system

Abstract

We provide the system. [Solution] A wearable camera for capturing the user's visual information, Artificial intelligence means that analyzes the aforementioned visual information and generates information based on object recognition and location information, An audio output device that provides the generated information to the user in audio format, A system that includes this.

Description

Technical Field

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

Background Art

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

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] Conventional information collection systems had problems of poor real-time information acquisition and convenience for users. In addition, visual support for the elderly and visually impaired was insufficient, making it difficult to efficiently collect information in daily life and business.

Means for Solving the Problems

[0005] The present invention solves these problems by providing a system equipped with artificial intelligence means for capturing a user's visual information in real time and analyzing the acquired information. Furthermore, by using an audio output device that provides the analyzed information to the user in audio format, visual support is provided to realize a comfortable and smart information acquisition means for the user.

[0006] "User" refers to a person who wears and uses this system, including various users such as general consumers, business users, the elderly, and visually impaired people.

[0007] "Visual information" refers to image data and video data within the visible range, including the object and its surrounding environment.

[0008] "Wearable imaging device" refers to a camera or other imaging device for acquiring visual information in a form that can be worn by a user, mainly in the form of glasses.

[0009] "Artificial intelligence means" refers to software or hardware for analyzing the acquired visual information, including algorithms for object recognition and data analysis.

[0010] "Location information" refers to the current geographical location acquired using GPS, etc., and is information used for real-time user location identification.

[0011] "Voice output device" refers to a device such as a speaker or earphone for transmitting the generated information and analysis results to the user as voice.

[0012] "Life log" refers to data recording various activities and events related to the user's life, and is a record that can be referred to or played back later.

Brief Description of Drawings

[0013] [Figure 1] It is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] It is a conceptual diagram showing an example of the main functions of a data processing device and a smart device according to the first embodiment. [Figure 3] It is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4]It is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] It is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] It is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] It is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] It is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] It shows an emotion map to which a plurality of emotions are mapped. [Figure 10] It shows an emotion map to which a plurality of emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Example 2 when an emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when an emotion engine is combined.

Embodiments for Carrying Out the Invention

[0014] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0015] First, the language used in the following description will be explained.

[0016] In the following embodiments, the numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0017] In the following embodiments, the numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0018] In the following embodiments, the numbered storage is one or more non-volatile storage devices that store various programs, various parameters, and the like. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes.

[0019] In the following embodiments, the numbered communication I / F (Interface) is an interface including a communication processor, an antenna, and the like. 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), or Bluetooth (registered trademark).

[0020] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0021] [First Embodiment]

[0022] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0023] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0024] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0025] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0026] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0027] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0028] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0029] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0030] As shown in Figure 2, in the data processing device 12, specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0031] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0032] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0033] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0034] This invention provides a system that allows users wearing a glasses-type device as a wearable imaging device to acquire and utilize information in real time in their daily lives and business environments. The system mainly consists of a glasses-type device worn by the user and a server that analyzes and provides the information.

[0035] The user captures visual information in real time using a wearable camera. This visual information is transmitted from the terminal to a server via the network. The server is equipped with artificial intelligence to analyze the received visual information, performing object recognition and acquiring data about the surrounding environment based on location information.

[0036] The information obtained from the analysis is converted into audio data on the server and transmitted to the terminal. The terminal provides this audio data to the user via an audio output device. This allows the user to receive real-time assistance based on visual information in audio format.

[0037] As a concrete example, when a user enters a store, a wearable camera captures visual information of the products on the shelves. The server analyzes these images, retrieves detailed product information (e.g., price, reviews), and provides it to the user via voice, allowing the user to shop more efficiently.

[0038] Furthermore, when travelers visit tourist destinations, the system recognizes surrounding landmarks and provides related historical and tourist information via audio, enabling an experience similar to a guided tour.

[0039] This invention allows users to benefit from digital technology on a daily basis without requiring any special operations, and particularly supports independent living for the elderly and visually impaired by enhancing visual support.

[0040] The following describes the processing flow.

[0041] Step 1:

[0042] The device captures visual information in real time through a wearable camera. The device continuously acquires image data within the user's field of vision.

[0043] Step 2:

[0044] The device packages the visual information it captures with the location information obtained from the GPS module and sends it to the server. The data is transmitted in real time over the network.

[0045] Step 3:

[0046] The server analyzes the received visual information using an AI algorithm to perform object recognition. This involves identifying the type and characteristics of the object and retrieving associated data from a database.

[0047] Step 4:

[0048] The server uses location information to understand the surrounding geographical environment and collects relevant geographical and local information. This includes map information and data on local commercial facilities.

[0049] Step 5:

[0050] The server generates information to be provided to the user based on the object recognition results and geographical information, and converts it into audio format. The information is then processed to meet the user's needs.

[0051] Step 6:

[0052] The server sends the generated audio data to the terminal. The data is configured to reach the user's device immediately.

[0053] Step 7:

[0054] The device receives audio data, which is then presented to the user via an audio output device. The user uses this information to understand the situation in real time and make decisions.

[0055] Step 8:

[0056] If the user requests additional information or gives new instructions based on voice feedback, they enter voice commands into the terminal. The terminal then sends another request to the server and receives information to assist with the next action.

[0057] (Example 1)

[0058] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0059] In modern society, users are required to quickly obtain necessary information about their surroundings and objects. However, conventional information acquisition methods require users to search for information themselves or operate devices, making them impractical for people with visual impairments or the elderly. In this situation, there is a need for systems that provide information more intuitively and in real time.

[0060] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0061] In this invention, the server includes a wearable imaging device for capturing the user's visual information, means for transmitting the visual information to an analysis device via a network, and analysis means including a generative AI model for analyzing the visual information and acquiring data based on object recognition and location information. This enables the user to receive necessary information in real time via voice based on the visual information without requiring any special operation.

[0062] A "wearable imaging device" is an imaging device that can be worn by a user and has the function of capturing visual information in real time.

[0063] An "analysis device" is a computing system located within a server that processes received visual information and acquires specific data.

[0064] "Means for transmitting to an analysis device via a network" refers to a protocol or mechanism for transmitting visual information to an analysis device using the internet or other communication infrastructure.

[0065] A "generative AI model" is a mathematical or software model that uses artificial intelligence technology to analyze data and perform object recognition.

[0066] "Analysis means" refers to a series of processing devices that include a generative AI model and extract relevant data from visual information.

[0067] "Speech synthesis means" refers to a technology or process for converting text data into a speech format, and is a means that plays a role in providing speech information to users.

[0068] "Audio output means" refers to audio devices such as speakers or earphones used to transmit generated audio data to the user.

[0069] This invention relates to a system that enables users to acquire and utilize visual information more efficiently. This system includes a wearable imaging device worn by the user, a server that analyzes visual information, and a terminal that provides the analysis results in audio format.

[0070] (System Overview)

[0071] Users wear a wearable imaging device to capture visual information in real time during their daily lives and business activities. This device is lightweight, comfortable to wear, and designed for extended use. The captured visual information is transmitted to a server via the user's device using an internet connection.

[0072] The server processes the received visual information using an analysis device. This analysis device incorporates a generative AI model and not only performs object recognition in images but also has the capability to acquire additional data based on location information. For example, it can search for detailed information about products identified through object recognition, or the historical background of tourist attractions at a particular location.

[0073] The analysis results are converted into audio data by a speech synthesis system on the server. This audio data is sent to the user's terminal and provided to the user via an audio output system. The user can receive various visual information in audio format and make decisions efficiently.

[0074] (Specific example)

[0075] For example, when a user enters a store, a wearable camera captures images of the product shelves, and a server analyzes them. A generated AI model identifies the products, and their prices and review information are provided via voice. This allows users to quickly compare products and make purchasing decisions.

[0076] Furthermore, when visiting tourist destinations, users can enjoy an experience similar to a guided tour by receiving information about landmarks in audio format.

[0077] (Example of a prompt message)

[0078] "I'm visiting a tourist spot, but I'd like to learn more about the surrounding historical buildings. What kind of information can I get using a device?"

[0079] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0080] Step 1:

[0081] (user)

[0082] The user uses a wearable imaging device to capture visual information about their surroundings.

[0083] Input: The object or scenery the user is looking at.

[0084] Output: Captured visual information (image data).

[0085] Specifically, when a user looks around at the shelves while shopping, the wearable camera automatically captures that scene.

[0086] Step 2:

[0087] (terminal)

[0088] The terminal sends the captured visual information to the server.

[0089] Input: Visual information (image data) received from the imaging device.

[0090] Output: Visual information transmitted over the network.

[0091] Specifically, the terminal compresses the image data and sends it to the server using the appropriate communication protocol.

[0092] Step 3:

[0093] (server)

[0094] The server analyzes the received visual information and retrieves data based on object recognition and location information.

[0095] Input: Visual information (image data) sent from the device.

[0096] Output: Analysis results (data related to specific objects or locations).

[0097] Specifically, the server uses a generative AI model to perform object recognition in images, identifying, for example, product names and their prices.

[0098] Step 4:

[0099] (server)

[0100] The server converts the analysis results into audio data.

[0101] Input: Analysis results (text or numerical data).

[0102] Output: Audio data provided to the user.

[0103] Specifically, the server uses text-to-speech technology to convert the analysis results into natural-sounding speech.

[0104] Step 5:

[0105] (terminal)

[0106] The device provides the generated audio data to the user.

[0107] Input: Audio data sent from the server.

[0108] Output: Audio information audible to the user.

[0109] Specifically, the device decodes the received audio data and plays it back through its built-in speaker to notify the user of the information.

[0110] (Application Example 1)

[0111] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0112] Modern consumers have access to a wide variety of product information when shopping in physical stores, but they lack efficient means to properly collect and utilize this information. Furthermore, it is difficult for consumers to make quick and effective purchasing decisions amidst information overload. Therefore, there is a need for technologies that enable consumers to shop more smartly and efficiently in stores.

[0113] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0114] In this invention, the server includes a wearable portable device for acquiring the user's visual information, intelligent processing means for generating information based on object recognition and spatial information, voice output means for providing the generated information in voice format, and communication means for acquiring product information and purchase support information and presenting it to the user. This makes it possible for consumers to acquire necessary product information in real time at physical stores and to be supported in making purchase decisions.

[0115] A "wearable device" is a device that a user can wear on their clothing or body and that has the function of acquiring visual information in real time.

[0116] "Intelligent processing means" refers to methods and processes that use artificial intelligence to analyze information and generate necessary data based on object recognition and spatial information.

[0117] A "sound output means" is a device that has the function of converting generated information into sound data and providing it to the user audibly.

[0118] "Communication methods" refer to the techniques and technologies used to send and receive data between a server and a user, and play a role in transmitting product information and purchasing support information via a network.

[0119] This invention is an advanced support system for improving the in-store shopping experience, utilizing a wearable device, a server, and communication means.

[0120] When a user wears a wearable device in the form of glasses and walks around a store, the device captures visual information in real time. The captured visual information is then transmitted from the device to a server via the network.

[0121] The server is equipped with intelligent processing capabilities using high-performance artificial intelligence to analyze the received visual information. Specifically, it uses software such as TENSORFLOW® and OpenCV to perform object recognition and spatial information analysis, and further acquires information about the recognized products. This includes price, reviews, and special offer information.

[0122] The information obtained from the analysis is converted into audio data using speech synthesis software such as Google Cloud Text-to-Speech. This audio data is sent to the user's device via communication and provided to the user through an audio output device. The user can audibly understand detailed information about the products on the shelf, enabling them to make smart purchasing decisions.

[0123] For example, if a user goes to the milk section in a supermarket and their glasses-type device recognizes a product on the shelf, the server retrieves detailed information about that product. This information is then presented aloud as, "This milk costs 200 yen. User rating is 4.5." In this way, specific processes are carried out to support an improved shopping experience.

[0124] An example of a prompt might be a question like, "Please tell me the reviews for the products in my current location." The system then provides information in real time in response to this prompt.

[0125] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0126] Step 1:

[0127] The user moves around the store wearing a wearable device. The device uses a camera to capture visual information in real time. The input is the visual information of the store, and the output is the captured image data. The device temporarily stores this data.

[0128] Step 2:

[0129] The terminal sends the captured visual information to the server. This process involves the device sending the acquired image data to the server over the network. The input is the captured image data, and the output is the data received by the server.

[0130] Step 3:

[0131] The server analyzes the received visual information using intelligent processing tools. Specifically, it performs object recognition and image processing using an AI model (e.g., TensorFlow). In this process, the server uses the received image data as input and obtains the object identification results as output. This output is a list of identified objects.

[0132] Step 4:

[0133] Based on the analysis results, the server retrieves detailed information about the identified object from the database. This process uses the object identification results as input and outputs product information (price, reviews, promotional information, etc.). The server then prepares this information for subsequent processing.

[0134] Step 5:

[0135] The server converts the retrieved product information into audio data. In this step, speech synthesis software such as Google Cloud Text-to-Speech is used to take product information as input and output data in audio format. The converted audio data is then ready to be provided to the user.

[0136] Step 6:

[0137] The terminal receives audio data from the server and provides information to the user using an audio output device. In this step, the input is the audio data transmitted from the server, and the output is the audio information perceived by the user's hearing. The terminal plays the audio at an appropriate volume so that the user can easily understand the information.

[0138] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0139] This invention is a system that realizes more personalized information delivery by combining a wearable camera, artificial intelligence means, and voice output device with an emotion engine for recognizing the user's emotions. The user wears glasses-type wearable camera and acquires visual information and emotional state in real time.

[0140] The device not only captures the user's visual information but also uses an emotion engine to analyze the user's emotions from their facial expressions and voice. This information is transmitted to a server via the network.

[0141] The server analyzes the received visual information and performs object recognition, while simultaneously receiving emotional state data from the emotion engine. Based on the object recognition results and emotional state, a process is carried out to generate optimal information and convert it into audio format.

[0142] This audio data is sent back to the terminal and provided to the user through an audio output device. The information can be customized according to the user's emotional state; for example, if the user is feeling stressed, relaxing music or advice can be provided.

[0143] For example, if a user is wearing the device in a busy business environment, the emotion engine will detect the user's stress, and the server will select relaxation methods and positive messages to communicate to the user via voice. Similarly, if a user visiting a tourist destination expresses feelings of joy, the system will suggest interesting tourist information and enjoyable activities.

[0144] Furthermore, by recording the history of the user's emotional changes in a life log and reviewing it later, it helps deepen self-awareness and facilitates better decision-making. Thus, the present invention aims to further improve the quality of life for users by enabling the integrated use of visual and linguistic information.

[0145] The following describes the processing flow.

[0146] Step 1:

[0147] The device captures visual information in real time through a wearable camera. Simultaneously, an emotion engine analyzes the user's emotional state based on their facial expressions and voice. This results in the acquisition of both visual and emotional data.

[0148] Step 2:

[0149] The device transmits visual information and emotional state data acquired by the device to a server via the network. The data package includes image data, location information, and emotional information.

[0150] Step 3:

[0151] The server analyzes the received visual information using an AI algorithm to perform object recognition. Simultaneously, it analyzes emotional state data received from the emotion engine to understand the user's current emotional state.

[0152] Step 4:

[0153] The server generates information to provide to the user based on the object recognition results and emotional state. If the emotional state indicates stress, the information is customized to include information related to relaxation.

[0154] Step 5:

[0155] The server converts the generated information into audio data and sends the audio information to the terminal. This audio data includes feedback tailored to the user's emotional state.

[0156] Step 6:

[0157] The device uses an audio output device to present the received audio data to the user. This allows the user to receive real-time support and information tailored to their emotional state.

[0158] Step 7:

[0159] The user requests additional information via voice commands as needed. These voice commands are sent from the terminal to the server, where the information is processed again.

[0160] Step 8:

[0161] The server continuously monitors changes in emotional state and updates the life log. This allows users to reflect on past emotional states and use that information to inform future actions and decision-making.

[0162] (Example 2)

[0163] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0164] A problem with modern information systems is that they do not adequately provide information tailored to the emotional state of individual users. In particular, the lack of nuanced information customization based on user emotions hinders improvements in the quality of the user experience. Therefore, there is a need for a system that can grasp the user's real-time emotional state and provide optimal information tailored to that state via voice.

[0165] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0166] In this invention, the server includes a wearable device means equipped with a camera and an audio acquisition device for acquiring the user's visual and audio information in real time; an emotion analysis means for analyzing the user's emotional state using the visual and audio information; and an artificial intelligence means for further analyzing the visual information and generating information based on object recognition and emotional state. This makes it possible to provide information that is appropriately customized according to the user's real-time emotional state.

[0167] "Visual information" refers to image and video data of the surroundings that the user is viewing, and is acquired in real time by wearable devices.

[0168] "Audio information" refers to audio data that includes the user's voice or surrounding sounds, and is collected by a wearable device.

[0169] A "wearable device" is a device that allows a user to acquire visual and auditory information by being worn by the user, and it comes in a form that the user can use on a daily basis, such as glasses.

[0170] "Emotional analysis means" refers to analysis methods and devices for identifying a user's emotional state based on acquired visual and auditory information.

[0171] "Object recognition" refers to the technology that identifies objects and situations that a user is seeing by analyzing visual information.

[0172] "Artificial intelligence tools" refer to machine learning algorithms and software used to analyze collected data and generate situation-appropriate information.

[0173] A "sound output device" refers to a device that converts generated information into sound data and provides it directly to the user audibly.

[0174] This invention is a system that can customize information according to the user's emotional state. The system includes the following main hardware and software components.

[0175] The user wears a wearable device in the form of glasses or other shapes, which is equipped with a high-resolution camera and a high-sensitivity microphone. The camera captures visual information in real time, and the audio acquisition device captures audio information in real time.

[0176] The device receives the acquired visual and audio information and first performs data conversion for image recognition and emotion analysis. Here, a general API (e.g., EmotionAPI) is used for face recognition, and speech recognition software is used for voice tone analysis.

[0177] The server receives data sent from the terminal and performs object recognition based on visual information. A deep learning framework (e.g., TensorFlow) is used for object recognition. Next, the server analyzes the user's emotional state using emotion analysis tools and generates information optimized for each individual user using a generative AI model.

[0178] The generated information is converted into audio data by speech synthesis software (e.g., a speech synthesis API). This audio data is transmitted to a terminal over the network and provided to the user via an audio output device (e.g., earphones).

[0179] For example, if a user visits a crowded shopping mall and the emotion engine detects "stress," the server will provide information about a quiet cafe as a way to relax. This information is conveyed to the user as audio on their device.

[0180] An example of a prompt message is, "Suggest relaxing music for the user to play when they are feeling emotionally exhausted."

[0181] Thus, this system aims to efficiently process the user's visual and auditory information and provide personalized information in real time to improve the user's quality of life.

[0182] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0183] Step 1:

[0184] The user wears a glasses-type wearable device to acquire visual and auditory information. This device captures video through a camera and audio through a microphone. Image and audio data are obtained as input.

[0185] Step 2:

[0186] The terminal preprocesses the visual and audio information received from the wearable device. Image data undergoes resolution adjustment, and audio data is denoised. Preprocessing prepares the data for easier analysis.

[0187] Step 3:

[0188] The device performs emotion analysis using pre-processed visual and audio information. It estimates the user's emotional state using a facial recognition algorithm and voice tone analysis software. The output of this process is data on the user's current emotional state.

[0189] Step 4:

[0190] The device transmits visual information and emotional state data to the server. This communication takes place over a network, and security is ensured through the use of data encryption technology.

[0191] Step 5:

[0192] The server analyzes the received visual information using a deep learning framework to perform object recognition. The input is visual information, and the output is object type and location information. Simultaneously, using emotional state data, a generative AI model generates suggestions tailored to the user's emotions. This results in customized information.

[0193] Step 6:

[0194] The server converts the generated information into speech data using speech synthesis software. This conversion results in output in a natural-sounding speech format.

[0195] Step 7:

[0196] The server retransmits the converted audio data to the terminal. The audio data is transmitted securely via the network using encryption.

[0197] Step 8:

[0198] The terminal transmits received audio data to the user. Using an audio output device, it plays the audio so that the user can easily receive the information. Interactive and real-time feedback is achieved.

[0199] (Application Example 2)

[0200] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0201] Traditional in-store customer service is uniform, making it difficult to understand individual customer needs and emotional states in real time and provide information accordingly. Therefore, there is a need to improve the customer experience. In particular, with the increasing need for personalized information based on customer emotions, the development of technological means to provide effective information in real time is urgently required.

[0202] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0203] In this invention, the server includes a portable imaging device means for capturing the user's visual and auditory information, a component means for analyzing the visual and auditory information and generating information based on specific object recognition and emotion analysis, and an output device means for providing the generated information to the user in audio format. This enables the provision of personalized information according to the user's emotional state.

[0204] A "user" refers to a consumer or customer who uses this system.

[0205] "Visual information" refers to data related to the user's visual environment, and includes image or video data.

[0206] "Audio information" refers to information that includes the voice emitted by the user and acoustic data of the surrounding environment.

[0207] A "portable recording device" is a device capable of recording and taking pictures that is small enough for a user to wear or carry with them.

[0208] "Specific object recognition" is a technology that analyzes visual information to identify specific objects, places, or human actions.

[0209] "Emotional analysis" is the process of analyzing audio and visual information to evaluate a user's emotional state.

[0210] "Components" refer to elements including the hardware and software necessary for information processing.

[0211] An "output device" is a device that presents generated information to the user in audio or video format.

[0212] "Personalized information" refers to personalized information provided based on a user's specific needs and emotions.

[0213] The system implementing this invention begins with the user wearing a portable imaging device to capture visual and auditory information in real time. The system's hardware includes a wearable device equipped with glasses-type cameras and microphones. This allows for the rapid collection of information obtained from the user's sight and hearing.

[0214] On the server, captured visual information is analyzed using image recognition libraries such as OpenCV. This identifies specific objects or people's actions. Additionally, audio information is analyzed by an emotion analysis engine utilizing the Microsoft® Azure® Emotion API to evaluate the user's emotional state. This allows for real-time understanding of the user's emotions, such as what interests them or what makes them feel uncomfortable.

[0215] Based on the analysis results, the server uses the artificial intelligence framework TensorFlow to generate personalized information to provide to the user. This information is converted from text to speech and played back through the user's output device (e.g., headset or smart speaker).

[0216] As a concrete example, when a customer picks up a product in a physical store, the system can provide detailed information related to that product based on the customer's interests and emotions. For instance, a voice guide might be provided saying, "This product features the latest function, XX."

[0217] The following is an example of a prompt message when using a generative AI model.

[0218] "When a customer shows interest in XX (a specific product), generate an audio guide that briefly explains the main features of that product."

[0219] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0220] Step 1:

[0221] The device captures visual and auditory information from the user's surroundings using a wearable camera. This device collects video and audio data using a built-in camera and microphone. The input data is sent to a server as raw data.

[0222] Step 2:

[0223] The server processes the received visual information using OpenCV to perform object recognition. Specifically, it identifies specific objects or people from the input video data and extracts their features. The output is a list of recognized objects.

[0224] Step 3:

[0225] The server uses the Microsoft Azure Emotion API to perform emotion analysis on the audio information. In this step, the server analyzes the user's voice tone and linguistic characteristics from the audio data and evaluates their emotional state. The output is data indicating the user's emotional state.

[0226] Step 4:

[0227] The server uses TensorFlow based on the analysis results to generate personalized information to display or play for the user. This process takes recognized object information and emotional state data as input, and the generative AI model selects the most relevant information. The output is the selected information in text format.

[0228] Step 5:

[0229] The server converts the generated information from text to speech and outputs it to the user via the terminal. This conversion uses a Text-to-Speech (TTS) engine to convert the information into audio format. The output is audio data that the user can listen to.

[0230] Step 6:

[0231] The user receives personalized information via voice and makes decisions based on it. In this step, the user can receive real-time feedback based on the voice information. This output is a crucial element in supporting the user's decision-making.

[0232] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0233] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search)<url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0234] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0235] [Second Embodiment]

[0236] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0237] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0238] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0239] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0240] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0241] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0242] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0243] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0244] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0245] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0246] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0247] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0248] This invention provides a system that allows users wearing a glasses-type device as a wearable imaging device to acquire and utilize information in real time in their daily lives and business environments. The system mainly consists of a glasses-type device worn by the user and a server that analyzes and provides the information.

[0249] The user captures visual information in real time using a wearable camera. This visual information is transmitted from the terminal to a server via the network. The server is equipped with artificial intelligence to analyze the received visual information, performing object recognition and acquiring data about the surrounding environment based on location information.

[0250] The information obtained from the analysis is converted into audio data on the server and transmitted to the terminal. The terminal provides this audio data to the user via an audio output device. This allows the user to receive real-time assistance based on visual information in audio format.

[0251] As a concrete example, when a user enters a store, a wearable camera captures visual information of the products on the shelves. The server analyzes these images, retrieves detailed product information (e.g., price, reviews), and provides it to the user via voice, allowing the user to shop more efficiently.

[0252] Furthermore, when travelers visit tourist destinations, the system recognizes surrounding landmarks and provides related historical and tourist information via audio, enabling an experience similar to a guided tour.

[0253] This invention allows users to benefit from digital technology on a daily basis without requiring any special operations, and particularly supports independent living for the elderly and visually impaired by enhancing visual support.

[0254] The following describes the processing flow.

[0255] Step 1:

[0256] The device captures visual information in real time through a wearable camera. The device continuously acquires image data within the user's field of vision.

[0257] Step 2:

[0258] The device packages the visual information it captures with the location information obtained from the GPS module and sends it to the server. The data is transmitted in real time over the network.

[0259] Step 3:

[0260] The server analyzes the received visual information using an AI algorithm to perform object recognition. This involves identifying the type and characteristics of the object and retrieving associated data from a database.

[0261] Step 4:

[0262] The server uses location information to understand the surrounding geographical environment and collects relevant geographical and local information. This includes map information and data on local commercial facilities.

[0263] Step 5:

[0264] The server generates information to be provided to the user based on the object recognition results and geographical information, and converts it into audio format. The information is then processed to meet the user's needs.

[0265] Step 6:

[0266] The server sends the generated audio data to the terminal. The data is configured to reach the user's device immediately.

[0267] Step 7:

[0268] The device receives audio data, which is then presented to the user via an audio output device. The user uses this information to understand the situation in real time and make decisions.

[0269] Step 8:

[0270] If the user requests additional information or gives new instructions based on voice feedback, they enter voice commands into the terminal. The terminal then sends another request to the server and receives information to assist with the next action.

[0271] (Example 1)

[0272] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0273] In modern society, users are required to quickly obtain necessary information about their surroundings and objects. However, conventional information acquisition methods require users to search for information themselves or operate devices, making them impractical for people with visual impairments or the elderly. In this situation, there is a need for systems that provide information more intuitively and in real time.

[0274] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0275] In this invention, the server includes a wearable imaging device for capturing the user's visual information, means for transmitting the visual information to an analysis device via a network, and analysis means including a generative AI model for analyzing the visual information and acquiring data based on object recognition and location information. This enables the user to receive necessary information in real time via voice based on the visual information without requiring any special operation.

[0276] A "wearable imaging device" is an imaging device that can be worn by a user and has the function of capturing visual information in real time.

[0277] An "analysis device" is a computing system located within a server that processes received visual information and acquires specific data.

[0278] "Means of transmitting to an analysis device via a network" refers to a protocol or mechanism for transmitting visual information to an analysis device using the internet or other communication infrastructure.

[0279] A "generative AI model" is a mathematical or software model that analyzes data using artificial intelligence technology for object recognition.

[0280] The "analysis means" is a series of processing devices that includes a generative AI model and extracts relevant data from visual information.

[0281] The "voice synthesis means" is a technology or process for converting text data into voice format and serves to provide voice information to the user.

[0282] The "voice output means" is an acoustic device such as a speaker or earphone for conveying the generated voice data to the user.

[0283] The present invention relates to a system that enables a user to more efficiently acquire and utilize visual information. This system includes a wearable imaging device worn by the user, a server that analyzes visual information, and a terminal that provides the analysis result in voice.

[0284] (Overview of the System)

[0285] The user wears a wearable imaging device and captures visual information in real time in daily life and business scenes. This device is designed to be lightweight, comfortable to wear, and durable for long - term use. The captured visual information is transmitted to the server via the user's terminal using an Internet connection.

[0286] The server processes the received visual information using an analysis device. The analysis device incorporates a generative AI model and has the function of not only performing object recognition of images but also acquiring additional data based on location information. For example, it searches for detailed information of a product identified by object recognition or the historical background of a tourist attraction at a certain location.

[0287] The analysis results are converted into audio data by a speech synthesis system on the server. This audio data is sent to the user's terminal and provided to the user via an audio output system. The user can receive various visual information in audio format and make decisions efficiently.

[0288] (Specific example)

[0289] For example, when a user enters a store, a wearable camera captures images of the product shelves, and a server analyzes them. A generated AI model identifies the products, and their prices and review information are provided via voice. This allows users to quickly compare products and make purchasing decisions.

[0290] Furthermore, when visiting tourist destinations, users can enjoy an experience similar to a guided tour by receiving information about landmarks in audio format.

[0291] (Example of a prompt message)

[0292] "I'm visiting a tourist spot, but I'd like to learn more about the surrounding historical buildings. What kind of information can I get using a device?"

[0293] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0294] Step 1:

[0295] (user)

[0296] The user uses a wearable imaging device to capture visual information about their surroundings.

[0297] Input: The object or scenery the user is looking at.

[0298] Output: Captured visual information (image data).

[0299] As a specific operation, when the user looks around the product shelves while shopping, the wearable imaging device automatically captures the scene.

[0300] Step 2:

[0301] (Terminal)

[0302] The terminal transmits the captured visual information to the server.

[0303] Input: Visual information (image data) received from the imaging device.

[0304] Output: Visual information transmitted via the network.

[0305] As a specific operation, the terminal compresses the image data and transmits it to the server using an appropriate communication protocol.

[0306] Step 3:

[0307] (Server)

[0308] The server analyzes the received visual information and obtains data based on object recognition and location information.

[0309] Input: Visual information (image data) transmitted from the terminal.

[0310] Output: Analysis result (data related to specific objects or locations).

[0311] As a specific operation, the server performs object recognition of the image using a generated AI model, for example, to identify the product name and its price.

[0312] Step 4:

[0313] (Server)

[0314] The server converts the analysis result into voice data.

[0315] Input: Analysis results (text or numerical data).

[0316] Output: Audio data provided to the user.

[0317] Specifically, the server uses text-to-speech technology to convert the analysis results into natural-sounding speech.

[0318] Step 5:

[0319] (terminal)

[0320] The device provides the generated audio data to the user.

[0321] Input: Audio data sent from the server.

[0322] Output: Audio information audible to the user.

[0323] Specifically, the device decodes the received audio data and plays it back through its built-in speaker to notify the user of the information.

[0324] (Application Example 1)

[0325] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0326] Modern consumers have access to a wide variety of product information when shopping in physical stores, but they lack efficient means to properly collect and utilize this information. Furthermore, it is difficult for consumers to make quick and effective purchasing decisions amidst information overload. Therefore, there is a need for technologies that enable consumers to shop more smartly and efficiently in stores.

[0327] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0328] In this invention, the server includes a wearable portable device for acquiring the user's visual information, intelligent processing means for generating information based on object recognition and spatial information, voice output means for providing the generated information in voice format, and communication means for acquiring product information and purchase support information and presenting it to the user. This makes it possible for consumers to acquire necessary product information in real time at physical stores and to be supported in making purchase decisions.

[0329] A "wearable device" is a device that a user can wear on their clothing or body and that has the function of acquiring visual information in real time.

[0330] "Intelligent processing means" refers to methods and processes that use artificial intelligence to analyze information and generate necessary data based on object recognition and spatial information.

[0331] A "sound output means" is a device that has the function of converting generated information into sound data and providing it to the user audibly.

[0332] "Communication methods" refer to the techniques and technologies used to send and receive data between a server and a user, and play a role in transmitting product information and purchasing support information via a network.

[0333] This invention is an advanced support system for improving the in-store shopping experience, utilizing a wearable device, a server, and communication means.

[0334] When a user wears a wearable device in the form of glasses and walks around a store, the device captures visual information in real time. The captured visual information is then transmitted from the device to a server via the network.

[0335] The server is equipped with intelligent processing capabilities using high-performance artificial intelligence to analyze the received visual information. Specifically, it uses software such as TensorFlow and OpenCV to perform object recognition and spatial information analysis, and further acquires information about the recognized products. This includes price, reviews, and special offer information.

[0336] The information obtained from the analysis is converted into audio data using speech synthesis software such as Google Cloud Text-to-Speech. This audio data is sent to the user's device via a communication method and provided to the user through an audio output device. The user can audibly understand detailed information about the products on the shelf, thereby enabling them to make smart purchasing decisions.

[0337] For example, if a user goes to the milk section in a supermarket and their glasses-type device recognizes a product on the shelf, the server retrieves detailed information about that product. This information is then presented aloud as, "This milk costs 200 yen. User rating is 4.5." In this way, specific processes are carried out to support an improved shopping experience.

[0338] An example of a prompt might be a question like, "Please tell me the reviews for the products in my current location." The system then provides information in real time in response to this prompt.

[0339] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0340] Step 1:

[0341] The user moves around the store wearing a wearable device. The device uses a camera to capture visual information in real time. The input is the visual information of the store, and the output is the captured image data. The device temporarily stores this data.

[0342] Step 2:

[0343] The terminal sends the captured visual information to the server. This process involves the device sending the acquired image data to the server over the network. The input is the captured image data, and the output is the data received by the server.

[0344] Step 3:

[0345] The server analyzes the received visual information using intelligent processing tools. Specifically, it performs object recognition and image processing using an AI model (e.g., TensorFlow). In this process, the server uses the received image data as input and obtains the object identification results as output. This output is a list of identified objects.

[0346] Step 4:

[0347] Based on the analysis results, the server retrieves detailed information about the identified object from the database. This process uses the object identification results as input and outputs product information (price, reviews, promotional information, etc.). The server then prepares this information for subsequent processing.

[0348] Step 5:

[0349] The server converts the retrieved product information into audio data. In this step, speech synthesis software such as Google Cloud Text-to-Speech is used to take product information as input and output data in audio format. The converted audio data is then ready to be provided to the user.

[0350] Step 6:

[0351] The terminal receives audio data from the server and provides information to the user using an audio output device. In this step, the input is the audio data transmitted from the server, and the output is the audio information perceived by the user's hearing. The terminal plays the audio at an appropriate volume so that the user can easily understand the information.

[0352] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0353] This invention is a system that realizes more personalized information delivery by combining a wearable camera, artificial intelligence means, and voice output device with an emotion engine for recognizing the user's emotions. The user wears glasses-type wearable camera and acquires visual information and emotional state in real time.

[0354] The device not only captures the user's visual information but also uses an emotion engine to analyze the user's emotions from their facial expressions and voice. This information is transmitted to a server via the network.

[0355] The server analyzes the received visual information and performs object recognition, while simultaneously receiving emotional state data from the emotion engine. Based on the object recognition results and emotional state, a process is carried out to generate optimal information and convert it into audio format.

[0356] This audio data is sent back to the terminal and provided to the user through an audio output device. The information can be customized according to the user's emotional state; for example, if the user is feeling stressed, relaxing music or advice can be provided.

[0357] For example, if a user is wearing the device in a busy business environment, the emotion engine will detect the user's stress, and the server will select relaxation methods and positive messages to communicate to the user via voice. Similarly, if a user visiting a tourist destination expresses feelings of joy, the system will suggest interesting tourist information and enjoyable activities.

[0358] Furthermore, by recording the history of the user's emotional changes in a life log and reviewing it later, it helps deepen self-awareness and facilitates better decision-making. Thus, the present invention aims to further improve the quality of life for users by enabling the integrated use of visual and linguistic information.

[0359] The following describes the processing flow.

[0360] Step 1:

[0361] The device captures visual information in real time through a wearable camera. Simultaneously, an emotion engine analyzes the user's emotional state based on their facial expressions and voice. This results in the acquisition of both visual and emotional data.

[0362] Step 2:

[0363] The device transmits visual information and emotional state data acquired by the device to a server via the network. The data package includes image data, location information, and emotional information.

[0364] Step 3:

[0365] The server analyzes the received visual information using an AI algorithm to perform object recognition. Simultaneously, it analyzes emotional state data received from the emotion engine to understand the user's current emotional state.

[0366] Step 4:

[0367] The server generates information to provide to the user based on the object recognition results and emotional state. If the emotional state indicates stress, the information is customized to include information related to relaxation.

[0368] Step 5:

[0369] The server converts the generated information into audio data and sends the audio information to the terminal. This audio data includes feedback tailored to the user's emotional state.

[0370] Step 6:

[0371] The device uses an audio output device to present the received audio data to the user. This allows the user to receive real-time support and information tailored to their emotional state.

[0372] Step 7:

[0373] The user requests additional information via voice commands as needed. These voice commands are sent from the terminal to the server, where the information is processed again.

[0374] Step 8:

[0375] The server continuously monitors changes in emotional state and updates the life log. This allows users to reflect on past emotional states and use that information to inform future actions and decision-making.

[0376] (Example 2)

[0377] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0378] A problem with modern information systems is that they do not adequately provide information tailored to the emotional state of individual users. In particular, the lack of nuanced information customization based on user emotions hinders improvements in the quality of the user experience. Therefore, there is a need for a system that can grasp the user's real-time emotional state and provide optimal information tailored to that state via voice.

[0379] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0380] In this invention, the server includes a wearable device means equipped with a camera and an audio acquisition device for acquiring the user's visual and audio information in real time; an emotion analysis means for analyzing the user's emotional state using the visual and audio information; and an artificial intelligence means for further analyzing the visual information and generating information based on object recognition and emotional state. This makes it possible to provide information that is appropriately customized according to the user's real-time emotional state.

[0381] "Visual information" refers to image and video data of the surroundings that the user is viewing, and is acquired in real time by wearable devices.

[0382] "Audio information" refers to audio data that includes the user's voice or surrounding sounds, and is collected by a wearable device.

[0383] A "wearable device" is a device that allows a user to acquire visual and auditory information by being worn by the user, and it comes in a form that the user can use on a daily basis, such as glasses.

[0384] "Emotional analysis means" refers to analysis methods and devices for identifying a user's emotional state based on acquired visual and auditory information.

[0385] "Object recognition" refers to the technology that identifies objects and situations that a user is seeing by analyzing visual information.

[0386] "Artificial intelligence tools" refer to machine learning algorithms and software used to analyze collected data and generate situation-appropriate information.

[0387] A "sound output device" refers to a device that converts generated information into sound data and provides it directly to the user audibly.

[0388] This invention is a system that can customize information according to the user's emotional state. The system includes the following main hardware and software components.

[0389] The user wears a wearable device in the form of glasses or other shapes, which is equipped with a high-resolution camera and a high-sensitivity microphone. The camera captures visual information in real time, and the audio acquisition device captures audio information in real time.

[0390] The device receives the acquired visual and audio information and first performs data conversion for image recognition and emotion analysis. Here, a general API (e.g., EmotionAPI) is used for face recognition, and speech recognition software is used for voice tone analysis.

[0391] The server receives data sent from the terminal and performs object recognition based on visual information. A deep learning framework (e.g., TensorFlow) is used for object recognition. Next, the server analyzes the user's emotional state using emotion analysis tools and generates information optimized for each individual user using a generative AI model.

[0392] The generated information is converted into audio data by speech synthesis software (e.g., a speech synthesis API). This audio data is transmitted to a terminal over the network and provided to the user via an audio output device (e.g., earphones).

[0393] For example, if a user visits a crowded shopping mall and the emotion engine detects "stress," the server will provide information about a quiet cafe as a way to relax. This information is conveyed to the user as audio on their device.

[0394] An example of a prompt message is, "Suggest relaxing music for the user to play when they are feeling emotionally exhausted."

[0395] Thus, this system aims to efficiently process the user's visual and auditory information and provide personalized information in real time to improve the user's quality of life.

[0396] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0397] Step 1:

[0398] The user wears a glasses-type wearable device to acquire visual and auditory information. This device captures video through a camera and audio through a microphone. Image and audio data are obtained as input.

[0399] Step 2:

[0400] The terminal preprocesses the visual and audio information received from the wearable device. Image data undergoes resolution adjustment, and audio data is denoised. Preprocessing prepares the data for easier analysis.

[0401] Step 3:

[0402] The device performs emotion analysis using pre-processed visual and audio information. It estimates the user's emotional state using a facial recognition algorithm and voice tone analysis software. The output of this process is data on the user's current emotional state.

[0403] Step 4:

[0404] The device transmits visual information and emotional state data to the server. This communication takes place over a network, and security is ensured through the use of data encryption technology.

[0405] Step 5:

[0406] The server analyzes the received visual information using a deep learning framework to perform object recognition. The input is visual information, and the output is object type and location information. Simultaneously, using emotional state data, a generative AI model generates suggestions tailored to the user's emotions. This results in customized information.

[0407] Step 6:

[0408] The server converts the generated information into speech data using speech synthesis software. This conversion results in output in a natural-sounding speech format.

[0409] Step 7:

[0410] The server retransmits the converted audio data to the terminal. The audio data is transmitted securely via the network using encryption.

[0411] Step 8:

[0412] The terminal transmits received audio data to the user. Using an audio output device, it plays the audio so that the user can easily receive the information. Interactive and real-time feedback is achieved.

[0413] (Application Example 2)

[0414] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0415] Traditional in-store customer service is uniform, making it difficult to understand individual customer needs and emotional states in real time and provide information accordingly. Therefore, there is a need to improve the customer experience. In particular, with the increasing need for personalized information based on customer emotions, the development of technological means to provide effective information in real time is urgently required.

[0416] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0417] In this invention, the server includes a portable imaging device means for capturing the user's visual and auditory information, a component means for analyzing the visual and auditory information and generating information based on specific object recognition and emotion analysis, and an output device means for providing the generated information to the user in audio format. This enables the provision of personalized information according to the user's emotional state.

[0418] A "user" refers to a consumer or customer who uses this system.

[0419] "Visual information" refers to data related to the user's visual environment, and includes image or video data.

[0420] "Audio information" refers to information that includes the voice emitted by the user and acoustic data of the surrounding environment.

[0421] A "portable recording device" is a device capable of recording and taking pictures that is small enough for a user to wear or carry with them.

[0422] "Specific object recognition" is a technology that analyzes visual information to identify specific objects, places, or human actions.

[0423] "Emotional analysis" is the process of analyzing audio and visual information to evaluate a user's emotional state.

[0424] "Components" refer to elements including the hardware and software necessary for information processing.

[0425] An "output device" is a device that presents generated information to the user in audio or video format.

[0426] "Personalized information" refers to personalized information provided based on a user's specific needs and emotions.

[0427] The system implementing this invention begins with the user wearing a portable imaging device to capture visual and auditory information in real time. The system's hardware includes a wearable device equipped with glasses-type cameras and microphones. This allows for the rapid collection of information obtained from the user's sight and hearing.

[0428] On the server, captured visual information is analyzed using image recognition libraries such as OpenCV. This identifies specific objects or people's actions. Additionally, audio information is analyzed by an emotion analysis engine utilizing the Microsoft Azure Emotion API to evaluate the user's emotional state. This allows for real-time understanding of the user's emotions, such as what interests them or what makes them feel uncomfortable.

[0429] Based on the analysis results, the server uses the artificial intelligence framework TensorFlow to generate personalized information to provide to the user. This information is converted from text to speech and played back through the user's output device (e.g., headset or smart speaker).

[0430] As a concrete example, when a customer picks up a product in a physical store, the system can provide detailed information related to that product based on the customer's interests and emotions. For instance, a voice guide might be provided saying, "This product features the latest function, XX."

[0431] The following is an example of a prompt message when using a generative AI model.

[0432] "When a customer shows interest in XX (a specific product), generate an audio guide that briefly explains the main features of that product."

[0433] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0434] Step 1:

[0435] The device captures visual and auditory information from the user's surroundings using a wearable camera. This device collects video and audio data using a built-in camera and microphone. The input data is sent to a server as raw data.

[0436] Step 2:

[0437] The server processes the received visual information using OpenCV to perform object recognition. Specifically, it identifies specific objects or people from the input video data and extracts their features. The output is a list of recognized objects.

[0438] Step 3:

[0439] The server uses the Microsoft Azure Emotion API to perform emotion analysis on the audio information. In this step, the server analyzes the user's voice tone and linguistic characteristics from the audio data and evaluates their emotional state. The output is data indicating the user's emotional state.

[0440] Step 4:

[0441] The server uses TensorFlow based on the analysis results to generate personalized information to display or play for the user. This process takes recognized object information and emotional state data as input, and the generative AI model selects the most relevant information. The output is the selected information in text format.

[0442] Step 5:

[0443] The server converts the generated information from text to speech and outputs it to the user via the terminal. This conversion uses a Text-to-Speech (TTS) engine to convert the information into audio format. The output is audio data that the user can listen to.

[0444] Step 6:

[0445] The user receives personalized information via voice and makes decisions based on it. In this step, the user can receive real-time feedback based on the voice information. This output is a crucial element in supporting the user's decision-making.

[0446] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0447] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0448] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0449] [Third Embodiment]

[0450] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0451] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0452] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0453] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0454] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0455] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0456] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0457] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0458] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0459] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0460] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0461] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0462] This invention provides a system that allows users wearing a glasses-type device as a wearable imaging device to acquire and utilize information in real time in their daily lives and business environments. The system mainly consists of a glasses-type device worn by the user and a server that analyzes and provides the information.

[0463] The user captures visual information in real time using a wearable camera. This visual information is transmitted from the terminal to a server via the network. The server is equipped with artificial intelligence to analyze the received visual information, performing object recognition and acquiring data about the surrounding environment based on location information.

[0464] The information obtained from the analysis is converted into audio data on the server and transmitted to the terminal. The terminal provides this audio data to the user via an audio output device. This allows the user to receive real-time assistance based on visual information in audio format.

[0465] As a concrete example, when a user enters a store, a wearable camera captures visual information of the products on the shelves. The server analyzes these images, retrieves detailed product information (e.g., price, reviews), and provides it to the user via voice, allowing the user to shop more efficiently.

[0466] Furthermore, when travelers visit tourist destinations, the system recognizes surrounding landmarks and provides related historical and tourist information via audio, enabling an experience similar to a guided tour.

[0467] This invention allows users to benefit from digital technology on a daily basis without requiring any special operations, and particularly supports independent living for the elderly and visually impaired by enhancing visual support.

[0468] The following describes the processing flow.

[0469] Step 1:

[0470] The device captures visual information in real time through a wearable camera. The device continuously acquires image data within the user's field of vision.

[0471] Step 2:

[0472] The device packages the visual information it captures with the location information obtained from the GPS module and sends it to the server. The data is transmitted in real time over the network.

[0473] Step 3:

[0474] The server analyzes the received visual information using an AI algorithm to perform object recognition. This involves identifying the type and characteristics of the object and retrieving associated data from a database.

[0475] Step 4:

[0476] The server uses location information to understand the surrounding geographical environment and collects relevant geographical and local information. This includes map information and data on local commercial facilities.

[0477] Step 5:

[0478] The server generates information to be provided to the user based on the object recognition results and geographical information, and converts it into audio format. The information is then processed to meet the user's needs.

[0479] Step 6:

[0480] The server sends the generated audio data to the terminal. The data is configured to reach the user's device immediately.

[0481] Step 7:

[0482] The device receives audio data, which is then presented to the user via an audio output device. The user uses this information to understand the situation in real time and make decisions.

[0483] Step 8:

[0484] If the user requests additional information or gives new instructions based on voice feedback, they enter voice commands into the terminal. The terminal then sends another request to the server and receives information to assist with the next action.

[0485] (Example 1)

[0486] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0487] In modern society, users are required to quickly obtain necessary information about their surroundings and objects. However, conventional information acquisition methods require users to search for information themselves or operate devices, making them impractical for people with visual impairments or the elderly. In this situation, there is a need for systems that provide information more intuitively and in real time.

[0488] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0489] In this invention, the server includes a wearable imaging device for capturing the user's visual information, means for transmitting the visual information to an analysis device via a network, and analysis means including a generative AI model for analyzing the visual information and acquiring data based on object recognition and location information. This enables the user to receive necessary information in real time via voice based on the visual information without requiring any special operation.

[0490] A "wearable imaging device" is an imaging device that can be worn by a user and has the function of capturing visual information in real time.

[0491] An "analysis device" is a computing system located within a server that processes received visual information and acquires specific data.

[0492] "Means for transmitting to an analysis device via a network" refers to a protocol or mechanism for transmitting visual information to an analysis device using the internet or other communication infrastructure.

[0493] A "generative AI model" is a mathematical or software model that uses artificial intelligence technology to analyze data and perform object recognition.

[0494] "Analysis means" refers to a series of processing devices that include a generative AI model and extract relevant data from visual information.

[0495] "Speech synthesis means" refers to a technology or process for converting text data into a speech format, and is a means that plays a role in providing speech information to users.

[0496] "Audio output means" refers to audio devices such as speakers or earphones used to transmit generated audio data to the user.

[0497] This invention relates to a system that enables users to acquire and utilize visual information more efficiently. This system includes a wearable imaging device worn by the user, a server that analyzes visual information, and a terminal that provides the analysis results in audio format.

[0498] (System Overview)

[0499] Users wear a wearable imaging device to capture visual information in real time during their daily lives and business activities. This device is lightweight, comfortable to wear, and designed for extended use. The captured visual information is transmitted to a server via the user's device using an internet connection.

[0500] The server processes the received visual information using an analysis device. This analysis device incorporates a generative AI model and not only performs object recognition in images but also has the capability to acquire additional data based on location information. For example, it can search for detailed information about products identified through object recognition, or the historical background of tourist attractions at a particular location.

[0501] The analysis results are converted into audio data by a speech synthesis system on the server. This audio data is sent to the user's terminal and provided to the user via an audio output system. The user can receive various visual information in audio format and make decisions efficiently.

[0502] (Specific example)

[0503] For example, when a user enters a store, a wearable camera captures images of the product shelves, and a server analyzes them. A generated AI model identifies the products, and their prices and review information are provided via voice. This allows users to quickly compare products and make purchasing decisions.

[0504] Furthermore, when visiting tourist destinations, users can enjoy an experience similar to a guided tour by receiving information about landmarks in audio format.

[0505] (Example of a prompt message)

[0506] "I'm visiting a tourist spot, but I'd like to learn more about the surrounding historical buildings. What kind of information can I get using a device?"

[0507] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0508] Step 1:

[0509] (user)

[0510] The user uses a wearable imaging device to capture visual information about their surroundings.

[0511] Input: The object or scenery the user is looking at.

[0512] Output: Captured visual information (image data).

[0513] Specifically, when a user looks around at the shelves while shopping, the wearable camera automatically captures that scene.

[0514] Step 2:

[0515] (terminal)

[0516] The terminal sends the captured visual information to the server.

[0517] Input: Visual information (image data) received from the imaging device.

[0518] Output: Visual information transmitted over the network.

[0519] Specifically, the terminal compresses the image data and sends it to the server using the appropriate communication protocol.

[0520] Step 3:

[0521] (server)

[0522] The server analyzes the received visual information and retrieves data based on object recognition and location information.

[0523] Input: Visual information (image data) sent from the device.

[0524] Output: Analysis results (data related to specific objects or locations).

[0525] Specifically, the server uses a generative AI model to perform object recognition in images, identifying, for example, product names and their prices.

[0526] Step 4:

[0527] (server)

[0528] The server converts the analysis results into audio data.

[0529] Input: Analysis results (text or numerical data).

[0530] Output: Audio data provided to the user.

[0531] Specifically, the server uses text-to-speech technology to convert the analysis results into natural-sounding speech.

[0532] Step 5:

[0533] (terminal)

[0534] The device provides the generated audio data to the user.

[0535] Input: Audio data sent from the server.

[0536] Output: Audio information audible to the user.

[0537] Specifically, the device decodes the received audio data and plays it back through its built-in speaker to notify the user of the information.

[0538] (Application Example 1)

[0539] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0540] Modern consumers have access to a wide variety of product information when shopping in physical stores, but they lack efficient means to properly collect and utilize this information. Furthermore, it is difficult for consumers to make quick and effective purchasing decisions amidst information overload. Therefore, there is a need for technologies that enable consumers to shop more smartly and efficiently in stores.

[0541] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0542] In this invention, the server includes a wearable portable device for acquiring the user's visual information, intelligent processing means for generating information based on object recognition and spatial information, voice output means for providing the generated information in voice format, and communication means for acquiring product information and purchase support information and presenting it to the user. This makes it possible for consumers to acquire necessary product information in real time at physical stores and to be supported in making purchase decisions.

[0543] A "wearable device" is a device that a user can wear on their clothing or body and that has the function of acquiring visual information in real time.

[0544] "Intelligent processing means" refers to methods and processes that use artificial intelligence to analyze information and generate necessary data based on object recognition and spatial information.

[0545] A "sound output means" is a device that has the function of converting generated information into sound data and providing it to the user audibly.

[0546] "Communication methods" refer to the techniques and technologies used to send and receive data between a server and a user, and play a role in transmitting product information and purchasing support information via a network.

[0547] This invention is an advanced support system for improving the in-store shopping experience, utilizing a wearable device, a server, and communication means.

[0548] When a user wears a wearable device in the form of glasses and walks around a store, the device captures visual information in real time. The captured visual information is then transmitted from the device to a server via the network.

[0549] The server is equipped with intelligent processing capabilities using high-performance artificial intelligence to analyze the received visual information. Specifically, it uses software such as TensorFlow and OpenCV to perform object recognition and spatial information analysis, and further acquires information about the recognized products. This includes price, reviews, and special offer information.

[0550] The information obtained from the analysis is converted into audio data using speech synthesis software such as Google Cloud Text-to-Speech. This audio data is sent to the user's device via a communication method and provided to the user through an audio output device. The user can audibly understand detailed information about the products on the shelf, thereby enabling them to make smart purchasing decisions.

[0551] For example, if a user goes to the milk section in a supermarket and their glasses-type device recognizes a product on the shelf, the server retrieves detailed information about that product. This information is then presented aloud as, "This milk costs 200 yen. User rating is 4.5." In this way, specific processes are carried out to support an improved shopping experience.

[0552] An example of a prompt might be a question like, "Please tell me the reviews for the products in my current location." The system then provides information in real time in response to this prompt.

[0553] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0554] Step 1:

[0555] The user moves around the store wearing a wearable device. The device uses a camera to capture visual information in real time. The input is the visual information of the store, and the output is the captured image data. The device temporarily stores this data.

[0556] Step 2:

[0557] The terminal sends the captured visual information to the server. This process involves the device sending the acquired image data to the server over the network. The input is the captured image data, and the output is the data received by the server.

[0558] Step 3:

[0559] The server analyzes the received visual information using intelligent processing tools. Specifically, it performs object recognition and image processing using an AI model (e.g., TensorFlow). In this process, the server uses the received image data as input and obtains the object identification results as output. This output is a list of identified objects.

[0560] Step 4:

[0561] Based on the analysis results, the server retrieves detailed information about the identified object from the database. This process uses the object identification results as input and outputs product information (price, reviews, promotional information, etc.). The server then prepares this information for subsequent processing.

[0562] Step 5:

[0563] The server converts the retrieved product information into audio data. In this step, speech synthesis software such as Google Cloud Text-to-Speech is used to take product information as input and output data in audio format. The converted audio data is then ready to be provided to the user.

[0564] Step 6:

[0565] The terminal receives audio data from the server and provides information to the user using an audio output device. In this step, the input is the audio data transmitted from the server, and the output is the audio information perceived by the user's hearing. The terminal plays the audio at an appropriate volume so that the user can easily understand the information.

[0566] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0567] This invention is a system that realizes more personalized information delivery by combining a wearable camera, artificial intelligence means, and voice output device with an emotion engine for recognizing the user's emotions. The user wears glasses-type wearable camera and acquires visual information and emotional state in real time.

[0568] The device not only captures the user's visual information but also uses an emotion engine to analyze the user's emotions from their facial expressions and voice. This information is transmitted to a server via the network.

[0569] The server analyzes the received visual information and performs object recognition, while simultaneously receiving emotional state data from the emotion engine. Based on the object recognition results and emotional state, a process is carried out to generate optimal information and convert it into audio format.

[0570] This audio data is sent back to the terminal and provided to the user through an audio output device. The information can be customized according to the user's emotional state; for example, if the user is feeling stressed, relaxing music or advice can be provided.

[0571] For example, if a user is wearing the device in a busy business environment, the emotion engine will detect the user's stress, and the server will select relaxation methods and positive messages to communicate to the user via voice. Similarly, if a user visiting a tourist destination expresses feelings of joy, the system will suggest interesting tourist information and enjoyable activities.

[0572] Furthermore, by recording the history of the user's emotional changes in a life log and reviewing it later, it helps deepen self-awareness and facilitates better decision-making. Thus, the present invention aims to further improve the quality of life for users by enabling the integrated use of visual and linguistic information.

[0573] The following describes the processing flow.

[0574] Step 1:

[0575] The device captures visual information in real time through a wearable camera. Simultaneously, an emotion engine analyzes the user's emotional state based on their facial expressions and voice. This results in the acquisition of both visual and emotional data.

[0576] Step 2:

[0577] The device transmits visual information and emotional state data acquired by the device to a server via the network. The data package includes image data, location information, and emotional information.

[0578] Step 3:

[0579] The server analyzes the received visual information using an AI algorithm to perform object recognition. Simultaneously, it analyzes emotional state data received from the emotion engine to understand the user's current emotional state.

[0580] Step 4:

[0581] The server generates information to provide to the user based on the object recognition results and emotional state. If the emotional state indicates stress, the information is customized to include information related to relaxation.

[0582] Step 5:

[0583] The server converts the generated information into audio data and sends the audio information to the terminal. This audio data includes feedback tailored to the user's emotional state.

[0584] Step 6:

[0585] The device uses an audio output device to present the received audio data to the user. This allows the user to receive real-time support and information tailored to their emotional state.

[0586] Step 7:

[0587] The user requests additional information via voice commands as needed. These voice commands are sent from the terminal to the server, where the information is processed again.

[0588] Step 8:

[0589] The server continuously monitors changes in emotional state and updates the life log. This allows users to reflect on past emotional states and use that information to inform future actions and decision-making.

[0590] (Example 2)

[0591] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0592] A problem with modern information systems is that they do not adequately provide information tailored to the emotional state of individual users. In particular, the lack of nuanced information customization based on user emotions hinders improvements in the quality of the user experience. Therefore, there is a need for a system that can grasp the user's real-time emotional state and provide optimal information tailored to that state via voice.

[0593] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0594] In this invention, the server includes a wearable device means equipped with a camera and an audio acquisition device for acquiring the user's visual and audio information in real time; an emotion analysis means for analyzing the user's emotional state using the visual and audio information; and an artificial intelligence means for further analyzing the visual information and generating information based on object recognition and emotional state. This makes it possible to provide information that is appropriately customized according to the user's real-time emotional state.

[0595] "Visual information" refers to image and video data of the surroundings that the user is viewing, and is acquired in real time by wearable devices.

[0596] "Audio information" refers to audio data that includes the user's voice or surrounding sounds, and is collected by a wearable device.

[0597] A "wearable device" is a device that allows a user to acquire visual and auditory information by being worn by the user, and it comes in a form that the user can use on a daily basis, such as glasses.

[0598] "Emotional analysis means" refers to analysis methods and devices for identifying a user's emotional state based on acquired visual and auditory information.

[0599] "Object recognition" refers to the technology that identifies objects and situations that a user is seeing by analyzing visual information.

[0600] "Artificial intelligence tools" refer to machine learning algorithms and software used to analyze collected data and generate situation-appropriate information.

[0601] A "sound output device" refers to a device that converts generated information into sound data and provides it directly to the user audibly.

[0602] This invention is a system that can customize information according to the user's emotional state. The system includes the following main hardware and software components.

[0603] The user wears a wearable device in the form of glasses or other shapes, which is equipped with a high-resolution camera and a high-sensitivity microphone. The camera captures visual information in real time, and the audio acquisition device captures audio information in real time.

[0604] The device receives the acquired visual and audio information and first performs data conversion for image recognition and emotion analysis. Here, a general API (e.g., EmotionAPI) is used for face recognition, and speech recognition software is used for voice tone analysis.

[0605] The server receives data sent from the terminal and performs object recognition based on visual information. A deep learning framework (e.g., TensorFlow) is used for object recognition. Next, the server analyzes the user's emotional state using emotion analysis tools and generates information optimized for each individual user using a generative AI model.

[0606] The generated information is converted into audio data by speech synthesis software (e.g., a speech synthesis API). This audio data is transmitted to a terminal over the network and provided to the user via an audio output device (e.g., earphones).

[0607] For example, if a user visits a crowded shopping mall and the emotion engine detects "stress," the server will provide information about a quiet cafe as a way to relax. This information is conveyed to the user as audio on their device.

[0608] An example of a prompt message is, "Suggest relaxing music for the user to play when they are feeling emotionally exhausted."

[0609] Thus, this system aims to efficiently process the user's visual and auditory information and provide personalized information in real time to improve the user's quality of life.

[0610] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0611] Step 1:

[0612] The user wears a glasses-type wearable device to acquire visual and auditory information. This device captures video through a camera and audio through a microphone. Image and audio data are obtained as input.

[0613] Step 2:

[0614] The terminal preprocesses the visual and audio information received from the wearable device. Image data undergoes resolution adjustment, and audio data is denoised. Preprocessing prepares the data for easier analysis.

[0615] Step 3:

[0616] The device performs emotion analysis using pre-processed visual and audio information. It estimates the user's emotional state using a facial recognition algorithm and voice tone analysis software. The output of this process is data on the user's current emotional state.

[0617] Step 4:

[0618] The device transmits visual information and emotional state data to the server. This communication takes place over a network, and security is ensured through the use of data encryption technology.

[0619] Step 5:

[0620] The server analyzes the received visual information using a deep learning framework to perform object recognition. The input is visual information, and the output is object type and location information. Simultaneously, using emotional state data, a generative AI model generates suggestions tailored to the user's emotions. This results in customized information.

[0621] Step 6:

[0622] The server converts the generated information into speech data using speech synthesis software. This conversion results in output in a natural-sounding speech format.

[0623] Step 7:

[0624] The server retransmits the converted audio data to the terminal. The audio data is transmitted securely via the network using encryption.

[0625] Step 8:

[0626] The terminal transmits received audio data to the user. Using an audio output device, it plays the audio so that the user can easily receive the information. Interactive and real-time feedback is achieved.

[0627] (Application Example 2)

[0628] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0629] Traditional in-store customer service is uniform, making it difficult to understand individual customer needs and emotional states in real time and provide information accordingly. Therefore, there is a need to improve the customer experience. In particular, with the increasing need for personalized information based on customer emotions, the development of technological means to provide effective information in real time is urgently required.

[0630] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0631] In this invention, the server includes a portable imaging device means for capturing the user's visual and auditory information, a component means for analyzing the visual and auditory information and generating information based on specific object recognition and emotion analysis, and an output device means for providing the generated information to the user in audio format. This enables the provision of personalized information according to the user's emotional state.

[0632] A "user" refers to a consumer or customer who uses this system.

[0633] "Visual information" refers to data related to the user's visual environment, and includes image or video data.

[0634] "Audio information" refers to information that includes the voice emitted by the user and acoustic data of the surrounding environment.

[0635] A "portable recording device" is a device capable of recording and taking pictures that is small enough for a user to wear or carry with them.

[0636] "Specific object recognition" is a technology that analyzes visual information to identify specific objects, places, or human actions.

[0637] "Emotional analysis" is the process of analyzing audio and visual information to evaluate a user's emotional state.

[0638] "Components" refer to elements including the hardware and software necessary for information processing.

[0639] An "output device" is a device that presents generated information to the user in audio or video format.

[0640] "Personalized information" refers to personalized information provided based on a user's specific needs and emotions.

[0641] The system implementing this invention begins with the user wearing a portable imaging device to capture visual and auditory information in real time. The system's hardware includes a wearable device equipped with glasses-type cameras and microphones. This allows for the rapid collection of information obtained from the user's sight and hearing.

[0642] On the server, captured visual information is analyzed using image recognition libraries such as OpenCV. This identifies specific objects or people's actions. Additionally, audio information is analyzed by an emotion analysis engine utilizing the Microsoft Azure Emotion API to evaluate the user's emotional state. This allows for real-time understanding of the user's emotions, such as what interests them or what makes them feel uncomfortable.

[0643] Based on the analysis results, the server uses the artificial intelligence framework TensorFlow to generate personalized information to provide to the user. This information is converted from text to speech and played back through the user's output device (e.g., headset or smart speaker).

[0644] As a concrete example, when a customer picks up a product in a physical store, the system can provide detailed information related to that product based on the customer's interests and emotions. For instance, a voice guide might be provided saying, "This product features the latest function, XX."

[0645] The following is an example of a prompt message when using a generative AI model.

[0646] "When a customer shows interest in XX (a specific product), generate an audio guide that briefly explains the main features of that product."

[0647] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0648] Step 1:

[0649] The device captures visual and auditory information from the user's surroundings using a wearable camera. This device collects video and audio data using a built-in camera and microphone. The input data is sent to a server as raw data.

[0650] Step 2:

[0651] The server processes the received visual information using OpenCV to perform object recognition. Specifically, it identifies specific objects or people from the input video data and extracts their features. The output is a list of recognized objects.

[0652] Step 3:

[0653] The server uses the Microsoft Azure Emotion API to perform emotion analysis on the audio information. In this step, the server analyzes the user's voice tone and linguistic characteristics from the audio data and evaluates their emotional state. The output is data indicating the user's emotional state.

[0654] Step 4:

[0655] The server uses TensorFlow based on the analysis results to generate personalized information to display or play for the user. This process takes recognized object information and emotional state data as input, and the generative AI model selects the most relevant information. The output is the selected information in text format.

[0656] Step 5:

[0657] The server converts the generated information from text to speech and outputs it to the user via the terminal. This conversion uses a Text-to-Speech (TTS) engine to convert the information into audio format. The output is audio data that the user can listen to.

[0658] Step 6:

[0659] The user receives personalized information via voice and makes decisions based on it. In this step, the user can receive real-time feedback based on the voice information. This output is a crucial element in supporting the user's decision-making.

[0660] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0661] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0662] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0663] [Fourth Embodiment]

[0664] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0665] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0666] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0667] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0668] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0669] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0670] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0671] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0672] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0673] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0674] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0675] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0676] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0677] This invention provides a system that allows users wearing a glasses-type device as a wearable imaging device to acquire and utilize information in real time in their daily lives and business environments. The system mainly consists of a glasses-type device worn by the user and a server that analyzes and provides the information.

[0678] The user captures visual information in real time using a wearable camera. This visual information is transmitted from the terminal to a server via the network. The server is equipped with artificial intelligence to analyze the received visual information, performing object recognition and acquiring data about the surrounding environment based on location information.

[0679] The information obtained from the analysis is converted into audio data on the server and transmitted to the terminal. The terminal provides this audio data to the user via an audio output device. This allows the user to receive real-time assistance based on visual information in audio format.

[0680] As a concrete example, when a user enters a store, a wearable camera captures visual information of the products on the shelves. The server analyzes these images, retrieves detailed product information (e.g., price, reviews), and provides it to the user via voice, allowing the user to shop more efficiently.

[0681] Furthermore, when travelers visit tourist destinations, the system recognizes surrounding landmarks and provides related historical and tourist information via audio, enabling an experience similar to a guided tour.

[0682] This invention allows users to benefit from digital technology on a daily basis without requiring any special operations, and particularly supports independent living for the elderly and visually impaired by enhancing visual support.

[0683] The following describes the processing flow.

[0684] Step 1:

[0685] The device captures visual information in real time through a wearable camera. The device continuously acquires image data within the user's field of vision.

[0686] Step 2:

[0687] The device packages the visual information it captures with the location information obtained from the GPS module and sends it to the server. The data is transmitted in real time over the network.

[0688] Step 3:

[0689] The server analyzes the received visual information using an AI algorithm to perform object recognition. This involves identifying the type and characteristics of the object and retrieving associated data from a database.

[0690] Step 4:

[0691] The server uses location information to understand the surrounding geographical environment and collects relevant geographical and local information. This includes map information and data on local commercial facilities.

[0692] Step 5:

[0693] The server generates information to be provided to the user based on the object recognition results and geographical information, and converts it into audio format. The information is then processed to meet the user's needs.

[0694] Step 6:

[0695] The server sends the generated audio data to the terminal. The data is configured to reach the user's device immediately.

[0696] Step 7:

[0697] The device receives audio data, which is then presented to the user via an audio output device. The user uses this information to understand the situation in real time and make decisions.

[0698] Step 8:

[0699] If the user requests additional information or gives new instructions based on voice feedback, they enter voice commands into the terminal. The terminal then sends another request to the server and receives information to assist with the next action.

[0700] (Example 1)

[0701] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0702] In modern society, users are required to quickly obtain necessary information about their surroundings and objects. However, conventional information acquisition methods require users to search for information themselves or operate devices, making them impractical for people with visual impairments or the elderly. In this situation, there is a need for systems that provide information more intuitively and in real time.

[0703] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0704] In this invention, the server includes a wearable imaging device for capturing the user's visual information, means for transmitting the visual information to an analysis device via a network, and analysis means including a generative AI model for analyzing the visual information and acquiring data based on object recognition and location information. This enables the user to receive necessary information in real time via voice based on the visual information without requiring any special operation.

[0705] A "wearable imaging device" is an imaging device that can be worn by a user and has the function of capturing visual information in real time.

[0706] An "analysis device" is a computing system located within a server that processes received visual information and acquires specific data.

[0707] "Means for transmitting to an analysis device via a network" refers to a protocol or mechanism for transmitting visual information to an analysis device using the internet or other communication infrastructure.

[0708] A "generative AI model" is a mathematical or software model that uses artificial intelligence technology to analyze data and perform object recognition.

[0709] "Analysis means" refers to a series of processing devices that include a generative AI model and extract relevant data from visual information.

[0710] "Speech synthesis means" refers to a technology or process for converting text data into a speech format, and is a means that plays a role in providing speech information to users.

[0711] "Audio output means" refers to audio devices such as speakers or earphones used to transmit generated audio data to the user.

[0712] This invention relates to a system that enables users to acquire and utilize visual information more efficiently. This system includes a wearable imaging device worn by the user, a server that analyzes visual information, and a terminal that provides the analysis results in audio format.

[0713] (System Overview)

[0714] Users wear a wearable imaging device to capture visual information in real time during their daily lives and business activities. This device is lightweight, comfortable to wear, and designed for extended use. The captured visual information is transmitted to a server via the user's device using an internet connection.

[0715] The server processes the received visual information using an analysis device. This analysis device incorporates a generative AI model and not only performs object recognition in images but also has the capability to acquire additional data based on location information. For example, it can search for detailed information about products identified through object recognition, or the historical background of tourist attractions at a particular location.

[0716] The analysis results are converted into audio data by a speech synthesis system on the server. This audio data is sent to the user's terminal and provided to the user via an audio output system. The user can receive various visual information in audio format and make decisions efficiently.

[0717] (Specific example)

[0718] For example, when a user enters a store, a wearable camera captures images of the product shelves, and a server analyzes them. A generated AI model identifies the products, and their prices and review information are provided via voice. This allows users to quickly compare products and make purchasing decisions.

[0719] Furthermore, when visiting tourist destinations, users can enjoy an experience similar to a guided tour by receiving information about landmarks in audio format.

[0720] (Example of a prompt message)

[0721] "I'm visiting a tourist spot, but I'd like to learn more about the surrounding historical buildings. What kind of information can I get using a device?"

[0722] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0723] Step 1:

[0724] (user)

[0725] The user uses a wearable imaging device to capture visual information about their surroundings.

[0726] Input: The object or scenery the user is looking at.

[0727] Output: Captured visual information (image data).

[0728] Specifically, when a user looks around at the shelves while shopping, the wearable camera automatically captures that scene.

[0729] Step 2:

[0730] (terminal)

[0731] The terminal sends the captured visual information to the server.

[0732] Input: Visual information (image data) received from the imaging device.

[0733] Output: Visual information transmitted over the network.

[0734] Specifically, the terminal compresses the image data and sends it to the server using the appropriate communication protocol.

[0735] Step 3:

[0736] (server)

[0737] The server analyzes the received visual information and retrieves data based on object recognition and location information.

[0738] Input: Visual information (image data) sent from the device.

[0739] Output: Analysis results (data related to specific objects or locations).

[0740] Specifically, the server uses a generative AI model to perform object recognition in images, identifying, for example, product names and their prices.

[0741] Step 4:

[0742] (server)

[0743] The server converts the analysis results into audio data.

[0744] Input: Analysis results (text or numerical data).

[0745] Output: Audio data provided to the user.

[0746] Specifically, the server uses text-to-speech technology to convert the analysis results into natural-sounding speech.

[0747] Step 5:

[0748] (terminal)

[0749] The device provides the generated audio data to the user.

[0750] Input: Audio data sent from the server.

[0751] Output: Audio information audible to the user.

[0752] Specifically, the device decodes the received audio data and plays it back through its built-in speaker to notify the user of the information.

[0753] (Application Example 1)

[0754] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0755] Modern consumers have access to a wide variety of product information when shopping in physical stores, but they lack efficient means to properly collect and utilize this information. Furthermore, it is difficult for consumers to make quick and effective purchasing decisions amidst information overload. Therefore, there is a need for technologies that enable consumers to shop more smartly and efficiently in stores.

[0756] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0757] In this invention, the server includes a wearable portable device for acquiring the user's visual information, intelligent processing means for generating information based on object recognition and spatial information, voice output means for providing the generated information in voice format, and communication means for acquiring product information and purchase support information and presenting it to the user. This makes it possible for consumers to acquire necessary product information in real time at physical stores and to be supported in making purchase decisions.

[0758] A "wearable device" is a device that a user can wear on their clothing or body and that has the function of acquiring visual information in real time.

[0759] "Intelligent processing means" refers to methods and processes that use artificial intelligence to analyze information and generate necessary data based on object recognition and spatial information.

[0760] A "sound output means" is a device that has the function of converting generated information into sound data and providing it to the user audibly.

[0761] "Communication methods" refer to the techniques and technologies used to send and receive data between a server and a user, and play a role in transmitting product information and purchasing support information via a network.

[0762] This invention is an advanced support system for improving the in-store shopping experience, utilizing a wearable device, a server, and communication means.

[0763] When a user wears a wearable device in the form of glasses and walks around a store, the device captures visual information in real time. The captured visual information is then transmitted from the device to a server via the network.

[0764] The server is equipped with intelligent processing capabilities using high-performance artificial intelligence to analyze the received visual information. Specifically, it uses software such as TensorFlow and OpenCV to perform object recognition and spatial information analysis, and further acquires information about the recognized products. This includes price, reviews, and special offer information.

[0765] The information obtained from the analysis is converted into audio data using speech synthesis software such as Google Cloud Text-to-Speech. This audio data is sent to the user's device via a communication method and provided to the user through an audio output device. The user can audibly understand detailed information about the products on the shelf, thereby enabling them to make smart purchasing decisions.

[0766] For example, if a user goes to the milk section in a supermarket and their glasses-type device recognizes a product on the shelf, the server retrieves detailed information about that product. This information is then presented aloud as, "This milk costs 200 yen. User rating is 4.5." In this way, specific processes are carried out to support an improved shopping experience.

[0767] An example of a prompt might be a question like, "Please tell me the reviews for the products in my current location." The system then provides information in real time in response to this prompt.

[0768] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0769] Step 1:

[0770] The user moves around the store wearing a wearable device. The device uses a camera to capture visual information in real time. The input is the visual information of the store, and the output is the captured image data. The device temporarily stores this data.

[0771] Step 2:

[0772] The terminal sends the captured visual information to the server. This process involves the device sending the acquired image data to the server over the network. The input is the captured image data, and the output is the data received by the server.

[0773] Step 3:

[0774] The server analyzes the received visual information using intelligent processing tools. Specifically, it performs object recognition and image processing using an AI model (e.g., TensorFlow). In this process, the server uses the received image data as input and obtains the object identification results as output. This output is a list of identified objects.

[0775] Step 4:

[0776] Based on the analysis results, the server retrieves detailed information about the identified object from the database. This process uses the object identification results as input and outputs product information (price, reviews, promotional information, etc.). The server then prepares this information for subsequent processing.

[0777] Step 5:

[0778] The server converts the retrieved product information into audio data. In this step, speech synthesis software such as Google Cloud Text-to-Speech is used to take product information as input and output data in audio format. The converted audio data is then ready to be provided to the user.

[0779] Step 6:

[0780] The terminal receives audio data from the server and provides information to the user using an audio output device. In this step, the input is the audio data transmitted from the server, and the output is the audio information perceived by the user's hearing. The terminal plays the audio at an appropriate volume so that the user can easily understand the information.

[0781] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0782] This invention is a system that realizes more personalized information delivery by combining a wearable camera, artificial intelligence means, and voice output device with an emotion engine for recognizing the user's emotions. The user wears glasses-type wearable camera and acquires visual information and emotional state in real time.

[0783] The device not only captures the user's visual information but also uses an emotion engine to analyze the user's emotions from their facial expressions and voice. This information is transmitted to a server via the network.

[0784] The server analyzes the received visual information and performs object recognition, while simultaneously receiving emotional state data from the emotion engine. Based on the object recognition results and emotional state, a process is carried out to generate optimal information and convert it into audio format.

[0785] This audio data is sent back to the terminal and provided to the user through an audio output device. The information can be customized according to the user's emotional state; for example, if the user is feeling stressed, relaxing music or advice can be provided.

[0786] For example, if a user is wearing the device in a busy business environment, the emotion engine will detect the user's stress, and the server will select relaxation methods and positive messages to communicate to the user via voice. Similarly, if a user visiting a tourist destination expresses feelings of joy, the system will suggest interesting tourist information and enjoyable activities.

[0787] Furthermore, by recording the history of the user's emotional changes in a life log and reviewing it later, it helps deepen self-awareness and facilitates better decision-making. Thus, the present invention aims to further improve the quality of life for users by enabling the integrated use of visual and linguistic information.

[0788] The following describes the processing flow.

[0789] Step 1:

[0790] The device captures visual information in real time through a wearable camera. Simultaneously, an emotion engine analyzes the user's emotional state based on their facial expressions and voice. This results in the acquisition of both visual and emotional data.

[0791] Step 2:

[0792] The device transmits visual information and emotional state data acquired by the device to a server via the network. The data package includes image data, location information, and emotional information.

[0793] Step 3:

[0794] The server analyzes the received visual information using an AI algorithm to perform object recognition. Simultaneously, it analyzes emotional state data received from the emotion engine to understand the user's current emotional state.

[0795] Step 4:

[0796] The server generates information to provide to the user based on the object recognition results and emotional state. If the emotional state indicates stress, the information is customized to include information related to relaxation.

[0797] Step 5:

[0798] The server converts the generated information into audio data and sends the audio information to the terminal. This audio data includes feedback tailored to the user's emotional state.

[0799] Step 6:

[0800] The device uses an audio output device to present the received audio data to the user. This allows the user to receive real-time support and information tailored to their emotional state.

[0801] Step 7:

[0802] The user requests additional information via voice commands as needed. These voice commands are sent from the terminal to the server, where the information is processed again.

[0803] Step 8:

[0804] The server continuously monitors changes in emotional state and updates the life log. This allows users to reflect on past emotional states and use that information to inform future actions and decision-making.

[0805] (Example 2)

[0806] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0807] A problem with modern information systems is that they do not adequately provide information tailored to the emotional state of individual users. In particular, the lack of nuanced information customization based on user emotions hinders improvements in the quality of the user experience. Therefore, there is a need for a system that can grasp the user's real-time emotional state and provide optimal information tailored to that state via voice.

[0808] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0809] In this invention, the server includes a wearable device means equipped with a camera and an audio acquisition device for acquiring the user's visual and audio information in real time; an emotion analysis means for analyzing the user's emotional state using the visual and audio information; and an artificial intelligence means for further analyzing the visual information and generating information based on object recognition and emotional state. This makes it possible to provide information that is appropriately customized according to the user's real-time emotional state.

[0810] "Visual information" refers to image and video data of the surroundings that the user is viewing, and is acquired in real time by wearable devices.

[0811] "Audio information" refers to audio data that includes the user's voice or surrounding sounds, and is collected by a wearable device.

[0812] A "wearable device" is a device that allows a user to acquire visual and auditory information by being worn by the user, and it comes in a form that the user can use on a daily basis, such as glasses.

[0813] "Emotional analysis means" refers to analysis methods and devices for identifying a user's emotional state based on acquired visual and auditory information.

[0814] "Object recognition" refers to the technology that identifies objects and situations that a user is seeing by analyzing visual information.

[0815] "Artificial intelligence tools" refer to machine learning algorithms and software used to analyze collected data and generate situation-appropriate information.

[0816] A "sound output device" refers to a device that converts generated information into sound data and provides it directly to the user audibly.

[0817] This invention is a system that can customize information according to the user's emotional state. The system includes the following main hardware and software components.

[0818] The user wears a wearable device in the form of glasses or other shapes, which is equipped with a high-resolution camera and a high-sensitivity microphone. The camera captures visual information in real time, and the audio acquisition device captures audio information in real time.

[0819] The device receives the acquired visual and audio information and first performs data conversion for image recognition and emotion analysis. Here, a general API (e.g., EmotionAPI) is used for face recognition, and speech recognition software is used for voice tone analysis.

[0820] The server receives data sent from the terminal and performs object recognition based on visual information. A deep learning framework (e.g., TensorFlow) is used for object recognition. Next, the server analyzes the user's emotional state using emotion analysis tools and generates information optimized for each individual user using a generative AI model.

[0821] The generated information is converted into audio data by speech synthesis software (e.g., a speech synthesis API). This audio data is transmitted to a terminal over the network and provided to the user via an audio output device (e.g., earphones).

[0822] For example, if a user visits a crowded shopping mall and the emotion engine detects "stress," the server will provide information about a quiet cafe as a way to relax. This information is conveyed to the user as audio on their device.

[0823] An example of a prompt message is, "Suggest relaxing music for the user to play when they are feeling emotionally exhausted."

[0824] Thus, this system aims to efficiently process the user's visual and auditory information and provide personalized information in real time to improve the user's quality of life.

[0825] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0826] Step 1:

[0827] The user wears a glasses-type wearable device to acquire visual and auditory information. This device captures video through a camera and audio through a microphone. Image and audio data are obtained as input.

[0828] Step 2:

[0829] The terminal preprocesses the visual and audio information received from the wearable device. Image data undergoes resolution adjustment, and audio data is denoised. Preprocessing prepares the data for easier analysis.

[0830] Step 3:

[0831] The device performs emotion analysis using pre-processed visual and audio information. It estimates the user's emotional state using a facial recognition algorithm and voice tone analysis software. The output of this process is data on the user's current emotional state.

[0832] Step 4:

[0833] The device transmits visual information and emotional state data to the server. This communication takes place over a network, and security is ensured through the use of data encryption technology.

[0834] Step 5:

[0835] The server analyzes the received visual information using a deep learning framework to perform object recognition. The input is visual information, and the output is object type and location information. Simultaneously, using emotional state data, a generative AI model generates suggestions tailored to the user's emotions. This results in customized information.

[0836] Step 6:

[0837] The server converts the generated information into speech data using speech synthesis software. This conversion results in output in a natural-sounding speech format.

[0838] Step 7:

[0839] The server retransmits the converted audio data to the terminal. The audio data is transmitted securely via the network using encryption.

[0840] Step 8:

[0841] The terminal transmits received audio data to the user. Using an audio output device, it plays the audio so that the user can easily receive the information. Interactive and real-time feedback is achieved.

[0842] (Application Example 2)

[0843] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0844] Traditional in-store customer service is uniform, making it difficult to understand individual customer needs and emotional states in real time and provide information accordingly. Therefore, there is a need to improve the customer experience. In particular, with the increasing need for personalized information based on customer emotions, the development of technological means to provide effective information in real time is urgently required.

[0845] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0846] In this invention, the server includes a portable imaging device means for capturing the user's visual and auditory information, a component means for analyzing the visual and auditory information and generating information based on specific object recognition and emotion analysis, and an output device means for providing the generated information to the user in audio format. This enables the provision of personalized information according to the user's emotional state.

[0847] A "user" refers to a consumer or customer who uses this system.

[0848] "Visual information" refers to data related to the user's visual environment, and includes image or video data.

[0849] "Audio information" refers to information that includes the voice emitted by the user and acoustic data of the surrounding environment.

[0850] A "portable recording device" is a device capable of recording and taking pictures that is small enough for a user to wear or carry with them.

[0851] "Specific object recognition" is a technology that analyzes visual information to identify specific objects, places, or human actions.

[0852] "Emotional analysis" is the process of analyzing audio and visual information to evaluate a user's emotional state.

[0853] "Components" refer to elements including the hardware and software necessary for information processing.

[0854] An "output device" is a device that presents generated information to the user in audio or video format.

[0855] "Personalized information" refers to personalized information provided based on a user's specific needs and emotions.

[0856] The system implementing this invention begins with the user wearing a portable imaging device to capture visual and auditory information in real time. The system's hardware includes a wearable device equipped with glasses-type cameras and microphones. This allows for the rapid collection of information obtained from the user's sight and hearing.

[0857] On the server, captured visual information is analyzed using image recognition libraries such as OpenCV. This identifies specific objects or people's actions. Additionally, audio information is analyzed by an emotion analysis engine utilizing the Microsoft Azure Emotion API to evaluate the user's emotional state. This allows for real-time understanding of the user's emotions, such as what interests them or what makes them feel uncomfortable.

[0858] Based on the analysis results, the server uses the artificial intelligence framework TensorFlow to generate personalized information to provide to the user. This information is converted from text to speech and played back through the user's output device (e.g., headset or smart speaker).

[0859] As a concrete example, when a customer picks up a product in a physical store, the system can provide detailed information related to that product based on the customer's interests and emotions. For instance, a voice guide might be provided saying, "This product features the latest function, XX."

[0860] The following is an example of a prompt message when using a generative AI model.

[0861] "When a customer shows interest in XX (a specific product), generate an audio guide that briefly explains the main features of that product."

[0862] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0863] Step 1:

[0864] The device captures visual and auditory information from the user's surroundings using a wearable camera. This device collects video and audio data using a built-in camera and microphone. The input data is sent to a server as raw data.

[0865] Step 2:

[0866] The server processes the received visual information using OpenCV to perform object recognition. Specifically, it identifies specific objects or people from the input video data and extracts their features. The output is a list of recognized objects.

[0867] Step 3:

[0868] The server uses the Microsoft Azure Emotion API to perform emotion analysis on the audio information. In this step, the server analyzes the user's voice tone and linguistic characteristics from the audio data and evaluates their emotional state. The output is data indicating the user's emotional state.

[0869] Step 4:

[0870] The server uses TensorFlow based on the analysis results to generate personalized information to display or play for the user. This process takes recognized object information and emotional state data as input, and the generative AI model selects the most relevant information. The output is the selected information in text format.

[0871] Step 5:

[0872] The server converts the generated information from text to speech and outputs it to the user via the terminal. This conversion uses a Text-to-Speech (TTS) engine to convert the information into audio format. The output is audio data that the user can listen to.

[0873] Step 6:

[0874] The user receives personalized information via voice and makes decisions based on it. In this step, the user can receive real-time feedback based on the voice information. This output is a crucial element in supporting the user's decision-making.

[0875] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0876] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0877] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0878] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0879] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0880] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0881] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0882] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0883] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0884] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0885] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0886] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0887] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0888] 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.

[0889] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0890] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0891] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0892] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0893] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0894] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0895] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted as being incorporated by reference.

[0896] The following is further disclosed regarding the embodiments described above.

[0897] (Claim 1)

[0898] A wearable camera for capturing the user's visual information,

[0899] Artificial intelligence means that analyzes the aforementioned visual information and generates information based on object recognition and location information,

[0900] An audio output device that provides the generated information to the user in audio format,

[0901] A system that includes this.

[0902] (Claim 2)

[0903] The system according to claim 1, characterized in that it grasps the user's location in real time and presents surrounding information by voice.

[0904] (Claim 3)

[0905] The system according to claim 1, characterized in that it automatically creates a life log and allows the user to review the information later.

[0906] "Example 1"

[0907] (Claim 1)

[0908] A wearable imaging device for capturing the user's visual information,

[0909] Means for transmitting the aforementioned visual information to an analysis device via a network,

[0910] Analysis means including a generative AI model that analyzes the aforementioned visual information and acquires data based on object recognition and location information,

[0911] A speech synthesis means for converting the analysis results into audio data,

[0912] A voice output means that provides the generated voice data to the user,

[0913] A system that includes this.

[0914] (Claim 2)

[0915] The system according to claim 1, characterized in that it grasps the user's location in real time and presents surrounding information in voice using a generated AI model.

[0916] (Claim 3)

[0917] The system according to claim 1, characterized in that it automatically creates a life log and allows the user to later review the data based on the generated AI model.

[0918] "Application Example 1"

[0919] (Claim 1)

[0920] A wearable portable device for acquiring the user's visual information,

[0921] Intelligent processing means for analyzing the aforementioned visual information and generating information based on object recognition and spatial information,

[0922] A voice output means that provides the generated information in audio format,

[0923] A means of communication that acquires product information and purchase support information and presents it to the user,

[0924] A system that includes this.

[0925] (Claim 2)

[0926] The system according to claim 1, characterized by real-time tracking of the user's location, providing environmental information via voice, and improving purchasing efficiency.

[0927] (Claim 3)

[0928] The system according to claim 1, characterized in that it automatically creates a consumer purchase history and allows the user to review the information later.

[0929] "Example 2 of combining an emotion engine"

[0930] (Claim 1)

[0931] A wearable device equipped with a camera and an audio acquisition device for acquiring the user's visual and audio information in real time,

[0932] An emotion analysis means for analyzing the user's emotional state using the aforementioned visual and auditory information,

[0933] An artificial intelligence means for further analyzing the aforementioned visual information and generating information based on object recognition and emotional state,

[0934] An audio output device that converts generated information into audio and provides it to the user,

[0935] A system that includes this.

[0936] (Claim 2)

[0937] The system according to claim 1, characterized in that it grasps the user's emotional state in real time and presents adaptive information in voice.

[0938] (Claim 3)

[0939] The system according to claim 1, characterized in that it automatically creates a life log based on the user's emotional changes and visual information, and allows the user to review it later.

[0940] "Application example 2 when combining with an emotional engine"

[0941] (Claim 1)

[0942] A portable camera for capturing user visual and audio information,

[0943] A component that analyzes the aforementioned visual and auditory information and generates information based on the recognition of a specific object and emotion analysis,

[0944] An output device that provides the generated information to the user in audio format,

[0945] A device for customizing information according to the user's emotional state,

[0946] A system that includes this.

[0947] (Claim 2)

[0948] The system according to claim 1, characterized by providing personalized information in real time and providing support in a physical space.

[0949] (Claim 3)

[0950] The system according to claim 1, characterized in that it saves a history of user emotional changes and makes it verifiable later as an activity history. [Explanation of Symbols]

[0951] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A wearable camera for capturing the user's visual information, An artificial intelligence means that analyzes the aforementioned visual information and generates information based on object recognition and location information, An audio output device that provides the generated information to the user in audio format, A system that includes this.

2. The system according to claim 1, characterized in that it grasps the user's location in real time and presents surrounding information by voice.

3. The system according to claim 1, characterized in that it automatically creates a life log and allows the user to review the information later.

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