System

Abstract

A system is provided.SOLUTION: The system includes a video capture means for capturing video data in front, an analysis server means for analyzing the captured video data, a voice output means for guiding information based on the analyzed video data to the visually handicapped person by voice, and a display means for displaying the information based on the analyzed video data by augmented reality.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] Visually impaired people face many inconveniences in their daily lives due to difficulty in recognizing what is ahead and the objects and people around them. Conventional methods such as tactile paving and guide dogs are unable to fully grasp their surroundings, and there are limitations to improving the quality of life for visually impaired people. In order for visually impaired people to live more independent lives, new technologies that provide information about their surroundings in real time are needed. [Means for solving the problem]

[0005] The present invention provides a visual support system for visually impaired persons, including a video capture means for capturing video data of the area ahead, an analysis server means for analyzing the captured video data, an audio output means for providing audio guidance to visually impaired persons based on the analyzed video data, and a display means for displaying the information based on the analyzed video data in an augmented reality format. Specifically, the video data captured by the video capture means is transmitted to the analysis server means via a wireless network, and the analysis server means analyzes the video data using multimodal artificial intelligence. Based on the analysis results, data for audio guidance and augmented reality display is generated, which is then transmitted back to the terminal and output as audio guidance, and the augmented reality display data is displayed on the display means. This system enables visually impaired persons to accurately grasp their surroundings in real time and act safely.

[0006] "Forward image data" refers to image information in the direction of the user's line of sight captured by a camera mounted on the visual support glasses.

[0007] "Video capture means" refers to the camera device and its control module built into the visual support glasses, and is a means for acquiring visual information of the environment in real time.

[0008] The term "analysis server means" refers to a set of a server and related hardware and software for receiving and analyzing video data transmitted by the video capture means.

[0009] "Multimodal AI" refers to an AI technology that comprehensively analyzes different types of data (e.g., video, audio, text).

[0010] The "voice guidance means" is a means for providing the user with the voice guide data transmitted from the analysis server means as auditory information, and typically includes a speaker embedded in the glasses and a control device for the speaker.

[0011] "Augmented reality display means" refers to a display and its control module for projecting and displaying the visual information sent from the analysis server means on the visual support glasses in order to visually complement and enhance the visual information. [Brief explanation of the drawings]

[0012] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14]FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0013] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0014] First, the terms used in the following description will be explained.

[0015] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0016] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0017] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0018] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0019] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0020] [First embodiment]

[0021] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0022] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0023] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0024] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0025] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0026] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0027] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0028] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0029] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0030] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0031] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0032] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0033] The present invention is a visual support system for visually impaired people, which includes a video capture unit, an analysis server unit, a voice guidance unit, and an augmented reality display unit. Using this system, visually impaired people can obtain information about their surrounding environment in real time and live their lives safely.

[0034] System configuration

[0035] Device (visual support glasses)

[0036] The terminal is equipped with a built-in camera that captures images of the area ahead. This camera acquires the user's line of sight as video data. The data is compressed by a signal processing module and transmitted to the analysis server means via a wireless communication module. The terminal is also equipped with a speaker and microphone, which function as a means for providing audio guidance. It also has a built-in augmented reality display that provides visual auxiliary information based on the analysis results.

[0037] Analysis Server

[0038] The analysis server means receives the video data sent from the terminal and analyzes the data using its built-in multimodal artificial intelligence (AI). The analysis means integrates functions such as object recognition, person recognition, and character recognition, and interprets the information obtained from the video data from multiple angles. Based on the resulting information, data for voice guidance and data for augmented reality display are generated and sent back to the terminal.

[0039] Program processing and specific examples

[0040] 1. Capture camera footage

[0041] Device: The user wears the vision support glasses and the camera captures images as they walk through the scenery in front of them. For example, if the user is about to cross an intersection, the camera captures images of cars, pedestrians, and cyclists in front of them in real time.

[0042] 2. Video transmission

[0043] Terminal: The captured video data is compressed by the signal processing module and sent to the analysis server via wireless communication.

[0044] 3. Video Analysis

[0045] Server: The server uses multimodal AI to analyze the received video data. For example, if the AI ​​detects a bicycle ahead, it tracks its movement and calculates its speed and direction of travel.

[0046] 4. Processing the analysis results

[0047] Server: The server generates a voice guidance message and AR display data for the user based on the analysis results. For example, if a bicycle is approaching ahead, the server creates a specific voice message such as, "A bicycle is approaching ahead. It will intersect in 3 meters."

[0048] 5. Returning the results

[0049] Server: Re-sends the voice guidance data and AR display data to the device.

[0050] 6. Voice guidance and AR display

[0051] Device: The device plays the received voice guidance data and notifies the user. It also displays AR display data on the glasses. For example, an arrow or icon on the glasses display can be used to visually indicate that a bicycle is approaching ahead.

[0052] In this way, users can understand their surroundings in real time and act safely even when they have visual impairments.

[0053] The processing flow will be explained below.

[0054] Step 1:

[0055] User: The user puts on the vision support glasses, which starts up the device and puts the system into operational mode.

[0056] Step 2:

[0057] Device: The device's built-in camera captures video data of the area in front of it. The camera module captures the user's line of sight as video data in real time.

[0058] Step 3:

[0059] Terminal: The terminal's signal processing module compresses the captured video data and transmits it to the analysis server via the wireless communication module.

[0060] Step 4:

[0061] Server: The analysis server receives the video data sent from the device, decodes the data, and reconstructs the original video data.

[0062] Step 5:

[0063] Server: The analytics server uses a multimodal artificial intelligence (AI) model to analyze the video data, identifying objects, people, and text in the video and calculating their respective positions and movements.

[0064] Step 6:

[0065] Server: Based on the analysis results, the server generates a voice guidance message and augmented reality (AR) display data for the user. For example, it creates a voice message saying "A bicycle is approaching ahead" and AR data showing an arrow mark indicating a bicycle.

[0066] Step 7:

[0067] Server: The server transmits the generated voice guidance data and AR display data back to the terminal via wireless communication.

[0068] Step 8:

[0069] Terminal: The terminal decodes the received voice guidance data and provides voice guidance to the user through the built-in speaker, such as "There is a bicycle approaching ahead, please be careful."

[0070] Step 9:

[0071] Device: The device decodes the received AR display data and highlights approaching bicycles ahead with arrows and boxes on the Glasses display.

[0072] Step 10:

[0073] User: The user understands the surrounding environment based on the voice guidance and AR display, and takes action such as avoiding bicycles.

[0074] This series of processing steps allows visually impaired people to accurately grasp their surroundings in real time and act safely.

[0075] Example 1

[0076] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0077] Visually impaired people have difficulty accurately understanding their surroundings, making it difficult for them to act safely. Furthermore, existing visual support systems often lack real-time capabilities and may not be able to provide sufficient support.

[0078] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0079] In this invention, the server includes an image capture means for capturing image data of the area ahead, a signal processing means for compressing the captured image data and transmitting it via a wireless communication module, an analysis server means for analyzing the compressed image data, an audio output means for providing audio guidance to the visually impaired person based on the analyzed image data, and a display means for displaying the information based on the analyzed image data in an augmented reality manner, thereby enabling the visually impaired person to grasp information about their surrounding environment in real time and act safely.

[0080] The "video capture means" is a device for acquiring video data in the direction of the user's line of sight.

[0081] The "signal processing means" is a module that has the function of compressing captured video data and transmitting it via the wireless communication module.

[0082] The "analysis server means" is a server for receiving compressed video data and analyzing the video data using multimodal artificial intelligence.

[0083] The "audio output means" is a device that provides audio guidance to visually impaired people about information based on analyzed video data.

[0084] The "display means" is a display for displaying information based on the analyzed video data as augmented reality.

[0085] The "wireless communication module" is a module having a wireless communication function for transmitting compressed video data to the analysis server.

[0086] "Multimodal artificial intelligence" is an artificial intelligence technology that analyzes data by integrating object recognition, person recognition, character recognition, etc.

[0087] The present invention is a visual support system for visually impaired people, which includes a video capture unit, a signal processing unit, an analysis server unit, an audio output unit, and a display unit. By using this system, visually impaired people can obtain information about their surrounding environment in real time and live their lives safely.

[0088] Device (visual support glasses)

[0089] The terminal is equipped with a built-in camera that captures images of the area ahead. This camera acquires the user's line of sight as video data. The data is compressed by a signal processing module and transmitted to the analysis server means via a wireless communication module. The terminal is also equipped with a speaker and microphone, which function as a means for providing audio guidance. It also has a built-in augmented reality display that provides visual auxiliary information based on the analysis results.

[0090] Analysis Server

[0091] The analysis server means receives the video data sent from the terminal and analyzes the data using its built-in multimodal artificial intelligence (AI). The analysis means integrates functions such as object recognition, person recognition, and character recognition, and interprets the information obtained from the video data from multiple angles. Based on the resulting information, data for voice guidance and data for augmented reality display are generated and sent back to the terminal.

[0092] Specific examples

[0093] The user wears the vision support glasses, and the camera captures images as they walk through the scenery ahead. For example, when the user is about to cross an intersection, the camera captures images of cars, pedestrians, and cyclists ahead in real time. The captured image data is compressed by a signal processing module and transmitted to an analysis server via wireless communication.

[0094] The analysis server uses multimodal AI to analyze the received video data. For example, if the AI ​​detects a bicycle ahead, it tracks its movement and calculates its speed and direction of travel. The server uses the analysis results to generate a voice guidance message for the user and AR display data. If a bicycle is approaching ahead, for example, it will create a specific voice message such as, "A bicycle is approaching ahead, and will cross in 3 meters."

[0095] The generated voice guidance data and AR display data are then sent back to the device. The device then plays the received voice guidance data and notifies the user. The AR display data is also displayed on the glasses. For example, an arrow or icon on the glasses' display can be used to visually indicate that a bicycle is approaching ahead.

[0096] Prompt Sentence Examples

[0097] "The server of a visual support system for the visually impaired receives and analyzes video data. Please explain the process by which people, objects, and text in the video are recognized and audio guidance data and augmented reality display data are generated for the user."

[0098] "Please explain in detail how the visual support glasses device compresses and transmits the video captured by the camera to the analysis server."

[0099] In this way, by using the system of the present invention, visually impaired people can grasp the situation around them in real time and act safely.

[0100] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0101] Step 1:

[0102] Camera footage capture and collection

[0103] Device: The user wears the vision support glasses. The built-in camera captures the scenery in the user's line of sight in real time. For example, when the user is approaching an intersection, the camera collects images of cars, pedestrians, bicycles, traffic lights, etc. ahead.

[0104] Input: Visual information from a camera attached to the vision support glasses.

[0105] How it works: The camera records high-resolution video at 30 frames per second and dynamically updates the view based on the user's movements.

[0106] Output: Captured high-resolution video data.

[0107] Step 2:

[0108] Video data compression and transmission

[0109] Terminal: The signal processing module compresses the captured video data in real time, and this compressed data is sent to the analysis server via the wireless communication module.

[0110] Input: Captured high-resolution video data.

[0111] Specific operation: Reduce the size of the video data using a compression algorithm (e.g., H.265) and optimize the transmission speed using a wireless communication module.

[0112] Output: Compressed video data.

[0113] Step 3:

[0114] Receiving and extracting video data

[0115] Server: The analysis server receives the compressed video data sent from the device and decompresses the data.

[0116] Input: Compressed video data.

[0117] Specific operation: Decompresses the received data and reconstructs the original high-resolution video data.

[0118] Output: Unpacked video data.

[0119] Step 4:

[0120] Video data analysis

[0121] Server: The video data is analyzed by the built-in multimodal artificial intelligence (AI), which uses functions such as object recognition, person recognition, and character recognition to identify information within the video.

[0122] Input: Unpacked high-resolution video data.

[0123] What it does: Uses AI models (e.g., YOLOv5 or DeepLab) to detect objects and people in video in real time and track their location and movement.

[0124] Output: Analyzed information (e.g., object location, human movement, text information, etc.).

[0125] Step 5:

[0126] Generate analysis results

[0127] Server: Generates voice guidance data and augmented reality (AR) display data based on the analysis of the video data. For example, if a bicycle is approaching ahead, it generates a message such as "A bicycle is approaching ahead. It will cross in 3 meters." It also generates corresponding arrows and icons for the AR display.

[0128] Input: Information as analysis results (object position, movement, text information, etc.).

[0129] Specific behavior: Uses predictive algorithms to analyze the movements of objects and people and generate appropriate warning messages and display data.

[0130] Output: Voice guidance data, AR display data.

[0131] Step 6:

[0132] Sending analysis results

[0133] Server: The generated voice guidance data and AR display data are recompressed and sent to the terminal via wireless communication.

[0134] Input: Generated voice guidance data and AR display data.

[0135] Specific actions: Optimize data transmission protocols and use technologies to prevent data loss (e.g., TCP / IP).

[0136] Output: Compressed voice guidance data, AR display data.

[0137] Step 7:

[0138] Results presentation (audio guidance and AR display)

[0139] Terminal: The device decodes the received voice guidance data and notifies the user through the speaker. At the same time, the device displays the received AR display data on the built-in display. For example, an arrow or icon may be used to visually indicate that a bicycle is approaching ahead.

[0140] Input: Compressed voice guidance data, AR display data.

[0141] Specific operation: Generates high-quality voice guidance using a speech synthesis engine (e.g., Google® Text-to-Speech) and renders overlay information in real time on the AR display.

[0142] Output: Voice guidance, AR display.

[0143] (Application example 1)

[0144] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0145] To ensure the safety of employees working in factories, not only visually impaired workers but also those who are visually unimpaired but require visual assistance for certain tasks need to be aware of their surroundings at all times. However, currently, the environment within a factory is complex and dynamic, making it difficult for workers to recognize dangerous situations. This poses a problem of threatening work efficiency and safety.

[0146] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0147] In this invention, the server includes a video capture means for capturing video data of the front, a voice output means for providing a voice guide to the recipient with information based on the analyzed video data, a display means for displaying the information based on the analyzed video data in augmented reality, and a robot assistant means for ensuring the safety of the recipient based on the analyzed video data. This enables workers in a factory to grasp the surrounding situation in real time and work safely.

[0148] The "image capture means" is a device that acquires forward image data in real time and provides it to other devices or systems.

[0149] The "analysis server means" is a server device that analyzes captured video data and generates useful information based on that data.

[0150] The "audio output means" is a device for outputting information based on the analyzed video data as audio to notify the recipient.

[0151] The "display means" is a device such as an augmented reality display for visually presenting information based on the analyzed video data.

[0152] The "robot assistant means" is a robot device that provides instructions and assistance to ensure the safety of the recipient based on the analyzed video data.

[0153] This invention provides a system for ensuring the safety of workers in a factory and supporting visually impaired workers and workers who are not visually impaired but require visual assistance for specific tasks. The system includes a video capture unit, an analysis server unit, an audio output unit, a display unit, and a robot assistant unit.

[0154] Hardware and Software

[0155] Hardware:

[0156] Camera: A device used to capture real-time images of the work area within the factory.

[0157] Speaker: A device for providing audio guidance to workers.

[0158] Display: A device for displaying augmented reality (AR).

[0159] Server: A device for analyzing video data.

[0160] Robot: An auxiliary device to ensure worker safety.

[0161] software:

[0162] Generative AI (multimodal AI): An artificial intelligence model used for video analysis.

[0163] Robot OS: Basic software for controlling the robot's movements.

[0164] Wireless communication module: Software for sending and receiving data.

[0165] System Flow

[0166] 1. Capture camera footage

[0167] The robot's camera captures real-time video of the factory's work area, for example, detecting forklifts entering the work area.

[0168] 2. Video transmission

[0169] The captured video data is compressed by a signal processing module and transmitted to an analysis server via wireless communication.

[0170] 3. Video Analysis

[0171] The analysis server uses generative AI to analyze the received video data, for example, to identify the movement of a forklift and predict its direction of travel.

[0172] 4. Processing the analysis results

[0173] Based on the analysis results, the server generates a voice guidance message and AR display data. For example, it creates a voice message such as "Caution! A forklift is approaching from the right."

[0174] 5. Returning the results

[0175] Data for voice guidance and data for AR display are sent to the robot.

[0176] 6. Voice guidance and AR display

[0177] The robot plays back the received voice guidance data and notifies the worker. It also displays AR display data on the display, for example, showing the location of a forklift approaching from the right.

[0178] Specific examples

[0179] 1. Voice prompts:

[0180] "Caution! A forklift is approaching from the right."

[0181] 2. AR display:

[0182] Displays the maintenance area and indicates approaching forklifts with arrows and icons.

[0183] Prompt Sentence Examples

[0184] To improve the safety of forklifts and workers in factories, create a robot program that captures camera footage, analyzes it, and provides voice guidance and AR displays. The robot is equipped with a wireless communication module, signal processing module, speaker, and display. When a forklift is approaching from the right, the robot will provide a voice message saying "Caution! A forklift is approaching from the right," and use AR to show the location of the approaching forklift.

[0185] This allows employees working in the factory to grasp the situation around them in real time and proceed with their work safely.

[0186] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0187] Step 1:

[0188] Camera footage capture

[0189] While a user moves around the factory using a vision support robot, a camera built into the robot captures images of what is in front of it in real time.

[0190] Input: Factory footage taken by a robotic camera

[0191] Output: Captured video data

[0192] Specific operation: The camera captures video at 30 frames per second and stores the captured video data in memory.

[0193] Step 2:

[0194] Video transmission

[0195] The terminal (robot) compresses the captured video data using a signal processing module and transmits it to an analysis server via a wireless communication module.

[0196] Input: Captured video data

[0197] Output: Compressed video data

[0198] Specific operation: The signal processing module compresses the video data in H.264 format and sends the compressed data to the analysis server using the Wi-Fi module.

[0199] Step 3:

[0200] Video analysis

[0201] The server analyzes the received video data using a generative AI model (multimodal AI) and uses object recognition algorithms to identify obstacles and moving objects in the factory and predict their behavior.

[0202] Input: Compressed video data

[0203] Output: Analysis results (e.g., forklift position and direction of travel)

[0204] How it works: Multimodal AI uses the YOLOv5 model to detect objects in video and OpenCV to track their movements.

[0205] Step 4:

[0206] Processing the analysis results

[0207] Based on the analysis results, the server generates a voice guidance message and data for augmented reality display.

[0208] Input: Analysis results (object position and movement information)

[0209] Output: Data for voice guidance and AR display

[0210] Specific operation: When the server detects the approach of a forklift, it generates a voice message saying, "Caution! A forklift is approaching from the right," and creates an arrow icon as AR data indicating the direction of the approach.

[0211] Step 5:

[0212] Returning the results

[0213] The generated voice guidance data and AR display data are transmitted to the robot via wireless communication.

[0214] Input: Data for voice guidance and AR display

[0215] Output: Received voice guidance data and AR display data

[0216] Specific operation: The server sends voice guidance and AR display data to the robot via the Wi-Fi module.

[0217] Step 6:

[0218] Voice guidance and AR display

[0219] The robot plays the received voice guidance data through a speaker to notify the worker, and also displays the AR display data on the display.

[0220] Input: Received voice guidance data and AR display data

[0221] Output: Warning notification to operator and display on screen

[0222] Specific operation: The robot's speaker announces, "Caution! A forklift is approaching from the right," and an arrow indicating the forklift's location appears on the display.

[0223] This allows users to understand the surrounding situation in real time, enabling safe work within the factory.

[0224] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0225] The present invention provides a system for providing personalized assistance based on the user's emotional state by combining a visual support system for the visually impaired with an emotion engine. The system includes a video capture unit, an analysis server unit, a voice guidance unit, an augmented reality display unit, and an emotion engine.

[0226] System configuration

[0227] Device (visual support glasses)

[0228] The terminal is equipped with a built-in camera that captures images of the area ahead. This camera acquires the user's line of sight as video data. The data is compressed by a signal processing module and transmitted to the analysis server means via a wireless communication module. The terminal is also equipped with a speaker and microphone, which function as a means for providing audio guidance. It also has a built-in augmented reality display that provides visual auxiliary information based on the analysis results.

[0229] Analysis Server

[0230] The analysis server means receives the video data sent from the terminal and analyzes the data using its built-in multimodal artificial intelligence (AI). The analysis means integrates functions such as object recognition, person recognition, and character recognition, and interprets the information obtained from the video data from multiple angles. Based on the resulting information, data for voice guidance and data for augmented reality display are generated and sent back to the terminal.

[0231] Emotion Engine

[0232] The emotion engine is a means for recognizing and analyzing the user's emotional state. It determines the user's current emotional state (e.g., anxiety, stress, joy, etc.) based on their voice and biometric data (e.g., heart rate). This information is sent to an analysis server and used to adjust the voice guidance and augmented reality display content.

[0233] Program processing and specific examples

[0234] 1. Capture camera footage

[0235] Device: The user wears the vision support glasses and the camera captures images as they walk through the scenery in front of them. For example, if the user is about to cross an intersection, the camera captures images of cars, pedestrians, and cyclists in front of them in real time.

[0236] 2. Video transmission

[0237] Terminal: The captured video data is compressed by the signal processing module and sent to the analysis server via wireless communication.

[0238] 3. Video Analysis

[0239] Server: The server uses multimodal AI to analyze the received video data. For example, if the AI ​​detects a bicycle ahead, it tracks its movement and calculates its speed and direction of travel.

[0240] 4. Emotion Analysis

[0241] Device: The emotion engine acquires the user's voice and biometric data and analyzes the user's current emotional state. For example, if the user's voice is trembling, it will be determined that the user is in an anxious state.

[0242] 5. Processing the analysis results

[0243] Server: The server generates voice guidance messages and AR display data for the user based on the analysis results and emotional state. For example, if a bicycle is approaching ahead and the server determines that the user is in an anxious state, it will create a specially tailored voice message such as, "Remain calm and be careful. A bicycle is approaching ahead."

[0244] 6. Return of results

[0245] Server: Re-sends the voice guidance data and AR display data to the device.

[0246] 7. Voice guidance and AR display

[0247] Device: The device decodes the received voice guidance data and provides voice guidance to the user through the built-in speaker, such as "There is a bicycle approaching ahead." It also displays the augmented reality data on the Glasses' display, highlighting the approaching bicycle with an arrow or box.

[0248] 8. User Actions

[0249] User: The user understands the surrounding environment based on the voice guidance and AR display, and takes action such as avoiding bicycles. By providing information based on the user's emotional state, the user can act with greater peace of mind.

[0250] This series of processes allows visually impaired people to accurately grasp their surroundings in real time and receive support tailored to their emotional state, enabling them to act safely and effectively.

[0251] The processing flow will be explained below.

[0252] Step 1:

[0253] User: The user puts on the vision support glasses, which starts up the device and puts the system into operational mode.

[0254] Step 2:

[0255] Device: The device's built-in camera captures video data of the area in front of it. The camera module captures the user's line of sight as video data in real time.

[0256] Step 3:

[0257] Terminal: The terminal's signal processing module compresses the captured video data and transmits it to the analysis server via the wireless communication module.

[0258] Step 4:

[0259] Server: The analysis server receives the video data sent from the device, decodes the data, and reconstructs the original video data.

[0260] Step 5:

[0261] Server: The analytics server uses a multimodal artificial intelligence (AI) model to analyze the video data, identifying objects, people, and text in the video and calculating their respective positions and movements.

[0262] Step 6:

[0263] Device: The emotion engine acquires the user's voice and biometric data (such as heart rate) and analyzes the user's current emotional state. For example, if the user's voice is trembling, it will be determined that the user is in an anxious state.

[0264] Step 7:

[0265] Terminal: Transmits the analysis results and emotional state to the analysis server via wireless communication.

[0266] Step 8:

[0267] Server: Based on the analysis results and the user's emotional state, the server generates a voice guidance message and AR display data for the user. For example, if a bicycle is approaching ahead, the server generates a specially tailored voice message such as "Remain calm and be careful. A bicycle is approaching ahead."

[0268] Step 9:

[0269] Server: Re-sends the voice guidance data and AR display data to the device.

[0270] Step 10:

[0271] Terminal: The terminal decodes the received voice guidance data and provides voice guidance to the user through the built-in speaker, such as "There is a bicycle approaching ahead, please be careful."

[0272] Step 11:

[0273] Device: Decodes the received AR display data and highlights approaching bicycles ahead with arrows and boxes on the Glasses display.

[0274] Step 12:

[0275] User: The user understands the surrounding environment based on the voice guidance and AR display, and can take action if necessary, such as avoiding bicycles. By providing information based on the user's emotional state, the user can act with peace of mind.

[0276] This series of processes not only enables visually impaired people to accurately grasp their surroundings in real time, but also provides support tailored to their emotional state, enabling them to act safely and effectively.

[0277] Example 2

[0278] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0279] It is difficult for visually impaired people to accurately grasp information about their surroundings in real time. Furthermore, conventional visual support systems cannot provide personalized assistance that takes into account the user's emotional state, which can increase anxiety and stress. This poses a challenge for visually impaired people to live their daily lives safely and confidently.

[0280] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a video capture means for capturing video data of the front, an analysis means for analyzing the captured video data, a voice output means for providing a user with audio guidance on information based on the analyzed video data, a display means for augmented reality display of information based on the analyzed video data, and an emotion analysis means for recognizing and analyzing the user's emotional state. This enables visually impaired people to accurately grasp information about their surrounding environment in real time and receive personalized support according to the user's emotional state.

[0281] "Video capture means" refers to a device or mechanism used to capture forward video data.

[0282] An "analysis means" is a server or software module used to analyze the captured video data.

[0283] The "audio output means" refers to a speaker or a voice synthesizer used to provide the user with audio guidance of information based on the analyzed video data.

[0284] The "display means" refers to a display or projector used to display information based on the analyzed video data in an augmented reality manner.

[0285] "Emotion analysis means" refers to sensors and analysis algorithms used to recognize and analyze a user's emotional state.

[0286] A "wireless network" is a network infrastructure for transmitting data wirelessly.

[0287] "Multimodal AI" is an AI technology that performs integrated analysis of multiple different types of data (for example, video data, audio data, etc.).

[0288] "User's emotional state" refers to the user's current psychological and physiological state, including anxiety, stress, joy, and the like.

[0289] "Personalized assistance" refers to providing individual assistance tailored to the user's specific situation and emotional state.

[0290] "Real-time" refers to immediate processing and response without delay.

[0291] The present invention provides a visual support system for visually impaired people that adds an emotion analysis function to provide personalized support based on the user's emotional state. The system includes a video capture unit, an analysis server unit, an audio output unit, a display unit, and an emotion analysis unit.

[0292] Device (visual support glasses)

[0293] The device is equipped with a built-in camera that captures images of the area ahead. This camera obtains the user's line of sight as video data. Specifically, the video is acquired in real time using a high-resolution sensor. This data is compressed by a signal processing module and sent to an analysis server via a wireless communication module. The H.264 codec is used as the compression technology. The device is also equipped with a speaker and microphone, which function as a means of providing audio guidance. It also has a built-in augmented reality display that provides visual support information based on the analysis results.

[0294] Analysis Server

[0295] The analysis server receives the video data sent from the device and analyzes it using its built-in multimodal artificial intelligence (AI). Specifically, it uses an object recognition algorithm (e.g., the YOLO algorithm) to identify objects (bicycles, pedestrians, cars, etc.) ahead and track their movements. It also receives the user's emotional data and determines their emotional state, such as anxiety, stress, or joy. Based on the resulting information, it generates data for audio guidance and augmented reality display and sends it back to the device.

[0296] Emotion analysis means

[0297] The emotion analysis means acquires the user's voice and biometric data (such as heart rate) to recognize and analyze their current emotional state. Specifically, a microphone collects the user's voice, and a biometric sensor measures their heart rate. Analysis is performed based on this data to determine the user's emotional state. This information is sent to an analysis server and used to adjust the voice guidance and augmented reality display content.

[0298] Specific examples

[0299] For example, when a user is about to cross an intersection, the device's camera captures video of the area ahead and sends it to an analysis server. The analysis server analyzes the video data and recognizes that a bicycle is approaching ahead. At the same time, the emotion analysis means detects an increase in the user's heart rate and determines that the user is in an anxious state. Based on this information, the analysis server generates a voice guidance message saying, "A bicycle is approaching ahead. Remain calm and be careful," and sends this to the device along with AR display data. The device receives this and visually displays the approaching bicycle on the display along with the voice guidance. Based on this, the user takes action to avoid the bicycle.

[0300] Prompt Sentence Examples

[0301] "When a user is about to cross an intersection, the vision support glasses should detect a bicycle ahead and, taking into account the user's anxiety state, notify them by saying, 'Remain calm and be careful. There is a bicycle approaching ahead.'"

[0302] These features allow visually impaired people to accurately grasp their surroundings in real time and receive assistance tailored to their emotional state, enabling them to act safely and effectively.

[0303] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0304] Step 1:

[0305] Device: The device's camera captures the image in front of it. High-resolution image data is acquired in real time in the direction the user is looking. This image data becomes the input for the system.

[0306] Step 2:

[0307] Terminal: The captured video data is compressed by the signal processing module. Specifically, the video data is compressed using the H.264 codec. The compressed data is sent to the analysis server via the wireless communication module. This data is input to the analysis server as output.

[0308] Step 3:

[0309] Server: The server decompresses the received compressed video data and analyzes the video using multimodal AI. The input data is video frames, and based on this, an object recognition algorithm (e.g., YOLO) is used to detect objects (bicycles, pedestrians, cars, etc.) ahead. The detection results include data such as the object's position, speed, and direction of travel.

[0310] Step 4:

[0311] Terminal: The emotion analysis means acquires the user's voice and biometric data. A microphone collects voice data, and a biometric sensor measures heart rate. These are the input data. Based on this data, the emotional state is analyzed and emotions such as anxiety and stress are determined. The determination result is sent to the analysis server as output.

[0312] Step 5:

[0313] Server: The server generates voice guidance messages and AR display data based on the analysis results and the user's emotional state. The input data are the results of video analysis and emotion analysis. Specifically, it detects the approach of a bicycle ahead, and if it determines that the user is in an anxious state, it generates an adjusted voice message saying, "A bicycle is approaching ahead. Remain calm and be careful." This voice guidance data and AR display data are sent to the device as output data.

[0314] Step 6:

[0315] Terminal: The terminal decodes the received voice guidance data and provides voice guidance to the user through the built-in speaker. The data input is voice guidance data from the server, and voice output is based on this. It also displays AR display data on the display to provide visual information to the user. For example, approaching bicycles ahead can be highlighted with arrows or boxes.

[0316] Step 7:

[0317] User: The user understands the surrounding environment based on the audio guidance and AR display, and takes action to avoid the bicycle. The input is the audio guidance and AR display information, and based on this, the user performs specific actions (for example, moving to the right).

[0318] This is the specific flow of the system's program processing. This system allows visually impaired people to accurately grasp their surroundings in real time and receive support according to their emotional state.

[0319] (Application example 2)

[0320] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0321] In order for visually impaired people to live their daily lives safely, they need support tools that allow them to accurately grasp their surroundings. However, conventional visual support systems lack physical and psychological support that takes into account the user's emotional state, which can lead to users feeling anxious and stressed, and resulting in insufficient safety measures.

[0322] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0323] In this invention, the server includes video capture means for capturing video data of the area ahead, analysis server means for analyzing the captured video data, audio output means for providing audio guidance to the visually impaired person based on the analyzed video data, display means for displaying the information based on the analyzed video data in an augmented reality manner, and emotion engine means for analyzing the user's emotional state and adjusting the audio guidance and display content based on the analysis. This allows the visually impaired person to grasp the situation around them in real time, receive appropriate support according to their emotional state, and act safely and with peace of mind.

[0324] "Video capture means" is a combination of hardware and software for capturing forward video data.

[0325] The "analysis server means" is a server for analyzing captured video data and a system that uses multimodal artificial intelligence to interpret the data.

[0326] The "audio output means" is a device that provides information based on the analyzed video data to visually impaired people as audio.

[0327] The "display means" is a device for displaying information based on the analyzed video data as augmented reality to visually impaired people.

[0328] The "emotion engine means" is a system for analyzing the user's emotional state and adjusting the voice guidance and display content according to that state.

[0329] A "wireless network" is a communication method for sending and receiving information via electromagnetic waves, and is used to send video data and analysis results to a server in a remote location.

[0330] "Multimodal AI" is an AI technology that processes multiple types of data (e.g., video data, audio data, biometric data) in an integrated manner and outputs analytical results.

[0331] A system and a program required to implement the present invention will be described.

[0332] First, the system uses the following major hardware and software:

[0333] Video capture method (e.g., camera in smart glasses)

[0334] Analysis server means (e.g. cloud server)

[0335] Audio output means (e.g., speakers in smart glasses)

[0336] Display means (e.g., smart glasses display)

[0337] Emotion engine means (e.g., dedicated software for analyzing biometric data)

[0338] Specific processing flow

[0339] 1. Capture video data

[0340] When a user wears the smart glasses and walks forward, the camera captures video data of the area ahead, which is acquired in real time and compressed by the signal processing module.

[0341] 2. Data transmission

[0342] The captured video data is transmitted to an analysis server via a wireless network, enabling real-time analysis.

[0343] 3. Data Analysis

[0344] The analysis server analyzes the received video data using multimodal artificial intelligence (AI), which recognizes objects, people, and characters from the video data and interprets the obtained information from multiple perspectives.

[0345] 4. Emotional state analysis

[0346] The emotion engine acquires the user's voice data and biometric data (e.g., heart rate) and analyzes the user's current emotional state. For example, if the user's voice is trembling, it is determined to be in a state of anxiety.

[0347] 5. Integration and processing of analysis results

[0348] The server then combines the analysis results of the video data with the user's emotional state to generate voice guidance messages and augmented reality display data for the user. Depending on the specific situation, the server generates voice guidance such as "Stay calm and be careful."

[0349] 6. Return of results

[0350] The generated voice guidance data and augmented reality display data are transmitted again to the smart glasses.

[0351] 7. Audio guidance and augmented reality displays

[0352] The smart glasses decode the received voice guidance data and provide voice guidance to the user through the built-in speaker, while also highlighting surrounding hazards on the display.

[0353] 8. User Actions

[0354] Based on the voice guidance and augmented reality display, users can understand the surrounding environment and, if necessary, take action to avoid danger.

[0355] The specific hardware and software used

[0356] Smart glasses (e.g., Microsoft® HoloLens®, Google Glass®)

[0357] Cloud servers (e.g., Amazon Web Services (AWS (registered trademark)), Google Cloud Platform (GCP))

[0358] Multimodal artificial intelligence models (e.g., Tensorflow, PyTorch)

[0359] Speech processing modules (e.g., Google Speech-to-Text, IBM Watson® Speech to Text)

[0360] Emotion analysis software (e.g., Affectiva, Microsoft Azure® Emotion API)

[0361] Specific examples and examples of prompts for generative AI models

[0362] For example, consider a situation where a visually impaired person is walking alone outside at night. If a person suddenly approaches in front of the user, the system will notify the user of the situation through voice guidance and an augmented reality display. An example of a prompt is as follows:

[0363] Prompt statement

[0364] When a visually impaired person is walking alone at night, if the assistant detects a person suddenly approaching in front of them, it will tell them "Please stay calm. There is a dangerous person ahead," and guide them to avoid that person. It should also provide support according to the user's emotional state.

[0365] In this way, visually impaired people can move around safely and with peace of mind.

[0366] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0367] Step 1:

[0368] The device captures images of the front using a camera. The input is image data in the direction of the user's line of sight, and the output is the captured raw image data. Specifically, the camera captures images of the scenery and objects in front in real time and collects the data.

[0369] Step 2:

[0370] The device compresses the captured video data using a signal processing module and transmits it to the analysis server using a wireless communication module. The input is the captured raw video data, and the output is the compressed video data. Specifically, the data size is reduced using a data compression algorithm and then transmitted to the server via a wireless network.

[0371] Step 3:

[0372] The server decompresses the received compressed video data and analyzes it using multimodal artificial intelligence (AI). The input is the compressed video data, and the output is the analysis results, such as object and person recognition. Specifically, the AI ​​model analyzes the video data frame by frame and identifies objects and people in front of the vehicle.

[0373] Step 4:

[0374] The device uses an emotion engine to capture the user's voice and biometric data and analyze their emotional state. The input is the user's voice data and heart rate data, and the output is the user's emotional state (e.g., anxiety, stress, joy). Specifically, microphones and sensors collect user data, and an emotion analysis algorithm determines the user's emotional state.

[0375] Step 5:

[0376] The server integrates the analysis results of the video data with the user's emotional state to generate voice guidance messages and augmented reality display data. The inputs are the results of object and person recognition and the user's emotional state, and the output is an adjusted voice guidance message and augmented reality display data. Specifically, the server generates warning and guidance messages appropriate for the user based on the analysis results and the user's emotional state.

[0377] Step 6:

[0378] The server retransmits the generated voice guidance data and augmented reality display data to the terminal. The input is the voice guidance message and the augmented reality display data, and the output is the completion of transmission to the terminal. Specifically, the data is transmitted to the terminal via a wireless communication module.

[0379] Step 7:

[0380] The device decodes the received voice guidance data and notifies the user through the built-in speaker. It also displays the augmented reality display data on the display. The input is the voice guidance message and display data, and the output is the voice notification and AR display. Specifically, the speaker plays the notification voice, and the display visually highlights the warning or guidance.

[0381] Step 8:

[0382] The user understands the surrounding information based on the voice guidance and augmented reality display, and takes action as necessary. The input is the notified voice guidance and AR display, and the output is the user's specific action (e.g., movement to avoid danger). Specific actions involve the user recognizing an approaching object ahead and selecting a safe route to move.

[0383] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0384] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0385] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0386] [Second embodiment]

[0387] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0388] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0389] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0390] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0391] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0392] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0393] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0394] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0395] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0396] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0397] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0398] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0399] The present invention is a visual support system for visually impaired people, which includes a video capture unit, an analysis server unit, a voice guidance unit, and an augmented reality display unit. Using this system, visually impaired people can obtain information about their surrounding environment in real time and live their lives safely.

[0400] System configuration

[0401] Device (visual support glasses)

[0402] The terminal is equipped with a built-in camera that captures images of the area ahead. This camera acquires the user's line of sight as video data. The data is compressed by a signal processing module and transmitted to the analysis server means via a wireless communication module. The terminal is also equipped with a speaker and microphone, which function as a means for providing audio guidance. It also has a built-in augmented reality display that provides visual auxiliary information based on the analysis results.

[0403] Analysis Server

[0404] The analysis server means receives the video data sent from the terminal and analyzes the data using its built-in multimodal artificial intelligence (AI). The analysis means integrates functions such as object recognition, person recognition, and character recognition, and interprets the information obtained from the video data from multiple angles. Based on the resulting information, data for voice guidance and data for augmented reality display are generated and sent back to the terminal.

[0405] Program processing and specific examples

[0406] 1. Capture camera footage

[0407] Device: The user wears the vision support glasses and the camera captures images as they walk through the scenery in front of them. For example, if the user is about to cross an intersection, the camera captures images of cars, pedestrians, and cyclists in front of them in real time.

[0408] 2. Video transmission

[0409] Terminal: The captured video data is compressed by the signal processing module and sent to the analysis server via wireless communication.

[0410] 3. Video Analysis

[0411] Server: The server uses multimodal AI to analyze the received video data. For example, if the AI ​​detects a bicycle ahead, it tracks its movement and calculates its speed and direction of travel.

[0412] 4. Processing the analysis results

[0413] Server: The server generates a voice guidance message and AR display data for the user based on the analysis results. For example, if a bicycle is approaching ahead, the server creates a specific voice message such as, "A bicycle is approaching ahead. It will intersect in 3 meters."

[0414] 5. Returning the results

[0415] Server: Re-sends the voice guidance data and AR display data to the device.

[0416] 6. Voice guidance and AR display

[0417] Device: The device plays the received voice guidance data and notifies the user. It also displays AR display data on the glasses. For example, an arrow or icon on the glasses display can be used to visually indicate that a bicycle is approaching ahead.

[0418] In this way, users can understand their surroundings in real time and act safely even when they have visual impairments.

[0419] The processing flow will be explained below.

[0420] Step 1:

[0421] User: The user puts on the vision support glasses, which starts up the device and puts the system into operational mode.

[0422] Step 2:

[0423] Device: The device's built-in camera captures video data of the area in front of it. The camera module captures the user's line of sight as video data in real time.

[0424] Step 3:

[0425] Terminal: The terminal's signal processing module compresses the captured video data and transmits it to the analysis server via the wireless communication module.

[0426] Step 4:

[0427] Server: The analysis server receives the video data sent from the device, decodes the data, and reconstructs the original video data.

[0428] Step 5:

[0429] Server: The analytics server uses a multimodal artificial intelligence (AI) model to analyze the video data, identifying objects, people, and text in the video and calculating their respective positions and movements.

[0430] Step 6:

[0431] Server: Based on the analysis results, the server generates a voice guidance message and augmented reality (AR) display data for the user. For example, it creates a voice message saying "A bicycle is approaching ahead" and AR data showing an arrow mark indicating a bicycle.

[0432] Step 7:

[0433] Server: The server transmits the generated voice guidance data and AR display data back to the terminal via wireless communication.

[0434] Step 8:

[0435] Terminal: The terminal decodes the received voice guidance data and provides voice guidance to the user through the built-in speaker, such as "There is a bicycle approaching ahead, please be careful."

[0436] Step 9:

[0437] Device: The device decodes the received AR display data and highlights approaching bicycles ahead with arrows and boxes on the Glasses display.

[0438] Step 10:

[0439] User: The user understands the surrounding environment based on the voice guidance and AR display, and takes action such as avoiding bicycles.

[0440] This series of processing steps allows visually impaired people to accurately grasp their surroundings in real time and act safely.

[0441] Example 1

[0442] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0443] Visually impaired people have difficulty accurately understanding their surroundings, making it difficult for them to act safely. Furthermore, existing visual support systems often lack real-time capabilities and may not be able to provide sufficient support.

[0444] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0445] In this invention, the server includes an image capture means for capturing image data of the area ahead, a signal processing means for compressing the captured image data and transmitting it via a wireless communication module, an analysis server means for analyzing the compressed image data, an audio output means for providing audio guidance to the visually impaired person based on the analyzed image data, and a display means for displaying the information based on the analyzed image data in an augmented reality manner, thereby enabling the visually impaired person to grasp information about their surrounding environment in real time and act safely.

[0446] The "video capture means" is a device for acquiring video data in the direction of the user's line of sight.

[0447] The "signal processing means" is a module that has the function of compressing captured video data and transmitting it via the wireless communication module.

[0448] The "analysis server means" is a server for receiving compressed video data and analyzing the video data using multimodal artificial intelligence.

[0449] The "audio output means" is a device that provides audio guidance to visually impaired people about information based on analyzed video data.

[0450] The "display means" is a display for displaying information based on the analyzed video data as augmented reality.

[0451] The "wireless communication module" is a module having a wireless communication function for transmitting compressed video data to the analysis server.

[0452] "Multimodal artificial intelligence" is an artificial intelligence technology that analyzes data by integrating object recognition, person recognition, character recognition, etc.

[0453] The present invention is a visual support system for visually impaired people, which includes a video capture unit, a signal processing unit, an analysis server unit, an audio output unit, and a display unit. By using this system, visually impaired people can obtain information about their surrounding environment in real time and live their lives safely.

[0454] Device (visual support glasses)

[0455] The terminal is equipped with a built-in camera that captures images of the area ahead. This camera acquires the user's line of sight as video data. The data is compressed by a signal processing module and transmitted to the analysis server means via a wireless communication module. The terminal is also equipped with a speaker and microphone, which function as a means for providing audio guidance. It also has a built-in augmented reality display that provides visual auxiliary information based on the analysis results.

[0456] Analysis Server

[0457] The analysis server means receives the video data sent from the terminal and analyzes the data using its built-in multimodal artificial intelligence (AI). The analysis means integrates functions such as object recognition, person recognition, and character recognition, and interprets the information obtained from the video data from multiple angles. Based on the resulting information, data for voice guidance and data for augmented reality display are generated and sent back to the terminal.

[0458] Specific examples

[0459] The user wears the vision support glasses, and the camera captures images as they walk through the scenery ahead. For example, when the user is about to cross an intersection, the camera captures images of cars, pedestrians, and cyclists ahead in real time. The captured image data is compressed by a signal processing module and transmitted to an analysis server via wireless communication.

[0460] The analysis server uses multimodal AI to analyze the received video data. For example, if the AI ​​detects a bicycle ahead, it tracks its movement and calculates its speed and direction of travel. The server uses the analysis results to generate a voice guidance message for the user and AR display data. If a bicycle is approaching ahead, for example, it will create a specific voice message such as, "A bicycle is approaching ahead, and will cross in 3 meters."

[0461] The generated voice guidance data and AR display data are then sent back to the device. The device then plays the received voice guidance data and notifies the user. The AR display data is also displayed on the glasses. For example, an arrow or icon on the glasses' display can be used to visually indicate that a bicycle is approaching ahead.

[0462] Prompt Sentence Examples

[0463] "The server of a visual support system for the visually impaired receives and analyzes video data. Please explain the process by which people, objects, and text in the video are recognized and audio guidance data and augmented reality display data are generated for the user."

[0464] "Please explain in detail how the visual support glasses device compresses and transmits the video captured by the camera to the analysis server."

[0465] In this way, by using the system of the present invention, visually impaired people can grasp the situation around them in real time and act safely.

[0466] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0467] Step 1:

[0468] Camera footage capture and collection

[0469] Device: The user wears the vision support glasses. The built-in camera captures the scenery in the user's line of sight in real time. For example, when the user is approaching an intersection, the camera collects images of cars, pedestrians, bicycles, traffic lights, etc. ahead.

[0470] Input: Visual information from a camera attached to the vision support glasses.

[0471] How it works: The camera records high-resolution video at 30 frames per second and dynamically updates the view based on the user's movements.

[0472] Output: Captured high-resolution video data.

[0473] Step 2:

[0474] Video data compression and transmission

[0475] Terminal: The signal processing module compresses the captured video data in real time, and this compressed data is sent to the analysis server via the wireless communication module.

[0476] Input: Captured high-resolution video data.

[0477] Specific operation: Reduce the size of the video data using a compression algorithm (e.g., H.265) and optimize the transmission speed using a wireless communication module.

[0478] Output: Compressed video data.

[0479] Step 3:

[0480] Receiving and extracting video data

[0481] Server: The analysis server receives the compressed video data sent from the device and decompresses the data.

[0482] Input: Compressed video data.

[0483] Specific operation: Decompresses the received data and reconstructs the original high-resolution video data.

[0484] Output: Unpacked video data.

[0485] Step 4:

[0486] Video data analysis

[0487] Server: The video data is analyzed by the built-in multimodal artificial intelligence (AI), which uses functions such as object recognition, person recognition, and character recognition to identify information within the video.

[0488] Input: Unpacked high-resolution video data.

[0489] What it does: Uses AI models (e.g., YOLOv5 or DeepLab) to detect objects and people in video in real time and track their location and movement.

[0490] Output: Analyzed information (e.g., object location, human movement, text information, etc.).

[0491] Step 5:

[0492] Generate analysis results

[0493] Server: Generates voice guidance data and augmented reality (AR) display data based on the analysis of the video data. For example, if a bicycle is approaching ahead, it generates a message such as "A bicycle is approaching ahead. It will cross in 3 meters." It also generates corresponding arrows and icons for the AR display.

[0494] Input: Information as analysis results (object position, movement, text information, etc.).

[0495] Specific behavior: Uses predictive algorithms to analyze the movements of objects and people and generate appropriate warning messages and display data.

[0496] Output: Voice guidance data, AR display data.

[0497] Step 6:

[0498] Sending analysis results

[0499] Server: The generated voice guidance data and AR display data are recompressed and sent to the terminal via wireless communication.

[0500] Input: Generated voice guidance data and AR display data.

[0501] Specific actions: Optimize data transmission protocols and use technologies to prevent data loss (e.g., TCP / IP).

[0502] Output: Compressed voice guidance data, AR display data.

[0503] Step 7:

[0504] Results presentation (audio guidance and AR display)

[0505] Terminal: The device decodes the received voice guidance data and notifies the user through the speaker. At the same time, the device displays the received AR display data on the built-in display. For example, an arrow or icon may be used to visually indicate that a bicycle is approaching ahead.

[0506] Input: Compressed voice guidance data, AR display data.

[0507] Specific operation: Generates high-quality voice guidance using a speech synthesis engine (e.g., Google Text-to-Speech) and renders overlay information in real time on the AR display.

[0508] Output: Voice guidance, AR display.

[0509] (Application example 1)

[0510] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0511] To ensure the safety of employees working in factories, not only visually impaired workers but also those who are visually unimpaired but require visual assistance for certain tasks need to be aware of their surroundings at all times. However, currently, the environment within a factory is complex and dynamic, making it difficult for workers to recognize dangerous situations. This poses a problem of threatening work efficiency and safety.

[0512] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0513] In this invention, the server includes a video capture means for capturing video data of the front, a voice output means for providing a voice guide to the recipient with information based on the analyzed video data, a display means for displaying the information based on the analyzed video data in augmented reality, and a robot assistant means for ensuring the safety of the recipient based on the analyzed video data. This enables workers in a factory to grasp the surrounding situation in real time and work safely.

[0514] The "image capture means" is a device that acquires forward image data in real time and provides it to other devices or systems.

[0515] The "analysis server means" is a server device that analyzes captured video data and generates useful information based on that data.

[0516] The "audio output means" is a device for outputting information based on the analyzed video data as audio to notify the recipient.

[0517] The "display means" is a device such as an augmented reality display for visually presenting information based on the analyzed video data.

[0518] The "robot assistant means" is a robot device that provides instructions and assistance to ensure the safety of the recipient based on the analyzed video data.

[0519] This invention provides a system for ensuring the safety of workers in a factory and supporting visually impaired workers and workers who are not visually impaired but require visual assistance for specific tasks. The system includes a video capture unit, an analysis server unit, an audio output unit, a display unit, and a robot assistant unit.

[0520] Hardware and Software

[0521] Hardware:

[0522] Camera: A device used to capture real-time images of the work area within the factory.

[0523] Speaker: A device for providing audio guidance to workers.

[0524] Display: A device for displaying augmented reality (AR).

[0525] Server: A device for analyzing video data.

[0526] Robot: An auxiliary device to ensure worker safety.

[0527] software:

[0528] Generative AI (multimodal AI): An artificial intelligence model used for video analysis.

[0529] Robot OS: Basic software for controlling the robot's movements.

[0530] Wireless communication module: Software for sending and receiving data.

[0531] System Flow

[0532] 1. Capture camera footage

[0533] The robot's camera captures real-time video of the factory's work area, for example, detecting forklifts entering the work area.

[0534] 2. Video transmission

[0535] The captured video data is compressed by a signal processing module and transmitted to an analysis server via wireless communication.

[0536] 3. Video Analysis

[0537] The analysis server uses generative AI to analyze the received video data, for example, to identify the movement of a forklift and predict its direction of travel.

[0538] 4. Processing the analysis results

[0539] Based on the analysis results, the server generates a voice guidance message and AR display data. For example, it creates a voice message such as "Caution! A forklift is approaching from the right."

[0540] 5. Returning the results

[0541] Data for voice guidance and data for AR display are sent to the robot.

[0542] 6. Voice guidance and AR display

[0543] The robot plays back the received voice guidance data and notifies the worker. It also displays AR display data on the display, for example, showing the location of a forklift approaching from the right.

[0544] Specific examples

[0545] 1. Voice prompts:

[0546] "Caution! A forklift is approaching from the right."

[0547] 2. AR display:

[0548] Displays the maintenance area and indicates approaching forklifts with arrows and icons.

[0549] Prompt Sentence Examples

[0550] To improve the safety of forklifts and workers in factories, create a robot program that captures camera footage, analyzes it, and provides voice guidance and AR displays. The robot is equipped with a wireless communication module, signal processing module, speaker, and display. When a forklift is approaching from the right, the robot will provide a voice message saying "Caution! A forklift is approaching from the right," and use AR to show the location of the approaching forklift.

[0551] This allows employees working in the factory to grasp the situation around them in real time and proceed with their work safely.

[0552] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0553] Step 1:

[0554] Camera footage capture

[0555] While a user moves around the factory using a vision support robot, a camera built into the robot captures images of what is in front of it in real time.

[0556] Input: Factory footage taken by a robotic camera

[0557] Output: Captured video data

[0558] Specific operation: The camera captures video at 30 frames per second and stores the captured video data in memory.

[0559] Step 2:

[0560] Video transmission

[0561] The terminal (robot) compresses the captured video data using a signal processing module and transmits it to an analysis server via a wireless communication module.

[0562] Input: Captured video data

[0563] Output: Compressed video data

[0564] Specific operation: The signal processing module compresses the video data in H.264 format and sends the compressed data to the analysis server using the Wi-Fi module.

[0565] Step 3:

[0566] Video analysis

[0567] The server analyzes the received video data using a generative AI model (multimodal AI) and uses object recognition algorithms to identify obstacles and moving objects in the factory and predict their behavior.

[0568] Input: Compressed video data

[0569] Output: Analysis results (e.g., forklift position and direction of travel)

[0570] How it works: Multimodal AI uses the YOLOv5 model to detect objects in video and OpenCV to track their movements.

[0571] Step 4:

[0572] Processing the analysis results

[0573] Based on the analysis results, the server generates a voice guidance message and data for augmented reality display.

[0574] Input: Analysis results (object position and movement information)

[0575] Output: Data for voice guidance and AR display

[0576] Specific operation: When the server detects the approach of a forklift, it generates a voice message saying, "Caution! A forklift is approaching from the right," and creates an arrow icon as AR data indicating the direction of the approach.

[0577] Step 5:

[0578] Returning the results

[0579] The generated voice guidance data and AR display data are transmitted to the robot via wireless communication.

[0580] Input: Data for voice guidance and AR display

[0581] Output: Received voice guidance data and AR display data

[0582] Specific operation: The server sends voice guidance and AR display data to the robot via the Wi-Fi module.

[0583] Step 6:

[0584] Voice guidance and AR display

[0585] The robot plays the received voice guidance data through a speaker to notify the worker, and also displays the AR display data on the display.

[0586] Input: Received voice guidance data and AR display data

[0587] Output: Warning notification to operator and display on screen

[0588] Specific operation: The robot's speaker announces, "Caution! A forklift is approaching from the right," and an arrow indicating the forklift's location appears on the display.

[0589] This allows users to understand the surrounding situation in real time, enabling safe work within the factory.

[0590] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0591] The present invention provides a system for providing personalized assistance based on the user's emotional state by combining a visual support system for the visually impaired with an emotion engine. The system includes a video capture unit, an analysis server unit, a voice guidance unit, an augmented reality display unit, and an emotion engine.

[0592] System configuration

[0593] Device (visual support glasses)

[0594] The terminal is equipped with a built-in camera that captures images of the area ahead. This camera acquires the user's line of sight as video data. The data is compressed by a signal processing module and transmitted to the analysis server means via a wireless communication module. The terminal is also equipped with a speaker and microphone, which function as a means for providing audio guidance. It also has a built-in augmented reality display that provides visual auxiliary information based on the analysis results.

[0595] Analysis Server

[0596] The analysis server means receives the video data sent from the terminal and analyzes the data using its built-in multimodal artificial intelligence (AI). The analysis means integrates functions such as object recognition, person recognition, and character recognition, and interprets the information obtained from the video data from multiple angles. Based on the resulting information, data for voice guidance and data for augmented reality display are generated and sent back to the terminal.

[0597] Emotion Engine

[0598] The emotion engine is a means for recognizing and analyzing the user's emotional state. It determines the user's current emotional state (e.g., anxiety, stress, joy, etc.) based on their voice and biometric data (e.g., heart rate). This information is sent to an analysis server and used to adjust the voice guidance and augmented reality display content.

[0599] Program processing and specific examples

[0600] 1. Capture camera footage

[0601] Device: The user wears the vision support glasses and the camera captures images as they walk through the scenery in front of them. For example, if the user is about to cross an intersection, the camera captures images of cars, pedestrians, and cyclists in front of them in real time.

[0602] 2. Video transmission

[0603] Terminal: The captured video data is compressed by the signal processing module and sent to the analysis server via wireless communication.

[0604] 3. Video Analysis

[0605] Server: The server uses multimodal AI to analyze the received video data. For example, if the AI ​​detects a bicycle ahead, it tracks its movement and calculates its speed and direction of travel.

[0606] 4. Emotion Analysis

[0607] Device: The emotion engine acquires the user's voice and biometric data and analyzes the user's current emotional state. For example, if the user's voice is trembling, it will be determined that the user is in an anxious state.

[0608] 5. Processing the analysis results

[0609] Server: The server generates voice guidance messages and AR display data for the user based on the analysis results and emotional state. For example, if a bicycle is approaching ahead and the server determines that the user is in an anxious state, it will create a specially tailored voice message such as, "Remain calm and be careful. A bicycle is approaching ahead."

[0610] 6. Return of results

[0611] Server: Re-sends the voice guidance data and AR display data to the device.

[0612] 7. Voice guidance and AR display

[0613] Device: The device decodes the received voice guidance data and provides voice guidance to the user through the built-in speaker, such as "There is a bicycle approaching ahead." It also displays the augmented reality data on the Glasses' display, highlighting the approaching bicycle with an arrow or box.

[0614] 8. User Actions

[0615] User: The user understands the surrounding environment based on the voice guidance and AR display, and takes action such as avoiding bicycles. By providing information based on the user's emotional state, the user can act with greater peace of mind.

[0616] This series of processes allows visually impaired people to accurately grasp their surroundings in real time and receive support tailored to their emotional state, enabling them to act safely and effectively.

[0617] The processing flow will be explained below.

[0618] Step 1:

[0619] User: The user puts on the vision support glasses, which starts up the device and puts the system into operational mode.

[0620] Step 2:

[0621] Device: The device's built-in camera captures video data of the area in front of it. The camera module captures the user's line of sight as video data in real time.

[0622] Step 3:

[0623] Terminal: The terminal's signal processing module compresses the captured video data and transmits it to the analysis server via the wireless communication module.

[0624] Step 4:

[0625] Server: The analysis server receives the video data sent from the device, decodes the data, and reconstructs the original video data.

[0626] Step 5:

[0627] Server: The analytics server uses a multimodal artificial intelligence (AI) model to analyze the video data, identifying objects, people, and text in the video and calculating their respective positions and movements.

[0628] Step 6:

[0629] Device: The emotion engine acquires the user's voice and biometric data (such as heart rate) and analyzes the user's current emotional state. For example, if the user's voice is trembling, it will be determined that the user is in an anxious state.

[0630] Step 7:

[0631] Terminal: Transmits the analysis results and emotional state to the analysis server via wireless communication.

[0632] Step 8:

[0633] Server: Based on the analysis results and the user's emotional state, the server generates a voice guidance message and AR display data for the user. For example, if a bicycle is approaching ahead, the server generates a specially tailored voice message such as "Remain calm and be careful. A bicycle is approaching ahead."

[0634] Step 9:

[0635] Server: Re-sends the voice guidance data and AR display data to the device.

[0636] Step 10:

[0637] Terminal: The terminal decodes the received voice guidance data and provides voice guidance to the user through the built-in speaker, such as "There is a bicycle approaching ahead, please be careful."

[0638] Step 11:

[0639] Device: Decodes the received AR display data and highlights approaching bicycles ahead with arrows and boxes on the Glasses display.

[0640] Step 12:

[0641] User: The user understands the surrounding environment based on the voice guidance and AR display, and can take action if necessary, such as avoiding bicycles. By providing information based on the user's emotional state, the user can act with peace of mind.

[0642] This series of processes not only enables visually impaired people to accurately grasp their surroundings in real time, but also provides support tailored to their emotional state, enabling them to act safely and effectively.

[0643] Example 2

[0644] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0645] It is difficult for visually impaired people to accurately grasp information about their surroundings in real time. Furthermore, conventional visual support systems cannot provide personalized assistance that takes into account the user's emotional state, which can increase anxiety and stress. This poses a challenge for visually impaired people to live their daily lives safely and confidently.

[0646] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a video capture means for capturing video data of the front, an analysis means for analyzing the captured video data, a voice output means for providing a user with audio guidance on information based on the analyzed video data, a display means for augmented reality display of information based on the analyzed video data, and an emotion analysis means for recognizing and analyzing the user's emotional state. This enables visually impaired people to accurately grasp information about their surrounding environment in real time and receive personalized support according to the user's emotional state.

[0647] "Video capture means" refers to a device or mechanism used to capture forward video data.

[0648] An "analysis means" is a server or software module used to analyze the captured video data.

[0649] The "audio output means" refers to a speaker or a voice synthesizer used to provide the user with audio guidance of information based on the analyzed video data.

[0650] The "display means" refers to a display or projector used to display information based on the analyzed video data in an augmented reality manner.

[0651] "Emotion analysis means" refers to sensors and analysis algorithms used to recognize and analyze a user's emotional state.

[0652] A "wireless network" is a network infrastructure for transmitting data wirelessly.

[0653] "Multimodal AI" is an AI technology that performs integrated analysis of multiple different types of data (for example, video data, audio data, etc.).

[0654] "User's emotional state" refers to the user's current psychological and physiological state, including anxiety, stress, joy, and the like.

[0655] "Personalized assistance" refers to providing individual assistance tailored to the user's specific situation and emotional state.

[0656] "Real-time" refers to immediate processing and response without delay.

[0657] The present invention provides a visual support system for visually impaired people that adds an emotion analysis function to provide personalized support based on the user's emotional state. The system includes a video capture unit, an analysis server unit, an audio output unit, a display unit, and an emotion analysis unit.

[0658] Device (visual support glasses)

[0659] The device is equipped with a built-in camera that captures images of the area ahead. This camera obtains the user's line of sight as video data. Specifically, the video is acquired in real time using a high-resolution sensor. This data is compressed by a signal processing module and sent to an analysis server via a wireless communication module. The H.264 codec is used as the compression technology. The device is also equipped with a speaker and microphone, which function as a means of providing audio guidance. It also has a built-in augmented reality display that provides visual support information based on the analysis results.

[0660] Analysis Server

[0661] The analysis server receives the video data sent from the device and analyzes it using its built-in multimodal artificial intelligence (AI). Specifically, it uses an object recognition algorithm (e.g., the YOLO algorithm) to identify objects (bicycles, pedestrians, cars, etc.) ahead and track their movements. It also receives the user's emotional data and determines their emotional state, such as anxiety, stress, or joy. Based on the resulting information, it generates data for audio guidance and augmented reality display and sends it back to the device.

[0662] Emotion analysis means

[0663] The emotion analysis means acquires the user's voice and biometric data (such as heart rate) to recognize and analyze their current emotional state. Specifically, a microphone collects the user's voice, and a biometric sensor measures their heart rate. Analysis is performed based on this data to determine the user's emotional state. This information is sent to an analysis server and used to adjust the voice guidance and augmented reality display content.

[0664] Specific examples

[0665] For example, when a user is about to cross an intersection, the device's camera captures video of the area ahead and sends it to an analysis server. The analysis server analyzes the video data and recognizes that a bicycle is approaching ahead. At the same time, the emotion analysis means detects an increase in the user's heart rate and determines that the user is in an anxious state. Based on this information, the analysis server generates a voice guidance message saying, "A bicycle is approaching ahead. Remain calm and be careful," and sends this to the device along with AR display data. The device receives this and visually displays the approaching bicycle on the display along with the voice guidance. Based on this, the user takes action to avoid the bicycle.

[0666] Prompt Sentence Examples

[0667] "When a user is about to cross an intersection, the vision support glasses should detect a bicycle ahead and, taking into account the user's anxiety state, notify them by saying, 'Remain calm and be careful. There is a bicycle approaching ahead.'"

[0668] These features allow visually impaired people to accurately grasp their surroundings in real time and receive assistance tailored to their emotional state, enabling them to act safely and effectively.

[0669] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0670] Step 1:

[0671] Device: The device's camera captures the image in front of it. High-resolution image data is acquired in real time in the direction the user is looking. This image data becomes the input for the system.

[0672] Step 2:

[0673] Terminal: The captured video data is compressed by the signal processing module. Specifically, the video data is compressed using the H.264 codec. The compressed data is sent to the analysis server via the wireless communication module. This data is input to the analysis server as output.

[0674] Step 3:

[0675] Server: The server decompresses the received compressed video data and analyzes the video using multimodal AI. The input data is video frames, and based on this, an object recognition algorithm (e.g., YOLO) is used to detect objects (bicycles, pedestrians, cars, etc.) ahead. The detection results include data such as the object's position, speed, and direction of travel.

[0676] Step 4:

[0677] Terminal: The emotion analysis means acquires the user's voice and biometric data. A microphone collects voice data, and a biometric sensor measures heart rate. These are the input data. Based on this data, the emotional state is analyzed and emotions such as anxiety and stress are determined. The determination result is sent to the analysis server as output.

[0678] Step 5:

[0679] Server: The server generates voice guidance messages and AR display data based on the analysis results and the user's emotional state. The input data are the results of video analysis and emotion analysis. Specifically, it detects the approach of a bicycle ahead, and if it determines that the user is in an anxious state, it generates an adjusted voice message saying, "A bicycle is approaching ahead. Remain calm and be careful." This voice guidance data and AR display data are sent to the device as output data.

[0680] Step 6:

[0681] Terminal: The terminal decodes the received voice guidance data and provides voice guidance to the user through the built-in speaker. The data input is voice guidance data from the server, and voice output is based on this. It also displays AR display data on the display to provide visual information to the user. For example, approaching bicycles ahead can be highlighted with arrows or boxes.

[0682] Step 7:

[0683] User: The user understands the surrounding environment based on the audio guidance and AR display, and takes action to avoid the bicycle. The input is the audio guidance and AR display information, and based on this, the user performs specific actions (for example, moving to the right).

[0684] This is the specific flow of the system's program processing. This system allows visually impaired people to accurately grasp their surroundings in real time and receive support according to their emotional state.

[0685] (Application example 2)

[0686] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0687] In order for visually impaired people to live their daily lives safely, they need support tools that allow them to accurately grasp their surroundings. However, conventional visual support systems lack physical and psychological support that takes into account the user's emotional state, which can lead to users feeling anxious and stressed, and resulting in insufficient safety measures.

[0688] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0689] In this invention, the server includes video capture means for capturing video data of the area ahead, analysis server means for analyzing the captured video data, audio output means for providing audio guidance to the visually impaired person based on the analyzed video data, display means for displaying the information based on the analyzed video data in an augmented reality manner, and emotion engine means for analyzing the user's emotional state and adjusting the audio guidance and display content based on the analysis. This allows the visually impaired person to grasp the situation around them in real time, receive appropriate support according to their emotional state, and act safely and with peace of mind.

[0690] "Video capture means" is a combination of hardware and software for capturing forward video data.

[0691] The "analysis server means" is a server for analyzing captured video data and a system that uses multimodal artificial intelligence to interpret the data.

[0692] The "audio output means" is a device that provides information based on the analyzed video data to visually impaired people as audio.

[0693] The "display means" is a device for displaying information based on the analyzed video data as augmented reality to visually impaired people.

[0694] The "emotion engine means" is a system for analyzing the user's emotional state and adjusting the voice guidance and display content according to that state.

[0695] A "wireless network" is a communication method for sending and receiving information via electromagnetic waves, and is used to send video data and analysis results to a server in a remote location.

[0696] "Multimodal AI" is an AI technology that processes multiple types of data (e.g., video data, audio data, biometric data) in an integrated manner and outputs analytical results.

[0697] A system and a program required to implement the present invention will be described.

[0698] First, the system uses the following major hardware and software:

[0699] Video capture method (e.g., camera in smart glasses)

[0700] Analysis server means (e.g. cloud server)

[0701] Audio output means (e.g., speakers in smart glasses)

[0702] Display means (e.g., smart glasses display)

[0703] Emotion engine means (e.g., dedicated software for analyzing biometric data)

[0704] Specific processing flow

[0705] 1. Capture video data

[0706] When a user wears the smart glasses and walks forward, the camera captures video data of the area ahead, which is acquired in real time and compressed by the signal processing module.

[0707] 2. Data transmission

[0708] The captured video data is transmitted to an analysis server via a wireless network, enabling real-time analysis.

[0709] 3. Data Analysis

[0710] The analysis server analyzes the received video data using multimodal artificial intelligence (AI), which recognizes objects, people, and characters from the video data and interprets the obtained information from multiple perspectives.

[0711] 4. Emotional state analysis

[0712] The emotion engine acquires the user's voice data and biometric data (e.g., heart rate) and analyzes the user's current emotional state. For example, if the user's voice is trembling, it is determined to be in a state of anxiety.

[0713] 5. Integration and processing of analysis results

[0714] The server then combines the analysis results of the video data with the user's emotional state to generate voice guidance messages and augmented reality display data for the user. Depending on the specific situation, the server generates voice guidance such as "Stay calm and be careful."

[0715] 6. Return of results

[0716] The generated voice guidance data and augmented reality display data are transmitted again to the smart glasses.

[0717] 7. Audio guidance and augmented reality displays

[0718] The smart glasses decode the received voice guidance data and provide voice guidance to the user through the built-in speaker, while also highlighting surrounding hazards on the display.

[0719] 8. User Actions

[0720] Based on the voice guidance and augmented reality display, users can understand the surrounding environment and, if necessary, take action to avoid danger.

[0721] The specific hardware and software used

[0722] Smart glasses (e.g. Microsoft HoloLens, Google Glass)

[0723] Cloud servers (e.g., Amazon Web Services (AWS), Google Cloud Platform (GCP))

[0724] Multimodal artificial intelligence models (e.g., TensorFlow, PyTorch)

[0725] Speech processing modules (e.g., Google Speech-to-Text, IBM Watson Speech to Text)

[0726] Emotion analysis software (e.g., Affectiva, Microsoft Azure Emotion API)

[0727] Specific examples and examples of prompts for generative AI models

[0728] For example, consider a situation where a visually impaired person is walking alone outside at night. If a person suddenly approaches in front of the user, the system will notify the user of the situation through voice guidance and an augmented reality display. An example of a prompt is as follows:

[0729] Prompt statement

[0730] When a visually impaired person is walking alone at night, if the assistant detects a person suddenly approaching in front of them, it will tell them "Please stay calm. There is a dangerous person ahead," and guide them to avoid that person. It should also provide support according to the user's emotional state.

[0731] In this way, visually impaired people can move around safely and with peace of mind.

[0732] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0733] Step 1:

[0734] The device captures images of the front using a camera. The input is image data in the direction of the user's line of sight, and the output is the captured raw image data. Specifically, the camera captures images of the scenery and objects in front in real time and collects the data.

[0735] Step 2:

[0736] The device compresses the captured video data using a signal processing module and transmits it to the analysis server using a wireless communication module. The input is the captured raw video data, and the output is the compressed video data. Specifically, the data size is reduced using a data compression algorithm and then transmitted to the server via a wireless network.

[0737] Step 3:

[0738] The server decompresses the received compressed video data and analyzes it using multimodal artificial intelligence (AI). The input is the compressed video data, and the output is the analysis results, such as object and person recognition. Specifically, the AI ​​model analyzes the video data frame by frame and identifies objects and people in front of the vehicle.

[0739] Step 4:

[0740] The device uses an emotion engine to capture the user's voice and biometric data and analyze their emotional state. The input is the user's voice data and heart rate data, and the output is the user's emotional state (e.g., anxiety, stress, joy). Specifically, microphones and sensors collect user data, and an emotion analysis algorithm determines the user's emotional state.

[0741] Step 5:

[0742] The server integrates the analysis results of the video data with the user's emotional state to generate voice guidance messages and augmented reality display data. The inputs are the results of object and person recognition and the user's emotional state, and the output is an adjusted voice guidance message and augmented reality display data. Specifically, the server generates warning and guidance messages appropriate for the user based on the analysis results and the user's emotional state.

[0743] Step 6:

[0744] The server retransmits the generated voice guidance data and augmented reality display data to the terminal. The input is the voice guidance message and the augmented reality display data, and the output is the completion of transmission to the terminal. Specifically, the data is transmitted to the terminal via a wireless communication module.

[0745] Step 7:

[0746] The device decodes the received voice guidance data and notifies the user through the built-in speaker. It also displays the augmented reality display data on the display. The input is the voice guidance message and display data, and the output is the voice notification and AR display. Specifically, the speaker plays the notification voice, and the display visually highlights the warning or guidance.

[0747] Step 8:

[0748] The user understands the surrounding information based on the voice guidance and augmented reality display, and takes action as necessary. The input is the notified voice guidance and AR display, and the output is the user's specific action (e.g., movement to avoid danger). Specific actions involve the user recognizing an approaching object ahead and selecting a safe route to move.

[0749] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0750] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0751] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0752] [Third embodiment]

[0753] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0754] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0755] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0756] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0757] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0758] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0759] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0760] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0761] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0762] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0763] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0764] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[0765] The present invention is a visual support system for visually impaired people, which includes a video capture unit, an analysis server unit, a voice guidance unit, and an augmented reality display unit. Using this system, visually impaired people can obtain information about their surrounding environment in real time and live their lives safely.

[0766] System configuration

[0767] Device (visual support glasses)

[0768] The terminal is equipped with a built-in camera that captures images of the area ahead. This camera acquires the user's line of sight as video data. The data is compressed by a signal processing module and transmitted to the analysis server means via a wireless communication module. The terminal is also equipped with a speaker and microphone, which function as a means for providing audio guidance. It also has a built-in augmented reality display that provides visual auxiliary information based on the analysis results.

[0769] Analysis Server

[0770] The analysis server means receives the video data sent from the terminal and analyzes the data using its built-in multimodal artificial intelligence (AI). The analysis means integrates functions such as object recognition, person recognition, and character recognition, and interprets the information obtained from the video data from multiple angles. Based on the resulting information, data for voice guidance and data for augmented reality display are generated and sent back to the terminal.

[0771] Program processing and specific examples

[0772] 1. Capture camera footage

[0773] Device: The user wears the vision support glasses and the camera captures images as they walk through the scenery in front of them. For example, if the user is about to cross an intersection, the camera captures images of cars, pedestrians, and cyclists in front of them in real time.

[0774] 2. Video transmission

[0775] Terminal: The captured video data is compressed by the signal processing module and sent to the analysis server via wireless communication.

[0776] 3. Video Analysis

[0777] Server: The server uses multimodal AI to analyze the received video data. For example, if the AI ​​detects a bicycle ahead, it tracks its movement and calculates its speed and direction of travel.

[0778] 4. Processing the analysis results

[0779] Server: The server generates a voice guidance message and AR display data for the user based on the analysis results. For example, if a bicycle is approaching ahead, the server creates a specific voice message such as, "A bicycle is approaching ahead. It will intersect in 3 meters."

[0780] 5. Returning the results

[0781] Server: Re-sends the voice guidance data and AR display data to the device.

[0782] 6. Voice guidance and AR display

[0783] Device: The device plays the received voice guidance data and notifies the user. It also displays AR display data on the glasses. For example, an arrow or icon on the glasses display can be used to visually indicate that a bicycle is approaching ahead.

[0784] In this way, users can understand their surroundings in real time and act safely even when they have visual impairments.

[0785] The processing flow will be explained below.

[0786] Step 1:

[0787] User: The user puts on the vision support glasses, which starts up the device and puts the system into operational mode.

[0788] Step 2:

[0789] Device: The device's built-in camera captures video data of the area in front of it. The camera module captures the user's line of sight as video data in real time.

[0790] Step 3:

[0791] Terminal: The terminal's signal processing module compresses the captured video data and transmits it to the analysis server via the wireless communication module.

[0792] Step 4:

[0793] Server: The analysis server receives the video data sent from the device, decodes the data, and reconstructs the original video data.

[0794] Step 5:

[0795] Server: The analytics server uses a multimodal artificial intelligence (AI) model to analyze the video data, identifying objects, people, and text in the video and calculating their respective positions and movements.

[0796] Step 6:

[0797] Server: Based on the analysis results, the server generates a voice guidance message and augmented reality (AR) display data for the user. For example, it creates a voice message saying "A bicycle is approaching ahead" and AR data showing an arrow mark indicating a bicycle.

[0798] Step 7:

[0799] Server: The server transmits the generated voice guidance data and AR display data back to the terminal via wireless communication.

[0800] Step 8:

[0801] Terminal: The terminal decodes the received voice guidance data and provides voice guidance to the user through the built-in speaker, such as "There is a bicycle approaching ahead, please be careful."

[0802] Step 9:

[0803] Device: The device decodes the received AR display data and highlights approaching bicycles ahead with arrows and boxes on the Glasses display.

[0804] Step 10:

[0805] User: The user understands the surrounding environment based on the voice guidance and AR display, and takes action such as avoiding bicycles.

[0806] This series of processing steps allows visually impaired people to accurately grasp their surroundings in real time and act safely.

[0807] Example 1

[0808] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0809] Visually impaired people have difficulty accurately understanding their surroundings, making it difficult for them to act safely. Furthermore, existing visual support systems often lack real-time capabilities and may not be able to provide sufficient support.

[0810] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0811] In this invention, the server includes an image capture means for capturing image data of the area ahead, a signal processing means for compressing the captured image data and transmitting it via a wireless communication module, an analysis server means for analyzing the compressed image data, an audio output means for providing audio guidance to the visually impaired person based on the analyzed image data, and a display means for displaying the information based on the analyzed image data in an augmented reality manner, thereby enabling the visually impaired person to grasp information about their surrounding environment in real time and act safely.

[0812] The "video capture means" is a device for acquiring video data in the direction of the user's line of sight.

[0813] The "signal processing means" is a module that has the function of compressing captured video data and transmitting it via the wireless communication module.

[0814] The "analysis server means" is a server for receiving compressed video data and analyzing the video data using multimodal artificial intelligence.

[0815] The "audio output means" is a device that provides audio guidance to visually impaired people about information based on analyzed video data.

[0816] The "display means" is a display for displaying information based on the analyzed video data as augmented reality.

[0817] The "wireless communication module" is a module having a wireless communication function for transmitting compressed video data to the analysis server.

[0818] "Multimodal artificial intelligence" is an artificial intelligence technology that analyzes data by integrating object recognition, person recognition, character recognition, etc.

[0819] The present invention is a visual support system for visually impaired people, which includes a video capture unit, a signal processing unit, an analysis server unit, an audio output unit, and a display unit. By using this system, visually impaired people can obtain information about their surrounding environment in real time and live their lives safely.

[0820] Device (visual support glasses)

[0821] The terminal is equipped with a built-in camera that captures images of the area ahead. This camera acquires the user's line of sight as video data. The data is compressed by a signal processing module and transmitted to the analysis server means via a wireless communication module. The terminal is also equipped with a speaker and microphone, which function as a means for providing audio guidance. It also has a built-in augmented reality display that provides visual auxiliary information based on the analysis results.

[0822] Analysis Server

[0823] The analysis server means receives the video data sent from the terminal and analyzes the data using its built-in multimodal artificial intelligence (AI). The analysis means integrates functions such as object recognition, person recognition, and character recognition, and interprets the information obtained from the video data from multiple angles. Based on the resulting information, data for voice guidance and data for augmented reality display are generated and sent back to the terminal.

[0824] Specific examples

[0825] The user wears the vision support glasses, and the camera captures images as they walk through the scenery ahead. For example, when the user is about to cross an intersection, the camera captures images of cars, pedestrians, and cyclists ahead in real time. The captured image data is compressed by a signal processing module and transmitted to an analysis server via wireless communication.

[0826] The analysis server uses multimodal AI to analyze the received video data. For example, if the AI ​​detects a bicycle ahead, it tracks its movement and calculates its speed and direction of travel. The server uses the analysis results to generate a voice guidance message for the user and AR display data. If a bicycle is approaching ahead, for example, it will create a specific voice message such as, "A bicycle is approaching ahead, and will cross in 3 meters."

[0827] The generated voice guidance data and AR display data are then sent back to the device. The device then plays the received voice guidance data and notifies the user. The AR display data is also displayed on the glasses. For example, an arrow or icon on the glasses' display can be used to visually indicate that a bicycle is approaching ahead.

[0828] Prompt Sentence Examples

[0829] "The server of a visual support system for the visually impaired receives and analyzes video data. Please explain the process by which people, objects, and text in the video are recognized and audio guidance data and augmented reality display data are generated for the user."

[0830] "Please explain in detail how the visual support glasses device compresses and transmits the video captured by the camera to the analysis server."

[0831] In this way, by using the system of the present invention, visually impaired people can grasp the situation around them in real time and act safely.

[0832] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0833] Step 1:

[0834] Camera footage capture and collection

[0835] Device: The user wears the vision support glasses. The built-in camera captures the scenery in the user's line of sight in real time. For example, when the user is approaching an intersection, the camera collects images of cars, pedestrians, bicycles, traffic lights, etc. ahead.

[0836] Input: Visual information from a camera attached to the vision support glasses.

[0837] How it works: The camera records high-resolution video at 30 frames per second and dynamically updates the view based on the user's movements.

[0838] Output: Captured high-resolution video data.

[0839] Step 2:

[0840] Video data compression and transmission

[0841] Terminal: The signal processing module compresses the captured video data in real time, and this compressed data is sent to the analysis server via the wireless communication module.

[0842] Input: Captured high-resolution video data.

[0843] Specific operation: Reduce the size of the video data using a compression algorithm (e.g., H.265) and optimize the transmission speed using a wireless communication module.

[0844] Output: Compressed video data.

[0845] Step 3:

[0846] Receiving and extracting video data

[0847] Server: The analysis server receives the compressed video data sent from the device and decompresses the data.

[0848] Input: Compressed video data.

[0849] Specific operation: Decompresses the received data and reconstructs the original high-resolution video data.

[0850] Output: Unpacked video data.

[0851] Step 4:

[0852] Video data analysis

[0853] Server: The video data is analyzed by the built-in multimodal artificial intelligence (AI), which uses functions such as object recognition, person recognition, and character recognition to identify information within the video.

[0854] Input: Unpacked high-resolution video data.

[0855] What it does: Uses AI models (e.g., YOLOv5 or DeepLab) to detect objects and people in video in real time and track their location and movement.

[0856] Output: Analyzed information (e.g., object location, human movement, text information, etc.).

[0857] Step 5:

[0858] Generate analysis results

[0859] Server: Generates voice guidance data and augmented reality (AR) display data based on the analysis of the video data. For example, if a bicycle is approaching ahead, it generates a message such as "A bicycle is approaching ahead. It will cross in 3 meters." It also generates corresponding arrows and icons for the AR display.

[0860] Input: Information as analysis results (object position, movement, text information, etc.).

[0861] Specific behavior: Uses predictive algorithms to analyze the movements of objects and people and generate appropriate warning messages and display data.

[0862] Output: Voice guidance data, AR display data.

[0863] Step 6:

[0864] Sending analysis results

[0865] Server: The generated voice guidance data and AR display data are recompressed and sent to the terminal via wireless communication.

[0866] Input: Generated voice guidance data and AR display data.

[0867] Specific actions: Optimize data transmission protocols and use technologies to prevent data loss (e.g., TCP / IP).

[0868] Output: Compressed voice guidance data, AR display data.

[0869] Step 7:

[0870] Results presentation (audio guidance and AR display)

[0871] Terminal: The device decodes the received voice guidance data and notifies the user through the speaker. At the same time, the device displays the received AR display data on the built-in display. For example, an arrow or icon may be used to visually indicate that a bicycle is approaching ahead.

[0872] Input: Compressed voice guidance data, AR display data.

[0873] Specific operation: Generates high-quality voice guidance using a speech synthesis engine (e.g., Google Text-to-Speech) and renders overlay information in real time on the AR display.

[0874] Output: Voice guidance, AR display.

[0875] (Application example 1)

[0876] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0877] To ensure the safety of employees working in factories, not only visually impaired workers but also those who are visually unimpaired but require visual assistance for certain tasks need to be aware of their surroundings at all times. However, currently, the environment within a factory is complex and dynamic, making it difficult for workers to recognize dangerous situations. This poses a problem of threatening work efficiency and safety.

[0878] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0879] In this invention, the server includes a video capture means for capturing video data of the front, a voice output means for providing a voice guide to the recipient with information based on the analyzed video data, a display means for displaying the information based on the analyzed video data in augmented reality, and a robot assistant means for ensuring the safety of the recipient based on the analyzed video data. This enables workers in a factory to grasp the surrounding situation in real time and work safely.

[0880] The "image capture means" is a device that acquires forward image data in real time and provides it to other devices or systems.

[0881] The "analysis server means" is a server device that analyzes captured video data and generates useful information based on that data.

[0882] The "audio output means" is a device for outputting information based on the analyzed video data as audio to notify the recipient.

[0883] The "display means" is a device such as an augmented reality display for visually presenting information based on the analyzed video data.

[0884] The "robot assistant means" is a robot device that provides instructions and assistance to ensure the safety of the recipient based on the analyzed video data.

[0885] This invention provides a system for ensuring the safety of workers in a factory and supporting visually impaired workers and workers who are not visually impaired but require visual assistance for specific tasks. The system includes a video capture unit, an analysis server unit, an audio output unit, a display unit, and a robot assistant unit.

[0886] Hardware and Software

[0887] Hardware:

[0888] Camera: A device used to capture real-time images of the work area within the factory.

[0889] Speaker: A device for providing audio guidance to workers.

[0890] Display: A device for displaying augmented reality (AR).

[0891] Server: A device for analyzing video data.

[0892] Robot: An auxiliary device to ensure worker safety.

[0893] software:

[0894] Generative AI (multimodal AI): An artificial intelligence model used for video analysis.

[0895] Robot OS: Basic software for controlling the robot's movements.

[0896] Wireless communication module: Software for sending and receiving data.

[0897] System Flow

[0898] 1. Capture camera footage

[0899] The robot's camera captures real-time video of the factory's work area, for example, detecting forklifts entering the work area.

[0900] 2. Video transmission

[0901] The captured video data is compressed by a signal processing module and transmitted to an analysis server via wireless communication.

[0902] 3. Video Analysis

[0903] The analysis server uses generative AI to analyze the received video data, for example, to identify the movement of a forklift and predict its direction of travel.

[0904] 4. Processing the analysis results

[0905] Based on the analysis results, the server generates a voice guidance message and AR display data. For example, it creates a voice message such as "Caution! A forklift is approaching from the right."

[0906] 5. Returning the results

[0907] Data for voice guidance and data for AR display are sent to the robot.

[0908] 6. Voice guidance and AR display

[0909] The robot plays back the received voice guidance data and notifies the worker. It also displays AR display data on the display, for example, showing the location of a forklift approaching from the right.

[0910] Specific examples

[0911] 1. Voice prompts:

[0912] "Caution! A forklift is approaching from the right."

[0913] 2. AR display:

[0914] Displays the maintenance area and indicates approaching forklifts with arrows and icons.

[0915] Prompt Sentence Examples

[0916] To improve the safety of forklifts and workers in factories, create a robot program that captures camera footage, analyzes it, and provides voice guidance and AR displays. The robot is equipped with a wireless communication module, signal processing module, speaker, and display. When a forklift is approaching from the right, the robot will provide a voice message saying "Caution! A forklift is approaching from the right," and use AR to show the location of the approaching forklift.

[0917] This allows employees working in the factory to grasp the situation around them in real time and proceed with their work safely.

[0918] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0919] Step 1:

[0920] Camera footage capture

[0921] While a user moves around the factory using a vision support robot, a camera built into the robot captures images of what is in front of it in real time.

[0922] Input: Factory footage taken by a robotic camera

[0923] Output: Captured video data

[0924] Specific operation: The camera captures video at 30 frames per second and stores the captured video data in memory.

[0925] Step 2:

[0926] Video transmission

[0927] The terminal (robot) compresses the captured video data using a signal processing module and transmits it to an analysis server via a wireless communication module.

[0928] Input: Captured video data

[0929] Output: Compressed video data

[0930] Specific operation: The signal processing module compresses the video data in H.264 format and sends the compressed data to the analysis server using the Wi-Fi module.

[0931] Step 3:

[0932] Video analysis

[0933] The server analyzes the received video data using a generative AI model (multimodal AI) and uses object recognition algorithms to identify obstacles and moving objects in the factory and predict their behavior.

[0934] Input: Compressed video data

[0935] Output: Analysis results (e.g., forklift position and direction of travel)

[0936] How it works: Multimodal AI uses the YOLOv5 model to detect objects in video and OpenCV to track their movements.

[0937] Step 4:

[0938] Processing the analysis results

[0939] Based on the analysis results, the server generates a voice guidance message and data for augmented reality display.

[0940] Input: Analysis results (object position and movement information)

[0941] Output: Data for voice guidance and AR display

[0942] Specific operation: When the server detects the approach of a forklift, it generates a voice message saying, "Caution! A forklift is approaching from the right," and creates an arrow icon as AR data indicating the direction of the approach.

[0943] Step 5:

[0944] Returning the results

[0945] The generated voice guidance data and AR display data are transmitted to the robot via wireless communication.

[0946] Input: Data for voice guidance and AR display

[0947] Output: Received voice guidance data and AR display data

[0948] Specific operation: The server sends voice guidance and AR display data to the robot via the Wi-Fi module.

[0949] Step 6:

[0950] Voice guidance and AR display

[0951] The robot plays the received voice guidance data through a speaker to notify the worker, and also displays the AR display data on the display.

[0952] Input: Received voice guidance data and AR display data

[0953] Output: Warning notification to operator and display on screen

[0954] Specific operation: The robot's speaker announces, "Caution! A forklift is approaching from the right," and an arrow indicating the forklift's location appears on the display.

[0955] This allows users to understand the surrounding situation in real time, enabling safe work within the factory.

[0956] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0957] The present invention provides a system for providing personalized assistance based on the user's emotional state by combining a visual support system for the visually impaired with an emotion engine. The system includes a video capture unit, an analysis server unit, a voice guidance unit, an augmented reality display unit, and an emotion engine.

[0958] System configuration

[0959] Device (visual support glasses)

[0960] The terminal is equipped with a built-in camera that captures images of the area ahead. This camera acquires the user's line of sight as video data. The data is compressed by a signal processing module and transmitted to the analysis server means via a wireless communication module. The terminal is also equipped with a speaker and microphone, which function as a means for providing audio guidance. It also has a built-in augmented reality display that provides visual auxiliary information based on the analysis results.

[0961] Analysis Server

[0962] The analysis server means receives the video data sent from the terminal and analyzes the data using its built-in multimodal artificial intelligence (AI). The analysis means integrates functions such as object recognition, person recognition, and character recognition, and interprets the information obtained from the video data from multiple angles. Based on the resulting information, data for voice guidance and data for augmented reality display are generated and sent back to the terminal.

[0963] Emotion Engine

[0964] The emotion engine is a means for recognizing and analyzing the user's emotional state. It determines the user's current emotional state (e.g., anxiety, stress, joy, etc.) based on their voice and biometric data (e.g., heart rate). This information is sent to an analysis server and used to adjust the voice guidance and augmented reality display content.

[0965] Program processing and specific examples

[0966] 1. Capture camera footage

[0967] Device: The user wears the vision support glasses and the camera captures images as they walk through the scenery in front of them. For example, if the user is about to cross an intersection, the camera captures images of cars, pedestrians, and cyclists in front of them in real time.

[0968] 2. Video transmission

[0969] Terminal: The captured video data is compressed by the signal processing module and sent to the analysis server via wireless communication.

[0970] 3. Video Analysis

[0971] Server: The server uses multimodal AI to analyze the received video data. For example, if the AI ​​detects a bicycle ahead, it tracks its movement and calculates its speed and direction of travel.

[0972] 4. Emotion Analysis

[0973] Device: The emotion engine acquires the user's voice and biometric data and analyzes the user's current emotional state. For example, if the user's voice is trembling, it will be determined that the user is in an anxious state.

[0974] 5. Processing the analysis results

[0975] Server: The server generates voice guidance messages and AR display data for the user based on the analysis results and emotional state. For example, if a bicycle is approaching ahead and the server determines that the user is in an anxious state, it will create a specially tailored voice message such as, "Remain calm and be careful. A bicycle is approaching ahead."

[0976] 6. Return of results

[0977] Server: Re-sends the voice guidance data and AR display data to the device.

[0978] 7. Voice guidance and AR display

[0979] Device: The device decodes the received voice guidance data and provides voice guidance to the user through the built-in speaker, such as "There is a bicycle approaching ahead." It also displays the augmented reality data on the Glasses' display, highlighting the approaching bicycle with an arrow or box.

[0980] 8. User Actions

[0981] User: The user understands the surrounding environment based on the voice guidance and AR display, and takes action such as avoiding bicycles. By providing information based on the user's emotional state, the user can act with greater peace of mind.

[0982] This series of processes allows visually impaired people to accurately grasp their surroundings in real time and receive support tailored to their emotional state, enabling them to act safely and effectively.

[0983] The processing flow will be explained below.

[0984] Step 1:

[0985] User: The user puts on the vision support glasses, which starts up the device and puts the system into operational mode.

[0986] Step 2:

[0987] Device: The device's built-in camera captures video data of the area in front of it. The camera module captures the user's line of sight as video data in real time.

[0988] Step 3:

[0989] Terminal: The terminal's signal processing module compresses the captured video data and transmits it to the analysis server via the wireless communication module.

[0990] Step 4:

[0991] Server: The analysis server receives the video data sent from the device, decodes the data, and reconstructs the original video data.

[0992] Step 5:

[0993] Server: The analytics server uses a multimodal artificial intelligence (AI) model to analyze the video data, identifying objects, people, and text in the video and calculating their respective positions and movements.

[0994] Step 6:

[0995] Device: The emotion engine acquires the user's voice and biometric data (such as heart rate) and analyzes the user's current emotional state. For example, if the user's voice is trembling, it will be determined that the user is in an anxious state.

[0996] Step 7:

[0997] Terminal: Transmits the analysis results and emotional state to the analysis server via wireless communication.

[0998] Step 8:

[0999] Server: Based on the analysis results and the user's emotional state, the server generates a voice guidance message and AR display data for the user. For example, if a bicycle is approaching ahead, the server generates a specially tailored voice message such as "Remain calm and be careful. A bicycle is approaching ahead."

[1000] Step 9:

[1001] Server: Re-sends the voice guidance data and AR display data to the device.

[1002] Step 10:

[1003] Terminal: The terminal decodes the received voice guidance data and provides voice guidance to the user through the built-in speaker, such as "There is a bicycle approaching ahead, please be careful."

[1004] Step 11:

[1005] Device: Decodes the received AR display data and highlights approaching bicycles ahead with arrows and boxes on the Glasses display.

[1006] Step 12:

[1007] User: The user understands the surrounding environment based on the voice guidance and AR display, and can take action if necessary, such as avoiding bicycles. By providing information based on the user's emotional state, the user can act with peace of mind.

[1008] This series of processes not only enables visually impaired people to accurately grasp their surroundings in real time, but also provides support tailored to their emotional state, enabling them to act safely and effectively.

[1009] Example 2

[1010] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1011] It is difficult for visually impaired people to accurately grasp information about their surroundings in real time. Furthermore, conventional visual support systems cannot provide personalized assistance that takes into account the user's emotional state, which can increase anxiety and stress. This poses a challenge for visually impaired people to live their daily lives safely and confidently.

[1012] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a video capture means for capturing video data of the front, an analysis means for analyzing the captured video data, a voice output means for providing a user with audio guidance on information based on the analyzed video data, a display means for augmented reality display of information based on the analyzed video data, and an emotion analysis means for recognizing and analyzing the user's emotional state. This enables visually impaired people to accurately grasp information about their surrounding environment in real time and receive personalized support according to the user's emotional state.

[1013] "Video capture means" refers to a device or mechanism used to capture forward video data.

[1014] An "analysis means" is a server or software module used to analyze the captured video data.

[1015] The "audio output means" refers to a speaker or a voice synthesizer used to provide the user with audio guidance of information based on the analyzed video data.

[1016] The "display means" refers to a display or projector used to display information based on the analyzed video data in an augmented reality manner.

[1017] "Emotion analysis means" refers to sensors and analysis algorithms used to recognize and analyze a user's emotional state.

[1018] A "wireless network" is a network infrastructure for transmitting data wirelessly.

[1019] "Multimodal AI" is an AI technology that performs integrated analysis of multiple different types of data (for example, video data, audio data, etc.).

[1020] "User's emotional state" refers to the user's current psychological and physiological state, including anxiety, stress, joy, and the like.

[1021] "Personalized assistance" refers to providing individual assistance tailored to the user's specific situation and emotional state.

[1022] "Real-time" refers to immediate processing and response without delay.

[1023] The present invention provides a visual support system for visually impaired people that adds an emotion analysis function to provide personalized support based on the user's emotional state. The system includes a video capture unit, an analysis server unit, an audio output unit, a display unit, and an emotion analysis unit.

[1024] Device (visual support glasses)

[1025] The device is equipped with a built-in camera that captures images of the area ahead. This camera obtains the user's line of sight as video data. Specifically, the video is acquired in real time using a high-resolution sensor. This data is compressed by a signal processing module and sent to an analysis server via a wireless communication module. The H.264 codec is used as the compression technology. The device is also equipped with a speaker and microphone, which function as a means of providing audio guidance. It also has a built-in augmented reality display that provides visual support information based on the analysis results.

[1026] Analysis Server

[1027] The analysis server receives the video data sent from the device and analyzes it using its built-in multimodal artificial intelligence (AI). Specifically, it uses an object recognition algorithm (e.g., the YOLO algorithm) to identify objects (bicycles, pedestrians, cars, etc.) ahead and track their movements. It also receives the user's emotional data and determines their emotional state, such as anxiety, stress, or joy. Based on the resulting information, it generates data for audio guidance and augmented reality display and sends it back to the device.

[1028] Emotion analysis means

[1029] The emotion analysis means acquires the user's voice and biometric data (such as heart rate) to recognize and analyze their current emotional state. Specifically, a microphone collects the user's voice, and a biometric sensor measures their heart rate. Analysis is performed based on this data to determine the user's emotional state. This information is sent to an analysis server and used to adjust the voice guidance and augmented reality display content.

[1030] Specific examples

[1031] For example, when a user is about to cross an intersection, the device's camera captures video of the area ahead and sends it to an analysis server. The analysis server analyzes the video data and recognizes that a bicycle is approaching ahead. At the same time, the emotion analysis means detects an increase in the user's heart rate and determines that the user is in an anxious state. Based on this information, the analysis server generates a voice guidance message saying, "A bicycle is approaching ahead. Remain calm and be careful," and sends this to the device along with AR display data. The device receives this and visually displays the approaching bicycle on the display along with the voice guidance. Based on this, the user takes action to avoid the bicycle.

[1032] Prompt Sentence Examples

[1033] "When a user is about to cross an intersection, the vision support glasses should detect a bicycle ahead and, taking into account the user's anxiety state, notify them by saying, 'Remain calm and be careful. There is a bicycle approaching ahead.'"

[1034] These features allow visually impaired people to accurately grasp their surroundings in real time and receive assistance tailored to their emotional state, enabling them to act safely and effectively.

[1035] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1036] Step 1:

[1037] Device: The device's camera captures the image in front of it. High-resolution image data is acquired in real time in the direction the user is looking. This image data becomes the input for the system.

[1038] Step 2:

[1039] Terminal: The captured video data is compressed by the signal processing module. Specifically, the video data is compressed using the H.264 codec. The compressed data is sent to the analysis server via the wireless communication module. This data is input to the analysis server as output.

[1040] Step 3:

[1041] Server: The server decompresses the received compressed video data and analyzes the video using multimodal AI. The input data is video frames, and based on this, an object recognition algorithm (e.g., YOLO) is used to detect objects (bicycles, pedestrians, cars, etc.) ahead. The detection results include data such as the object's position, speed, and direction of travel.

[1042] Step 4:

[1043] Terminal: The emotion analysis means acquires the user's voice and biometric data. A microphone collects voice data, and a biometric sensor measures heart rate. These are the input data. Based on this data, the emotional state is analyzed and emotions such as anxiety and stress are determined. The determination result is sent to the analysis server as output.

[1044] Step 5:

[1045] Server: The server generates voice guidance messages and AR display data based on the analysis results and the user's emotional state. The input data are the results of video analysis and emotion analysis. Specifically, it detects the approach of a bicycle ahead, and if it determines that the user is in an anxious state, it generates an adjusted voice message saying, "A bicycle is approaching ahead. Remain calm and be careful." This voice guidance data and AR display data are sent to the device as output data.

[1046] Step 6:

[1047] Terminal: The terminal decodes the received voice guidance data and provides voice guidance to the user through the built-in speaker. The data input is voice guidance data from the server, and voice output is based on this. It also displays AR display data on the display to provide visual information to the user. For example, approaching bicycles ahead can be highlighted with arrows or boxes.

[1048] Step 7:

[1049] User: The user understands the surrounding environment based on the audio guidance and AR display, and takes action to avoid the bicycle. The input is the audio guidance and AR display information, and based on this, the user performs specific actions (for example, moving to the right).

[1050] This is the specific flow of the system's program processing. This system allows visually impaired people to accurately grasp their surroundings in real time and receive support according to their emotional state.

[1051] (Application example 2)

[1052] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1053] In order for visually impaired people to live their daily lives safely, they need support tools that allow them to accurately grasp their surroundings. However, conventional visual support systems lack physical and psychological support that takes into account the user's emotional state, which can lead to users feeling anxious and stressed, and resulting in insufficient safety measures.

[1054] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1055] In this invention, the server includes video capture means for capturing video data of the area ahead, analysis server means for analyzing the captured video data, audio output means for providing audio guidance to the visually impaired person based on the analyzed video data, display means for displaying the information based on the analyzed video data in an augmented reality manner, and emotion engine means for analyzing the user's emotional state and adjusting the audio guidance and display content based on the analysis. This allows the visually impaired person to grasp the situation around them in real time, receive appropriate support according to their emotional state, and act safely and with peace of mind.

[1056] "Video capture means" is a combination of hardware and software for capturing forward video data.

[1057] The "analysis server means" is a server for analyzing captured video data and a system that uses multimodal artificial intelligence to interpret the data.

[1058] The "audio output means" is a device that provides information based on the analyzed video data to visually impaired people as audio.

[1059] The "display means" is a device for displaying information based on the analyzed video data as augmented reality to visually impaired people.

[1060] The "emotion engine means" is a system for analyzing the user's emotional state and adjusting the voice guidance and display content according to that state.

[1061] A "wireless network" is a communication method for sending and receiving information via electromagnetic waves, and is used to send video data and analysis results to a server in a remote location.

[1062] "Multimodal AI" is an AI technology that processes multiple types of data (e.g., video data, audio data, biometric data) in an integrated manner and outputs analytical results.

[1063] A system and a program required to implement the present invention will be described.

[1064] First, the system uses the following major hardware and software:

[1065] Video capture method (e.g., camera in smart glasses)

[1066] Analysis server means (e.g. cloud server)

[1067] Audio output means (e.g., speakers in smart glasses)

[1068] Display means (e.g., smart glasses display)

[1069] Emotion engine means (e.g., dedicated software for analyzing biometric data)

[1070] Specific processing flow

[1071] 1. Capture video data

[1072] When a user wears the smart glasses and walks forward, the camera captures video data of the area ahead, which is acquired in real time and compressed by the signal processing module.

[1073] 2. Data transmission

[1074] The captured video data is transmitted to an analysis server via a wireless network, enabling real-time analysis.

[1075] 3. Data Analysis

[1076] The analysis server analyzes the received video data using multimodal artificial intelligence (AI), which recognizes objects, people, and characters from the video data and interprets the obtained information from multiple perspectives.

[1077] 4. Emotional state analysis

[1078] The emotion engine acquires the user's voice data and biometric data (e.g., heart rate) and analyzes the user's current emotional state. For example, if the user's voice is trembling, it is determined to be in a state of anxiety.

[1079] 5. Integration and processing of analysis results

[1080] The server then combines the analysis results of the video data with the user's emotional state to generate voice guidance messages and augmented reality display data for the user. Depending on the specific situation, the server generates voice guidance such as "Stay calm and be careful."

[1081] 6. Return of results

[1082] The generated voice guidance data and augmented reality display data are transmitted again to the smart glasses.

[1083] 7. Audio guidance and augmented reality displays

[1084] The smart glasses decode the received voice guidance data and provide voice guidance to the user through the built-in speaker, while also highlighting surrounding hazards on the display.

[1085] 8. User Actions

[1086] Based on the voice guidance and augmented reality display, users can understand the surrounding environment and, if necessary, take action to avoid danger.

[1087] The specific hardware and software used

[1088] Smart glasses (e.g. Microsoft HoloLens, Google Glass)

[1089] Cloud servers (e.g., Amazon Web Services (AWS), Google Cloud Platform (GCP))

[1090] Multimodal artificial intelligence models (e.g., TensorFlow, PyTorch)

[1091] Speech processing modules (e.g., Google Speech-to-Text, IBM Watson Speech to Text)

[1092] Emotion analysis software (e.g., Affectiva, Microsoft Azure Emotion API)

[1093] Specific examples and examples of prompts for generative AI models

[1094] For example, consider a situation where a visually impaired person is walking alone outside at night. If a person suddenly approaches in front of the user, the system will notify the user of the situation through voice guidance and an augmented reality display. An example of a prompt is as follows:

[1095] Prompt statement

[1096] When a visually impaired person is walking alone at night, if the assistant detects a person suddenly approaching in front of them, it will tell them "Please stay calm. There is a dangerous person ahead," and guide them to avoid that person. It should also provide support according to the user's emotional state.

[1097] In this way, visually impaired people can move around safely and with peace of mind.

[1098] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1099] Step 1:

[1100] The device captures images of the front using a camera. The input is image data in the direction of the user's line of sight, and the output is the captured raw image data. Specifically, the camera captures images of the scenery and objects in front in real time and collects the data.

[1101] Step 2:

[1102] The device compresses the captured video data using a signal processing module and transmits it to the analysis server using a wireless communication module. The input is the captured raw video data, and the output is the compressed video data. Specifically, the data size is reduced using a data compression algorithm and then transmitted to the server via a wireless network.

[1103] Step 3:

[1104] The server decompresses the received compressed video data and analyzes it using multimodal artificial intelligence (AI). The input is the compressed video data, and the output is the analysis results, such as object and person recognition. Specifically, the AI ​​model analyzes the video data frame by frame and identifies objects and people in front of the vehicle.

[1105] Step 4:

[1106] The device uses an emotion engine to capture the user's voice and biometric data and analyze their emotional state. The input is the user's voice data and heart rate data, and the output is the user's emotional state (e.g., anxiety, stress, joy). Specifically, microphones and sensors collect user data, and an emotion analysis algorithm determines the user's emotional state.

[1107] Step 5:

[1108] The server integrates the analysis results of the video data with the user's emotional state to generate voice guidance messages and augmented reality display data. The inputs are the results of object and person recognition and the user's emotional state, and the output is an adjusted voice guidance message and augmented reality display data. Specifically, the server generates warning and guidance messages appropriate for the user based on the analysis results and the user's emotional state.

[1109] Step 6:

[1110] The server retransmits the generated voice guidance data and augmented reality display data to the terminal. The input is the voice guidance message and the augmented reality display data, and the output is the completion of transmission to the terminal. Specifically, the data is transmitted to the terminal via a wireless communication module.

[1111] Step 7:

[1112] The device decodes the received voice guidance data and notifies the user through the built-in speaker. It also displays the augmented reality display data on the display. The input is the voice guidance message and display data, and the output is the voice notification and AR display. Specifically, the speaker plays the notification voice, and the display visually highlights the warning or guidance.

[1113] Step 8:

[1114] The user understands the surrounding information based on the voice guidance and augmented reality display, and takes action as necessary. The input is the notified voice guidance and AR display, and the output is the user's specific action (e.g., movement to avoid danger). Specific actions involve the user recognizing an approaching object ahead and selecting a safe route to move.

[1115] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1116] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1117] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1118] [Fourth embodiment]

[1119] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1120] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1121] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1122] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1123] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1124] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1125] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1126] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1127] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1128] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1129] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1130] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1131] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1132] The present invention is a visual support system for visually impaired people, which includes a video capture unit, an analysis server unit, a voice guidance unit, and an augmented reality display unit. Using this system, visually impaired people can obtain information about their surrounding environment in real time and live their lives safely.

[1133] System configuration

[1134] Device (visual support glasses)

[1135] The terminal is equipped with a built-in camera that captures images of the area ahead. This camera acquires the user's line of sight as video data. The data is compressed by a signal processing module and transmitted to the analysis server means via a wireless communication module. The terminal is also equipped with a speaker and microphone, which function as a means for providing audio guidance. It also has a built-in augmented reality display that provides visual auxiliary information based on the analysis results.

[1136] Analysis Server

[1137] The analysis server means receives the video data sent from the terminal and analyzes the data using its built-in multimodal artificial intelligence (AI). The analysis means integrates functions such as object recognition, person recognition, and character recognition, and interprets the information obtained from the video data from multiple angles. Based on the resulting information, data for voice guidance and data for augmented reality display are generated and sent back to the terminal.

[1138] Program processing and specific examples

[1139] 1. Capture camera footage

[1140] Device: The user wears the vision support glasses and the camera captures images as they walk through the scenery in front of them. For example, if the user is about to cross an intersection, the camera captures images of cars, pedestrians, and cyclists in front of them in real time.

[1141] 2. Video transmission

[1142] Terminal: The captured video data is compressed by the signal processing module and sent to the analysis server via wireless communication.

[1143] 3. Video Analysis

[1144] Server: The server uses multimodal AI to analyze the received video data. For example, if the AI ​​detects a bicycle ahead, it tracks its movement and calculates its speed and direction of travel.

[1145] 4. Processing the analysis results

[1146] Server: The server generates a voice guidance message and AR display data for the user based on the analysis results. For example, if a bicycle is approaching ahead, the server creates a specific voice message such as, "A bicycle is approaching ahead. It will intersect in 3 meters."

[1147] 5. Returning the results

[1148] Server: Re-sends the voice guidance data and AR display data to the device.

[1149] 6. Voice guidance and AR display

[1150] Device: The device plays the received voice guidance data and notifies the user. It also displays AR display data on the glasses. For example, an arrow or icon on the glasses display can be used to visually indicate that a bicycle is approaching ahead.

[1151] In this way, users can understand their surroundings in real time and act safely even when they have visual impairments.

[1152] The processing flow will be explained below.

[1153] Step 1:

[1154] User: The user puts on the vision support glasses, which starts up the device and puts the system into operational mode.

[1155] Step 2:

[1156] Device: The device's built-in camera captures video data of the area in front of it. The camera module captures the user's line of sight as video data in real time.

[1157] Step 3:

[1158] Terminal: The terminal's signal processing module compresses the captured video data and transmits it to the analysis server via the wireless communication module.

[1159] Step 4:

[1160] Server: The analysis server receives the video data sent from the device, decodes the data, and reconstructs the original video data.

[1161] Step 5:

[1162] Server: The analytics server uses a multimodal artificial intelligence (AI) model to analyze the video data, identifying objects, people, and text in the video and calculating their respective positions and movements.

[1163] Step 6:

[1164] Server: Based on the analysis results, the server generates a voice guidance message and augmented reality (AR) display data for the user. For example, it creates a voice message saying "A bicycle is approaching ahead" and AR data showing an arrow mark indicating a bicycle.

[1165] Step 7:

[1166] Server: The server transmits the generated voice guidance data and AR display data back to the terminal via wireless communication.

[1167] Step 8:

[1168] Terminal: The terminal decodes the received voice guidance data and provides voice guidance to the user through the built-in speaker, such as "There is a bicycle approaching ahead, please be careful."

[1169] Step 9:

[1170] Device: The device decodes the received AR display data and highlights approaching bicycles ahead with arrows and boxes on the Glasses display.

[1171] Step 10:

[1172] User: The user understands the surrounding environment based on the voice guidance and AR display, and takes action such as avoiding bicycles.

[1173] This series of processing steps allows visually impaired people to accurately grasp their surroundings in real time and act safely.

[1174] Example 1

[1175] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1176] Visually impaired people have difficulty accurately understanding their surroundings, making it difficult for them to act safely. Furthermore, existing visual support systems often lack real-time capabilities and may not be able to provide sufficient support.

[1177] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1178] In this invention, the server includes an image capture means for capturing image data of the area ahead, a signal processing means for compressing the captured image data and transmitting it via a wireless communication module, an analysis server means for analyzing the compressed image data, an audio output means for providing audio guidance to the visually impaired person based on the analyzed image data, and a display means for displaying the information based on the analyzed image data in an augmented reality manner, thereby enabling the visually impaired person to grasp information about their surrounding environment in real time and act safely.

[1179] The "video capture means" is a device for acquiring video data in the direction of the user's line of sight.

[1180] The "signal processing means" is a module that has the function of compressing captured video data and transmitting it via the wireless communication module.

[1181] The "analysis server means" is a server for receiving compressed video data and analyzing the video data using multimodal artificial intelligence.

[1182] The "audio output means" is a device that provides audio guidance to visually impaired people about information based on analyzed video data.

[1183] The "display means" is a display for displaying information based on the analyzed video data as augmented reality.

[1184] The "wireless communication module" is a module having a wireless communication function for transmitting compressed video data to the analysis server.

[1185] "Multimodal artificial intelligence" is an artificial intelligence technology that analyzes data by integrating object recognition, person recognition, character recognition, etc.

[1186] The present invention is a visual support system for visually impaired people, which includes a video capture unit, a signal processing unit, an analysis server unit, an audio output unit, and a display unit. By using this system, visually impaired people can obtain information about their surrounding environment in real time and live their lives safely.

[1187] Device (visual support glasses)

[1188] The terminal is equipped with a built-in camera that captures images of the area ahead. This camera acquires the user's line of sight as video data. The data is compressed by a signal processing module and transmitted to the analysis server means via a wireless communication module. The terminal is also equipped with a speaker and microphone, which function as a means for providing audio guidance. It also has a built-in augmented reality display that provides visual auxiliary information based on the analysis results.

[1189] Analysis Server

[1190] The analysis server means receives the video data sent from the terminal and analyzes the data using its built-in multimodal artificial intelligence (AI). The analysis means integrates functions such as object recognition, person recognition, and character recognition, and interprets the information obtained from the video data from multiple angles. Based on the resulting information, data for voice guidance and data for augmented reality display are generated and sent back to the terminal.

[1191] Specific examples

[1192] The user wears the vision support glasses, and the camera captures images as they walk through the scenery ahead. For example, when the user is about to cross an intersection, the camera captures images of cars, pedestrians, and cyclists ahead in real time. The captured image data is compressed by a signal processing module and transmitted to an analysis server via wireless communication.

[1193] The analysis server uses multimodal AI to analyze the received video data. For example, if the AI ​​detects a bicycle ahead, it tracks its movement and calculates its speed and direction of travel. The server uses the analysis results to generate a voice guidance message for the user and AR display data. If a bicycle is approaching ahead, for example, it will create a specific voice message such as, "A bicycle is approaching ahead, and will cross in 3 meters."

[1194] The generated voice guidance data and AR display data are then sent back to the device. The device then plays the received voice guidance data and notifies the user. The AR display data is also displayed on the glasses. For example, an arrow or icon on the glasses' display can be used to visually indicate that a bicycle is approaching ahead.

[1195] Prompt Sentence Examples

[1196] "The server of a visual support system for the visually impaired receives and analyzes video data. Please explain the process by which people, objects, and text in the video are recognized and audio guidance data and augmented reality display data are generated for the user."

[1197] "Please explain in detail how the visual support glasses device compresses and transmits the video captured by the camera to the analysis server."

[1198] In this way, by using the system of the present invention, visually impaired people can grasp the situation around them in real time and act safely.

[1199] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1200] Step 1:

[1201] Camera footage capture and collection

[1202] Device: The user wears the vision support glasses. The built-in camera captures the scenery in the user's line of sight in real time. For example, when the user is approaching an intersection, the camera collects images of cars, pedestrians, bicycles, traffic lights, etc. ahead.

[1203] Input: Visual information from a camera attached to the vision support glasses.

[1204] How it works: The camera records high-resolution video at 30 frames per second and dynamically updates the view based on the user's movements.

[1205] Output: Captured high-resolution video data.

[1206] Step 2:

[1207] Video data compression and transmission

[1208] Terminal: The signal processing module compresses the captured video data in real time, and this compressed data is sent to the analysis server via the wireless communication module.

[1209] Input: Captured high-resolution video data.

[1210] Specific operation: Reduce the size of the video data using a compression algorithm (e.g., H.265) and optimize the transmission speed using a wireless communication module.

[1211] Output: Compressed video data.

[1212] Step 3:

[1213] Receiving and extracting video data

[1214] Server: The analysis server receives the compressed video data sent from the device and decompresses the data.

[1215] Input: Compressed video data.

[1216] Specific operation: Decompresses the received data and reconstructs the original high-resolution video data.

[1217] Output: Unpacked video data.

[1218] Step 4:

[1219] Video data analysis

[1220] Server: The video data is analyzed by the built-in multimodal artificial intelligence (AI), which uses functions such as object recognition, person recognition, and character recognition to identify information within the video.

[1221] Input: Unpacked high-resolution video data.

[1222] What it does: Uses AI models (e.g., YOLOv5 or DeepLab) to detect objects and people in video in real time and track their location and movement.

[1223] Output: Analyzed information (e.g., object location, human movement, text information, etc.).

[1224] Step 5:

[1225] Generate analysis results

[1226] Server: Generates voice guidance data and augmented reality (AR) display data based on the analysis of the video data. For example, if a bicycle is approaching ahead, it generates a message such as "A bicycle is approaching ahead. It will cross in 3 meters." It also generates corresponding arrows and icons for the AR display.

[1227] Input: Information as analysis results (object position, movement, text information, etc.).

[1228] Specific behavior: Uses predictive algorithms to analyze the movements of objects and people and generate appropriate warning messages and display data.

[1229] Output: Voice guidance data, AR display data.

[1230] Step 6:

[1231] Sending analysis results

[1232] Server: The generated voice guidance data and AR display data are recompressed and sent to the terminal via wireless communication.

[1233] Input: Generated voice guidance data and AR display data.

[1234] Specific actions: Optimize data transmission protocols and use technologies to prevent data loss (e.g., TCP / IP).

[1235] Output: Compressed voice guidance data, AR display data.

[1236] Step 7:

[1237] Results presentation (audio guidance and AR display)

[1238] Terminal: The device decodes the received voice guidance data and notifies the user through the speaker. At the same time, the device displays the received AR display data on the built-in display. For example, an arrow or icon may be used to visually indicate that a bicycle is approaching ahead.

[1239] Input: Compressed voice guidance data, AR display data.

[1240] Specific operation: Generates high-quality voice guidance using a speech synthesis engine (e.g., Google Text-to-Speech) and renders overlay information in real time on the AR display.

[1241] Output: Voice guidance, AR display.

[1242] (Application example 1)

[1243] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1244] To ensure the safety of employees working in factories, not only visually impaired workers but also those who are visually unimpaired but require visual assistance for certain tasks need to be aware of their surroundings at all times. However, currently, the environment within a factory is complex and dynamic, making it difficult for workers to recognize dangerous situations. This poses a problem of threatening work efficiency and safety.

[1245] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1246] In this invention, the server includes a video capture means for capturing video data of the front, a voice output means for providing a voice guide to the recipient with information based on the analyzed video data, a display means for displaying the information based on the analyzed video data in augmented reality, and a robot assistant means for ensuring the safety of the recipient based on the analyzed video data. This enables workers in a factory to grasp the surrounding situation in real time and work safely.

[1247] The "image capture means" is a device that acquires forward image data in real time and provides it to other devices or systems.

[1248] The "analysis server means" is a server device that analyzes captured video data and generates useful information based on that data.

[1249] The "audio output means" is a device for outputting information based on the analyzed video data as audio to notify the recipient.

[1250] The "display means" is a device such as an augmented reality display for visually presenting information based on the analyzed video data.

[1251] The "robot assistant means" is a robot device that provides instructions and assistance to ensure the safety of the recipient based on the analyzed video data.

[1252] This invention provides a system for ensuring the safety of workers in a factory and supporting visually impaired workers and workers who are not visually impaired but require visual assistance for specific tasks. The system includes a video capture unit, an analysis server unit, an audio output unit, a display unit, and a robot assistant unit.

[1253] Hardware and Software

[1254] Hardware:

[1255] Camera: A device used to capture real-time images of the work area within the factory.

[1256] Speaker: A device for providing audio guidance to workers.

[1257] Display: A device for displaying augmented reality (AR).

[1258] Server: A device for analyzing video data.

[1259] Robot: An auxiliary device to ensure worker safety.

[1260] software:

[1261] Generative AI (multimodal AI): An artificial intelligence model used for video analysis.

[1262] Robot OS: Basic software for controlling the robot's movements.

[1263] Wireless communication module: Software for sending and receiving data.

[1264] System Flow

[1265] 1. Capture camera footage

[1266] The robot's camera captures real-time video of the factory's work area, for example, detecting forklifts entering the work area.

[1267] 2. Video transmission

[1268] The captured video data is compressed by a signal processing module and transmitted to an analysis server via wireless communication.

[1269] 3. Video Analysis

[1270] The analysis server uses generative AI to analyze the received video data, for example, to identify the movement of a forklift and predict its direction of travel.

[1271] 4. Processing the analysis results

[1272] Based on the analysis results, the server generates a voice guidance message and AR display data. For example, it creates a voice message such as "Caution! A forklift is approaching from the right."

[1273] 5. Returning the results

[1274] Data for voice guidance and data for AR display are sent to the robot.

[1275] 6. Voice guidance and AR display

[1276] The robot plays back the received voice guidance data and notifies the worker. It also displays AR display data on the display, for example, showing the location of a forklift approaching from the right.

[1277] Specific examples

[1278] 1. Voice prompts:

[1279] "Caution! A forklift is approaching from the right."

[1280] 2. AR display:

[1281] Displays the maintenance area and indicates approaching forklifts with arrows and icons.

[1282] Prompt Sentence Examples

[1283] To improve the safety of forklifts and workers in factories, create a robot program that captures camera footage, analyzes it, and provides voice guidance and AR displays. The robot is equipped with a wireless communication module, signal processing module, speaker, and display. When a forklift is approaching from the right, the robot will provide a voice message saying "Caution! A forklift is approaching from the right," and use AR to show the location of the approaching forklift.

[1284] This allows employees working in the factory to grasp the situation around them in real time and proceed with their work safely.

[1285] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1286] Step 1:

[1287] Camera footage capture

[1288] While a user moves around the factory using a vision support robot, a camera built into the robot captures images of what is in front of it in real time.

[1289] Input: Factory footage taken by a robotic camera

[1290] Output: Captured video data

[1291] Specific operation: The camera captures video at 30 frames per second and stores the captured video data in memory.

[1292] Step 2:

[1293] Video transmission

[1294] The terminal (robot) compresses the captured video data using a signal processing module and transmits it to an analysis server via a wireless communication module.

[1295] Input: Captured video data

[1296] Output: Compressed video data

[1297] Specific operation: The signal processing module compresses the video data in H.264 format and sends the compressed data to the analysis server using the Wi-Fi module.

[1298] Step 3:

[1299] Video analysis

[1300] The server analyzes the received video data using a generative AI model (multimodal AI) and uses object recognition algorithms to identify obstacles and moving objects in the factory and predict their behavior.

[1301] Input: Compressed video data

[1302] Output: Analysis results (e.g., forklift position and direction of travel)

[1303] How it works: Multimodal AI uses the YOLOv5 model to detect objects in video and OpenCV to track their movements.

[1304] Step 4:

[1305] Processing the analysis results

[1306] Based on the analysis results, the server generates a voice guidance message and data for augmented reality display.

[1307] Input: Analysis results (object position and movement information)

[1308] Output: Data for voice guidance and AR display

[1309] Specific operation: When the server detects the approach of a forklift, it generates a voice message saying, "Caution! A forklift is approaching from the right," and creates an arrow icon as AR data indicating the direction of the approach.

[1310] Step 5:

[1311] Returning the results

[1312] The generated voice guidance data and AR display data are transmitted to the robot via wireless communication.

[1313] Input: Data for voice guidance and AR display

[1314] Output: Received voice guidance data and AR display data

[1315] Specific operation: The server sends voice guidance and AR display data to the robot via the Wi-Fi module.

[1316] Step 6:

[1317] Voice guidance and AR display

[1318] The robot plays the received voice guidance data through a speaker to notify the worker, and also displays the AR display data on the display.

[1319] Input: Received voice guidance data and AR display data

[1320] Output: Warning notification to operator and display on screen

[1321] Specific operation: The robot's speaker announces, "Caution! A forklift is approaching from the right," and an arrow indicating the forklift's location appears on the display.

[1322] This allows users to understand the surrounding situation in real time, enabling safe work within the factory.

[1323] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1324] The present invention provides a system for providing personalized assistance based on the user's emotional state by combining a visual support system for the visually impaired with an emotion engine. The system includes a video capture unit, an analysis server unit, a voice guidance unit, an augmented reality display unit, and an emotion engine.

[1325] System configuration

[1326] Device (visual support glasses)

[1327] The terminal is equipped with a built-in camera that captures images of the area ahead. This camera acquires the user's line of sight as video data. The data is compressed by a signal processing module and transmitted to the analysis server means via a wireless communication module. The terminal is also equipped with a speaker and microphone, which function as a means for providing audio guidance. It also has a built-in augmented reality display that provides visual auxiliary information based on the analysis results.

[1328] Analysis Server

[1329] The analysis server means receives the video data sent from the terminal and analyzes the data using its built-in multimodal artificial intelligence (AI). The analysis means integrates functions such as object recognition, person recognition, and character recognition, and interprets the information obtained from the video data from multiple angles. Based on the resulting information, data for voice guidance and data for augmented reality display are generated and sent back to the terminal.

[1330] Emotion Engine

[1331] The emotion engine is a means for recognizing and analyzing the user's emotional state. It determines the user's current emotional state (e.g., anxiety, stress, joy, etc.) based on their voice and biometric data (e.g., heart rate). This information is sent to an analysis server and used to adjust the voice guidance and augmented reality display content.

[1332] Program processing and specific examples

[1333] 1. Capture camera footage

[1334] Device: The user wears the vision support glasses and the camera captures images as they walk through the scenery in front of them. For example, if the user is about to cross an intersection, the camera captures images of cars, pedestrians, and cyclists in front of them in real time.

[1335] 2. Video transmission

[1336] Terminal: The captured video data is compressed by the signal processing module and sent to the analysis server via wireless communication.

[1337] 3. Video Analysis

[1338] Server: The server uses multimodal AI to analyze the received video data. For example, if the AI ​​detects a bicycle ahead, it tracks its movement and calculates its speed and direction of travel.

[1339] 4. Emotion Analysis

[1340] Device: The emotion engine acquires the user's voice and biometric data and analyzes the user's current emotional state. For example, if the user's voice is trembling, it will be determined that the user is in an anxious state.

[1341] 5. Processing the analysis results

[1342] Server: The server generates voice guidance messages and AR display data for the user based on the analysis results and emotional state. For example, if a bicycle is approaching ahead and the server determines that the user is in an anxious state, it will create a specially tailored voice message such as, "Remain calm and be careful. A bicycle is approaching ahead."

[1343] 6. Return of results

[1344] Server: Re-sends the voice guidance data and AR display data to the device.

[1345] 7. Voice guidance and AR display

[1346] Device: The device decodes the received voice guidance data and provides voice guidance to the user through the built-in speaker, such as "There is a bicycle approaching ahead." It also displays the augmented reality data on the Glasses' display, highlighting the approaching bicycle with an arrow or box.

[1347] 8. User Actions

[1348] User: The user understands the surrounding environment based on the voice guidance and AR display, and takes action such as avoiding bicycles. By providing information based on the user's emotional state, the user can act with greater peace of mind.

[1349] This series of processes allows visually impaired people to accurately grasp their surroundings in real time and receive support tailored to their emotional state, enabling them to act safely and effectively.

[1350] The processing flow will be explained below.

[1351] Step 1:

[1352] User: The user puts on the vision support glasses, which starts up the device and puts the system into operational mode.

[1353] Step 2:

[1354] Device: The device's built-in camera captures video data of the area in front of it. The camera module captures the user's line of sight as video data in real time.

[1355] Step 3:

[1356] Terminal: The terminal's signal processing module compresses the captured video data and transmits it to the analysis server via the wireless communication module.

[1357] Step 4:

[1358] Server: The analysis server receives the video data sent from the device, decodes the data, and reconstructs the original video data.

[1359] Step 5:

[1360] Server: The analytics server uses a multimodal artificial intelligence (AI) model to analyze the video data, identifying objects, people, and text in the video and calculating their respective positions and movements.

[1361] Step 6:

[1362] Device: The emotion engine acquires the user's voice and biometric data (such as heart rate) and analyzes the user's current emotional state. For example, if the user's voice is trembling, it will be determined that the user is in an anxious state.

[1363] Step 7:

[1364] Terminal: Transmits the analysis results and emotional state to the analysis server via wireless communication.

[1365] Step 8:

[1366] Server: Based on the analysis results and the user's emotional state, the server generates a voice guidance message and AR display data for the user. For example, if a bicycle is approaching ahead, the server generates a specially tailored voice message such as "Remain calm and be careful. A bicycle is approaching ahead."

[1367] Step 9:

[1368] Server: Re-sends the voice guidance data and AR display data to the device.

[1369] Step 10:

[1370] Terminal: The terminal decodes the received voice guidance data and provides voice guidance to the user through the built-in speaker, such as "There is a bicycle approaching ahead, please be careful."

[1371] Step 11:

[1372] Device: Decodes the received AR display data and highlights approaching bicycles ahead with arrows and boxes on the Glasses display.

[1373] Step 12:

[1374] User: The user understands the surrounding environment based on the voice guidance and AR display, and can take action if necessary, such as avoiding bicycles. By providing information based on the user's emotional state, the user can act with peace of mind.

[1375] This series of processes not only enables visually impaired people to accurately grasp their surroundings in real time, but also provides support tailored to their emotional state, enabling them to act safely and effectively.

[1376] Example 2

[1377] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1378] It is difficult for visually impaired people to accurately grasp information about their surroundings in real time. Furthermore, conventional visual support systems cannot provide personalized assistance that takes into account the user's emotional state, which can increase anxiety and stress. This poses a challenge for visually impaired people to live their daily lives safely and confidently.

[1379] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a video capture means for capturing video data of the front, an analysis means for analyzing the captured video data, a voice output means for providing a user with audio guidance on information based on the analyzed video data, a display means for augmented reality display of information based on the analyzed video data, and an emotion analysis means for recognizing and analyzing the user's emotional state. This enables visually impaired people to accurately grasp information about their surrounding environment in real time and receive personalized support according to the user's emotional state.

[1380] "Video capture means" refers to a device or mechanism used to capture forward video data.

[1381] An "analysis means" is a server or software module used to analyze the captured video data.

[1382] The "audio output means" refers to a speaker or a voice synthesizer used to provide the user with audio guidance of information based on the analyzed video data.

[1383] The "display means" refers to a display or projector used to display information based on the analyzed video data in an augmented reality manner.

[1384] "Emotion analysis means" refers to sensors and analysis algorithms used to recognize and analyze a user's emotional state.

[1385] A "wireless network" is a network infrastructure for transmitting data wirelessly.

[1386] "Multimodal AI" is an AI technology that performs integrated analysis of multiple different types of data (for example, video data, audio data, etc.).

[1387] "User's emotional state" refers to the user's current psychological and physiological state, including anxiety, stress, joy, and the like.

[1388] "Personalized assistance" refers to providing individual assistance tailored to the user's specific situation and emotional state.

[1389] "Real-time" refers to immediate processing and response without delay.

[1390] The present invention provides a visual support system for visually impaired people that adds an emotion analysis function to provide personalized support based on the user's emotional state. The system includes a video capture unit, an analysis server unit, an audio output unit, a display unit, and an emotion analysis unit.

[1391] Device (visual support glasses)

[1392] The device is equipped with a built-in camera that captures images of the area ahead. This camera obtains the user's line of sight as video data. Specifically, the video is acquired in real time using a high-resolution sensor. This data is compressed by a signal processing module and sent to an analysis server via a wireless communication module. The H.264 codec is used as the compression technology. The device is also equipped with a speaker and microphone, which function as a means of providing audio guidance. It also has a built-in augmented reality display that provides visual support information based on the analysis results.

[1393] Analysis Server

[1394] The analysis server receives the video data sent from the device and analyzes it using its built-in multimodal artificial intelligence (AI). Specifically, it uses an object recognition algorithm (e.g., the YOLO algorithm) to identify objects (bicycles, pedestrians, cars, etc.) ahead and track their movements. It also receives the user's emotional data and determines their emotional state, such as anxiety, stress, or joy. Based on the resulting information, it generates data for audio guidance and augmented reality display and sends it back to the device.

[1395] Emotion analysis means

[1396] The emotion analysis means acquires the user's voice and biometric data (such as heart rate) to recognize and analyze their current emotional state. Specifically, a microphone collects the user's voice, and a biometric sensor measures their heart rate. Analysis is performed based on this data to determine the user's emotional state. This information is sent to an analysis server and used to adjust the voice guidance and augmented reality display content.

[1397] Specific examples

[1398] For example, when a user is about to cross an intersection, the device's camera captures video of the area ahead and sends it to an analysis server. The analysis server analyzes the video data and recognizes that a bicycle is approaching ahead. At the same time, the emotion analysis means detects an increase in the user's heart rate and determines that the user is in an anxious state. Based on this information, the analysis server generates a voice guidance message saying, "A bicycle is approaching ahead. Remain calm and be careful," and sends this to the device along with AR display data. The device receives this and visually displays the approaching bicycle on the display along with the voice guidance. Based on this, the user takes action to avoid the bicycle.

[1399] Prompt Sentence Examples

[1400] "When a user is about to cross an intersection, the vision support glasses should detect a bicycle ahead and, taking into account the user's anxiety state, notify them by saying, 'Remain calm and be careful. There is a bicycle approaching ahead.'"

[1401] These features allow visually impaired people to accurately grasp their surroundings in real time and receive assistance tailored to their emotional state, enabling them to act safely and effectively.

[1402] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1403] Step 1:

[1404] Device: The device's camera captures the image in front of it. High-resolution image data is acquired in real time in the direction the user is looking. This image data becomes the input for the system.

[1405] Step 2:

[1406] Terminal: The captured video data is compressed by the signal processing module. Specifically, the video data is compressed using the H.264 codec. The compressed data is sent to the analysis server via the wireless communication module. This data is input to the analysis server as output.

[1407] Step 3:

[1408] Server: The server decompresses the received compressed video data and analyzes the video using multimodal AI. The input data is video frames, and based on this, an object recognition algorithm (e.g., YOLO) is used to detect objects (bicycles, pedestrians, cars, etc.) ahead. The detection results include data such as the object's position, speed, and direction of travel.

[1409] Step 4:

[1410] Terminal: The emotion analysis means acquires the user's voice and biometric data. A microphone collects voice data, and a biometric sensor measures heart rate. These are the input data. Based on this data, the emotional state is analyzed and emotions such as anxiety and stress are determined. The determination result is sent to the analysis server as output.

[1411] Step 5:

[1412] Server: The server generates voice guidance messages and AR display data based on the analysis results and the user's emotional state. The input data are the results of video analysis and emotion analysis. Specifically, it detects the approach of a bicycle ahead, and if it determines that the user is in an anxious state, it generates an adjusted voice message saying, "A bicycle is approaching ahead. Remain calm and be careful." This voice guidance data and AR display data are sent to the device as output data.

[1413] Step 6:

[1414] Terminal: The terminal decodes the received voice guidance data and provides voice guidance to the user through the built-in speaker. The data input is voice guidance data from the server, and voice output is based on this. It also displays AR display data on the display to provide visual information to the user. For example, approaching bicycles ahead can be highlighted with arrows or boxes.

[1415] Step 7:

[1416] User: The user understands the surrounding environment based on the audio guidance and AR display, and takes action to avoid the bicycle. The input is the audio guidance and AR display information, and based on this, the user performs specific actions (for example, moving to the right).

[1417] This is the specific flow of the system's program processing. This system allows visually impaired people to accurately grasp their surroundings in real time and receive support according to their emotional state.

[1418] (Application example 2)

[1419] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1420] In order for visually impaired people to live their daily lives safely, they need support tools that allow them to accurately grasp their surroundings. However, conventional visual support systems lack physical and psychological support that takes into account the user's emotional state, which can lead to users feeling anxious and stressed, and resulting in insufficient safety measures.

[1421] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1422] In this invention, the server includes video capture means for capturing video data of the area ahead, analysis server means for analyzing the captured video data, audio output means for providing audio guidance to the visually impaired person based on the analyzed video data, display means for displaying the information based on the analyzed video data in an augmented reality manner, and emotion engine means for analyzing the user's emotional state and adjusting the audio guidance and display content based on the analysis. This allows the visually impaired person to grasp the situation around them in real time, receive appropriate support according to their emotional state, and act safely and with peace of mind.

[1423] "Video capture means" is a combination of hardware and software for capturing forward video data.

[1424] The "analysis server means" is a server for analyzing captured video data and a system that uses multimodal artificial intelligence to interpret the data.

[1425] The "audio output means" is a device that provides information based on the analyzed video data to visually impaired people as audio.

[1426] The "display means" is a device for displaying information based on the analyzed video data as augmented reality to visually impaired people.

[1427] The "emotion engine means" is a system for analyzing the user's emotional state and adjusting the voice guidance and display content according to that state.

[1428] A "wireless network" is a communication method for sending and receiving information via electromagnetic waves, and is used to send video data and analysis results to a server in a remote location.

[1429] "Multimodal AI" is an AI technology that processes multiple types of data (e.g., video data, audio data, biometric data) in an integrated manner and outputs analytical results.

[1430] A system and a program required to implement the present invention will be described.

[1431] First, the system uses the following major hardware and software:

[1432] Video capture method (e.g., camera in smart glasses)

[1433] Analysis server means (e.g. cloud server)

[1434] Audio output means (e.g., speakers in smart glasses)

[1435] Display means (e.g., smart glasses display)

[1436] Emotion engine means (e.g., dedicated software for analyzing biometric data)

[1437] Specific processing flow

[1438] 1. Capture video data

[1439] When a user wears the smart glasses and walks forward, the camera captures video data of the area ahead, which is acquired in real time and compressed by the signal processing module.

[1440] 2. Data transmission

[1441] The captured video data is transmitted to an analysis server via a wireless network, enabling real-time analysis.

[1442] 3. Data Analysis

[1443] The analysis server analyzes the received video data using multimodal artificial intelligence (AI), which recognizes objects, people, and characters from the video data and interprets the obtained information from multiple perspectives.

[1444] 4. Emotional state analysis

[1445] The emotion engine acquires the user's voice data and biometric data (e.g., heart rate) and analyzes the user's current emotional state. For example, if the user's voice is trembling, it is determined to be in a state of anxiety.

[1446] 5. Integration and processing of analysis results

[1447] The server then combines the analysis results of the video data with the user's emotional state to generate voice guidance messages and augmented reality display data for the user. Depending on the specific situation, the server generates voice guidance such as "Stay calm and be careful."

[1448] 6. Return of results

[1449] The generated voice guidance data and augmented reality display data are transmitted again to the smart glasses.

[1450] 7. Audio guidance and augmented reality displays

[1451] The smart glasses decode the received voice guidance data and provide voice guidance to the user through the built-in speaker, while also highlighting surrounding hazards on the display.

[1452] 8. User Actions

[1453] Based on the voice guidance and augmented reality display, users can understand the surrounding environment and, if necessary, take action to avoid danger.

[1454] The specific hardware and software used

[1455] Smart glasses (e.g. Microsoft HoloLens, Google Glass)

[1456] Cloud servers (e.g., Amazon Web Services (AWS), Google Cloud Platform (GCP))

[1457] Multimodal artificial intelligence models (e.g., TensorFlow, PyTorch)

[1458] Speech processing modules (e.g., Google Speech-to-Text, IBM Watson Speech to Text)

[1459] Emotion analysis software (e.g., Affectiva, Microsoft Azure Emotion API)

[1460] Specific examples and examples of prompts for generative AI models

[1461] For example, consider a situation where a visually impaired person is walking alone outside at night. If a person suddenly approaches in front of the user, the system will notify the user of the situation through voice guidance and an augmented reality display. An example of a prompt is as follows:

[1462] Prompt statement

[1463] When a visually impaired person is walking alone at night, if the assistant detects a person suddenly approaching in front of them, it will tell them "Please stay calm. There is a dangerous person ahead," and guide them to avoid that person. It should also provide support according to the user's emotional state.

[1464] In this way, visually impaired people can move around safely and with peace of mind.

[1465] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1466] Step 1:

[1467] The device captures images of the front using a camera. The input is image data in the direction of the user's line of sight, and the output is the captured raw image data. Specifically, the camera captures images of the scenery and objects in front in real time and collects the data.

[1468] Step 2:

[1469] The device compresses the captured video data using a signal processing module and transmits it to the analysis server using a wireless communication module. The input is the captured raw video data, and the output is the compressed video data. Specifically, the data size is reduced using a data compression algorithm and then transmitted to the server via a wireless network.

[1470] Step 3:

[1471] The server decompresses the received compressed video data and analyzes it using multimodal artificial intelligence (AI). The input is the compressed video data, and the output is the analysis results, such as object and person recognition. Specifically, the AI ​​model analyzes the video data frame by frame and identifies objects and people in front of the vehicle.

[1472] Step 4:

[1473] The device uses an emotion engine to capture the user's voice and biometric data and analyze their emotional state. The input is the user's voice data and heart rate data, and the output is the user's emotional state (e.g., anxiety, stress, joy). Specifically, microphones and sensors collect user data, and an emotion analysis algorithm determines the user's emotional state.

[1474] Step 5:

[1475] The server integrates the analysis results of the video data with the user's emotional state to generate voice guidance messages and augmented reality display data. The inputs are the results of object and person recognition and the user's emotional state, and the output is an adjusted voice guidance message and augmented reality display data. Specifically, the server generates warning and guidance messages appropriate for the user based on the analysis results and the user's emotional state.

[1476] Step 6:

[1477] The server retransmits the generated voice guidance data and augmented reality display data to the terminal. The input is the voice guidance message and the augmented reality display data, and the output is the completion of transmission to the terminal. Specifically, the data is transmitted to the terminal via a wireless communication module.

[1478] Step 7:

[1479] The device decodes the received voice guidance data and notifies the user through the built-in speaker. It also displays the augmented reality display data on the display. The input is the voice guidance message and display data, and the output is the voice notification and AR display. Specifically, the speaker plays the notification voice, and the display visually highlights the warning or guidance.

[1480] Step 8:

[1481] The user understands the surrounding information based on the voice guidance and augmented reality display, and takes action as necessary. The input is the notified voice guidance and AR display, and the output is the user's specific action (e.g., movement to avoid danger). Specific actions involve the user recognizing an approaching object ahead and selecting a safe route to move.

[1482] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1483] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1484] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1485] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1486] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1487] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1488] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1489] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1490] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1491] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1492] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1493] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1494] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1495] 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.

[1496] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1497] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1498] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1499] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1500] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1501] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1502] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1503] The following is further disclosed regarding the above embodiment.

[1504] (Claim 1)

[1505] a video capture means for capturing video data of a front view;

[1506] analysis server means for analyzing the captured video data;

[1507] an audio output means for providing audio guidance to a visually impaired person about information based on the analyzed video data;

[1508] a display means for displaying information based on the analyzed video data in augmented reality;

[1509] A system including:

[1510] (Claim 2)

[1511] 10. The system of claim 1, wherein the video capture means transmits the captured video data to the analysis server means via a wireless network.

[1512] (Claim 3)

[1513] 10. The system of claim 1, wherein the analysis server means analyzes the video data using multimodal artificial intelligence.

[1514] (Claim 4)

[1515] 10. The system of claim 1, further comprising analysis server means for generating data for audio guidance and augmented reality display based on the analyzed video data.

[1516] (Claim 5)

[1517] 2. The system according to claim 1, wherein the voice guidance data transmitted from the analysis server means is decoded and output as voice.

[1518] (Claim 6)

[1519] 2. The system according to claim 1, wherein the augmented reality display data transmitted from the analysis server means is decoded and displayed on the display means.

[1520] "Example 1"

[1521] (Claim 1)

[1522] a video capture means for capturing video data of a front view;

[1523] a signal processing means for compressing the captured video data and transmitting it via a wireless communication module;

[1524] analysis server means for analyzing the compressed video data;

[1525] an audio output means for providing audio guidance to a visually impaired person about information based on the analyzed video data;

[1526] a display means for displaying information based on the analyzed video data in augmented reality;

[1527] A system including:

[1528] (Claim 2)

[1529] 2. The system according to claim 1, wherein the video data captured by the video capture means is compressed by the signal processing means and transmitted to the analysis server means via a wireless network.

[1530] (Claim 3)

[1531] 10. The system of claim 1, wherein the analysis server means analyzes the video data using multimodal artificial intelligence.

[1532] "Application Example 1"

[1533] (Claim 1)

[1534] a video capture means for capturing video data of a front view;

[1535] analysis server means for analyzing the captured video data;

[1536] an audio output means for providing audio guidance to the recipient about information based on the analyzed video data;

[1537] a display means for displaying information based on the analyzed video data in augmented reality;

[1538] a robot assistant means for ensuring the safety of the recipient based on the analyzed video data;

[1539] A system including:

[1540] (Claim 2)

[1541] 10. The system of claim 1, wherein the video capture means transmits the captured video data to the analysis server means via a wireless network.

[1542] (Claim 3)

[1543] 10. The system of claim 1, wherein the analysis server means uses multimodal artificial intelligence to analyze the video data and generate instructions to ensure the safety of the recipient.

[1544] "Example 2: Combining Emotion Engines"

[1545] (Claim 1)

[1546] a video capture means for capturing video data of a front view;

[1547] analysis means for analyzing the captured video data;

[1548] an audio output means for providing audio guidance to a user on information based on the analyzed video data;

[1549] a display means for displaying information based on the analyzed video data in augmented reality;

[1550] emotion analysis means for recognizing and analyzing the user's emotional state;

[1551] A system including:

[1552] (Claim 2)

[1553] 10. The system of claim 1, wherein the video capture means transmits the captured video data and the user's emotional state to the analysis means via a wireless network.

[1554] (Claim 3)

[1555] 10. The system of claim 1, wherein the analysis means uses multimodal artificial intelligence to analyze the video data and the user's emotional state.

[1556] "Application example 2 when combining emotion engines"

[1557] (Claim 1)

[1558] a video capture means for capturing video data of a front view;

[1559] analysis server means for analyzing the captured video data;

[1560] an audio output means for providing audio guidance to a visually impaired person about information based on the analyzed video data;

[1561] a display means for displaying information based on the analyzed video data in augmented reality;

[1562] emotion engine means for analyzing the emotional state of a user and adjusting voice guidance and display content based on the analysis;

[1563] A system including:

[1564] (Claim 2)

[1565] 10. The system of claim 1, wherein the video capture means transmits the captured video data to the analysis server means via a wireless network.

[1566] (Claim 3)

[1567] 10. The system of claim 1, wherein the analysis server means analyzes the video data using multimodal artificial intelligence. [Explanation of symbols]

[1568] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. a video capture means for capturing video data of a front view; analysis server means for analyzing the captured video data; an audio output means for providing audio guidance to a visually impaired person about information based on the analyzed video data; a display means for displaying information based on the analyzed video data in augmented reality; A system including:

2. 2. The system according to claim 1, wherein the video capture means transmits the captured video data to the analysis server means via a wireless network.

3. 10. The system of claim 1, wherein the analysis server means analyzes the video data using multimodal artificial intelligence.

4. 10. The system of claim 1, further comprising analysis server means for generating data for audio guidance and augmented reality display based on the analyzed video data.

5. 2. The system according to claim 1, wherein the voice guidance data transmitted from the analysis server means is decoded and output as voice.

6. The system according to claim 1 , wherein the augmented reality display data transmitted from the analysis server means is decoded and displayed on the display means.

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