profiles. Furthermore, the generation of specific detailed information based on image data and location information often lacks precision, resulting in reduced user convenience.

[1379] 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.

[1380] In this invention, the server includes a means for analyzing the received image data and recognizing a specific object, a means for acquiring information related to the recognized object from an accumulation database, and a means for generating detailed information using a generative AI model based on the acquired information, thereby enabling real-time generation and personalization of detailed information.

[1381] A "camera device" is a device for photographing surrounding scenery and objects.

[1382] "Wearable device" is a general term for electronic devices that can be worn by the user.

[1383] "Image data" is data that includes visual information captured by a camera device.

[1384] A "location information acquisition device" is a device that uses GPS or other location measurement technology to determine a current location.

[1385] A "communication means" is a device that has the function of transmitting image data and location information to a server.

[1386] A "server" is a high-performance computer that processes and manages data over a network.

[1387] "Image analysis" is a process of analyzing received image data and recognizing objects.

[1388] An "object" refers to a specific object or location that exists within image data.

[1389] An "accumulation database" is a database that stores acquired information and allows it to be searched and used as needed.

[1390] A "generative AI model" is an algorithm or system that uses artificial intelligence to generate detailed information.

[1391] "Detailed information" is specific explanations and recommended information generated based on image data and location information.

[1392] "Personalization" refers to customizing information based on a user's profile information.

[1393] The "display means" is a device for displaying information superimposed on the user's field of vision.

[1394] "Profile information" is information relating to a user's personal interests and history.

[1395] This invention is a system that uses a wearable device including a camera device to analyze image data and location information in real time and provide personalized information to the user. This system mainly consists of three elements: the user, the terminal (wearable device), and the server. Specifically, the system uses the following hardware and software:

[1396] System Configuration

[1397] 1. Users

[1398] Users wear wearable devices (hereafter referred to as smart glasses) while walking around town or working. User profile information is shared between the smart glasses and a server, and the user's past usage history and interests are stored.

[1399] 2. Device (smart glasses)

[1400] The smart glasses have the following features:

[1401] 1. Camera equipment

[1402] Capture the surrounding scenery and save it as image data.

[1403] 2. Location information acquisition device

[1404] Use GPS to determine the user's current location.

[1405] 3. Means of communication

[1406] Image data and location information are sent to the server.

[1407] 4. Display means

[1408] The information received from the server is displayed superimposed on the user's field of view.

[1409] 3. Server

[1410] The server performs the following process.

[1411] 1. Data Reception

[1412] Receive image data and location information transmitted from the smart glasses.

[1413] 2. Image Analysis

[1414] It uses image recognition AI to identify objects in image data, specifically using Google Cloud Vision API, for example.

[1415] 3. Information generation

[1416] Information related to the recognized object is obtained from the accumulated database and external databases, and detailed information is generated using a generative AI model (e.g., OpenAI's GPT-4).

[1417] 4. Personalization

[1418] Personalize the generated information based on the user's profile information.

[1419] 5. Data Transmission

[1420] Send personalized information to smart glasses.

[1421] Specific examples

[1422] For example, as a user walks around town, the camera in the smart glasses captures the surrounding scenery. The image data and location information are sent to a server, where the Google Cloud Vision API identifies specific restaurants. The server retrieves information about the restaurant, such as its menu, reviews, and opening hours, from a database and uses a generative AI model (e.g., GPT-4) to generate detailed information. This information is personalized based on the user's profile and sent back to the smart glasses.

[1423] Through the smart glasses, users can see whether a particular restaurant suits their tastes, and detailed menu information and reviews are overlaid on the visuals, helping them make an intuitive choice. In this way, users receive personalized, helpful information in real time, facilitating decision-making.

[1424] Smart glasses can also be used in business settings, allowing delivery personnel, for example, to obtain detailed destination information and efficient routes in real time, enabling smoother operations. Even if sudden changes occur, they can be quickly responded to based on shared information.

[1425] Prompt Sentence Examples

[1426] If you use a generation AI, the prompt sentence is shown below as an example.

[1427] 1. Prompt to generate restaurant details:

[1428] Input: Restaurant name, menu items, hours, review rating

[1429] Answer: Create the following details: [restaurant name] overview, popular menu items, opening hours, what makes it great, and user review highlights.

[1430] 2. Information generation prompt for delivery agents:

[1431] Input: Delivery address, landmarks along the way, traffic conditions

[1432] Answer: Detailed route directions and landmark information along the way to help couriers reach their destination in the most efficient and smoothest way possible.

[1433] This is expected to significantly improve user convenience and the efficiency of information acquisition.

[1434] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1435] Step 1:

[1436] Initial setup and startup

[1437] The user puts on the smart glasses and launches the application. The user taps the application icon to launch it and enters their profile information and interests. This allows the user's personal setting information to be shared between the smart glasses and the server.

[1438] Input: User profile information, interests

[1439] Output: Save the setting information to the smart glasses.

[1440] Step 2:

[1441] Image capture and location acquisition

[1442] The device (smart glasses) uses a camera device to capture the surrounding scenery and create image data, and also uses a GPS module to obtain current location information.

[1443] Input: Surrounding scenery, current location

[1444] Output: Captured image data, location information

[1445] Step 3:

[1446] Data transmission

[1447] The device sends the captured image data and location information to a server, and the communication module in the smart glasses uploads the data using Wi-Fi or 4G / 5G networks.

[1448] Input: Image data, location information

[1449] Output: Data sent (reaches the server)

[1450] Step 4:

[1451] Data reception and analysis

[1452] The server analyzes the image data and location information received from the device, adds the received data to a dedicated processing queue, and uses image recognition AI (such as Google Cloud Vision API) to identify objects in the image.

[1453] Input: Image data, location information

[1454] Output: Recognized object information

[1455] Step 5:

[1456] information generation

[1457] The server retrieves information related to the recognized object from the stored database and external databases, then generates detailed information using a generative AI model (e.g., OpenAI's GPT-4).

[1458] Input: Recognized object information, accumulated database information

[1459] Output: Detailed information generated

[1460] Step 6:

[1461] Personalizing Information

[1462] The server personalizes the generated information based on the user's profile information, providing information that is relevant to the user's interests and past usage history.

[1463] Input: Generated details, user profile information

[1464] Output: personalized information

[1465] Step 7:

[1466] Data transmission and information display

[1467] The server sends personalized information to the device (smart glasses), which receives the information and displays it over the user's field of vision.

[1468] Input: Personalized Information

[1469] Output: Information displayed in the field of view of the smart glasses

[1470] Step 8:

[1471] User Interaction

[1472] The user can check the displayed information and request more details using voice commands or gaze. Voice commands are given using words such as "Show me more details," and the microphone in the smart glasses recognizes this and takes appropriate action.

[1473] Input: Voice command, gaze information

[1474] Output: Updated display information

[1475] (Application example 1)

[1476] 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."

[1477] Current information provision systems using wearable devices have challenges in that it is difficult for users to obtain detailed product information in real time in physical stores, and they are unable to personalize information based on individual users' preferences and past purchase history. In particular, they lack product recognition and navigation functions in physical stores, which often limit users' shopping experiences. Therefore, the development of a new system that significantly improves user convenience is desirable.

[1478] 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.

[1479] In this invention, the server includes a means for analyzing image data and recognizing specific objects, a means for retrieving information related to the recognized object from a database and generating detailed information using a generative AI model, and a means for personalizing the generated information based on a user's profile information. This allows for real-time provision of detailed information about products in a physical store and personalized information based on the user's profile. Furthermore, by enhancing product recognition and navigation functions, it is possible to support a user's efficient shopping experience.

[1480] A "camera device" is hardware for capturing image data.

[1481] A "wearable device" is a portable device that can be worn and used by a user.

[1482] "Image data" is visual information captured from a camera device.

[1483] A "location information acquisition device" is a device that uses technology such as GPS to identify a user's current location.

[1484] "Communication means" refers to a connection means for transmitting image data and location information to the server.

[1485] A "server" is a computer system that receives, analyzes, and generates data.

[1486] "Image Recognition AI" is an artificial intelligence algorithm that analyzes received image data and recognizes specific objects.

[1487] A "database" is a system for efficiently storing, searching, and managing large amounts of information.

[1488] A "generative AI model" is an artificial intelligence model that generates detailed information based on data.

[1489] "Profile information" is personal information such as a user's past usage history and interests.

[1490] "Personalization" refers to optimizing the information provided based on the user's individual profile information.

[1491] "Display means for displaying information overlaid on the user's field of vision" refers to technology that allows wearable devices such as smart glasses to overlay information on the user's field of vision.

[1492] A "brick and mortar store" is a commercial establishment that exists in a physical location.

[1493] A "navigation feature" is a feature that helps a user locate a particular product within a physical store.

[1494] This invention is a system that uses a wearable device including a camera to analyze image data and location information in real time and provide personalized information to users. This system is mainly composed of three elements: the user, the terminal (wearable device), and the server.

[1495] System Configuration

[1496] 1. Users

[1497] Users wear a wearable device (hereafter referred to as smart glasses) to check products in physical stores and obtain necessary information. User profile information is shared between the smart glasses and a server, and the user's past usage history and interests are stored.

[1498] 2. Device (smart glasses)

[1499] The smart glasses have the following features:

[1500] 1. Camera equipment

[1501] Capture surrounding products and save them as image data.

[1502] 2. Location information acquisition device

[1503] Use GPS to determine the user's current location.

[1504] 3. Means of communication

[1505] Image data and location information are sent to the server.

[1506] 4. Display means

[1507] The information received from the server is displayed superimposed on the user's field of view.

[1508] 3. Server

[1509] The server performs the following process.

[1510] 1. Data Reception

[1511] Receive image data and location information transmitted from the smart glasses.

[1512] 2. Image Analysis

[1513] Use image recognition AI to identify objects in image data.

[1514] 3. Information generation

[1515] Information related to the recognized object is retrieved from a database, and detailed information is generated using a generative AI model.

[1516] 4. Personalization

[1517] Personalize the generated information based on the user's profile information.

[1518] 5. Data Transmission

[1519] Send personalized information to smart glasses.

[1520] Program processing explanation

[1521] User operations and initial settings

[1522] The user puts on the smart glasses, launches a dedicated application, and enters their profile settings and interests to prepare for personalized information provision.

[1523] Image capture and data transmission

[1524] The camera device of the smart glasses captures the surrounding products and creates image data, and the GPS module acquires the current location data, and then transmits the captured image data and location information to the server.

[1525] Data analysis and information generation

[1526] The server analyzes the received image data and location information. It uses image recognition AI (e.g., TensorFlow) to recognize objects in the image. It retrieves information related to the recognized object from a database and generates detailed information using a generative AI model (e.g., GPT-4). The generated information is personalized based on the user's profile information.

[1527] Information presentation and user interaction

[1528] The smart glasses overlay the received information onto the user's field of vision, allowing the user to review the displayed information and request more information via voice commands or eye contact.

[1529] Specific examples

[1530] For example, imagine a user is in the chocolate section of a supermarket. The camera in the smart glasses captures products on the shelf and sends the image data and location information to a server. The server uses image recognition AI to recognize the specific product and retrieves its details from a database. A generative AI model is used to generate product reviews, nutritional information, and pricing information, personalizing it based on the user's profile. The generated information is sent to the smart glasses and displayed in the user's field of view. The user can then view the information and make product selections.

[1531] Prompt Sentence Examples

[1532] "When a user sees a new product in the supermarket, generate personalized details about that product. We'd like a natural language description based on the user's past purchases, allergies, and preferences."

[1533] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1534] Step 1:

[1535] The user puts on the smart glasses and launches the dedicated application. The user's profile information and interests are required as input. This information is stored on the smart glasses and serves as the basis for providing personalized information. As output, the smart glasses prepare the user's profile information and can then connect to the server.

[1536] Step 2:

[1537] The device (smart glasses) uses a camera device to capture surrounding products. The input is visual information (image data) acquired through the camera lens. The output is the acquired image data.

[1538] Step 3:

[1539] The device (smart glasses) uses a GPS location information acquisition device to obtain current location data. The input is a signal from the GPS sensor. The output is current location information.

[1540] Step 4:

[1541] The terminal transmits the captured image data and location information to the server using a communication means. The inputs are the image data and location information generated earlier. The output is transmitted to the server.

[1542] Step 5:

[1543] The server analyzes the received image data and location information. The inputs are the transmitted image data and location information. The server uses image recognition AI (e.g., TensorFlow) to identify objects in the image data. The output is information about the recognized objects.

[1544] Step 6:

[1545] The server retrieves information related to the recognized object from the database and generates detailed information using a generative AI model (e.g., GPT-4). The inputs are information about the object stored in the database and information about the recognized object. The output is the detailed information generated by the generative AI model.

[1546] Step 7:

[1547] The server personalizes the generated information based on the user's profile information. The inputs are the generated details and the user's profile information. The output is personalized details.

[1548] Step 8:

[1549] The server sends personalized information to the smart glasses. As input, there are personalized details. As output, the details are sent to the smart glasses.

[1550] Step 9:

[1551] The device (smart glasses) receives information and displays it over the user's field of view. The input is personalized details sent from the server. The output is the information overlaid on the user's field of view.

[1552] Step 10:

[1553] The user reviews the displayed information and requests more information if necessary. The inputs are the visual information from the smart glasses, as well as the user's voice commands and gaze information. The output is a request for additional information.

[1554] 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.

[1555] This invention is a system that uses a wearable device including a camera to analyze image data and location information in real time and provide personalized information based on the user's emotional data. This system is mainly composed of four elements: the user, the terminal (wearable device), the server, and the emotion engine.

[1556] System Configuration

[1557] 1. Users

[1558] Users wear wearable devices (hereafter referred to as smart glasses) while walking around town or working. User profile information is shared between the smart glasses and a server, and the user's past usage history and interests are stored. In addition, emotion data is collected in real time by an emotion engine.

[1559] 2. Device (smart glasses)

[1560] The smart glasses have the following features:

[1561] 1. Camera equipment

[1562] Capture the surrounding scenery and save it as image data.

[1563] 2. Location information acquisition device

[1564] Use GPS to determine the user's current location.

[1565] 3. Means of communication

[1566] Image data and location information are sent to the server.

[1567] 4. Display means

[1568] The information received from the server is displayed superimposed on the user's field of view.

[1569] 5. Emotion Engine

[1570] The user's voice and facial expressions are analyzed to generate emotional data, which is then sent to the server.

[1571] 3. Server

[1572] The server performs the following process.

[1573] 1. Data Reception

[1574] The image data, location information, and emotion data transmitted from the terminal are received.

[1575] 2. Image Analysis

[1576] Use image recognition AI to recognize objects in image data.

[1577] 3. Information generation

[1578] Information related to the recognized object is obtained from the LY database and GTP database, and information is generated using generation AI.

[1579] 4. Personalization

[1580] The generated information is personalized based on the user's profile information and emotion data obtained from the emotion engine.

[1581] 5. Data Transmission

[1582] Send personalized information to your device.

[1583] Program processing explanation

[1584] User operations and initial settings

[1585] The user puts on the smart glasses and launches the application.

[1586] A user enters information about their interests and preferences in a profile setting screen.

[1587] Image capture and data transmission

[1588] The device (smart glasses) uses a camera device to continuously capture the surrounding scenery and create image data.

[1589] The device uses the GPS module to obtain its current location.

[1590] The emotion engine analyzes the user's voice and facial expressions to generate emotion data.

[1591] The terminal transmits the captured image data, location information, and emotion data to a server.

[1592] Data analysis and information generation

[1593] The server receives the image data, location information, and emotion data transmitted from the terminal.

[1594] The server uses an image analysis module to recognize objects in the image.

[1595] The server retrieves information from the LY and GTP databases related to the recognized object.

[1596] The server uses generation AI to generate detailed information.

[1597] The server personalizes the information based on the user's profile information and emotional data.

[1598] The server returns the generated personalized information to the terminal.

[1599] Information presentation and user interaction

[1600] The information received by the device (smart glasses) is displayed in the user's field of vision.

[1601] The user can review the displayed information and, if they want more details about a particular piece of information, make a request using voice commands or eye control.

[1602] Specific examples

[1603] For example, as a user walks around town, the camera in the smart glasses captures the surrounding scenery. The image data and location information are sent to a server, where image recognition AI identifies specific restaurants. The server retrieves information about the restaurant, such as its menu, reviews, and opening hours, from the LY database and uses generative AI to generate detailed information. This information is personalized based on the user's profile and emotional data and sent back to the smart glasses.

[1604] For example, if the emotion engine recognizes that the user is tired, it will prioritize information about relaxing cafes and rest spots. Conversely, if the user is excited, it will display information about active leisure activities.

[1605] This allows users to obtain the most appropriate information for their situation in real time, allowing them to enjoy walking around town. In business situations, delivery companies can use emotion data to efficiently carry out their work and flexibly respond to sudden changes. The above is an embodiment of the present invention, which provides information according to the user's emotional state and improves the user experience.

[1606] The processing flow will be explained below.

[1607] Program processing steps

[1608] Step 1:

[1609] The user puts on the smart glasses, turns them on, and launches the application.

[1610] A user enters information about their interests and preferences in a profile setting screen.

[1611] Step 2:

[1612] The device (smart glasses) continuously captures the surrounding scenery using a camera device.

[1613] The device obtains current location information using the GPS module.

[1614] Step 3:

[1615] The emotion engine analyzes the user's voice and facial expressions in real time and generates emotion data.

[1616] Voice analysis detects the tone of a user's voice and the rhythm of their speech to identify their emotional state (e.g., joy, anger, sadness, etc.).

[1617] Facial expression analysis involves capturing a user's facial expressions and using emotion analysis algorithms to identify their emotional state.

[1618] Step 4:

[1619] The image data, location information, and emotional data acquired by the device are temporarily stored and transmitted to a server using a communication module.

[1620] Step 5:

[1621] The server receives the image data, location information, and emotion data transmitted from the terminal.

[1622] Step 6:

[1623] The server uses an image analysis module to recognize objects in the image.

[1624] The server retrieves information from the LY and GTP databases related to the recognized object.

[1625] Example: If a specific restaurant is recognized, retrieve its menu, reviews, opening hours, etc.

[1626] Step 7:

[1627] The server uses generation AI to generate detailed information about the recognized objects.

[1628] Step 8:

[1629] The server personalizes the generated details based on the user's profile information and emotion data.

[1630] Example: If the user is tired, provide them with information about cafes and rest spots where they can relax.

[1631] Step 9:

[1632] The server sends the personalized information to the device.

[1633] Step 10:

[1634] The device (smart glasses) analyzes the personalized information received.

[1635] The information analyzed by the device is displayed overlaid on the user's field of vision.

[1636] Step 11:

[1637] If the user checks the displayed information and wants to know more, they can make a request using voice commands or eye movements.

[1638] For example, say the voice command, "Tell me more about this restaurant's menu."

[1639] Step 12:

[1640] The terminal transmits a request from the user to the server through the communication module.

[1641] Step 13:

[1642] The server receives the request, generates additional details and sends them back to the device.

[1643] Step 14:

[1644] The additional information received by the device (smart glasses) is displayed in the user's field of view, providing navigation and further details.

[1645] Examples:

[1646] As a user walks around town, the smartglasses' camera captures the surrounding scenery. The image data and location information are sent to a server, where image recognition AI identifies specific restaurants. The server retrieves information about the restaurant, such as its menu, reviews, and opening hours, from the LY database and uses generative AI to generate detailed information. This information is personalized based on the user's profile and emotional data and sent back to the smartglasses.

[1647] For example, if the emotion engine recognizes that the user is tired, it will prioritize displaying information about relaxing cafes and rest spots. Conversely, if the user is excited, it will display information about active leisure activities. In this way, users can obtain optimal information in real time and enjoy a highly satisfying experience. In business situations, emotional data can also be used to efficiently carry out work and flexibly respond to sudden changes.

[1648] Example 2

[1649] 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."

[1650] Conventional wearable device systems have limited information that users can obtain in real time, making it difficult to provide appropriate information tailored to the user's emotional state and individual interests. Furthermore, due to a lack of personalization of information, it has been difficult to efficiently obtain information that is valuable to the user. Therefore, it is necessary to further improve user convenience and the usefulness of information.

[1651] 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.

[1652] In this invention, the server includes means for analyzing a user's voice and facial expressions to generate emotional data, means for analyzing image data received by the server and recognizing a specific object, means for acquiring information related to the recognized object, means for generating detailed information using a generative AI model, and means for personalizing the generated detailed information based on the user's profile information and emotional data, thereby enabling the provision of appropriate information in real time according to the user's emotional state and individual interests.

[1653] A "camera device" is a device used to capture image data.

[1654] A "wearable device" is an electronic device that can be worn by a user.

[1655] A "location information acquisition device" is a device that acquires information about a user's current location using technology such as GPS.

[1656] "Communication means" refers to a means for transmitting data to other devices or servers.

[1657] "Emotion data" is data relating to the user's emotional state obtained by analyzing the user's voice and facial expressions.

[1658] "Image analysis means" is a means for analyzing captured image data and recognizing specific objects within the image.

[1659] The "information acquisition means" is a means for acquiring information related to a recognized object from a database or the like.

[1660] A "generative AI model" is an algorithm that uses artificial intelligence techniques to generate detailed information based on specific inputs.

[1661] "Personalization means" refers to means for individualizing the generated detailed information based on the user's profile information and emotional data.

[1662] A "display means" is a means for displaying generated or personalized information to the user's view.

[1663] "Profile information" is individual information about a user, such as information about the user's interests and preferences.

[1664] "Voice command" refers to an operation or request made by a user through voice.

[1665] This invention is a system that uses a wearable device including a camera to analyze image data and location information in real time and provide personalized information based on the user's emotional data. This system is mainly composed of four elements: the user, the terminal (wearable device), the server, and the emotion engine.

[1666] System Configuration

[1667] 1. Users

[1668] Users wear wearable devices (hereafter referred to as smart glasses) while walking around town or working. User profile information is shared between the smart glasses and a server, and the user's past usage history and interests are stored. In addition, emotion data is collected in real time by an emotion engine.

[1669] 2. Device (smart glasses)

[1670] The smart glasses have the following features:

[1671] 1. Camera equipment

[1672] Capture the surrounding scenery and save it as image data.

[1673] 2. Location information acquisition device

[1674] Use GPS to determine the user's current location.

[1675] 3. Means of communication

[1676] Image data and location information are sent to the server.

[1677] 4. Display means

[1678] The information received from the server is displayed superimposed on the user's field of view.

[1679] 5. Emotion Engine

[1680] The user's voice and facial expressions are analyzed to generate emotional data, which is then sent to the server.

[1681] 3. Server

[1682] The server performs the following process.

[1683] 1. Data Reception

[1684] The image data, location information, and emotion data transmitted from the terminal are received.

[1685] 2. Image Analysis

[1686] Use image recognition AI to recognize objects in image data.

[1687] 3. Information acquisition

[1688] Information related to the recognized object is retrieved from the database.

[1689] 4. Information generation

[1690] A generative AI model is used to generate detailed information, such as OpenAI's GPT model.

[1691] 5. Personalization

[1692] The generated information is personalized based on the user's profile information and emotion data obtained from the emotion engine.

[1693] 6. Data Transmission

[1694] Send personalized information to your device.

[1695] Program processing explanation

[1696] Image capture and data transmission

[1697] The device (smart glasses) uses a camera device to continuously capture the surrounding scenery and create image data. The device acquires its current location information using a GPS module. The emotion engine analyzes the user's voice and facial expressions to generate emotion data. The device sends the captured image data, location information, and emotion data to a server.

[1698] Data analysis and information generation

[1699] The server receives image data, location information, and emotion data sent from the device. The server uses an image analysis module to recognize objects in the image. The server retrieves information related to the recognized object from a database. The server uses a generative AI model to generate detailed information. The server personalizes the information based on the user's profile information and emotion data. The server sends the generated personalized information to the device.

[1700] Information presentation and user interaction

[1701] The device (smart glasses) displays the received information in the user's field of vision. If the user checks the displayed information and wants more details about a specific piece of information, they can make a request using voice commands or eye movements. In this way, the most appropriate information can be provided based on the user's real-time emotional state and profile information.

[1702] Specific examples

[1703] For example, as a user walks around town, the camera in the smart glasses captures the surrounding scenery and identifies restaurants. The image data and location information are sent to a server, where image recognition AI identifies the specific restaurant. The server retrieves information about the restaurant, such as its menu, reviews, and opening hours, from a database and uses generative AI to generate detailed information. This information is personalized based on the user's profile and emotional data and sent back to the smart glasses.

[1704] For example, if the emotion engine recognizes that the user is tired, it will prioritize information about cafes and rest spots where they can relax. Conversely, if the user is excited, it will display information about active leisure activities. The following is an example of a prompt sentence:

[1705] "Recommend restaurants near my current location"

[1706] "Looking for a relaxing cafe"

[1707] "What live event can I go to tonight?"

[1708] This allows users to obtain the most appropriate information for their situation in real time, allowing them to enjoy walking around town.In business settings, delivery companies can use emotion data to carry out their work efficiently and respond flexibly to sudden changes.

[1709] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1710] System program processing flow

[1711] Step 1: User interaction and initial setup

[1712] Input: The user puts on the smart glasses and launches the application.

[1713] Action: The user powers on the smart glasses and launches the application. The application begins its startup sequence and displays the initial setup screen.

[1714] Output: The smart glasses start up and the profile setting screen is displayed.

[1715] Step 2: Profile Settings

[1716] Input: The user enters information about interests and preferences in a profile setup screen.

[1717] How it works: A user fills out a profile screen that describes their interests, preferences, and general interests. This includes selecting categories and entering text.

[1718] Output: The entered information is sent to the server and a user profile is generated.

[1719] Step 3: Image capture

[1720] Input: A user puts on smart glasses and starts moving.

[1721] Operation: The device (smart glasses) uses a camera device to continuously capture the surrounding scenery and generate image data.

[1722] Output: The generated image data is saved in the internal memory.

[1723] Step 4: Obtaining location information

[1724] Input: A user puts on smart glasses and continues moving.

[1725] Operation: The device (smart glasses) uses the GPS module to obtain current location information. This process is performed automatically at regular intervals.

[1726] Output: The acquired location information is stored in the internal memory.

[1727] Step 5: Emotion data generation

[1728] Input: The user wears the smart glasses and can speak or change their facial expressions.

[1729] How it works: The emotion engine analyzes the user's voice and facial expressions to generate emotion data. Waveform analysis and phoneme analysis are used for voice analysis, and image processing algorithms are used for facial expression analysis.

[1730] Output: The generated emotion data is stored in the internal memory.

[1731] Step 6: Send data

[1732] Input: Generated image data, location information, and emotion data.

[1733] Operation: The device transmits the captured image data, location information, and emotion data to the server. This transmission is performed using wireless communication means.

[1734] Output: The server receives these data.

[1735] Step 7: Receiving Data

[1736] Input: Image data, location information, and emotional data sent from the device.

[1737] Operation: The server receives image data, location information, and emotion data sent from the device.

[1738] Output: The received data is saved in a specific directory on the server.

[1739] Step 8: Image analysis

[1740] Input: Received image data.

[1741] How it works: The server uses an image analysis module to recognize objects in an image, for example using an image recognition algorithm such as YOLO (You Only Look Once).

[1742] Output: Recognized object information is generated.

[1743] Step 9: Information Acquisition

[1744] Input: Recognized object information.

[1745] How it works: The server retrieves information related to the recognized object from a database (e.g., an LY database or a GTP database), typically using an SQL query.

[1746] Output: Relevant information is obtained.

[1747] Step 10: Information Generation

[1748] Input: The relevant information retrieved.

[1749] How it works: The server uses a generative AI model (e.g., OpenAI's GPT model) to generate detailed information. It sends prompts to the model to generate detailed explanations and additional information.

[1750] Output: Detailed information is generated.

[1751] Step 11: Personalize

[1752] Input: Generated details, user profile information, and sentiment data.

[1753] How it works: The server personalizes the generated information based on the user's profile information and emotional data, taking into account the user's current emotional state and past behavioral patterns.

[1754] Output: Personalized information is generated.

[1755] Step 12: Data transmission (retransmission)

[1756] Input: Personalized information.

[1757] Operation: The server transmits the generated personalized information to the terminal. This transmission is also performed using wireless communication means.

[1758] Output: The device receives the personalized information.

[1759] Step 13: Display Information

[1760] Input: Received personalization information.

[1761] How it works: The device (smart glasses) displays the information it receives in the user's field of vision using HUD (head-up display) technology.

[1762] Output: The user sees the personalized information.

[1763] Step 14: User Interaction

[1764] Input: User's reaction to the received personalized information.

[1765] How it works: If the user wants to know more about a particular piece of information, they can make a request using voice commands or eye contact. This request is sent to the server via the device.

[1766] Output: The server receives the new request information and the process repeats, generating the relevant information again.

[1767] Through these steps, this system will be able to provide appropriate information in real time according to the user's emotional state and individual interests.

[1768] (Application example 2)

[1769] 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."

[1770] In today's shopping experience, it is difficult for users to obtain appropriate information in real time based on their interests and emotions. Specifically, it is difficult to instantly find products and services that match their preferences in a store, which reduces shopping satisfaction. Furthermore, when users want to know more about information that interests them, there is a lack of a way to quickly and intuitively obtain detailed information. There is a need for a way to resolve these issues and improve the user experience.

[1771] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1772] In this invention, the server includes an emotion analysis means for analyzing the user's emotion data, a means for generating detailed information using a generative AI model, and a means for personalizing information based on the user's profile information and emotion data, thereby enabling the provision of personalized information based on the user's location information and emotion.

[1773] A "camera device" is a device that is built into a wearable device and captures image data of the surroundings.

[1774] A "location information acquisition device" is a device that identifies the user's current location. It uses GPS or in-store beacons.

[1775] The "communication means" is a means for transmitting captured image data and location information to a server.

[1776] A "server" is a computer system that analyzes received image data and recognizes specific objects.

[1777] A "means for recognizing specific objects" is an algorithm or device that identifies and identifies objects or people based on image data.

[1778] The "means for generating information" is a function that generates information related to a recognized object.

[1779] "Means for generating detailed information using a generative AI model" refers to means for automatically generating detailed information to be provided to a user using an artificial intelligence model.

[1780] The "emotion analysis means that provides user emotion data based on an emotion engine" refers to a device or software that analyzes the user's voice and facial expressions and derives emotion data.

[1781] The "display means" is a device that displays the generated information superimposed on the user's field of vision. It usually includes smart glasses or the like.

[1782] "User profile information" is data including the user's past usage history, interests, personal information, etc.

[1783] "Personalization" means tailoring and individually optimizing the information provided based on each user's individual profile and emotional data.

[1784] "Means for requesting detailed information about specific information using eye movements or voice commands" refers to an operating means for obtaining details about information of interest to the user through eye movements or voice instructions.

[1785] The present invention relates to a system using a wearable device that provides personalized information based on a user's emotional data. This system analyzes image data, location information, and emotional data in real time when the user wears the wearable device, and provides personalized information to the user.

[1786] System Configuration

[1787] User

[1788] A user wears a wearable device (e.g., smart glasses) and uses the device while walking around town or inside a store.

[1789] Device (smart glasses)

[1790] The smart glasses have the following features:

[1791] 1. Camera equipment

[1792] Capture image data of the surroundings in real time.

[1793] 2. Location information acquisition device

[1794] Use GPS or in-store beacons to determine the user's current location.

[1795] 3. Means of communication

[1796] The captured image data, location information, and emotion data are transmitted to a server.

[1797] 4. Display means

[1798] The personalized information received from the server is displayed superimposed on the user's field of view.

[1799] 5. Emotion analysis method

[1800] The system analyzes the user's voice and facial expressions to generate emotional data, which is then sent to the server.

[1801] server

[1802] The server performs the following process.

[1803] 1. Data Reception

[1804] The image data, position information, and emotion data transmitted from the terminal are received.

[1805] 2. Image Analysis

[1806] Image recognition algorithms are used to recognize specific objects within the image data.

[1807] 3. Emotion analysis

[1808] The received emotional data is analyzed to understand the user's emotional state.

[1809] 4. Information generation

[1810] Information related to the recognized object is retrieved from a database and detailed information is generated using a generative AI model.

[1811] 5. Personalization

[1812] The generated information is personalized based on the user's profile information and emotional data.

[1813] 6. Data Transmission

[1814] Send personalized information to your device.

[1815] Program processing explanation

[1816] Hardware

[1817] Camera devices (e.g., cameras built into wearable devices)

[1818] GPS devices (e.g., smartphone GPS modules, in-store beacons)

[1819] Smart glasses (e.g. Google Glass)

[1820] Display device (smart glasses built-in display)

[1821] software

[1822] EmotionRecognizer (emotion analysis library)

[1823] GPS module (location information acquisition library)

[1824] Requests library (HTTP request library)

[1825] Generative AI model (AI model for generating detailed information)

[1826] Data processing and calculation

[1827] 1. Capture image data

[1828] The camera device captures images of the surroundings in real time.

[1829] 2. Obtaining location information

[1830] The user's current location is obtained using a GPS module or beacon.

[1831] 3. Generating Emotion Data

[1832] Emotion data is generated from the user's voice and facial expressions using EmotionRecognizer.

[1833] 4. Data Transmission

[1834] Use the Requests library to send image data, location information, and emotion data to the server.

[1835] 5. Server-side data analysis

[1836] The server analyzes the images based on the received data and recognizes specific objects. It also analyzes the emotional data to understand the user's emotional state.

[1837] 6. Information generation

[1838] Information related to the recognized object is retrieved from a database and detailed information is generated using a generative AI model.

[1839] 7. Personalization

[1840] The generated information is personalized based on the user's profile information and emotional data.

[1841] 8. Information display

[1842] The generated personalized information is displayed on the smart glasses display.

[1843] Specific examples

[1844] Example prompt sentence:

[1845] The user's name is User 1. He is 30 years old and enjoys active shopping. He is currently on the third floor of a department store. He is wearing smart glasses, and the emotion engine recognizes his excitement. Provide him with information that may interest him. His favorite brands are popular, and he is interested in new products.

[1846] Based on these prompts, users can receive information optimized for their emotions and profile in real time. For example, as a user walks through a store, the camera in the smart glasses captures a specific product, and detailed information about that product is instantly displayed on the display. Recommended products and services based on the user's emotional state are also displayed, improving the user's shopping experience.

[1847] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1848] Step 1:

[1849] The user puts on the smart glasses and launches the application.

[1850] Input: User profile information (interests, favorite brands, etc.)

[1851] Output: Profile information is shared between smart glasses and the server.

[1852] Specific operation: The user puts on the smart glasses, launches the app, and enters information on the profile settings screen.

[1853] Step 2:

[1854] The device (smart glasses) uses a camera device to capture image data of the surroundings in real time.

[1855] Input: Surrounding landscape

[1856] Output: Real-time image data

[1857] How it works: The camera built into the smart glasses continuously captures images and stores them in its internal memory.

[1858] Step 3:

[1859] The device uses the GPS module to obtain its current location.

[1860] Input: Current location satellite data

[1861] Output: Current location information

[1862] Specific operation: The GPS module receives satellite data and calculates latitude and longitude.

[1863] Step 4:

[1864] The emotion engine analyzes the user's voice and facial expressions to generate emotion data.

[1865] Input: User's voice and facial expression data

[1866] Output: Emotion data (e.g., joy, anger, surprise, etc.)

[1867] How it works: The smart glasses' microphone and camera capture voice and facial expressions, and the emotion engine analyzes this data to infer emotions.

[1868] Step 5:

[1869] The terminal transmits the captured image data, location information, and emotion data to a server.

[1870] Input: image data, location information, emotion data

[1871] Output: Data sent to the server

[1872] Specific operation: The communication module uploads data to the server using an HTTP request.

[1873] Step 6:

[1874] The server analyzes the received image data and recognizes specific objects.

[1875] Input: Image data

[1876] Output: Recognized object information

[1877] What it does: Image recognition algorithms on the server analyze the image and identify the object.

[1878] Step 7:

[1879] The server analyzes the received emotional data and understands the user's emotional state.

[1880] Input: Emotion data

[1881] Output: Emotional state (e.g. "Excited")

[1882] Specific operation: Emotion analysis software on the server analyzes the emotion data and evaluates the user's emotional state.

[1883] Step 8:

[1884] The server retrieves information related to a specific object from a database and generates detailed information using a generative AI model.

[1885] Input: Recognized object information

[1886] Output:Detailed information

[1887] How it works: The server retrieves information related to the object from the database and generates detailed information using a generative AI model.

[1888] Step 9:

[1889] The server personalizes the information based on the user's profile information and emotional data.

[1890] Input: Details, profile information, emotional data

[1891] Output: Personalized information

[1892] Specific operation: The server customizes detailed information to suit the user based on profile information and emotional data.

[1893] Step 10:

[1894] The server sends the personalized information to the device.

[1895] Input: Personalized Information

[1896] Output: Information sent to the terminal

[1897] Specific operation: The server transmits the personalized information to the terminal via the communication module.

[1898] Step 11:

[1899] The information received by the device (smart glasses) is displayed overlaid on the user's field of vision.

[1900] Input: Personalized Information

[1901] Output: Information displayed in the user's field of view

[1902] Specific operation: The smart glasses display device displays the received information as an overlay.

[1903] Step 12:

[1904] The user uses gaze or voice commands to request detailed information about a specific item.

[1905] Input: Voice commands and gaze data

[1906] Output: Request for more information

[1907] Specific actions: The user sends a request by speaking a specific command into the smart glasses or by directing their gaze in a specific location.

[1908] 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.

[1909] 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.

[1910] 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.

[1911] [Fourth embodiment]

[1912] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1913] 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.

[1914] 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).

[1915] 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.

[1916] 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.

[1917] 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).

[1918] 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.

[1919] 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.

[1920] 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.

[1921] 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.

[1922] 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.

[1923] 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.

[1924] 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."

[1925] This invention is a system that uses a wearable device including a camera to analyze image data and location information in real time and provide personalized information to users. This system is mainly composed of three elements: the user, the terminal (wearable device), and the server.

[1926] System Configuration

[1927] 1. Users

[1928] Users wear wearable devices (hereafter referred to as smart glasses) while walking around town or working. User profile information is shared between the smart glasses and a server, and the user's past usage history and interests are stored.

[1929] 2. Device (smart glasses)

[1930] The smart glasses have the following features:

[1931] 1. Camera equipment

[1932] Capture the surrounding scenery and save it as image data.

[1933] 2. Location information acquisition device

[1934] Use GPS to determine the user's current location.

[1935] 3. Means of communication

[1936] Image data and location information are sent to the server.

[1937] 4. Display means

[1938] The information received from the server is displayed superimposed on the user's field of view.

[1939] 3. Server

[1940] The server performs the following process.

[1941] 1. Data Reception

[1942] Receive image data and location information transmitted from the smart glasses.

[1943] 2. Image Analysis

[1944] Use image recognition AI to identify objects in image data.

[1945] 3. Information generation

[1946] Information related to the recognized object is obtained from the LY database and GTP database, and information is generated using generation AI.

[1947] 4. Personalization

[1948] Personalize the generated information based on the user's profile information.

[1949] 5. Data Transmission

[1950] Send personalized information to smart glasses.

[1951] Program processing explanation

[1952] User operations and initial settings

[1953] The user puts on the smart glasses and launches the application.

[1954] Enter your profile settings and interests.

[1955] Image capture and data transmission

[1956] The device (smart glasses) uses a camera device to capture the surrounding scenery and create image data.

[1957] The device uses the GPS module to obtain current location data.

[1958] The device transmits the captured image data and location information to the server.

[1959] Data analysis and information generation

[1960] The server analyzes the image data and location information received from the device.

[1961] The server uses image recognition AI to recognize objects in the image.

[1962] The server retrieves information from the LY and GTP databases related to the recognized object.

[1963] The server uses generation AI to generate detailed information.

[1964] The server personalizes the information based on the user's profile information.

[1965] The server returns the generated information to the terminal.

[1966] Information presentation and user interaction

[1967] The information received by the device (smart glasses) is displayed in the user's field of vision.

[1968] The user reviews the displayed information and requests more details using voice commands or gaze.

[1969] Specific examples

[1970] For example, as a user walks around town, the camera in the smart glasses captures the surrounding scenery. The image data and location information are sent to a server, where image recognition AI identifies specific restaurants. The server retrieves information about the restaurant, such as its menu, reviews, and opening hours, from the LY database and uses generative AI to generate detailed information. This information is personalized based on the user's profile and sent back to the smart glasses.

[1971] Through the smart glasses, users can see whether a particular restaurant suits their tastes, and detailed menu information and reviews are overlaid on the visuals, helping them make an intuitive choice. In this way, users receive personalized, helpful information in real time, facilitating decision-making.

[1972] Smart glasses can also be used in business settings, allowing delivery personnel, for example, to obtain detailed destination information and efficient routes in real time, enabling smoother operations. Even if sudden changes occur, they can be quickly responded to based on shared information.

[1973] The above is an embodiment of the present invention, which significantly improves user convenience and efficiency in obtaining information.

[1974] The processing flow will be explained below.

[1975] Program processing steps

[1976] Step 1:

[1977] The user puts on the smart glasses, turns them on, and launches the application.

[1978] A user enters information about their interests and preferences in a profile setting screen.

[1979] Step 2:

[1980] The device (smart glasses) continuously captures the surrounding scenery using a camera device.

[1981] The device obtains current location information using the GPS module.

[1982] Step 3:

[1983] The image data and location information acquired by the device are temporarily stored and then sent to the server using a communication module.

[1984] Step 4:

[1985] The server receives the image data and location information sent from the terminal.

[1986] The server uses an image analysis module to recognize objects in the image.

[1987] Step 5:

[1988] The server retrieves information related to the recognized object from the LY database and the GTP database.

[1989] The server uses a generation AI to generate detailed information about the recognized object.

[1990] Step 6:

[1991] The server refers to the user's profile information and personalizes the generated information.

[1992] The server sends the personalized information to the device.

[1993] Step 7:

[1994] The terminal analyzes the personalized information received from the server.

[1995] The information analyzed by the device is displayed overlaid on the user's field of vision.

[1996] Step 8:

[1997] When a user checks the information displayed on the smart glasses and wants to know more about a particular piece of information, they can make a request using voice commands or eye movements.

[1998] Step 9:

[1999] The terminal transmits a request from the user to the server through the communication module.

[2000] Step 10:

[2001] The server receives the request, generates additional details and sends them back to the device.

[2002] Step 11:

[2003] The additional information received by the device is displayed in the user's field of view, providing navigation and further details.

[2004] This allows users to obtain detailed information about their surroundings in real time based on visually overlaid information, enabling smooth decision-making.Similarly, in business situations, users can quickly obtain necessary information and carry out their work efficiently.

[2005] Example 1

[2006] 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."

[2007] Conventional wearable device systems have faced the issue of not being able to obtain necessary information in a timely manner due to a lack of real-time information provision and personalization based on user profiles. Furthermore, the generation of specific detailed information based on image data and location information often lacks precision, resulting in reduced user convenience.

[2008] 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.

[2009] In this invention, the server includes a means for analyzing the received image data and recognizing a specific object, a means for acquiring information related to the recognized object from an accumulation database, and a means for generating detailed information using a generative AI model based on the acquired information, thereby enabling real-time generation and personalization of detailed information.

[2010] A "camera device" is a device for photographing surrounding scenery and objects.

[2011] "Wearable device" is a general term for electronic devices that can be worn by the user.

[2012] "Image data" is data that includes visual information captured by a camera device.

[2013] A "location information acquisition device" is a device that uses GPS or other location measurement technology to determine a current location.

[2014] A "communication means" is a device that has the function of transmitting image data and location information to a server.

[2015] A "server" is a high-performance computer that processes and manages data over a network.

[2016] "Image analysis" is a process of analyzing received image data and recognizing objects.

[2017] An "object" refers to a specific object or location that exists within image data.

[2018] An "accumulation database" is a database that stores acquired information and allows it to be searched and used as needed.

[2019] A "generative AI model" is an algorithm or system that uses artificial intelligence to generate detailed information.

[2020] "Detailed information" is specific explanations and recommended information generated based on image data and location information.

[2021] "Personalization" refers to customizing information based on a user's profile information.

[2022] The "display means" is a device for displaying information superimposed on the user's field of vision.

[2023] "Profile information" is information relating to a user's personal interests and history.

[2024] This invention is a system that uses a wearable device including a camera device to analyze image data and location information in real time and provide personalized information to the user. This system mainly consists of three elements: the user, the terminal (wearable device), and the server. Specifically, the system uses the following hardware and software:

[2025] System Configuration

[2026] 1. Users

[2027] Users wear wearable devices (hereafter referred to as smart glasses) while walking around town or working. User profile information is shared between the smart glasses and a server, and the user's past usage history and interests are stored.

[2028] 2. Device (smart glasses)

[2029] The smart glasses have the following features:

[2030] 1. Camera equipment

[2031] Capture the surrounding scenery and save it as image data.

[2032] 2. Location information acquisition device

[2033] Use GPS to determine the user's current location.

[2034] 3. Means of communication

[2035] Image data and location information are sent to the server.

[2036] 4. Display means

[2037] The information received from the server is displayed superimposed on the user's field of view.

[2038] 3. Server

[2039] The server performs the following process.

[2040] 1. Data Reception

[2041] Receive image data and location information transmitted from the smart glasses.

[2042] 2. Image Analysis

[2043] It uses image recognition AI to identify objects in image data, specifically using Google Cloud Vision API, for example.

[2044] 3. Information generation

[2045] Information related to the recognized object is obtained from the accumulated database and external databases, and detailed information is generated using a generative AI model (e.g., OpenAI's GPT-4).

[2046] 4. Personalization

[2047] Personalize the generated information based on the user's profile information.

[2048] 5. Data Transmission

[2049] Send personalized information to smart glasses.

[2050] Specific examples

[2051] For example, as a user walks around town, the camera in the smart glasses captures the surrounding scenery. The image data and location information are sent to a server, where the Google Cloud Vision API identifies specific restaurants. The server retrieves information about the restaurant, such as its menu, reviews, and opening hours, from a database and uses a generative AI model (e.g., GPT-4) to generate detailed information. This information is personalized based on the user's profile and sent back to the smart glasses.

[2052] Through the smart glasses, users can see whether a particular restaurant suits their tastes, and detailed menu information and reviews are overlaid on the visuals, helping them make an intuitive choice. In this way, users receive personalized, helpful information in real time, facilitating decision-making.

[2053] Smart glasses can also be used in business settings, allowing delivery personnel, for example, to obtain detailed destination information and efficient routes in real time, enabling smoother operations. Even if sudden changes occur, they can be quickly responded to based on shared information.

[2054] Prompt Sentence Examples

[2055] If you use a generation AI, the prompt sentence is shown below as an example.

[2056] 1. Prompt to generate restaurant details:

[2057] Input: Restaurant name, menu items, hours, review rating

[2058] Answer: Create the following details: [restaurant name] overview, popular menu items, opening hours, what makes it great, and user review highlights.

[2059] 2. Information generation prompt for delivery agents:

[2060] Input: Delivery address, landmarks along the way, traffic conditions

[2061] Answer: Detailed route directions and landmark information along the way to help couriers reach their destination in the most efficient and smoothest way possible.

[2062] This is expected to significantly improve user convenience and the efficiency of information acquisition.

[2063] The flow of the identification process in the first embodiment will be described with reference to FIG.

[2064] Step 1:

[2065] Initial setup and startup

[2066] The user puts on the smart glasses and launches the application. The user taps the application icon to launch it and enters their profile information and interests. This allows the user's personal setting information to be shared between the smart glasses and the server.

[2067] Input: User profile information, interests

[2068] Output: Save the setting information to the smart glasses.

[2069] Step 2:

[2070] Image capture and location acquisition

[2071] The device (smart glasses) uses a camera device to capture the surrounding scenery and create image data, and also uses a GPS module to obtain current location information.

[2072] Input: Surrounding scenery, current location

[2073] Output: Captured image data, location information

[2074] Step 3:

[2075] Data transmission

[2076] The device sends the captured image data and location information to a server, and the communication module in the smart glasses uploads the data using Wi-Fi or 4G / 5G networks.

[2077] Input: Image data, location information

[2078] Output: Data sent (reaches the server)

[2079] Step 4:

[2080] Data reception and analysis

[2081] The server analyzes the image data and location information received from the device, adds the received data to a dedicated processing queue, and uses image recognition AI (such as Google Cloud Vision API) to identify objects in the image.

[2082] Input: Image data, location information

[2083] Output: Recognized object information

[2084] Step 5:

[2085] information generation

[2086] The server retrieves information related to the recognized object from the stored database and external databases, then generates detailed information using a generative AI model (e.g., OpenAI's GPT-4).

[2087] Input: Recognized object information, accumulated database information

[2088] Output: Detailed information generated

[2089] Step 6:

[2090] Personalizing Information

[2091] The server personalizes the generated information based on the user's profile information, providing information that is relevant to the user's interests and past usage history.

[2092] Input: Generated details, user profile information

[2093] Output: personalized information

[2094] Step 7:

[2095] Data transmission and information display

[2096] The server sends personalized information to the device (smart glasses), which receives the information and displays it over the user's field of vision.

[2097] Input: Personalized Information

[2098] Output: Information displayed in the field of view of the smart glasses

[2099] Step 8:

[2100] User Interaction

[2101] The user can check the displayed information and request more details using voice commands or gaze. Voice commands are given using words such as "Show me more details," and the microphone in the smart glasses recognizes this and takes appropriate action.

[2102] Input: Voice command, gaze information

[2103] Output: Updated display information

[2104] (Application example 1)

[2105] 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."

[2106] Current information provision systems using wearable devices have challenges in that it is difficult for users to obtain detailed product information in real time in physical stores, and they are unable to personalize information based on individual users' preferences and past purchase history. In particular, they lack product recognition and navigation functions in physical stores, which often limit users' shopping experiences. Therefore, the development of a new system that significantly improves user convenience is desirable.

[2107] 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.

[2108] In this invention, the server includes a means for analyzing image data and recognizing specific objects, a means for retrieving information related to the recognized object from a database and generating detailed information using a generative AI model, and a means for personalizing the generated information based on a user's profile information. This allows for real-time provision of detailed information about products in a physical store and personalized information based on the user's profile. Furthermore, by enhancing product recognition and navigation functions, it is possible to support a user's efficient shopping experience.

[2109] A "camera device" is hardware for capturing image data.

[2110] A "wearable device" is a portable device that can be worn and used by a user.

[2111] "Image data" is visual information captured from a camera device.

[2112] A "location information acquisition device" is a device that uses technology such as GPS to identify a user's current location.

[2113] "Communication means" refers to a connection means for transmitting image data and location information to the server.

[2114] A "server" is a computer system that receives, analyzes, and generates data.

[2115] "Image Recognition AI" is an artificial intelligence algorithm that analyzes received image data and recognizes specific objects.

[2116] A "database" is a system for efficiently storing, searching, and managing large amounts of information.

[2117] A "generative AI model" is an artificial intelligence model that generates detailed information based on data.

[2118] "Profile information" is personal information such as a user's past usage history and interests.

[2119] "Personalization" refers to optimizing the information provided based on the user's individual profile information.

[2120] "Display means for displaying information overlaid on the user's field of vision" refers to technology that allows wearable devices such as smart glasses to overlay information on the user's field of vision.

[2121] A "brick and mortar store" is a commercial establishment that exists in a physical location.

[2122] A "navigation feature" is a feature that helps a user locate a particular product within a physical store.

[2123] This invention is a system that uses a wearable device including a camera to analyze image data and location information in real time and provide personalized information to users. This system is mainly composed of three elements: the user, the terminal (wearable device), and the server.

[2124] System Configuration

[2125] 1. Users

[2126] Users wear a wearable device (hereafter referred to as smart glasses) to check products in physical stores and obtain necessary information. User profile information is shared between the smart glasses and a server, and the user's past usage history and interests are stored.

[2127] 2. Device (smart glasses)

[2128] The smart glasses have the following features:

[2129] 1. Camera equipment

[2130] Capture surrounding products and save them as image data.

[2131] 2. Location information acquisition device

[2132] Use GPS to determine the user's current location.

[2133] 3. Means of communication

[2134] Image data and location information are sent to the server.

[2135] 4. Display means

[2136] The information received from the server is displayed superimposed on the user's field of view.

[2137] 3. Server

[2138] The server performs the following process.

[2139] 1. Data Reception

[2140] Receive image data and location information transmitted from the smart glasses.

[2141] 2. Image Analysis

[2142] Use image recognition AI to identify objects in image data.

[2143] 3. Information generation

[2144] Information related to the recognized object is retrieved from a database, and detailed information is generated using a generative AI model.

[2145] 4. Personalization

[2146] Personalize the generated information based on the user's profile information.

[2147] 5. Data Transmission

[2148] Send personalized information to smart glasses.

[2149] Program processing explanation

[2150] User operations and initial settings

[2151] The user puts on the smart glasses, launches a dedicated application, and enters their profile settings and interests to prepare for personalized information provision.

[2152] Image capture and data transmission

[2153] The camera device of the smart glasses captures the surrounding products and creates image data, and the GPS module acquires the current location data, and then transmits the captured image data and location information to the server.

[2154] Data analysis and information generation

[2155] The server analyzes the received image data and location information. It uses image recognition AI (e.g., TensorFlow) to recognize objects in the image. It retrieves information related to the recognized object from a database and generates detailed information using a generative AI model (e.g., GPT-4). The generated information is personalized based on the user's profile information.

[2156] Information presentation and user interaction

[2157] The smart glasses overlay the received information onto the user's field of vision, allowing the user to review the displayed information and request more information via voice commands or eye contact.

[2158] Specific examples

[2159] For example, imagine a user is in the chocolate section of a supermarket. The camera in the smart glasses captures products on the shelf and sends the image data and location information to a server. The server uses image recognition AI to recognize the specific product and retrieves its details from a database. A generative AI model is used to generate product reviews, nutritional information, and pricing information, personalizing it based on the user's profile. The generated information is sent to the smart glasses and displayed in the user's field of view. The user can then view the information and make product selections.

[2160] Prompt Sentence Examples

[2161] "When a user sees a new product in the supermarket, generate personalized details about that product. We'd like a natural language description based on the user's past purchases, allergies, and preferences."

[2162] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[2163] Step 1:

[2164] The user puts on the smart glasses and launches the dedicated application. The user's profile information and interests are required as input. This information is stored on the smart glasses and serves as the basis for providing personalized information. As output, the smart glasses prepare the user's profile information and can then connect to the server.

[2165] Step 2:

[2166] The device (smart glasses) uses a camera device to capture surrounding products. The input is visual information (image data) acquired through the camera lens. The output is the acquired image data.

[2167] Step 3:

[2168] The device (smart glasses) uses a GPS location information acquisition device to obtain current location data. The input is a signal from the GPS sensor. The output is current location information.

[2169] Step 4:

[2170] The terminal transmits the captured image data and location information to the server using a communication means. The inputs are the image data and location information generated earlier. The output is transmitted to the server.

[2171] Step 5:

[2172] The server analyzes the received image data and location information. The inputs are the transmitted image data and location information. The server uses image recognition AI (e.g., TensorFlow) to identify objects in the image data. The output is information about the recognized objects.

[2173] Step 6:

[2174] The server retrieves information related to the recognized object from the database and generates detailed information using a generative AI model (e.g., GPT-4). The inputs are information about the object stored in the database and information about the recognized object. The output is the detailed information generated by the generative AI model.

[2175] Step 7:

[2176] The server personalizes the generated information based on the user's profile information. The inputs are the generated details and the user's profile information. The output is personalized details.

[2177] Step 8:

[2178] The server sends personalized information to the smart glasses. As input, there are personalized details. As output, the details are sent to the smart glasses.

[2179] Step 9:

[2180] The device (smart glasses) receives information and displays it over the user's field of view. The input is personalized details sent from the server. The output is the information overlaid on the user's field of view.

[2181] Step 10:

[2182] The user reviews the displayed information and requests more information if necessary. The inputs are the visual information from the smart glasses, as well as the user's voice commands and gaze information. The output is a request for additional information.

[2183] 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.

[2184] This invention is a system that uses a wearable device including a camera to analyze image data and location information in real time and provide personalized information based on the user's emotional data. This system is mainly composed of four elements: the user, the terminal (wearable device), the server, and the emotion engine.

[2185] System Configuration

[2186] 1. Users

[2187] Users wear wearable devices (hereafter referred to as smart glasses) while walking around town or working. User profile information is shared between the smart glasses and a server, and the user's past usage history and interests are stored. In addition, emotion data is collected in real time by an emotion engine.

[2188] 2. Device (smart glasses)

[2189] The smart glasses have the following features:

[2190] 1. Camera equipment

[2191] Capture the surrounding scenery and save it as image data.

[2192] 2. Location information acquisition device

[2193] Use GPS to determine the user's current location.

[2194] 3. Means of communication

[2195] Image data and location information are sent to the server.

[2196] 4. Display means

[2197] The information received from the server is displayed superimposed on the user's field of view.

[2198] 5. Emotion Engine

[2199] The user's voice and facial expressions are analyzed to generate emotional data, which is then sent to the server.

[2200] 3. Server

[2201] The server performs the following process.

[2202] 1. Data Reception

[2203] The image data, location information, and emotion data transmitted from the terminal are received.

[2204] 2. Image Analysis

[2205] Use image recognition AI to recognize objects in image data.

[2206] 3. Information generation

[2207] Information related to the recognized object is obtained from the LY database and GTP database, and information is generated using generation AI.

[2208] 4. Personalization

[2209] The generated information is personalized based on the user's profile information and emotion data obtained from the emotion engine.

[2210] 5. Data Transmission

[2211] Send personalized information to your device.

[2212] Program processing explanation

[2213] User operations and initial settings

[2214] The user puts on the smart glasses and launches the application.

[2215] A user enters information about their interests and preferences in a profile setting screen.

[2216] Image capture and data transmission

[2217] The device (smart glasses) uses a camera device to continuously capture the surrounding scenery and create image data.

[2218] The device uses the GPS module to obtain its current location.

[2219] The emotion engine analyzes the user's voice and facial expressions to generate emotion data.

[2220] The terminal transmits the captured image data, location information, and emotion data to a server.

[2221] Data analysis and information generation

[2222] The server receives the image data, location information, and emotion data transmitted from the terminal.

[2223] The server uses an image analysis module to recognize objects in the image.

[2224] The server retrieves information from the LY and GTP databases related to the recognized object.

[2225] The server uses generation AI to generate detailed information.

[2226] The server personalizes the information based on the user's profile information and emotional data.

[2227] The server returns the generated personalized information to the terminal.

[2228] Information presentation and user interaction

[2229] The information received by the device (smart glasses) is displayed in the user's field of vision.

[2230] The user can review the displayed information and, if they want more details about a particular piece of information, make a request using voice commands or eye control.

[2231] Specific examples

[2232] For example, as a user walks around town, the camera in the smart glasses captures the surrounding scenery. The image data and location information are sent to a server, where image recognition AI identifies specific restaurants. The server retrieves information about the restaurant, such as its menu, reviews, and opening hours, from the LY database and uses generative AI to generate detailed information. This information is personalized based on the user's profile and emotional data and sent back to the smart glasses.

[2233] For example, if the emotion engine recognizes that the user is tired, it will prioritize information about relaxing cafes and rest spots. Conversely, if the user is excited, it will display information about active leisure activities.

[2234] This allows users to obtain the most appropriate information for their situation in real time, allowing them to enjoy walking around town. In business situations, delivery companies can use emotion data to efficiently carry out their work and flexibly respond to sudden changes. The above is an embodiment of the present invention, which provides information according to the user's emotional state and improves the user experience.

[2235] The processing flow will be explained below.

[2236] Program processing steps

[2237] Step 1:

[2238] The user puts on the smart glasses, turns them on, and launches the application.

[2239] A user enters information about their interests and preferences in a profile setting screen.

[2240] Step 2:

[2241] The device (smart glasses) continuously captures the surrounding scenery using a camera device.

[2242] The device obtains current location information using the GPS module.

[2243] Step 3:

[2244] The emotion engine analyzes the user's voice and facial expressions in real time and generates emotion data.

[2245] Voice analysis detects the tone of a user's voice and the rhythm of their speech to identify their emotional state (e.g., joy, anger, sadness, etc.).

[2246] Facial expression analysis involves capturing a user's facial expressions and using emotion analysis algorithms to identify their emotional state.

[2247] Step 4:

[2248] The image data, location information, and emotional data acquired by the device are temporarily stored and transmitted to a server using a communication module.

[2249] Step 5:

[2250] The server receives the image data, location information, and emotion data transmitted from the terminal.

[2251] Step 6:

[2252] The server uses an image analysis module to recognize objects in the image.

[2253] The server retrieves information from the LY and GTP databases related to the recognized object.

[2254] Example: If a specific restaurant is recognized, retrieve its menu, reviews, opening hours, etc.

[2255] Step 7:

[2256] The server uses generation AI to generate detailed information about the recognized objects.

[2257] Step 8:

[2258] The server personalizes the generated details based on the user's profile information and emotion data.

[2259] Example: If the user is tired, provide them with information about cafes and rest spots where they can relax.

[2260] Step 9:

[2261] The server sends the personalized information to the device.

[2262] Step 10:

[2263] The device (smart glasses) analyzes the personalized information received.

[2264] The information analyzed by the device is displayed overlaid on the user's field of vision.

[2265] Step 11:

[2266] If the user checks the displayed information and wants to know more, they can make a request using voice commands or eye movements.

[2267] For example, say the voice command, "Tell me more about this restaurant's menu."

[2268] Step 12:

[2269] The terminal transmits a request from the user to the server through the communication module.

[2270] Step 13:

[2271] The server receives the request, generates additional details and sends them back to the device.

[2272] Step 14:

[2273] The additional information received by the device (smart glasses) is displayed in the user's field of view, providing navigation and further details.

[2274] Examples:

[2275] As a user walks around town, the smartglasses' camera captures the surrounding scenery. The image data and location information are sent to a server, where image recognition AI identifies specific restaurants. The server retrieves information about the restaurant, such as its menu, reviews, and opening hours, from the LY database and uses generative AI to generate detailed information. This information is personalized based on the user's profile and emotional data and sent back to the smartglasses.

[2276] For example, if the emotion engine recognizes that the user is tired, it will prioritize displaying information about relaxing cafes and rest spots. Conversely, if the user is excited, it will display information about active leisure activities. In this way, users can obtain optimal information in real time and enjoy a highly satisfying experience. In business situations, emotional data can also be used to efficiently carry out work and flexibly respond to sudden changes.

[2277] Example 2

[2278] 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."

[2279] Conventional wearable device systems have limited information that users can obtain in real time, making it difficult to provide appropriate information tailored to the user's emotional state and individual interests. Furthermore, due to a lack of personalization of information, it has been difficult to efficiently obtain information that is valuable to the user. Therefore, it is necessary to further improve user convenience and the usefulness of information.

[2280] 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.

[2281] In this invention, the server includes means for analyzing a user's voice and facial expressions to generate emotional data, means for analyzing image data received by the server and recognizing a specific object, means for acquiring information related to the recognized object, means for generating detailed information using a generative AI model, and means for personalizing the generated detailed information based on the user's profile information and emotional data, thereby enabling the provision of appropriate information in real time according to the user's emotional state and individual interests.

[2282] A "camera device" is a device used to capture image data.

[2283] A "wearable device" is an electronic device that can be worn by a user.

[2284] A "location information acquisition device" is a device that acquires information about a user's current location using technology such as GPS.

[2285] "Communication means" refers to a means for transmitting data to other devices or servers.

[2286] "Emotion data" is data relating to the user's emotional state obtained by analyzing the user's voice and facial expressions.

[2287] "Image analysis means" is a means for analyzing captured image data and recognizing specific objects within the image.

[2288] The "information acquisition means" is a means for acquiring information related to a recognized object from a database or the like.

[2289] A "generative AI model" is an algorithm that uses artificial intelligence techniques to generate detailed information based on specific inputs.

[2290] "Personalization means" refers to means for individualizing the generated detailed information based on the user's profile information and emotional data.

[2291] A "display means" is a means for displaying generated or personalized information to the user's view.

[2292] "Profile information" is individual information about a user, such as information about the user's interests and preferences.

[2293] "Voice command" refers to an operation or request made by a user through voice.

[2294] This invention is a system that uses a wearable device including a camera to analyze image data and location information in real time and provide personalized information based on the user's emotional data. This system is mainly composed of four elements: the user, the terminal (wearable device), the server, and the emotion engine.

[2295] System Configuration

[2296] 1. Users

[2297] Users wear wearable devices (hereafter referred to as smart glasses) while walking around town or working. User profile information is shared between the smart glasses and a server, and the user's past usage history and interests are stored. In addition, emotion data is collected in real time by an emotion engine.

[2298] 2. Device (smart glasses)

[2299] The smart glasses have the following features:

[2300] 1. Camera equipment

[2301] Capture the surrounding scenery and save it as image data.

[2302] 2. Location information acquisition device

[2303] Use GPS to determine the user's current location.

[2304] 3. Means of communication

[2305] Image data and location information are sent to the server.

[2306] 4. Display means

[2307] The information received from the server is displayed superimposed on the user's field of view.

[2308] 5. Emotion Engine

[2309] The user's voice and facial expressions are analyzed to generate emotional data, which is then sent to the server.

[2310] 3. Server

[2311] The server performs the following process.

[2312] 1. Data Reception

[2313] The image data, location information, and emotion data transmitted from the terminal are received.

[2314] 2. Image Analysis

[2315] Use image recognition AI to recognize objects in image data.

[2316] 3. Information acquisition

[2317] Information related to the recognized object is retrieved from the database.

[2318] 4. Information generation

[2319] A generative AI model is used to generate detailed information, such as OpenAI's GPT model.

[2320] 5. Personalization

[2321] The generated information is personalized based on the user's profile information and emotion data obtained from the emotion engine.

[2322] 6. Data Transmission

[2323] Send personalized information to your device.

[2324] Program processing explanation

[2325] Image capture and data transmission

[2326] The device (smart glasses) uses a camera device to continuously capture the surrounding scenery and create image data. The device acquires its current location information using a GPS module. The emotion engine analyzes the user's voice and facial expressions to generate emotion data. The device sends the captured image data, location information, and emotion data to a server.

[2327] Data analysis and information generation

[2328] The server receives image data, location information, and emotion data sent from the device. The server uses an image analysis module to recognize objects in the image. The server retrieves information related to the recognized object from a database. The server uses a generative AI model to generate detailed information. The server personalizes the information based on the user's profile information and emotion data. The server sends the generated personalized information to the device.

[2329] Information presentation and user interaction

[2330] The device (smart glasses) displays the received information in the user's field of vision. If the user checks the displayed information and wants more details about a specific piece of information, they can make a request using voice commands or eye movements. In this way, the most appropriate information can be provided based on the user's real-time emotional state and profile information.

[2331] Specific examples

[2332] For example, as a user walks around town, the camera in the smart glasses captures the surrounding scenery and identifies restaurants. The image data and location information are sent to a server, where image recognition AI identifies the specific restaurant. The server retrieves information about the restaurant, such as its menu, reviews, and opening hours, from a database and uses generative AI to generate detailed information. This information is personalized based on the user's profile and emotional data and sent back to the smart glasses.

[2333] For example, if the emotion engine recognizes that the user is tired, it will prioritize information about cafes and rest spots where they can relax. Conversely, if the user is excited, it will display information about active leisure activities. The following is an example of a prompt sentence:

[2334] "Recommend restaurants near my current location"

[2335] "Looking for a relaxing cafe"

[2336] "What live event can I go to tonight?"

[2337] This allows users to obtain the most appropriate information for their situation in real time, allowing them to enjoy walking around town.In business settings, delivery companies can use emotion data to carry out their work efficiently and respond flexibly to sudden changes.

[2338] The flow of the identification process in the second embodiment will be described with reference to FIG.

[2339] System program processing flow

[2340] Step 1: User interaction and initial setup

[2341] Input: The user puts on the smart glasses and launches the application.

[2342] Action: The user powers on the smart glasses and launches the application. The application begins its startup sequence and displays the initial setup screen.

[2343] Output: The smart glasses start up and the profile setting screen is displayed.

[2344] Step 2: Profile Settings

[2345] Input: The user enters information about interests and preferences in a profile setup screen.

[2346] How it works: A user fills out a profile screen that describes their interests, preferences, and general interests. This includes selecting categories and entering text.

[2347] Output: The entered information is sent to the server and a user profile is generated.

[2348] Step 3: Image capture

[2349] Input: A user puts on smart glasses and starts moving.

[2350] Operation: The device (smart glasses) uses a camera device to continuously capture the surrounding scenery and generate image data.

[2351] Output: The generated image data is saved in the internal memory.

[2352] Step 4: Obtaining location information

[2353] Input: A user puts on smart glasses and continues moving.

[2354] Operation: The device (smart glasses) uses the GPS module to obtain current location information. This process is performed automatically at regular intervals.

[2355] Output: The acquired location information is stored in the internal memory.

[2356] Step 5: Emotion data generation

[2357] Input: The user wears the smart glasses and can speak or change their facial expressions.

[2358] How it works: The emotion engine analyzes the user's voice and facial expressions to generate emotion data. Waveform analysis and phoneme analysis are used for voice analysis, and image processing algorithms are used for facial expression analysis.

[2359] Output: The generated emotion data is stored in the internal memory.

[2360] Step 6: Send data

[2361] Input: Generated image data, location information, and emotion data.

[2362] Operation: The device transmits the captured image data, location information, and emotion data to the server. This transmission is performed using wireless communication means.

[2363] Output: The server receives these data.

[2364] Step 7: Receiving Data

[2365] Input: Image data, location information, and emotional data sent from the device.

[2366] Operation: The server receives image data, location information, and emotion data sent from the device.

[2367] Output: The received data is saved in a specific directory on the server.

[2368] Step 8: Image analysis

[2369] Input: Received image data.

[2370] How it works: The server uses an image analysis module to recognize objects in an image, for example using an image recognition algorithm such as YOLO (You Only Look Once).

[2371] Output: Recognized object information is generated.

[2372] Step 9: Information Acquisition

[2373] Input: Recognized object information.

[2374] How it works: The server retrieves information related to the recognized object from a database (e.g., an LY database or a GTP database), typically using an SQL query.

[2375] Output: Relevant information is obtained.

[2376] Step 10: Information Generation

[2377] Input: The relevant information retrieved.

[2378] How it works: The server uses a generative AI model (e.g., OpenAI's GPT model) to generate detailed information. It sends prompts to the model to generate detailed explanations and additional information.

[2379] Output: Detailed information is generated.

[2380] Step 11: Personalize

[2381] Input: Generated details, user profile information, and sentiment data.

[2382] How it works: The server personalizes the generated information based on the user's profile information and emotional data, taking into account the user's current emotional state and past behavioral patterns.

[2383] Output: Personalized information is generated.

[2384] Step 12: Data transmission (retransmission)

[2385] Input: Personalized information.

[2386] Operation: The server transmits the generated personalized information to the terminal. This transmission is also performed using wireless communication means.

[2387] Output: The device receives the personalized information.

[2388] Step 13: Display Information

[2389] Input: Received personalization information.

[2390] How it works: The device (smart glasses) displays the information it receives in the user's field of vision using HUD (head-up display) technology.

[2391] Output: The user sees the personalized information.

[2392] Step 14: User Interaction

[2393] Input: User's reaction to the received personalized information.

[2394] How it works: If the user wants to know more about a particular piece of information, they can make a request using voice commands or eye contact. This request is sent to the server via the device.

[2395] Output: The server receives the new request information and the process repeats, generating the relevant information again.

[2396] Through these steps, this system will be able to provide appropriate information in real time according to the user's emotional state and individual interests.

[2397] (Application example 2)

[2398] 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."

[2399] In today's shopping experience, it is difficult for users to obtain appropriate information in real time based on their interests and emotions. Specifically, it is difficult to instantly find products and services that match their preferences in a store, which reduces shopping satisfaction. Furthermore, when users want to know more about information that interests them, there is a lack of a way to quickly and intuitively obtain detailed information. There is a need for a way to resolve these issues and improve the user experience.

[2400] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[2401] In this invention, the server includes an emotion analysis means for analyzing the user's emotion data, a means for generating detailed information using a generative AI model, and a means for personalizing information based on the user's profile information and emotion data, thereby enabling the provision of personalized information based on the user's location information and emotion.

[2402] A "camera device" is a device that is built into a wearable device and captures image data of the surroundings.

[2403] A "location information acquisition device" is a device that identifies the user's current location. It uses GPS or in-store beacons.

[2404] The "communication means" is a means for transmitting captured image data and location information to a server.

[2405] A "server" is a computer system that analyzes received image data and recognizes specific objects.

[2406] A "means for recognizing specific objects" is an algorithm or device that identifies and identifies objects or people based on image data.

[2407] The "means for generating information" is a function that generates information related to a recognized object.

[2408] "Means for generating detailed information using a generative AI model" refers to means for automatically generating detailed information to be provided to a user using an artificial intelligence model.

[2409] The "emotion analysis means that provides user emotion data based on an emotion engine" refers to a device or software that analyzes the user's voice and facial expressions and derives emotion data.

[2410] The "display means" is a device that displays the generated information superimposed on the user's field of vision. It usually includes smart glasses or the like.

[2411] "User profile information" is data including the user's past usage history, interests, personal information, etc.

[2412] "Personalization" means tailoring and individually optimizing the information provided based on each user's individual profile and emotional data.

[2413] "Means for requesting detailed information about specific information using eye movements or voice commands" refers to an operating means for obtaining details about information of interest to the user through eye movements or voice instructions.

[2414] The present invention relates to a system using a wearable device that provides personalized information based on a user's emotional data. This system analyzes image data, location information, and emotional data in real time when the user wears the wearable device, and provides personalized information to the user.

[2415] System Configuration

[2416] User

[2417] A user wears a wearable device (e.g., smart glasses) and uses the device while walking around town or inside a store.

[2418] Device (smart glasses)

[2419] The smart glasses have the following features:

[2420] 1. Camera equipment

[2421] Capture image data of the surroundings in real time.

[2422] 2. Location information acquisition device

[2423] Use GPS or in-store beacons to determine the user's current location.

[2424] 3. Means of communication

[2425] The captured image data, location information, and emotion data are transmitted to a server.

[2426] 4. Display means

[2427] The personalized information received from the server is displayed superimposed on the user's field of view.

[2428] 5. Emotion analysis method

[2429] The system analyzes the user's voice and facial expressions to generate emotional data, which is then sent to the server.

[2430] server

[2431] The server performs the following process.

[2432] 1. Data Reception

[2433] The image data, position information, and emotion data transmitted from the terminal are received.

[2434] 2. Image Analysis

[2435] Image recognition algorithms are used to recognize specific objects within the image data.

[2436] 3. Emotion analysis

[2437] The received emotional data is analyzed to understand the user's emotional state.

[2438] 4. Information generation

[2439] Information related to the recognized object is retrieved from a database and detailed information is generated using a generative AI model.

[2440] 5. Personalization

[2441] The generated information is personalized based on the user's profile information and emotional data.

[2442] 6. Data Transmission

[2443] Send personalized information to your device.

[2444] Program processing explanation

[2445] Hardware

[2446] Camera devices (e.g., cameras built into wearable devices)

[2447] GPS devices (e.g., smartphone GPS modules, in-store beacons)

[2448] Smart glasses (e.g. Google Glass)

[2449] Display device (smart glasses built-in display)

[2450] software

[2451] EmotionRecognizer (emotion analysis library)

[2452] GPS module (location information acquisition library)

[2453] Requests library (HTTP request library)

[2454] Generative AI model (AI model for generating detailed information)

[2455] Data processing and calculation

[2456] 1. Capture image data

[2457] The camera device captures images of the surroundings in real time.

[2458] 2. Obtaining location information

[2459] The user's current location is obtained using a GPS module or beacon.

[2460] 3. Generating Emotion Data

[2461] Emotion data is generated from the user's voice and facial expressions using EmotionRecognizer.

[2462] 4. Data Transmission

[2463] Use the Requests library to send image data, location information, and emotion data to the server.

[2464] 5. Server-side data analysis

[2465] The server analyzes the images based on the received data and recognizes specific objects. It also analyzes the emotional data to understand the user's emotional state.

[2466] 6. Information generation

[2467] Information related to the recognized object is retrieved from a database and detailed information is generated using a generative AI model.

[2468] 7. Personalization

[2469] The generated information is personalized based on the user's profile information and emotional data.

[2470] 8. Information display

[2471] The generated personalized information is displayed on the smart glasses display.

[2472] Specific examples

[2473] Example prompt sentence:

[2474] The user's name is User 1. He is 30 years old and enjoys active shopping. He is currently on the third floor of a department store. He is wearing smart glasses, and the emotion engine recognizes his excitement. Provide him with information that may interest him. His favorite brands are popular, and he is interested in new products.

[2475] Based on these prompts, users can receive information optimized for their emotions and profile in real time. For example, as a user walks through a store, the camera in the smart glasses captures a specific product, and detailed information about that product is instantly displayed on the display. Recommended products and services based on the user's emotional state are also displayed, improving the user's shopping experience.

[2476] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[2477] Step 1:

[2478] The user puts on the smart glasses and launches the application.

[2479] Input: User profile information (interests, favorite brands, etc.)

[2480] Output: Profile information is shared between smart glasses and the server.

[2481] Specific operation: The user puts on the smart glasses, launches the app, and enters information on the profile settings screen.

[2482] Step 2:

[2483] The device (smart glasses) uses a camera device to capture image data of the surroundings in real time.

[2484] Input: Surrounding landscape

[2485] Output: Real-time image data

[2486] How it works: The camera built into the smart glasses continuously captures images and stores them in its internal memory.

[2487] Step 3:

[2488] The device uses the GPS module to obtain its current location.

[2489] Input: Current location satellite data

[2490] Output: Current location information

[2491] Specific operation: The GPS module receives satellite data and calculates latitude and longitude.

[2492] Step 4:

[2493] The emotion engine analyzes the user's voice and facial expressions to generate emotion data.

[2494] Input: User's voice and facial expression data

[2495] Output: Emotion data (e.g., joy, anger, surprise, etc.)

[2496] How it works: The smart glasses' microphone and camera capture voice and facial expressions, and the emotion engine analyzes this data to infer emotions.

[2497] Step 5:

[2498] The terminal transmits the captured image data, location information, and emotion data to a server.

[2499] Input: image data, location information, emotion data

[2500] Output: Data sent to the server

[2501] Specific operation: The communication module uploads data to the server using an HTTP request.

[2502] Step 6:

[2503] The server analyzes the received image data and recognizes specific objects.

[2504] Input: Image data

[2505] Output: Recognized object information

[2506] What it does: Image recognition algorithms on the server analyze the image and identify the object.

[2507] Step 7:

[2508] The server analyzes the received emotional data and understands the user's emotional state.

[2509] Input: Emotion data

[2510] Output: Emotional state (e.g. "Excited")

[2511] Specific operation: Emotion analysis software on the server analyzes the emotion data and evaluates the user's emotional state.

[2512] Step 8:

[2513] The server retrieves information related to a specific object from a database and generates detailed information using a generative AI model.

[2514] Input: Recognized object information

[2515] Output:Detailed information

[2516] How it works: The server retrieves information related to the object from the database and generates detailed information using a generative AI model.

[2517] Step 9:

[2518] The server personalizes the information based on the user's profile information and emotional data.

[2519] Input: Details, profile information, emotional data

[2520] Output: Personalized information

[2521] Specific operation: The server customizes detailed information to suit the user based on profile information and emotional data.

[2522] Step 10:

[2523] The server sends the personalized information to the device.

[2524] Input: Personalized Information

[2525] Output: Information sent to the terminal

[2526] Specific operation: The server transmits the personalized information to the terminal via the communication module.

[2527] Step 11:

[2528] The information received by the device (smart glasses) is displayed overlaid on the user's field of vision.

[2529] Input: Personalized Information

[2530] Output: Information displayed in the user's field of view

[2531] Specific operation: The smart glasses display device displays the received information as an overlay.

[2532] Step 12:

[2533] The user uses gaze or voice commands to request detailed information about a specific item.

[2534] Input: Voice commands and gaze data

[2535] Output: Request for more information

[2536] Specific actions: The user sends a request by speaking a specific command into the smart glasses or by directing their gaze in a specific location.

[2537] 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.

[2538] 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.

[2539] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[2540] 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.

[2541] FIG. 9 is a diagram illustrating 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 actions 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.

[2542] 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.

[2543] 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).

[2544] 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.

[2545] 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."

[2546] 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.

[2547] 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).

[2548] 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.

[2549] 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.

[2550] 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.

[2551] 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 porti...

Claims

1. a wearable device including a camera device, means for capturing image data; A means including a location information acquisition device; a communication means for transmitting the captured image data and location information to a server; means for analyzing the image data received by the server and recognizing a specific object; means for generating information related to the recognized object; a display means for receiving the generated information and displaying it in the user's field of view; A system including:

2. 10. The system of claim 1, further comprising means for storing user profile information.

3. 10. The system of claim 1, wherein the generated information is personalized based on user profile information.

Images