system

Abstract

We provide the system. [Solution] A means for receiving video data from a video acquisition device that can be worn by the user and location information from a location acquisition device, A means of analyzing received video data and location information and using an artificial intelligence model to determine the surrounding situation, Based on the identified situation, a means of providing users with important information about their surroundings via voice, A system that includes this.

Description

Technical Field

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

Background Art

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

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] There is a problem that users with limitations in obtaining visual information cannot move safely and efficiently in their living environment and have difficulty ensuring independence in their daily lives. Also, in order to solve this problem, there is an emerging issue that a system for providing real-time and accurate environmental information is required.

Means for Solving the Problems

[0005] This invention collects environmental data in real time using a video acquisition device and a location acquisition device that can be worn by the user. This received data is then analyzed and categorized by an artificial intelligence model, and the user's situation is provided in real time via voice. To achieve this, a system configuration using high-speed wireless communication technology is employed, providing a means to maintain low latency and accuracy in information transmission.

[0006] A "video acquisition device" is a device that can be worn by a user to capture visual information of the environment.

[0007] A "location acquisition device" is a device that collects data to determine the user's current location.

[0008] "Reception" refers to the process of receiving data transmitted from the video acquisition device and the location acquisition device.

[0009] "Analysis" is the act of processing collected data to extract information for understanding the environment and situation.

[0010] An "artificial intelligence model" is a computational system that analyzes data and performs pattern recognition and situational discrimination.

[0011] "Audio provision" is the process of using hearing to convey information to users in order to communicate environmental information.

[0012] "High-speed wireless communication technology" refers to network technology that can transfer data quickly, and mainly includes 5G communication. [Brief explanation of the drawing]

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

Embodiments for Carrying Out the Invention

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

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

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

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

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

[0019] In the following embodiments, the numbered communication I / F (Interface) is an interface that includes a communication processor, an antenna, and the like. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

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

[0021] [First Embodiment]

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

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

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

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

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

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

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

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

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

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

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

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

[0034] This invention is a system centered around a wearable device that enables users with limited visual information acquisition to act independently. In this system, the terminal acquires video data of the user's surrounding environment in real time and transmits this data, along with location information from a location acquisition device, to a server. After receiving the data, the server analyzes the environment using an artificial intelligence model.

[0035] The analysis extracts the user's current location, risk factors in their environment, and guidance information, which the server then generates as natural language audio. This generated audio is transmitted back to the terminal with low latency, and the terminal provides this information to the user using speech synthesis technology. High-speed wireless communication technology is used throughout this process to ensure real-time information transmission.

[0036] As a concrete example, when a user uses this system while walking in an urban area, the video data and location information acquired by the terminal are transmitted to a server, and the system analyzes the surrounding pedestrians, bicycles, vehicles, and traffic light status. The system then provides the user with specific voice guidance such as, "There is an intersection 10 meters ahead. The traffic light is red. Please stop for your safety." In this way, the present invention realizes a system that helps users with visual impairments to reach their destination safely and effectively.

[0037] The following describes the processing flow.

[0038] Step 1:

[0039] The terminal acquires video data in real time from the attached video acquisition device.

[0040] Step 2:

[0041] The device obtains its current precise location information from a location acquisition device.

[0042] Step 3:

[0043] The device transmits the acquired video data and location information to the server using 5G communication.

[0044] Step 4:

[0045] The server receives and stores the data sent from the terminal.

[0046] Step 5:

[0047] The server inputs the received data into an artificial intelligence model to perform object recognition, obstacle detection, and traffic light status analysis of the environment.

[0048] Step 6:

[0049] The server translates the information that should be provided to the user into natural language based on the analysis results.

[0050] Step 7:

[0051] The server sends the generated natural language audio information to the terminal.

[0052] Step 8:

[0053] The terminal uses speech synthesis technology to transmit audio information received from the server to the user.

[0054] Step 9:

[0055] Users determine safe course of action based on the provided audio information.

[0056] (Example 1)

[0057] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0058] The challenge lies in realizing support systems that enable users with limited visual information acquisition to act safely and independently. In particular, there is a need to acquire information about the surrounding environment in real time and effectively communicate it to the user.

[0059] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0060] In this invention, the server includes means for receiving visual information data and location information from an information acquisition device wearable by the user; means for analyzing the received visual information data and location information and using a machine learning model to evaluate the surrounding environment; and means for transmitting important information about the surrounding environment to the user via an acoustic signal based on the analyzed information. This enables users whose ability to acquire visual information is limited to understand their surroundings in real time and act safely.

[0061] A "user-wearable information acquisition device" is a device that can be used by a user by being worn on their body, and which collects visual information and location information.

[0062] "Visual information data" refers to image or video data acquired from the surrounding environment using cameras or sensors.

[0063] "Location information" refers to information that indicates a user's current geographical location, obtained using global positioning systems and other location-based technologies.

[0064] "Means of receiving" refers to the functions and technologies that a server uses to acquire data and information transmitted from an external source.

[0065] "Machine learning models for analysis and evaluation of the surrounding environment" refers to machine learning algorithms and technologies used to analyze received data and understand the surrounding situation through object recognition and obstacle detection.

[0066] "Means of transmission via acoustic signals" means a technology or method for converting analyzed information into sound and transmitting it to the user.

[0067] "High-speed wireless communication technology" refers to mobile communication technology that enables the rapid transmission and reception of large amounts of data with low latency.

[0068] "Speech synthesis technology" is a technology that converts text information into speech and plays it back as natural-sounding utterances.

[0069] This system is designed to support users with limited visual information access, enabling them to act independently. The system primarily consists of wearable information acquisition devices, a server, and a terminal.

[0070] The device is equipped with hardware such as a camera, sensors, and GPS, which acquire visual and location information in real time. The device then rapidly transfers the acquired data to a server using a high-performance communication module (e.g., 5G communication).

[0071] The server analyzes the received visual and location data. This uses a generative AI model as a machine learning model. The generative AI model leverages computer vision technology to recognize surrounding objects and detect obstacles, evaluating the environmental conditions. The information obtained from the analysis is used to ensure the user's safety and is updated immediately as needed.

[0072] The analyzed information is converted into natural language acoustic signals by the server and transmitted back to the terminal via high-speed wireless communication technology. The terminal then provides the received information to the user in voice using speech synthesis technology, such as a text-to-speech engine. This allows the user to grasp important information about their surroundings in real time.

[0073] For example, if a visually impaired user is walking in an urban area, this system can provide voice guidance such as, "There is an intersection 100 meters ahead. The traffic light is red. Please stop."

[0074] An example of a prompt message is, "Generate voice guidance based on intersection location and signal information for a visually impaired user walking in an urban area." Based on this example, the generation AI model can appropriately generate the necessary guidance information.

[0075] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0076] Step 1:

[0077] The device acquires visual and location information of its surroundings. The camera and sensors on the device capture video data of the surroundings, and GPS obtains the current location information. The video data from the camera and the location data from GPS are used as input, and this becomes the initial input to the system.

[0078] Step 2:

[0079] The device sends the acquired data to the server. Video data and location information are sent to the server using high-speed wireless communication technology. The input is video data and location data acquired by the device, and the server receives this data as output.

[0080] Step 3:

[0081] The server analyzes the received data. The server uses a generative AI model to perform computer vision processing on the video data and identify objects and obstacles. The input consists of video data and location data received by the server, and after processing, analysis results regarding the user's surrounding environment are obtained.

[0082] Step 4:

[0083] The server generates natural language voice guidance based on the analysis results. Using natural language processing technology, it generates guidance information as text based on the analysis results. The input is analyzed surrounding environment data, and the output is natural language guidance text.

[0084] Step 5:

[0085] The server generates voice guidance text and sends it to the terminal. Using high-speed wireless communication technology, the generated guidance information is quickly sent back to the terminal. The input is the voice guidance text generated by the server, and the output is the completion of the transmission of the text data to the terminal.

[0086] Step 6:

[0087] The device receives text and transmits it to the user as audio. The device uses speech synthesis technology to convert text into speech and play it back to the user. The input is the audio guidance text received from the server, and the output is an audio notification to the user. This allows the user to receive real-time information about their surroundings via audio.

[0088] (Application Example 1)

[0089] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0090] This addresses the challenge of a lack of means to support safe and efficient movement for users who have difficulty acquiring visual information. In particular, when using autonomous vehicles, there is a need for technology that can accurately acquire information about the travel environment in real time and appropriately transmit it to the user.

[0091] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0092] In this invention, the server includes means for receiving ambient information from a video acquisition device and a location acquisition device that can be worn by the user; means for analyzing the received ambient information and using a generative AI model for determining the travel environment; and means for providing the user with travel guidance information via voice based on the determined situation. This enables users with limited visual information to safely understand their environment while traveling and to appropriately reach their destination using an autonomous vehicle.

[0093] A "user" is a person who wears this system and receives information from it.

[0094] A "video acquisition device" is a device worn by a user to collect visual information about their surroundings.

[0095] A "location acquisition device" is a device used to determine the user's current location.

[0096] "Surrounding information" is a general term for visual and positional data collected by image acquisition devices and position acquisition devices.

[0097] A "generative AI model" is an artificial intelligence model used to analyze acquired surrounding information and determine the environment and situation.

[0098] "Travel guidance information" refers to information that takes into account the user's current travel environment and includes instructions and warnings to guide them toward safe and efficient travel.

[0099] "Mobile object" refers to a mobile vehicle, such as an autonomous vehicle, on which this system is installed.

[0100] A "cloud server" is a remote server device that analyzes acquired information and allows the generated AI model to operate.

[0101] "High-speed wireless communication technology" refers to technology for transmitting data quickly in real time.

[0102] This invention is a system that assists users who have difficulty acquiring visual information in moving independently. The system collects information about the surroundings from an image acquisition device and a position acquisition device that can be worn by the user. This information is transmitted from the terminal to a cloud server. A generating AI model is deployed on the server, and this AI model analyzes the received information and performs a detailed analysis of the movement environment.

[0103] Specifically, in this system, the terminal acquires data in real time using hardware such as cameras and LIDAR sensors installed in the vehicle. This data is transmitted to a cloud server using high-speed wireless communication technology (e.g., 5G or Wi-Fi). The server performs object recognition and environmental analysis using software such as TENSORFLOW®, and based on the results, a generated AI model generates voice guidance information using prompt sentences.

[0104] The generated voice guidance information is sent back to the terminal and provided to the user in real time by a speech synthesis engine such as Google® Text-to-Speech. For example, when an autonomous vehicle is driving through a congested urban area, it is envisioned that the user will be provided with detailed and immediate voice guidance such as "We will be stopping at the intersection ahead" or "We have detected a group of pedestrians on the right."

[0105] Examples of prompt messages include, "Do you need to stop at the next traffic light?" and "There is an obstacle ahead, do you want to detour?" This allows users with limited visual information to effectively utilize autonomous vehicles and travel safely and efficiently.

[0106] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0107] Step 1:

[0108] The terminal acquires ambient environmental data in real time from cameras and LiDAR sensors installed in the vehicle. The input is raw data from the cameras and LiDAR sensors, and the output is obtained in the form of image data and distance information. The terminal stores this data in temporary storage and prepares it as input for the next step.

[0109] Step 2:

[0110] The terminal transmits acquired image data and distance information to a cloud server using high-speed wireless communication technology. The input is the image and distance information stored in the terminal's storage, and the output is the data structure sent to the server. The terminal uses a protocol to ensure stable data transfer.

[0111] Step 3:

[0112] The server analyzes the received data and performs object recognition and environmental analysis using a generated AI model with TensorFlow. The input consists of images and distance information sent from the terminal, and the output is environmental recognition data as a result of the analysis. Based on this data, the server understands the surrounding environment of a moving object and extracts risk and guidance information.

[0113] Step 4:

[0114] Based on the analysis results, the server uses a generative AI model to generate voice guidance information from prompt text. The input is environmental recognition data, and the output is text data of the voice guidance information. The server generates necessary warnings and instructions for the user and presents them as voice messages.

[0115] Step 5:

[0116] The server sends the generated voice guidance information back to the terminal, which receives it via high-speed wireless communication. The input is voice guidance information created by the generation AI model, and the output is stored as voice data on the terminal. The terminal manages the communication to receive the data stably and with low latency.

[0117] Step 6:

[0118] The device uses a text-to-speech engine, such as Google Text-to-Speech, to provide users with real-time voice guidance information. The input is text data of the voice guidance information, and the output is synthesized speech. Through this speech, users can receive guidance about their surroundings.

[0119] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0120] This invention provides a system that enables users with limitations in acquiring visual information to accurately perceive their surroundings and act safely and efficiently, taking into account their emotional state at the time. The system centers around a device worn by the user, integrating a video acquisition device and a location acquisition device. The device transmits real-time acquired video data and location information to a server.

[0121] The server receives this information and uses an artificial intelligence model to recognize objects in the environment and detect obstacles. Based on this information, the emotion engine activates and analyzes the user's emotional state. The emotion engine evaluates the user's stress level and sense of security by analyzing the tone and speed of the user's voice, as well as subtle biological responses.

[0122] Based on the analysis results, the server generates specific voice information in natural language and provides voice feedback to the user. This feedback is adjusted according to the user's emotional state. For example, if the user is feeling anxious, more detailed and reassuring guidance will be provided. Also, if sudden danger is detected, an immediate warning sound will be emitted to alert the user.

[0123] As a concrete example, when a user is walking through a busy area, this system allows the device to transmit information about the surroundings to the server in real time. The server then analyzes the environmental conditions and the user's emotions. If the user is feeling anxious, the system calmly provides voice messages such as, "There are many people around, but there are no obstacles in your path," to alleviate the user's anxiety and support safe movement.

[0124] Thus, the present invention realizes a system that supports users with visual limitations, enabling them to act with emotional confidence, based on comprehensive environmental and emotional analysis.

[0125] The following describes the processing flow.

[0126] Step 1:

[0127] The terminal acquires real-time video data of the environment from a video acquisition device worn by the user.

[0128] Step 2:

[0129] The terminal obtains accurate current location information from the location acquisition device and transmits it to the server along with video data.

[0130] Step 3:

[0131] The server uses an artificial intelligence model based on the video data and location information received from the terminal to perform object recognition and obstacle detection in the surrounding area.

[0132] Step 4:

[0133] The server activates the emotion engine and analyzes the user's emotional state. It uses the user's voice tone and speed, as well as biometric responses, to assess levels of stress and comfort.

[0134] Step 5:

[0135] The server generates necessary audio information for the user in natural language based on the analyzed surrounding environment and emotional state. The feedback is customized to take the user's emotional state into consideration.

[0136] Step 6:

[0137] The server transmits the generated audio information to the terminal with low latency.

[0138] Step 7:

[0139] The terminal uses speech synthesis technology to convey voice information sent from the server to the user. The voice can be used as a warning sound or a message of encouragement, as needed.

[0140] Step 8:

[0141] Based on the provided voice feedback, the user makes decisions about their surroundings and moves safely.

[0142] (Example 2)

[0143] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0144] There is a need to provide a system that allows users with limitations in visual information acquisition to safely and efficiently understand their surroundings and act with confidence. In particular, a system is needed that can provide information while considering not only the recognition of surrounding objects but also the user's emotional state.

[0145] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0146] In this invention, the server includes means for receiving video data from a video acquisition device wearable by the user and location information from a location acquisition device; means for analyzing the received video data and location information and using an artificial intelligence algorithm to recognize surrounding objects and detect obstacles; and analysis means for analyzing the characteristics of the user's voice and understanding their emotional state. This makes it possible to provide appropriate voice guidance in real time so that the user can act with a sense of security.

[0147] "User" refers to the entity that wears the system and receives information.

[0148] A "video acquisition device" is a device used to record surrounding visual information as digital data.

[0149] A "location acquisition device" is a device used to acquire geographical location information.

[0150] "Reception" refers to the process by which the server acquires video data and location information.

[0151] "Analysis" refers to the act of processing acquired data and extracting specific information.

[0152] An "artificial intelligence algorithm" is a computational method that analyzes data to perform object recognition and situational judgment.

[0153] "Voice guidance" is a method of providing information to users through audio.

[0154] "Natural language generation" refers to the technology of creating natural-sounding language expressions based on analyzed data.

[0155] "Voice output means" refers to a mechanism for transmitting generated voice guidance to the user.

[0156] "Real-time" means that processing or communication takes place instantly.

[0157] "A sense of security" refers to a safe and comfortable emotional state provided to the user.

[0158] This system helps users with visual impairments to understand their surroundings and act with confidence. First, the user wears a dedicated device that integrates a video acquisition device and a location acquisition device. This device is equipped with a camera and a location detection module, which acquires video and location information as digital data.

[0159] The terminal receives this data in real time and transmits it to the server via the communication network. Digital communication technology is used for data transmission to ensure communication stability and security. Data is compressed during transmission to efficiently transfer it to the server.

[0160] The server receives the transmitted data and first uses artificial intelligence algorithms to recognize objects in the environment and detect obstacles. Object detection algorithms such as YOLO (You Only Look Once) are used in this process. It also receives user voice data and analyzes the tone and speed of the voice to understand the emotional state. For voice analysis, it is possible to use libraries and tools for voice processing.

[0161] Based on the analysis results, the server uses natural language generation technology to create voice guidance tailored to the user. The generated voice guidance is designed to be adjusted according to the user's emotional state and to provide reassuring content. This process utilizes a generative AI model and employs appropriate prompt sentences to deliver optimal feedback to the user.

[0162] As a concrete example, let's say a user uses this system while moving through a crowded city. The device sends video footage and location data to a server, which uses YOLO to detect and analyze pedestrians and obstacles. Furthermore, it uses emotion analysis to determine the user's level of anxiety and generates voice advice such as, "There are many people around, but you can proceed safely," which is then fed back to the user.

[0163] An example of a prompt message would be, "Generate voice guidance explaining the surrounding environment to a user with limited visual information." By giving detailed instructions to the generation AI model in this way, it is possible to provide highly accurate guidance.

[0164] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0165] Step 1:

[0166] The user wears a dedicated device to acquire surrounding video data and location information. The device is equipped with a camera and a location detection module; the camera captures video data, and the location detection module records location information. The input is surrounding visual information and location information, and the output is digitized video and location information.

[0167] Step 2:

[0168] The terminal receives video data and location information acquired from the user's device. This data is first compressed using digital compression technology to improve communication efficiency. The compressed data is then ready to be transmitted to the server via the communication network. The input is video and location information from the device, and the output is a compressed data package.

[0169] Step 3:

[0170] The server receives compressed data sent from the terminal and decompresses it. By processing the decompressed data, the server performs object recognition and obstacle detection in the environment. Artificial intelligence algorithms (e.g., object detection algorithms) are used here. The input is compressed video and location information, and the output is a list of objects and their location information.

[0171] Step 4:

[0172] The server receives user voice data and analyzes the tone and speed of the voice. This allows for the estimation of the user's emotional state. A voice processing library is used for the analysis, and stress levels and feelings of comfort are evaluated. The input is voice data, and the output is the emotion analysis result.

[0173] Step 5:

[0174] The server integrates the results of object recognition and sentiment analysis, and generates voice guidance using natural language generation technology. The generated voice guidance is adjusted to the user's emotional state. Here, the generation AI model creates feedback using prompt sentences and generates appropriate guidance. The input is the results of object recognition and sentiment analysis, and the output is the voice guidance provided to the user.

[0175] Step 6:

[0176] The terminal receives voice guidance generated from the server and outputs it to the user in real time. The voice is delivered to the user through headphones or other means, supporting safe movement. Through this process, users can obtain information to act with a sense of security. The input is voice guidance, and the output is voice feedback to the user.

[0177] (Application Example 2)

[0178] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0179] Conventional factory robots often lack sufficient environmental awareness and operational monitoring capabilities to enhance safety during work, and may be unable to adequately alert workers or provide advice on their movements. Furthermore, the lack of means to determine the efficiency of robot operation and make appropriate adjustments makes it difficult to improve productivity. It is necessary to address these challenges and realize a safe and efficient work environment.

[0180] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0181] This invention includes a server technology that receives image data from a wearable visual information acquisition device and location information from a location acquisition device; a technology that analyzes the received image data and location information and uses an intelligent model to determine the surrounding environment; a technology that monitors the robot's operation in the industrial field and prompts the worker with instructions and warnings via voice when errors or dangers are detected; and a technology that performs emotion analysis to evaluate the stress and load on the robot's operation and advises on efficient operation. This enables accurate understanding of the surrounding environment and real-time safe work instructions, as well as improved productivity through efficient robot operation.

[0182] A "visual information acquisition device that can be worn by users" is a device attached to a robot working in an industrial area to visually observe the surrounding environment.

[0183] An "intelligent model for analyzing image data and location information to determine the surrounding environment" is an artificial intelligence analysis method used by a robot to understand its surroundings from image data and location information acquired by the robot.

[0184] "Technology that allows robots to monitor their operation in an industrial setting and provide instructions and warnings to workers via voice when errors or hazards are detected" refers to technology in which robots monitor their own movements and surrounding conditions, and when problems or hazards are discovered, they prompt workers to take appropriate action.

[0185] "A technology that performs emotional analysis, evaluates the stress and load on robot movements, and advises on efficient movement" is a technology that analyzes the robot's movement state and proposes the optimal movement procedure to reduce stress and load.

[0186] "Technology that uses voice to provide instructions and warnings to workers" refers to a method of using voice output to communicate changes in the surrounding environment or dangerous conditions to workers.

[0187] To realize this invention, it is first necessary to equip the robot with a visual information acquisition device and a location information acquisition device. These devices acquire environmental information from the factory, and the obtained data is transmitted to a server in real time. The server uses an artificial intelligence model to recognize the environment in order to analyze the received image data and location information, and manages the robot's movements so that it can perform tasks safely and efficiently.

[0188] Specifically, the server utilizes cloud-based AI platforms such as Google Cloud AI and IBM Watson® to perform object recognition and obstacle detection in the environment. Furthermore, it evaluates the stress and load generated during robot operation using an emotion analysis engine and optimizes its movements accordingly. This enables the robot to quickly communicate warnings and instructions to workers via voice.

[0189] For example, when a robot is handling multiple parts in a factory, if a worker passes nearby, the server will generate a prompt such as "There is a worker nearby. Please slow down," and safely control the robot. An example of such a prompt might be text like, "Generate optimal actions and precautions for the robot to work safely in the factory."

[0190] This system improves the precision of robot movements, enhances safety within the factory, and supports increased productivity.

[0191] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0192] Step 1:

[0193] The terminal uses a visual information acquisition device and a location information acquisition device attached to a robot to acquire image data and location information within the factory. The input is the acquired image data and location information, and the output is the transmission of data to a server. This data is transmitted to the server in real time via a Wi-Fi network.

[0194] Step 2:

[0195] Based on the image data and location information received by the server, it uses cloud AI services such as Google Cloud AI and IBM Watson to perform environmental discrimination using an intelligent model. The input is image data and location information sent from the terminal, and the output is information on recognized objects and detected obstacles. The server analyzes this data using the AI ​​model to understand the surrounding environment.

[0196] Step 3:

[0197] Based on the environmental analysis results, the server uses an emotion analysis engine to evaluate the stress and load associated with the robot's movements. The input for this step is the environmental analysis results, and the output is evaluation information regarding stress and load. The server uses this information to adjust the voice feedback.

[0198] Step 4:

[0199] Based on the processing results, the server uses a generative AI model to create specific voice instructions and warning prompts. The input is stress and load evaluation information, and the output is voice prompts. The server generates these prompts to output appropriate instructions via voice, taking safety and efficiency into consideration.

[0200] Step 5:

[0201] The terminal transmits generated voice prompts to the robot, which then issues voice warnings and instructions to nearby workers. The input is the generated prompt text, and the output is voice instructions and warnings. The terminal uses a Bluetooth speaker or similar device to emit voice and manage its actions.

[0202] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0203] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0204] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0205] [Second Embodiment]

[0206] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0207] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0208] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0209] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0210] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0211] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0212] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0213] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0214] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0215] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0216] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0217] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0218] This invention is a system centered around a wearable device that enables users with limited visual information acquisition to act independently. In this system, the terminal acquires video data of the user's surrounding environment in real time and transmits this data, along with location information from a location acquisition device, to a server. After receiving the data, the server analyzes the environment using an artificial intelligence model.

[0219] The analysis extracts the user's current location, risk factors in their environment, and guidance information, which the server then generates as natural language audio. This generated audio is transmitted back to the terminal with low latency, and the terminal provides this information to the user using speech synthesis technology. High-speed wireless communication technology is used throughout this process to ensure real-time information transmission.

[0220] As a concrete example, when a user uses this system while walking in an urban area, the video data and location information acquired by the terminal are transmitted to a server, and the system analyzes the surrounding pedestrians, bicycles, vehicles, and traffic light status. The system then provides the user with specific voice guidance such as, "There is an intersection 10 meters ahead. The traffic light is red. Please stop for your safety." In this way, the present invention realizes a system that helps users with visual impairments to reach their destination safely and effectively.

[0221] The following describes the processing flow.

[0222] Step 1:

[0223] The terminal acquires video data in real time from the attached video acquisition device.

[0224] Step 2:

[0225] The device obtains its current precise location information from a location acquisition device.

[0226] Step 3:

[0227] The device transmits the acquired video data and location information to the server using 5G communication.

[0228] Step 4:

[0229] The server receives and stores the data sent from the terminal.

[0230] Step 5:

[0231] The server inputs the received data into an artificial intelligence model to perform object recognition, obstacle detection, and traffic light status analysis of the environment.

[0232] Step 6:

[0233] The server translates the information that should be provided to the user into natural language based on the analysis results.

[0234] Step 7:

[0235] The server sends the generated natural language audio information to the terminal.

[0236] Step 8:

[0237] The terminal uses speech synthesis technology to transmit audio information received from the server to the user.

[0238] Step 9:

[0239] Users determine safe course of action based on the provided audio information.

[0240] (Example 1)

[0241] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0242] The challenge lies in realizing support systems that enable users with limited visual information acquisition to act safely and independently. In particular, there is a need to acquire information about the surrounding environment in real time and effectively communicate it to the user.

[0243] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0244] In this invention, the server includes means for receiving visual information data and location information from an information acquisition device wearable by the user; means for analyzing the received visual information data and location information and using a machine learning model to evaluate the surrounding environment; and means for transmitting important information about the surrounding environment to the user via an acoustic signal based on the analyzed information. This enables users whose ability to acquire visual information is limited to understand their surroundings in real time and act safely.

[0245] A "user-wearable information acquisition device" is a device that can be used by a user by being worn on their body, and which collects visual information and location information.

[0246] "Visual information data" refers to image or video data acquired from the surrounding environment using cameras or sensors.

[0247] "Location information" refers to information that indicates a user's current geographical location, obtained using global positioning systems and other location-based technologies.

[0248] "Means of receiving" refers to the functions and technologies that a server uses to acquire data and information transmitted from an external source.

[0249] "Machine learning models for analysis and evaluation of the surrounding environment" refers to machine learning algorithms and technologies used to analyze received data and understand the surrounding situation through object recognition and obstacle detection.

[0250] "Means of transmission via acoustic signals" means a technology or method for converting analyzed information into sound and transmitting it to the user.

[0251] "High-speed wireless communication technology" refers to mobile communication technology that enables the rapid transmission and reception of large amounts of data with low latency.

[0252] "Speech synthesis technology" is a technology that converts text information into speech and plays it back as natural-sounding utterances.

[0253] This system is designed to support users with limited visual information access, enabling them to act independently. The system primarily consists of wearable information acquisition devices, a server, and a terminal.

[0254] The device is equipped with hardware such as a camera, sensors, and GPS, which acquire visual and location information in real time. The device then rapidly transfers the acquired data to a server using a high-performance communication module (e.g., 5G communication).

[0255] The server analyzes the received visual and location data. This uses a generative AI model as a machine learning model. The generative AI model leverages computer vision technology to recognize surrounding objects and detect obstacles, evaluating the environmental conditions. The information obtained from the analysis is used to ensure the user's safety and is updated immediately as needed.

[0256] The analyzed information is converted into natural language acoustic signals by the server and transmitted back to the terminal via high-speed wireless communication technology. The terminal then provides the received information to the user in voice using speech synthesis technology, such as a text-to-speech engine. This allows the user to grasp important information about their surroundings in real time.

[0257] For example, if a visually impaired user is walking in an urban area, this system can provide voice guidance such as, "There is an intersection 100 meters ahead. The traffic light is red. Please stop."

[0258] An example of a prompt message is, "Generate voice guidance based on intersection location and signal information for a visually impaired user walking in an urban area." Based on this example, the generation AI model can appropriately generate the necessary guidance information.

[0259] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0260] Step 1:

[0261] The device acquires visual and location information of its surroundings. The camera and sensors on the device capture video data of the surroundings, and GPS obtains the current location information. The video data from the camera and the location data from GPS are used as input, and this becomes the initial input to the system.

[0262] Step 2:

[0263] The device sends the acquired data to the server. Video data and location information are sent to the server using high-speed wireless communication technology. The input is video data and location data acquired by the device, and the server receives this data as output.

[0264] Step 3:

[0265] The server analyzes the received data. The server uses a generative AI model to perform computer vision processing on the video data and identify objects and obstacles. The input consists of video data and location data received by the server, and after processing, analysis results regarding the user's surrounding environment are obtained.

[0266] Step 4:

[0267] The server generates natural language voice guidance based on the analysis results. Using natural language processing technology, it generates guidance information as text based on the analysis results. The input is analyzed surrounding environment data, and the output is natural language guidance text.

[0268] Step 5:

[0269] The server generates voice guidance text and sends it to the terminal. Using high-speed wireless communication technology, the generated guidance information is quickly sent back to the terminal. The input is the voice guidance text generated by the server, and the output is the completion of the transmission of the text data to the terminal.

[0270] Step 6:

[0271] The device receives text and transmits it to the user as audio. The device uses speech synthesis technology to convert text into speech and play it back to the user. The input is the audio guidance text received from the server, and the output is an audio notification to the user. This allows the user to receive real-time information about their surroundings via audio.

[0272] (Application Example 1)

[0273] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0274] This addresses the challenge of a lack of means to support safe and efficient movement for users who have difficulty acquiring visual information. In particular, when using autonomous vehicles, there is a need for technology that can accurately acquire information about the travel environment in real time and appropriately transmit it to the user.

[0275] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0276] In this invention, the server includes means for receiving ambient information from a video acquisition device and a location acquisition device that can be worn by the user; means for analyzing the received ambient information and using a generative AI model for determining the travel environment; and means for providing the user with travel guidance information via voice based on the determined situation. This enables users with limited visual information to safely understand their environment while traveling and to appropriately reach their destination using an autonomous vehicle.

[0277] The "user" refers to a person who wears this system and receives information provision.

[0278] The "video acquisition device" is a device worn by the user to collect surrounding visual information.

[0279] The "position acquisition device" is a device for identifying the current position of the user.

[0280] "Surrounding information" is a general term for visual and position-related data collected by the video acquisition device and the position acquisition device.

[0281] The "generated AI model" is an artificial intelligence model used to analyze the acquired surrounding information and distinguish the environment and situation.

[0282] "Guidance information regarding movement" is information including instructions and warnings for guiding safe and efficient movement considering the user's current movement environment.

[0283] The "mobile body" refers to a movable vehicle such as an autonomous driving vehicle equipped with this system.

[0284] The "cloud server" is a server device located remotely for analyzing the acquired information and operating the generated AI model.

[0285] The "high-speed wireless communication technology" is a technology for quickly communicating data in real time.

[0286] This invention is a system that supports users with difficulty in obtaining visual information to move independently. The system collects surrounding information from a video acquisition device and a position acquisition device that the user can wear. These information are transmitted from the terminal to the cloud server. A generated AI model is arranged in the server, and this AI model analyzes the received information and conducts a detailed analysis of the movement environment.

[0287] Specifically, in this system, the terminal acquires data in real time using hardware such as cameras and LIDAR sensors installed in the vehicle. This data is transmitted to a cloud server using high-speed wireless communication technology (e.g., 5G or Wi-Fi). The server performs object recognition and environmental analysis using software such as TensorFlow, and based on the results, a generated AI model generates voice guidance information using prompt sentences.

[0288] The generated voice guidance information is sent back to the terminal and provided to the user in real time by a speech synthesis engine such as Google Text-to-Speech. For example, when an autonomous vehicle is driving through a congested urban area, it is envisioned that the user will be provided with detailed and immediate voice guidance such as "We will be stopping at the intersection ahead" or "We have detected a group of pedestrians on the right."

[0289] Examples of prompt messages include, "Do you need to stop at the next traffic light?" and "There is an obstacle ahead, do you want to detour?" This allows users with limited visual information to effectively utilize autonomous vehicles and travel safely and efficiently.

[0290] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0291] Step 1:

[0292] The terminal acquires ambient environmental data in real time from cameras and LiDAR sensors installed in the vehicle. The input is raw data from the cameras and LiDAR sensors, and the output is obtained in the form of image data and distance information. The terminal stores this data in temporary storage and prepares it as input for the next step.

[0293] Step 2:

[0294] The terminal transmits acquired image data and distance information to a cloud server using high-speed wireless communication technology. The input is the image and distance information stored in the terminal's storage, and the output is the data structure sent to the server. The terminal uses a protocol to ensure stable data transfer.

[0295] Step 3:

[0296] The server analyzes the received data and performs object recognition and environmental analysis using a generated AI model with TensorFlow. The input consists of images and distance information sent from the terminal, and the output is environmental recognition data as a result of the analysis. Based on this data, the server understands the surrounding environment of a moving object and extracts risk and guidance information.

[0297] Step 4:

[0298] Based on the analysis results, the server uses a generative AI model to generate voice guidance information from prompt text. The input is environmental recognition data, and the output is text data of the voice guidance information. The server generates necessary warnings and instructions for the user and presents them as voice messages.

[0299] Step 5:

[0300] The server sends the generated voice guidance information back to the terminal, which receives it via high-speed wireless communication. The input is voice guidance information created by the generation AI model, and the output is stored as voice data on the terminal. The terminal manages the communication to receive the data stably and with low latency.

[0301] Step 6:

[0302] The device uses a text-to-speech engine, such as Google Text-to-Speech, to provide users with real-time voice guidance information. The input is text data of the voice guidance information, and the output is synthesized speech. Through this speech, users can receive guidance about their surroundings.

[0303] Furthermore, an emotion engine for estimating the user's emotion may be combined. That is, the specific processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform specific processing using the user's emotion.

[0304] The present invention is a system that enables a user with limited ability to acquire visual information to accurately grasp the surrounding situation and act safely and efficiently while considering the emotional state at that time. This system is centered around a device worn by the user, and a video acquisition device and a position acquisition device are integrated. The terminal transmits the video data and position information acquired in real time to the server.

[0305] The server receives this information and performs object recognition and obstacle detection in the environment using an artificial intelligence model. Also, based on this information, the emotion engine operates to analyze the user's emotional state. The emotion engine evaluates the user's stress level and sense of security by analyzing the tone and speed of the user's voice, and minute biological reactions.

[0306] Based on the analysis result, the server generates specific voice information in natural language and provides voice feedback to the user. This feedback is adjusted according to the user's emotional state. For example, when the user feels anxious, guidance with more detailed and reassuring content is provided. Also, when an urgent danger is detected, a warning sound is immediately emitted to alert the user.

[0307] As a specific example, when the user is walking on a busy street and uses this system, the terminal transmits the surrounding situation to the server in real time, and the server analyzes the environmental situation and the user's emotion. When the user is nervous, a voice such as "There are many people around, but there are no obstacles in the direction of travel." is gently provided to support safe movement while reducing the user's anxiety.

[0308] Thus, the present invention realizes a system that supports users with visual limitations, enabling them to act with emotional confidence, based on comprehensive environmental and emotional analysis.

[0309] The following describes the processing flow.

[0310] Step 1:

[0311] The terminal acquires real-time video data of the environment from a video acquisition device worn by the user.

[0312] Step 2:

[0313] The terminal obtains accurate current location information from the location acquisition device and transmits it to the server along with video data.

[0314] Step 3:

[0315] The server uses an artificial intelligence model based on the video data and location information received from the terminal to perform object recognition and obstacle detection in the surrounding area.

[0316] Step 4:

[0317] The server activates the emotion engine and analyzes the user's emotional state. It uses the user's voice tone and speed, as well as biometric responses, to assess levels of stress and comfort.

[0318] Step 5:

[0319] The server generates necessary audio information for the user in natural language based on the analyzed surrounding environment and emotional state. The feedback is customized to take the user's emotional state into consideration.

[0320] Step 6:

[0321] The server transmits the generated audio information to the terminal with low latency.

[0322] Step 7:

[0323] The terminal uses speech synthesis technology to convey voice information sent from the server to the user. The voice can be used as a warning sound or a message of encouragement, as needed.

[0324] Step 8:

[0325] Based on the provided voice feedback, the user makes decisions about their surroundings and moves safely.

[0326] (Example 2)

[0327] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0328] There is a need to provide a system that allows users with limitations in visual information acquisition to safely and efficiently understand their surroundings and act with confidence. In particular, a system is needed that can provide information while considering not only the recognition of surrounding objects but also the user's emotional state.

[0329] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0330] In this invention, the server includes means for receiving video data from a video acquisition device wearable by the user and location information from a location acquisition device; means for analyzing the received video data and location information and using an artificial intelligence algorithm to recognize surrounding objects and detect obstacles; and analysis means for analyzing the characteristics of the user's voice and understanding their emotional state. This makes it possible to provide appropriate voice guidance in real time so that the user can act with a sense of security.

[0331] "User" refers to the entity that wears the system and receives information.

[0332] A "video acquisition device" is a device used to record surrounding visual information as digital data.

[0333] A "location acquisition device" is a device used to acquire geographical location information.

[0334] "Reception" refers to the process by which the server acquires video data and location information.

[0335] "Analysis" refers to the act of processing acquired data and extracting specific information.

[0336] An "artificial intelligence algorithm" is a computational method that analyzes data to perform object recognition and situational judgment.

[0337] "Voice guidance" is a method of providing information to users through audio.

[0338] "Natural language generation" refers to the technology of creating natural-sounding language expressions based on analyzed data.

[0339] "Voice output means" refers to a mechanism for transmitting generated voice guidance to the user.

[0340] "Real-time" means that processing or communication takes place instantly.

[0341] "A sense of security" refers to a safe and comfortable emotional state provided to the user.

[0342] This system helps users with visual impairments to understand their surroundings and act with confidence. First, the user wears a dedicated device that integrates a video acquisition device and a location acquisition device. This device is equipped with a camera and a location detection module, which acquires video and location information as digital data.

[0343] The terminal receives this data in real time and transmits it to the server via the communication network. Digital communication technology is used for data transmission to ensure communication stability and security. Data is compressed during transmission to efficiently transfer it to the server.

[0344] The server receives the transmitted data and first uses artificial intelligence algorithms to recognize objects in the environment and detect obstacles. Object detection algorithms such as YOLO (You Only Look Once) are used in this process. It also receives user voice data and analyzes the tone and speed of the voice to understand the emotional state. For voice analysis, it is possible to use libraries and tools for voice processing.

[0345] Based on the analysis results, the server uses natural language generation technology to create voice guidance tailored to the user. The generated voice guidance is designed to be adjusted according to the user's emotional state and to provide reassuring content. This process utilizes a generative AI model and employs appropriate prompt sentences to deliver optimal feedback to the user.

[0346] As a concrete example, let's say a user uses this system while moving through a crowded city. The device sends video footage and location data to a server, which uses YOLO to detect and analyze pedestrians and obstacles. Furthermore, it uses emotion analysis to determine the user's level of anxiety and generates voice advice such as, "There are many people around, but you can proceed safely," which is then fed back to the user.

[0347] An example of a prompt message would be, "Generate voice guidance explaining the surrounding environment to a user with limited visual information." By giving detailed instructions to the generation AI model in this way, it is possible to provide highly accurate guidance.

[0348] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0349] Step 1:

[0350] The user wears a dedicated device to acquire surrounding video data and location information. The device is equipped with a camera and a location detection module; the camera captures video data, and the location detection module records location information. The input is surrounding visual information and location information, and the output is digitized video and location information.

[0351] Step 2:

[0352] The terminal receives video data and location information acquired from the user's device. This data is first compressed using digital compression technology to improve communication efficiency. The compressed data is then ready to be transmitted to the server via the communication network. The input is video and location information from the device, and the output is a compressed data package.

[0353] Step 3:

[0354] The server receives compressed data sent from the terminal and decompresses it. By processing the decompressed data, the server performs object recognition and obstacle detection in the environment. Artificial intelligence algorithms (e.g., object detection algorithms) are used here. The input is compressed video and location information, and the output is a list of objects and their location information.

[0355] Step 4:

[0356] The server receives user voice data and analyzes the tone and speed of the voice. This allows for the estimation of the user's emotional state. A voice processing library is used for the analysis, and stress levels and feelings of comfort are evaluated. The input is voice data, and the output is the emotion analysis result.

[0357] Step 5:

[0358] The server integrates the results of object recognition and sentiment analysis, and generates voice guidance using natural language generation technology. The generated voice guidance is adjusted to the user's emotional state. Here, the generation AI model creates feedback using prompt sentences and generates appropriate guidance. The input is the results of object recognition and sentiment analysis, and the output is the voice guidance provided to the user.

[0359] Step 6:

[0360] The terminal receives voice guidance generated from the server and outputs it to the user in real time. The voice is delivered to the user through headphones or other means, supporting safe movement. Through this process, users can obtain information to act with a sense of security. The input is voice guidance, and the output is voice feedback to the user.

[0361] (Application Example 2)

[0362] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0363] Conventional factory robots often lack sufficient environmental awareness and operational monitoring capabilities to enhance safety during work, and may be unable to adequately alert workers or provide advice on their movements. Furthermore, the lack of means to determine the efficiency of robot operation and make appropriate adjustments makes it difficult to improve productivity. It is necessary to address these challenges and realize a safe and efficient work environment.

[0364] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0365] This invention includes a server technology that receives image data from a wearable visual information acquisition device and location information from a location acquisition device; a technology that analyzes the received image data and location information and uses an intelligent model to determine the surrounding environment; a technology that monitors the robot's operation in the industrial field and prompts the worker with instructions and warnings via voice when errors or dangers are detected; and a technology that performs emotion analysis to evaluate the stress and load on the robot's operation and advises on efficient operation. This enables accurate understanding of the surrounding environment and real-time safe work instructions, as well as improved productivity through efficient robot operation.

[0366] A "visual information acquisition device that can be worn by users" is a device attached to a robot working in an industrial area to visually observe the surrounding environment.

[0367] An "intelligent model for analyzing image data and location information to determine the surrounding environment" is an artificial intelligence analysis method used by a robot to understand its surroundings from image data and location information acquired by the robot.

[0368] "Technology that allows robots to monitor their operation in an industrial setting and provide instructions and warnings to workers via voice when errors or hazards are detected" refers to technology in which robots monitor their own movements and surrounding conditions, and when problems or hazards are discovered, they prompt workers to take appropriate action.

[0369] "A technology that performs emotional analysis, evaluates the stress and load on robot movements, and advises on efficient movement" is a technology that analyzes the robot's movement state and proposes the optimal movement procedure to reduce stress and load.

[0370] "Technology that uses voice to provide instructions and warnings to workers" refers to a method of using voice output to communicate changes in the surrounding environment or dangerous conditions to workers.

[0371] To realize this invention, it is first necessary to equip the robot with a visual information acquisition device and a location information acquisition device. These devices acquire environmental information from the factory, and the obtained data is transmitted to a server in real time. The server uses an artificial intelligence model to recognize the environment in order to analyze the received image data and location information, and manages the robot's movements so that it can perform tasks safely and efficiently.

[0372] Specifically, the server utilizes cloud-based AI platforms such as Google Cloud AI and IBM Watson to perform object recognition and obstacle detection in the environment. Furthermore, it evaluates the stress and load generated during robot operation using an emotion analysis engine and optimizes its movements accordingly. This enables the robot to quickly communicate warnings and instructions to workers via voice.

[0373] For example, when a robot is handling multiple parts in a factory, if a worker passes nearby, the server will generate a prompt such as "There is a worker nearby. Please slow down," and safely control the robot. An example of such a prompt might be text like, "Generate optimal actions and precautions for the robot to work safely in the factory."

[0374] This system improves the precision of robot movements, enhances safety within the factory, and supports increased productivity.

[0375] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0376] Step 1:

[0377] The terminal uses a visual information acquisition device and a location information acquisition device attached to a robot to acquire image data and location information within the factory. The input is the acquired image data and location information, and the output is the transmission of data to a server. This data is transmitted to the server in real time via a Wi-Fi network.

[0378] Step 2:

[0379] Based on the image data and location information received by the server, it uses cloud AI services such as Google Cloud AI and IBM Watson to perform environmental discrimination using an intelligent model. The input is image data and location information sent from the terminal, and the output is information on recognized objects and detected obstacles. The server analyzes this data using the AI ​​model to understand the surrounding environment.

[0380] Step 3:

[0381] Based on the environmental analysis results, the server uses an emotion analysis engine to evaluate the stress and load associated with the robot's movements. The input for this step is the environmental analysis results, and the output is evaluation information regarding stress and load. The server uses this information to adjust the voice feedback.

[0382] Step 4:

[0383] Based on the processing results, the server uses a generative AI model to create specific voice instructions and warning prompts. The input is stress and load evaluation information, and the output is voice prompts. The server generates these prompts to output appropriate instructions via voice, taking safety and efficiency into consideration.

[0384] Step 5:

[0385] The terminal transmits generated voice prompts to the robot, which then issues voice warnings and instructions to nearby workers. The input is the generated prompt text, and the output is voice instructions and warnings. The terminal uses a Bluetooth speaker or similar device to emit voice and manage its actions.

[0386] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0387] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet Search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0388] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0389] [Third Embodiment]

[0390] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0391] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0392] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0393] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0394] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0395] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0396] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0397] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0398] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0399] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0400] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0401] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0402] This invention is a system centered around a wearable device that enables users with limited visual information acquisition to act independently. In this system, the terminal acquires video data of the user's surrounding environment in real time and transmits this data, along with location information from a location acquisition device, to a server. After receiving the data, the server analyzes the environment using an artificial intelligence model.

[0403] The analysis extracts the user's current location, risk factors in their environment, and guidance information, which the server then generates as natural language audio. This generated audio is transmitted back to the terminal with low latency, and the terminal provides this information to the user using speech synthesis technology. High-speed wireless communication technology is used throughout this process to ensure real-time information transmission.

[0404] As a concrete example, when a user uses this system while walking in an urban area, the video data and location information acquired by the terminal are transmitted to a server, and the system analyzes the surrounding pedestrians, bicycles, vehicles, and traffic light status. The system then provides the user with specific voice guidance such as, "There is an intersection 10 meters ahead. The traffic light is red. Please stop for your safety." In this way, the present invention realizes a system that helps users with visual impairments to reach their destination safely and effectively.

[0405] The following describes the processing flow.

[0406] Step 1:

[0407] The terminal acquires video data in real time from the attached video acquisition device.

[0408] Step 2:

[0409] The device obtains its current precise location information from a location acquisition device.

[0410] Step 3:

[0411] The device transmits the acquired video data and location information to the server using 5G communication.

[0412] Step 4:

[0413] The server receives and stores the data sent from the terminal.

[0414] Step 5:

[0415] The server inputs the received data into an artificial intelligence model to perform object recognition, obstacle detection, and traffic light status analysis of the environment.

[0416] Step 6:

[0417] The server translates the information that should be provided to the user into natural language based on the analysis results.

[0418] Step 7:

[0419] The server sends the generated natural language audio information to the terminal.

[0420] Step 8:

[0421] The terminal uses speech synthesis technology to transmit audio information received from the server to the user.

[0422] Step 9:

[0423] Users determine safe course of action based on the provided audio information.

[0424] (Example 1)

[0425] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0426] The challenge lies in realizing support systems that enable users with limited visual information acquisition to act safely and independently. In particular, there is a need to acquire information about the surrounding environment in real time and effectively communicate it to the user.

[0427] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0428] In this invention, the server includes means for receiving visual information data and location information from an information acquisition device wearable by the user; means for analyzing the received visual information data and location information and using a machine learning model to evaluate the surrounding environment; and means for transmitting important information about the surrounding environment to the user via an acoustic signal based on the analyzed information. This enables users whose ability to acquire visual information is limited to understand their surroundings in real time and act safely.

[0429] A "user-wearable information acquisition device" is a device that can be used by a user by being worn on their body, and which collects visual information and location information.

[0430] "Visual information data" refers to image or video data acquired from the surrounding environment using cameras or sensors.

[0431] "Location information" refers to information that indicates a user's current geographical location, obtained using global positioning systems and other location-based technologies.

[0432] "Means of receiving" refers to the functions and technologies that a server uses to acquire data and information transmitted from an external source.

[0433] "Machine learning models for analysis and evaluation of the surrounding environment" refers to machine learning algorithms and technologies used to analyze received data and understand the surrounding situation through object recognition and obstacle detection.

[0434] "Means of transmission via acoustic signals" means a technology or method for converting analyzed information into sound and transmitting it to the user.

[0435] "High-speed wireless communication technology" refers to mobile communication technology that enables the rapid transmission and reception of large amounts of data with low latency.

[0436] "Speech synthesis technology" is a technology that converts text information into speech and plays it back as natural-sounding utterances.

[0437] This system is designed to support users with limited visual information access, enabling them to act independently. The system primarily consists of wearable information acquisition devices, a server, and a terminal.

[0438] The device is equipped with hardware such as a camera, sensors, and GPS, which acquire visual and location information in real time. The device then rapidly transfers the acquired data to a server using a high-performance communication module (e.g., 5G communication).

[0439] The server analyzes the received visual and location data. This uses a generative AI model as a machine learning model. The generative AI model leverages computer vision technology to recognize surrounding objects and detect obstacles, evaluating the environmental conditions. The information obtained from the analysis is used to ensure the user's safety and is updated immediately as needed.

[0440] The analyzed information is converted into natural language acoustic signals by the server and transmitted back to the terminal via high-speed wireless communication technology. The terminal then provides the received information to the user in voice using speech synthesis technology, such as a text-to-speech engine. This allows the user to grasp important information about their surroundings in real time.

[0441] For example, if a visually impaired user is walking in an urban area, this system can provide voice guidance such as, "There is an intersection 100 meters ahead. The traffic light is red. Please stop."

[0442] An example of a prompt message is, "Generate voice guidance based on intersection location and signal information for a visually impaired user walking in an urban area." Based on this example, the generation AI model can appropriately generate the necessary guidance information.

[0443] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0444] Step 1:

[0445] The device acquires visual and location information of its surroundings. The camera and sensors on the device capture video data of the surroundings, and GPS obtains the current location information. The video data from the camera and the location data from GPS are used as input, and this becomes the initial input to the system.

[0446] Step 2:

[0447] The device sends the acquired data to the server. Video data and location information are sent to the server using high-speed wireless communication technology. The input is video data and location data acquired by the device, and the server receives this data as output.

[0448] Step 3:

[0449] The server analyzes the received data. The server uses a generative AI model to perform computer vision processing on the video data and identify objects and obstacles. The input consists of video data and location data received by the server, and after processing, analysis results regarding the user's surrounding environment are obtained.

[0450] Step 4:

[0451] The server generates natural language voice guidance based on the analysis results. Using natural language processing technology, it generates guidance information as text based on the analysis results. The input is analyzed surrounding environment data, and the output is natural language guidance text.

[0452] Step 5:

[0453] The server generates voice guidance text and sends it to the terminal. Using high-speed wireless communication technology, the generated guidance information is quickly sent back to the terminal. The input is the voice guidance text generated by the server, and the output is the completion of the transmission of the text data to the terminal.

[0454] Step 6:

[0455] The device receives text and transmits it to the user as audio. The device uses speech synthesis technology to convert text into speech and play it back to the user. The input is the audio guidance text received from the server, and the output is an audio notification to the user. This allows the user to receive real-time information about their surroundings via audio.

[0456] (Application Example 1)

[0457] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0458] This addresses the challenge of a lack of means to support safe and efficient movement for users who have difficulty acquiring visual information. In particular, when using autonomous vehicles, there is a need for technology that can accurately acquire information about the travel environment in real time and appropriately transmit it to the user.

[0459] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0460] In this invention, the server includes means for receiving ambient information from a video acquisition device and a location acquisition device that can be worn by the user; means for analyzing the received ambient information and using a generative AI model for determining the travel environment; and means for providing the user with travel guidance information via voice based on the determined situation. This enables users with limited visual information to safely understand their environment while traveling and to appropriately reach their destination using an autonomous vehicle.

[0461] A "user" is a person who wears this system and receives information from it.

[0462] A "video acquisition device" is a device worn by a user to collect visual information about their surroundings.

[0463] A "location acquisition device" is a device used to determine the user's current location.

[0464] "Surrounding information" is a general term for visual and positional data collected by image acquisition devices and position acquisition devices.

[0465] A "generative AI model" is an artificial intelligence model used to analyze acquired surrounding information and determine the environment and situation.

[0466] "Travel guidance information" refers to information that takes into account the user's current travel environment and includes instructions and warnings to guide them toward safe and efficient travel.

[0467] "Mobile object" refers to a mobile vehicle, such as an autonomous vehicle, on which this system is installed.

[0468] A "cloud server" is a remote server device that analyzes acquired information and allows the generated AI model to operate.

[0469] "High-speed wireless communication technology" refers to technology for transmitting data quickly in real time.

[0470] This invention is a system that assists users who have difficulty acquiring visual information in moving independently. The system collects information about the surroundings from an image acquisition device and a position acquisition device that can be worn by the user. This information is transmitted from the terminal to a cloud server. A generating AI model is deployed on the server, and this AI model analyzes the received information and performs a detailed analysis of the movement environment.

[0471] Specifically, in this system, the terminal acquires data in real time using hardware such as cameras and LIDAR sensors installed in the vehicle. This data is transmitted to a cloud server using high-speed wireless communication technology (e.g., 5G or Wi-Fi). The server performs object recognition and environmental analysis using software such as TensorFlow, and based on the results, a generated AI model generates voice guidance information using prompt sentences.

[0472] The generated voice guidance information is sent back to the terminal and provided to the user in real time by a speech synthesis engine such as Google Text-to-Speech. For example, when an autonomous vehicle is driving through a congested urban area, it is envisioned that the user will be provided with detailed and immediate voice guidance such as "We will be stopping at the intersection ahead" or "We have detected a group of pedestrians on the right."

[0473] Examples of prompt messages include, "Do you need to stop at the next traffic light?" and "There is an obstacle ahead, do you want to detour?" This allows users with limited visual information to effectively utilize autonomous vehicles and travel safely and efficiently.

[0474] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0475] Step 1:

[0476] The terminal acquires ambient environmental data in real time from cameras and LiDAR sensors installed in the vehicle. The input is raw data from the cameras and LiDAR sensors, and the output is obtained in the form of image data and distance information. The terminal stores this data in temporary storage and prepares it as input for the next step.

[0477] Step 2:

[0478] The terminal transmits acquired image data and distance information to a cloud server using high-speed wireless communication technology. The input is the image and distance information stored in the terminal's storage, and the output is the data structure sent to the server. The terminal uses a protocol to ensure stable data transfer.

[0479] Step 3:

[0480] The server analyzes the received data and performs object recognition and environmental analysis using a generated AI model with TensorFlow. The input consists of images and distance information sent from the terminal, and the output is environmental recognition data as a result of the analysis. Based on this data, the server understands the surrounding environment of a moving object and extracts risk and guidance information.

[0481] Step 4:

[0482] Based on the analysis results, the server uses a generative AI model to generate voice guidance information from prompt text. The input is environmental recognition data, and the output is text data of the voice guidance information. The server generates necessary warnings and instructions for the user and presents them as voice messages.

[0483] Step 5:

[0484] The server sends the generated voice guidance information back to the terminal, which receives it via high-speed wireless communication. The input is voice guidance information created by the generation AI model, and the output is stored as voice data on the terminal. The terminal manages the communication to receive the data stably and with low latency.

[0485] Step 6:

[0486] The device uses a text-to-speech engine, such as Google Text-to-Speech, to provide users with real-time voice guidance information. The input is text data of the voice guidance information, and the output is synthesized speech. Through this speech, users can receive guidance about their surroundings.

[0487] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0488] This invention provides a system that enables users with limitations in acquiring visual information to accurately perceive their surroundings and act safely and efficiently, taking into account their emotional state at the time. The system centers around a device worn by the user, integrating a video acquisition device and a location acquisition device. The device transmits real-time acquired video data and location information to a server.

[0489] The server receives this information and uses an artificial intelligence model to recognize objects in the environment and detect obstacles. Based on this information, the emotion engine activates and analyzes the user's emotional state. The emotion engine evaluates the user's stress level and sense of security by analyzing the tone and speed of the user's voice, as well as subtle biological responses.

[0490] Based on the analysis results, the server generates specific voice information in natural language and provides voice feedback to the user. This feedback is adjusted according to the user's emotional state. For example, if the user is feeling anxious, more detailed and reassuring guidance will be provided. Also, if sudden danger is detected, an immediate warning sound will be emitted to alert the user.

[0491] As a concrete example, when a user is walking through a busy area, this system allows the device to transmit information about the surroundings to the server in real time. The server then analyzes the environmental conditions and the user's emotions. If the user is feeling anxious, the system calmly provides voice messages such as, "There are many people around, but there are no obstacles in your path," to alleviate the user's anxiety and support safe movement.

[0492] Thus, the present invention realizes a system that supports users with visual limitations, enabling them to act with emotional confidence, based on comprehensive environmental and emotional analysis.

[0493] The following describes the processing flow.

[0494] Step 1:

[0495] The terminal acquires real-time video data of the environment from a video acquisition device worn by the user.

[0496] Step 2:

[0497] The terminal obtains accurate current location information from the location acquisition device and transmits it to the server along with video data.

[0498] Step 3:

[0499] The server uses an artificial intelligence model based on the video data and location information received from the terminal to perform object recognition and obstacle detection in the surrounding area.

[0500] Step 4:

[0501] The server activates the emotion engine and analyzes the user's emotional state. It uses the user's voice tone and speed, as well as biometric responses, to assess levels of stress and comfort.

[0502] Step 5:

[0503] The server generates necessary audio information for the user in natural language based on the analyzed surrounding environment and emotional state. The feedback is customized to take the user's emotional state into consideration.

[0504] Step 6:

[0505] The server transmits the generated audio information to the terminal with low latency.

[0506] Step 7:

[0507] The terminal uses speech synthesis technology to convey voice information sent from the server to the user. The voice can be used as a warning sound or a message of encouragement, as needed.

[0508] Step 8:

[0509] Based on the provided voice feedback, the user makes decisions about their surroundings and moves safely.

[0510] (Example 2)

[0511] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0512] There is a need to provide a system that allows users with limitations in visual information acquisition to safely and efficiently understand their surroundings and act with confidence. In particular, a system is needed that can provide information while considering not only the recognition of surrounding objects but also the user's emotional state.

[0513] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0514] In this invention, the server includes means for receiving video data from a video acquisition device wearable by the user and location information from a location acquisition device; means for analyzing the received video data and location information and using an artificial intelligence algorithm to recognize surrounding objects and detect obstacles; and analysis means for analyzing the characteristics of the user's voice and understanding their emotional state. This makes it possible to provide appropriate voice guidance in real time so that the user can act with a sense of security.

[0515] "User" refers to the entity that wears the system and receives information.

[0516] A "video acquisition device" is a device used to record surrounding visual information as digital data.

[0517] A "location acquisition device" is a device used to acquire geographical location information.

[0518] "Reception" refers to the process by which the server acquires video data and location information.

[0519] "Analysis" refers to the act of processing acquired data and extracting specific information.

[0520] An "artificial intelligence algorithm" is a computational method that analyzes data to perform object recognition and situational judgment.

[0521] "Voice guidance" is a method of providing information to users through audio.

[0522] "Natural language generation" refers to the technology of creating natural-sounding language expressions based on analyzed data.

[0523] "Voice output means" refers to a mechanism for transmitting generated voice guidance to the user.

[0524] "Real-time" means that processing or communication takes place instantly.

[0525] "A sense of security" refers to a safe and comfortable emotional state provided to the user.

[0526] This system helps users with visual impairments to understand their surroundings and act with confidence. First, the user wears a dedicated device that integrates a video acquisition device and a location acquisition device. This device is equipped with a camera and a location detection module, which acquires video and location information as digital data.

[0527] The terminal receives this data in real time and transmits it to the server via the communication network. Digital communication technology is used for data transmission to ensure communication stability and security. Data is compressed during transmission to efficiently transfer it to the server.

[0528] The server receives the transmitted data and first uses artificial intelligence algorithms to recognize objects in the environment and detect obstacles. Object detection algorithms such as YOLO (You Only Look Once) are used in this process. It also receives user voice data and analyzes the tone and speed of the voice to understand the emotional state. For voice analysis, it is possible to use libraries and tools for voice processing.

[0529] Based on the analysis results, the server uses natural language generation technology to create voice guidance tailored to the user. The generated voice guidance is designed to be adjusted according to the user's emotional state and to provide reassuring content. This process utilizes a generative AI model and employs appropriate prompt sentences to deliver optimal feedback to the user.

[0530] As a concrete example, let's say a user uses this system while moving through a crowded city. The device sends video footage and location data to a server, which uses YOLO to detect and analyze pedestrians and obstacles. Furthermore, it uses emotion analysis to determine the user's level of anxiety and generates voice advice such as, "There are many people around, but you can proceed safely," which is then fed back to the user.

[0531] An example of a prompt message would be, "Generate voice guidance explaining the surrounding environment to a user with limited visual information." By giving detailed instructions to the generation AI model in this way, it is possible to provide highly accurate guidance.

[0532] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0533] Step 1:

[0534] The user wears a dedicated device to acquire surrounding video data and location information. The device is equipped with a camera and a location detection module; the camera captures video data, and the location detection module records location information. The input is surrounding visual information and location information, and the output is digitized video and location information.

[0535] Step 2:

[0536] The terminal receives video data and location information acquired from the user's device. This data is first compressed using digital compression technology to improve communication efficiency. The compressed data is then ready to be transmitted to the server via the communication network. The input is video and location information from the device, and the output is a compressed data package.

[0537] Step 3:

[0538] The server receives compressed data sent from the terminal and decompresses it. By processing the decompressed data, the server performs object recognition and obstacle detection in the environment. Artificial intelligence algorithms (e.g., object detection algorithms) are used here. The input is compressed video and location information, and the output is a list of objects and their location information.

[0539] Step 4:

[0540] The server receives user voice data and analyzes the tone and speed of the voice. This allows for the estimation of the user's emotional state. A voice processing library is used for the analysis, and stress levels and feelings of comfort are evaluated. The input is voice data, and the output is the emotion analysis result.

[0541] Step 5:

[0542] The server integrates the results of object recognition and sentiment analysis, and generates voice guidance using natural language generation technology. The generated voice guidance is adjusted to the user's emotional state. Here, the generation AI model creates feedback using prompt sentences and generates appropriate guidance. The input is the results of object recognition and sentiment analysis, and the output is the voice guidance provided to the user.

[0543] Step 6:

[0544] The terminal receives voice guidance generated from the server and outputs it to the user in real time. The voice is delivered to the user through headphones or other means, supporting safe movement. Through this process, users can obtain information to act with a sense of security. The input is voice guidance, and the output is voice feedback to the user.

[0545] (Application Example 2)

[0546] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0547] Conventional factory robots often lack sufficient environmental awareness and operational monitoring capabilities to enhance safety during work, and may be unable to adequately alert workers or provide advice on their movements. Furthermore, the lack of means to determine the efficiency of robot operation and make appropriate adjustments makes it difficult to improve productivity. It is necessary to address these challenges and realize a safe and efficient work environment.

[0548] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0549] This invention includes a server technology that receives image data from a wearable visual information acquisition device and location information from a location acquisition device; a technology that analyzes the received image data and location information and uses an intelligent model to determine the surrounding environment; a technology that monitors the robot's operation in the industrial field and prompts the worker with instructions and warnings via voice when errors or dangers are detected; and a technology that performs emotion analysis to evaluate the stress and load on the robot's operation and advises on efficient operation. This enables accurate understanding of the surrounding environment and real-time safe work instructions, as well as improved productivity through efficient robot operation.

[0550] A "visual information acquisition device that can be worn by users" is a device attached to a robot working in an industrial area to visually observe the surrounding environment.

[0551] An "intelligent model for analyzing image data and location information to determine the surrounding environment" is an artificial intelligence analysis method used by a robot to understand its surroundings from image data and location information acquired by the robot.

[0552] "Technology that allows robots to monitor their operation in an industrial setting and provide instructions and warnings to workers via voice when errors or hazards are detected" refers to technology in which robots monitor their own movements and surrounding conditions, and when problems or hazards are discovered, they prompt workers to take appropriate action.

[0553] "A technology that performs emotional analysis, evaluates the stress and load on robot movements, and advises on efficient movement" is a technology that analyzes the robot's movement state and proposes the optimal movement procedure to reduce stress and load.

[0554] "Technology that uses voice to provide instructions and warnings to workers" refers to a method of using voice output to communicate changes in the surrounding environment or dangerous conditions to workers.

[0555] To realize this invention, it is first necessary to equip the robot with a visual information acquisition device and a location information acquisition device. These devices acquire environmental information from the factory, and the obtained data is transmitted to a server in real time. The server uses an artificial intelligence model to recognize the environment in order to analyze the received image data and location information, and manages the robot's movements so that it can perform tasks safely and efficiently.

[0556] Specifically, the server utilizes cloud-based AI platforms such as Google Cloud AI and IBM Watson to perform object recognition and obstacle detection in the environment. Furthermore, it evaluates the stress and load generated during robot operation using an emotion analysis engine and optimizes its movements accordingly. This enables the robot to quickly communicate warnings and instructions to workers via voice.

[0557] For example, when a robot is handling multiple parts in a factory, if a worker passes nearby, the server will generate a prompt such as "There is a worker nearby. Please slow down," and safely control the robot. An example of such a prompt might be text like, "Generate optimal actions and precautions for the robot to work safely in the factory."

[0558] This system improves the precision of robot movements, enhances safety within the factory, and supports increased productivity.

[0559] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0560] Step 1:

[0561] The terminal uses a visual information acquisition device and a location information acquisition device attached to a robot to acquire image data and location information within the factory. The input is the acquired image data and location information, and the output is the transmission of data to a server. This data is transmitted to the server in real time via a Wi-Fi network.

[0562] Step 2:

[0563] Based on the image data and location information received by the server, it uses cloud AI services such as Google Cloud AI and IBM Watson to perform environmental discrimination using an intelligent model. The input is image data and location information sent from the terminal, and the output is information on recognized objects and detected obstacles. The server analyzes this data using the AI ​​model to understand the surrounding environment.

[0564] Step 3:

[0565] Based on the environmental analysis results, the server uses an emotion analysis engine to evaluate the stress and load associated with the robot's movements. The input for this step is the environmental analysis results, and the output is evaluation information regarding stress and load. The server uses this information to adjust the voice feedback.

[0566] Step 4:

[0567] Based on the processing results, the server uses a generative AI model to create specific voice instructions and warning prompts. The input is stress and load evaluation information, and the output is voice prompts. The server generates these prompts to output appropriate instructions via voice, taking safety and efficiency into consideration.

[0568] Step 5:

[0569] The terminal transmits generated voice prompts to the robot, which then issues voice warnings and instructions to nearby workers. The input is the generated prompt text, and the output is voice instructions and warnings. The terminal uses a Bluetooth speaker or similar device to emit voice and manage its actions.

[0570] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0571] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet Search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0572] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0573] [Fourth Embodiment]

[0574] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0575] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0576] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0577] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0578] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0579] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0580] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0581] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0582] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0583] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0584] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0585] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0586] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0587] This invention is a system centered around a wearable device that enables users with limited visual information acquisition to act independently. In this system, the terminal acquires video data of the user's surrounding environment in real time and transmits this data, along with location information from a location acquisition device, to a server. After receiving the data, the server analyzes the environment using an artificial intelligence model.

[0588] The analysis extracts the user's current location, risk factors in their environment, and guidance information, which the server then generates as natural language audio. This generated audio is transmitted back to the terminal with low latency, and the terminal provides this information to the user using speech synthesis technology. High-speed wireless communication technology is used throughout this process to ensure real-time information transmission.

[0589] As a concrete example, when a user uses this system while walking in an urban area, the video data and location information acquired by the terminal are transmitted to a server, and the system analyzes the surrounding pedestrians, bicycles, vehicles, and traffic light status. The system then provides the user with specific voice guidance such as, "There is an intersection 10 meters ahead. The traffic light is red. Please stop for your safety." In this way, the present invention realizes a system that helps users with visual impairments to reach their destination safely and effectively.

[0590] The following describes the processing flow.

[0591] Step 1:

[0592] The terminal acquires video data in real time from the attached video acquisition device.

[0593] Step 2:

[0594] The device obtains its current precise location information from a location acquisition device.

[0595] Step 3:

[0596] The device transmits the acquired video data and location information to the server using 5G communication.

[0597] Step 4:

[0598] The server receives and stores the data sent from the terminal.

[0599] Step 5:

[0600] The server inputs the received data into an artificial intelligence model to perform object recognition, obstacle detection, and traffic light status analysis of the environment.

[0601] Step 6:

[0602] The server translates the information that should be provided to the user into natural language based on the analysis results.

[0603] Step 7:

[0604] The server sends the generated natural language audio information to the terminal.

[0605] Step 8:

[0606] The terminal uses speech synthesis technology to transmit audio information received from the server to the user.

[0607] Step 9:

[0608] Users determine safe course of action based on the provided audio information.

[0609] (Example 1)

[0610] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0611] The challenge lies in realizing support systems that enable users with limited visual information acquisition to act safely and independently. In particular, there is a need to acquire information about the surrounding environment in real time and effectively communicate it to the user.

[0612] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0613] In this invention, the server includes means for receiving visual information data and location information from an information acquisition device wearable by the user; means for analyzing the received visual information data and location information and using a machine learning model to evaluate the surrounding environment; and means for transmitting important information about the surrounding environment to the user via an acoustic signal based on the analyzed information. This enables users whose ability to acquire visual information is limited to understand their surroundings in real time and act safely.

[0614] A "user-wearable information acquisition device" is a device that can be used by a user by being worn on their body, and which collects visual information and location information.

[0615] "Visual information data" refers to image or video data acquired from the surrounding environment using cameras or sensors.

[0616] "Location information" refers to information that indicates a user's current geographical location, obtained using global positioning systems and other location-based technologies.

[0617] "Means of receiving" refers to the functions and technologies that a server uses to acquire data and information transmitted from an external source.

[0618] "Machine learning models for analysis and evaluation of the surrounding environment" refers to machine learning algorithms and technologies used to analyze received data and understand the surrounding situation through object recognition and obstacle detection.

[0619] "Means of transmission via acoustic signals" means a technology or method for converting analyzed information into sound and transmitting it to the user.

[0620] "High-speed wireless communication technology" refers to mobile communication technology that enables the rapid transmission and reception of large amounts of data with low latency.

[0621] "Speech synthesis technology" is a technology that converts text information into speech and plays it back as natural-sounding utterances.

[0622] This system is designed to support users with limited visual information access, enabling them to act independently. The system primarily consists of wearable information acquisition devices, a server, and a terminal.

[0623] The device is equipped with hardware such as a camera, sensors, and GPS, which acquire visual and location information in real time. The device then rapidly transfers the acquired data to a server using a high-performance communication module (e.g., 5G communication).

[0624] The server analyzes the received visual and location data. This uses a generative AI model as a machine learning model. The generative AI model leverages computer vision technology to recognize surrounding objects and detect obstacles, evaluating the environmental conditions. The information obtained from the analysis is used to ensure the user's safety and is updated immediately as needed.

[0625] The analyzed information is converted into natural language acoustic signals by the server and transmitted back to the terminal via high-speed wireless communication technology. The terminal then provides the received information to the user in voice using speech synthesis technology, such as a text-to-speech engine. This allows the user to grasp important information about their surroundings in real time.

[0626] For example, if a visually impaired user is walking in an urban area, this system can provide voice guidance such as, "There is an intersection 100 meters ahead. The traffic light is red. Please stop."

[0627] An example of a prompt message is, "Generate voice guidance based on intersection location and signal information for a visually impaired user walking in an urban area." Based on this example, the generation AI model can appropriately generate the necessary guidance information.

[0628] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0629] Step 1:

[0630] The device acquires visual and location information of its surroundings. The camera and sensors on the device capture video data of the surroundings, and GPS obtains the current location information. The video data from the camera and the location data from GPS are used as input, and this becomes the initial input to the system.

[0631] Step 2:

[0632] The device sends the acquired data to the server. Video data and location information are sent to the server using high-speed wireless communication technology. The input is video data and location data acquired by the device, and the server receives this data as output.

[0633] Step 3:

[0634] The server analyzes the received data. The server uses a generative AI model to perform computer vision processing on the video data and identify objects and obstacles. The input consists of video data and location data received by the server, and after processing, analysis results regarding the user's surrounding environment are obtained.

[0635] Step 4:

[0636] The server generates natural language voice guidance based on the analysis results. Using natural language processing technology, it generates guidance information as text based on the analysis results. The input is analyzed surrounding environment data, and the output is natural language guidance text.

[0637] Step 5:

[0638] The server generates voice guidance text and sends it to the terminal. Using high-speed wireless communication technology, the generated guidance information is quickly sent back to the terminal. The input is the voice guidance text generated by the server, and the output is the completion of the transmission of the text data to the terminal.

[0639] Step 6:

[0640] The device receives text and transmits it to the user as audio. The device uses speech synthesis technology to convert text into speech and play it back to the user. The input is the audio guidance text received from the server, and the output is an audio notification to the user. This allows the user to receive real-time information about their surroundings via audio.

[0641] (Application Example 1)

[0642] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0643] This addresses the challenge of a lack of means to support safe and efficient movement for users who have difficulty acquiring visual information. In particular, when using autonomous vehicles, there is a need for technology that can accurately acquire information about the travel environment in real time and appropriately transmit it to the user.

[0644] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0645] In this invention, the server includes means for receiving ambient information from a video acquisition device and a location acquisition device that can be worn by the user; means for analyzing the received ambient information and using a generative AI model for determining the travel environment; and means for providing the user with travel guidance information via voice based on the determined situation. This enables users with limited visual information to safely understand their environment while traveling and to appropriately reach their destination using an autonomous vehicle.

[0646] A "user" is a person who wears this system and receives information from it.

[0647] A "video acquisition device" is a device worn by a user to collect visual information about their surroundings.

[0648] A "location acquisition device" is a device used to determine the user's current location.

[0649] "Surrounding information" is a general term for visual and positional data collected by image acquisition devices and position acquisition devices.

[0650] A "generative AI model" is an artificial intelligence model used to analyze acquired surrounding information and determine the environment and situation.

[0651] "Travel guidance information" refers to information that takes into account the user's current travel environment and includes instructions and warnings to guide them toward safe and efficient travel.

[0652] "Mobile object" refers to a mobile vehicle, such as an autonomous vehicle, on which this system is installed.

[0653] A "cloud server" is a remote server device that analyzes acquired information and allows the generated AI model to operate.

[0654] "High-speed wireless communication technology" refers to technology for transmitting data quickly in real time.

[0655] This invention is a system that assists users who have difficulty acquiring visual information in moving independently. The system collects information about the surroundings from an image acquisition device and a position acquisition device that can be worn by the user. This information is transmitted from the terminal to a cloud server. A generating AI model is deployed on the server, and this AI model analyzes the received information and performs a detailed analysis of the movement environment.

[0656] Specifically, in this system, the terminal acquires data in real time using hardware such as cameras and LIDAR sensors installed in the vehicle. This data is transmitted to a cloud server using high-speed wireless communication technology (e.g., 5G or Wi-Fi). The server performs object recognition and environmental analysis using software such as TensorFlow, and based on the results, a generated AI model generates voice guidance information using prompt sentences.

[0657] The generated voice guidance information is sent back to the terminal and provided to the user in real time by a speech synthesis engine such as Google Text-to-Speech. For example, when an autonomous vehicle is driving through a congested urban area, it is envisioned that the user will be provided with detailed and immediate voice guidance such as "We will be stopping at the intersection ahead" or "We have detected a group of pedestrians on the right."

[0658] Examples of prompt messages include, "Do you need to stop at the next traffic light?" and "There is an obstacle ahead, do you want to detour?" This allows users with limited visual information to effectively utilize autonomous vehicles and travel safely and efficiently.

[0659] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0660] Step 1:

[0661] The terminal acquires ambient environmental data in real time from cameras and LiDAR sensors installed in the vehicle. The input is raw data from the cameras and LiDAR sensors, and the output is obtained in the form of image data and distance information. The terminal stores this data in temporary storage and prepares it as input for the next step.

[0662] Step 2:

[0663] The terminal transmits acquired image data and distance information to a cloud server using high-speed wireless communication technology. The input is the image and distance information stored in the terminal's storage, and the output is the data structure sent to the server. The terminal uses a protocol to ensure stable data transfer.

[0664] Step 3:

[0665] The server analyzes the received data and performs object recognition and environmental analysis using a generated AI model with TensorFlow. The input consists of images and distance information sent from the terminal, and the output is environmental recognition data as a result of the analysis. Based on this data, the server understands the surrounding environment of a moving object and extracts risk and guidance information.

[0666] Step 4:

[0667] Based on the analysis results, the server uses a generative AI model to generate voice guidance information from prompt text. The input is environmental recognition data, and the output is text data of the voice guidance information. The server generates necessary warnings and instructions for the user and presents them as voice messages.

[0668] Step 5:

[0669] The server sends the generated voice guidance information back to the terminal, which receives it via high-speed wireless communication. The input is voice guidance information created by the generation AI model, and the output is stored as voice data on the terminal. The terminal manages the communication to receive the data stably and with low latency.

[0670] Step 6:

[0671] The device uses a text-to-speech engine, such as Google Text-to-Speech, to provide users with real-time voice guidance information. The input is text data of the voice guidance information, and the output is synthesized speech. Through this speech, users can receive guidance about their surroundings.

[0672] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0673] This invention provides a system that enables users with limitations in acquiring visual information to accurately perceive their surroundings and act safely and efficiently, taking into account their emotional state at the time. The system centers around a device worn by the user, integrating a video acquisition device and a location acquisition device. The device transmits real-time acquired video data and location information to a server.

[0674] The server receives this information and uses an artificial intelligence model to recognize objects in the environment and detect obstacles. Based on this information, the emotion engine activates and analyzes the user's emotional state. The emotion engine evaluates the user's stress level and sense of security by analyzing the tone and speed of the user's voice, as well as subtle biological responses.

[0675] Based on the analysis results, the server generates specific voice information in natural language and provides voice feedback to the user. This feedback is adjusted according to the user's emotional state. For example, if the user is feeling anxious, more detailed and reassuring guidance will be provided. Also, if sudden danger is detected, an immediate warning sound will be emitted to alert the user.

[0676] As a concrete example, when a user is walking through a busy area, this system allows the device to transmit information about the surroundings to the server in real time. The server then analyzes the environmental conditions and the user's emotions. If the user is feeling anxious, the system calmly provides voice messages such as, "There are many people around, but there are no obstacles in your path," to alleviate the user's anxiety and support safe movement.

[0677] Thus, the present invention realizes a system that supports users with visual limitations, enabling them to act with emotional confidence, based on comprehensive environmental and emotional analysis.

[0678] The following describes the processing flow.

[0679] Step 1:

[0680] The terminal acquires real-time video data of the environment from a video acquisition device worn by the user.

[0681] Step 2:

[0682] The terminal obtains accurate current location information from the location acquisition device and transmits it to the server along with video data.

[0683] Step 3:

[0684] The server uses an artificial intelligence model based on the video data and location information received from the terminal to perform object recognition and obstacle detection in the surrounding area.

[0685] Step 4:

[0686] The server activates the emotion engine and analyzes the user's emotional state. It uses the user's voice tone and speed, as well as biometric responses, to assess levels of stress and comfort.

[0687] Step 5:

[0688] The server generates necessary audio information for the user in natural language based on the analyzed surrounding environment and emotional state. The feedback is customized to take the user's emotional state into consideration.

[0689] Step 6:

[0690] The server transmits the generated audio information to the terminal with low latency.

[0691] Step 7:

[0692] The terminal uses speech synthesis technology to convey voice information sent from the server to the user. The voice can be used as a warning sound or a message of encouragement, as needed.

[0693] Step 8:

[0694] Based on the provided voice feedback, the user makes decisions about their surroundings and moves safely.

[0695] (Example 2)

[0696] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0697] There is a need to provide a system that allows users with limitations in visual information acquisition to safely and efficiently understand their surroundings and act with confidence. In particular, a system is needed that can provide information while considering not only the recognition of surrounding objects but also the user's emotional state.

[0698] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0699] In this invention, the server includes means for receiving video data from a video acquisition device wearable by the user and location information from a location acquisition device; means for analyzing the received video data and location information and using an artificial intelligence algorithm to recognize surrounding objects and detect obstacles; and analysis means for analyzing the characteristics of the user's voice and understanding their emotional state. This makes it possible to provide appropriate voice guidance in real time so that the user can act with a sense of security.

[0700] "User" refers to the entity that wears the system and receives information.

[0701] A "video acquisition device" is a device used to record surrounding visual information as digital data.

[0702] A "location acquisition device" is a device used to acquire geographical location information.

[0703] "Reception" refers to the process by which the server acquires video data and location information.

[0704] "Analysis" refers to the act of processing acquired data and extracting specific information.

[0705] An "artificial intelligence algorithm" is a computational method that analyzes data to perform object recognition and situational judgment.

[0706] "Voice guidance" is a method of providing information to users through audio.

[0707] "Natural language generation" refers to the technology of creating natural-sounding language expressions based on analyzed data.

[0708] "Voice output means" refers to a mechanism for transmitting generated voice guidance to the user.

[0709] "Real-time" means that processing or communication takes place instantly.

[0710] "A sense of security" refers to a safe and comfortable emotional state provided to the user.

[0711] This system helps users with visual impairments to understand their surroundings and act with confidence. First, the user wears a dedicated device that integrates a video acquisition device and a location acquisition device. This device is equipped with a camera and a location detection module, which acquires video and location information as digital data.

[0712] The terminal receives this data in real time and transmits it to the server via the communication network. Digital communication technology is used for data transmission to ensure communication stability and security. Data is compressed during transmission to efficiently transfer it to the server.

[0713] The server receives the transmitted data and first uses artificial intelligence algorithms to recognize objects in the environment and detect obstacles. Object detection algorithms such as YOLO (You Only Look Once) are used in this process. It also receives user voice data and analyzes the tone and speed of the voice to understand the emotional state. For voice analysis, it is possible to use libraries and tools for voice processing.

[0714] Based on the analysis results, the server uses natural language generation technology to create voice guidance tailored to the user. The generated voice guidance is designed to be adjusted according to the user's emotional state and to provide reassuring content. This process utilizes a generative AI model and employs appropriate prompt sentences to deliver optimal feedback to the user.

[0715] As a concrete example, let's say a user uses this system while moving through a crowded city. The device sends video footage and location data to a server, which uses YOLO to detect and analyze pedestrians and obstacles. Furthermore, it uses emotion analysis to determine the user's level of anxiety and generates voice advice such as, "There are many people around, but you can proceed safely," which is then fed back to the user.

[0716] An example of a prompt message would be, "Generate voice guidance explaining the surrounding environment to a user with limited visual information." By giving detailed instructions to the generation AI model in this way, it is possible to provide highly accurate guidance.

[0717] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0718] Step 1:

[0719] The user wears a dedicated device to acquire surrounding video data and location information. The device is equipped with a camera and a location detection module; the camera captures video data, and the location detection module records location information. The input is surrounding visual information and location information, and the output is digitized video and location information.

[0720] Step 2:

[0721] The terminal receives video data and location information acquired from the user's device. This data is first compressed using digital compression technology to improve communication efficiency. The compressed data is then ready to be transmitted to the server via the communication network. The input is video and location information from the device, and the output is a compressed data package.

[0722] Step 3:

[0723] The server receives compressed data sent from the terminal and decompresses it. By processing the decompressed data, the server performs object recognition and obstacle detection in the environment. Artificial intelligence algorithms (e.g., object detection algorithms) are used here. The input is compressed video and location information, and the output is a list of objects and their location information.

[0724] Step 4:

[0725] The server receives user voice data and analyzes the tone and speed of the voice. This allows for the estimation of the user's emotional state. A voice processing library is used for the analysis, and stress levels and feelings of comfort are evaluated. The input is voice data, and the output is the emotion analysis result.

[0726] Step 5:

[0727] The server integrates the results of object recognition and sentiment analysis, and generates voice guidance using natural language generation technology. The generated voice guidance is adjusted to the user's emotional state. Here, the generation AI model creates feedback using prompt sentences and generates appropriate guidance. The input is the results of object recognition and sentiment analysis, and the output is the voice guidance provided to the user.

[0728] Step 6:

[0729] The terminal receives voice guidance generated from the server and outputs it to the user in real time. The voice is delivered to the user through headphones or other means, supporting safe movement. Through this process, users can obtain information to act with a sense of security. The input is voice guidance, and the output is voice feedback to the user.

[0730] (Application Example 2)

[0731] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0732] Conventional factory robots often lack sufficient environmental awareness and operational monitoring capabilities to enhance safety during work, and may be unable to adequately alert workers or provide advice on their movements. Furthermore, the lack of means to determine the efficiency of robot operation and make appropriate adjustments makes it difficult to improve productivity. It is necessary to address these challenges and realize a safe and efficient work environment.

[0733] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0734] This invention includes a server technology that receives image data from a wearable visual information acquisition device and location information from a location acquisition device; a technology that analyzes the received image data and location information and uses an intelligent model to determine the surrounding environment; a technology that monitors the robot's operation in the industrial field and prompts the worker with instructions and warnings via voice when errors or dangers are detected; and a technology that performs emotion analysis to evaluate the stress and load on the robot's operation and advises on efficient operation. This enables accurate understanding of the surrounding environment and real-time safe work instructions, as well as improved productivity through efficient robot operation.

[0735] A "visual information acquisition device that can be worn by users" is a device attached to a robot working in an industrial area to visually observe the surrounding environment.

[0736] An "intelligent model for analyzing image data and location information to determine the surrounding environment" is an artificial intelligence analysis method used by a robot to understand its surroundings from image data and location information acquired by the robot.

[0737] "Technology that allows robots to monitor their operation in an industrial setting and provide instructions and warnings to workers via voice when errors or hazards are detected" refers to technology in which robots monitor their own movements and surrounding conditions, and when problems or hazards are discovered, they prompt workers to take appropriate action.

[0738] "A technology that performs emotional analysis, evaluates the stress and load on robot movements, and advises on efficient movement" is a technology that analyzes the robot's movement state and proposes the optimal movement procedure to reduce stress and load.

[0739] "Technology that uses voice to provide instructions and warnings to workers" refers to a method of using voice output to communicate changes in the surrounding environment or dangerous conditions to workers.

[0740] To realize this invention, it is first necessary to equip the robot with a visual information acquisition device and a location information acquisition device. These devices acquire environmental information from the factory, and the obtained data is transmitted to a server in real time. The server uses an artificial intelligence model to recognize the environment in order to analyze the received image data and location information, and manages the robot's movements so that it can perform tasks safely and efficiently.

[0741] Specifically, the server utilizes cloud-based AI platforms such as Google Cloud AI and IBM Watson to perform object recognition and obstacle detection in the environment. Furthermore, it evaluates the stress and load generated during robot operation using an emotion analysis engine and optimizes its movements accordingly. This enables the robot to quickly communicate warnings and instructions to workers via voice.

[0742] For example, when a robot is handling multiple parts in a factory, if a worker passes nearby, the server will generate a prompt such as "There is a worker nearby. Please slow down," and safely control the robot. An example of such a prompt might be text like, "Generate optimal actions and precautions for the robot to work safely in the factory."

[0743] This system improves the precision of robot movements, enhances safety within the factory, and supports increased productivity.

[0744] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0745] Step 1:

[0746] The terminal uses a visual information acquisition device and a location information acquisition device attached to a robot to acquire image data and location information within the factory. The input is the acquired image data and location information, and the output is the transmission of data to a server. This data is transmitted to the server in real time via a Wi-Fi network.

[0747] Step 2:

[0748] Based on the image data and location information received by the server, it uses cloud AI services such as Google Cloud AI and IBM Watson to perform environmental discrimination using an intelligent model. The input is image data and location information sent from the terminal, and the output is information on recognized objects and detected obstacles. The server analyzes this data using the AI ​​model to understand the surrounding environment.

[0749] Step 3:

[0750] Based on the environmental analysis results, the server uses an emotion analysis engine to evaluate the stress and load associated with the robot's movements. The input for this step is the environmental analysis results, and the output is evaluation information regarding stress and load. The server uses this information to adjust the voice feedback.

[0751] Step 4:

[0752] Based on the processing results, the server uses a generative AI model to create specific voice instructions and warning prompts. The input is stress and load evaluation information, and the output is voice prompts. The server generates these prompts to output appropriate instructions via voice, taking safety and efficiency into consideration.

[0753] Step 5:

[0754] The terminal transmits generated voice prompts to the robot, which then issues voice warnings and instructions to nearby workers. The input is the generated prompt text, and the output is voice instructions and warnings. The terminal uses a Bluetooth speaker or similar device to emit voice and manage its actions.

[0755] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0756] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet Search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0757] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0758] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0759] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0760] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0761] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0762] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0763] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0764] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0765] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0766] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0767] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0768] 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.

[0769] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0770] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0771] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0772] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0773] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0774] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0775] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted as being incorporated by reference.

[0776] The following is further disclosed regarding the embodiments described above.

[0777] (Claim 1)

[0778] A means for receiving video data from a video acquisition device that can be worn by the user and location information from a location acquisition device,

[0779] A means of analyzing received video data and location information and using an artificial intelligence model to determine the surrounding situation,

[0780] Based on the identified situation, a means of providing users with important information about their surroundings via voice,

[0781] A system that includes this.

[0782] (Claim 2)

[0783] The system according to claim 1, wherein the artificial intelligence model includes means for performing object recognition and obstacle detection.

[0784] (Claim 3)

[0785] The system according to claim 1, wherein the provision of information by voice is performed using high-speed wireless communication technology for real-time communication.

[0786] "Example 1"

[0787] (Claim 1)

[0788] A means for receiving visual information data and location information from an information acquisition device that can be worn by the user,

[0789] A means for analyzing received visual information data and location information and using a machine learning model to evaluate the surrounding environment,

[0790] Based on the analyzed information, a means of transmitting important information about the surrounding environment to the user via acoustic signals,

[0791] A means of transferring information in real time using high-speed wireless communication technology,

[0792] A system that includes this.

[0793] (Claim 2)

[0794] The system according to claim 1, wherein the machine learning model includes means for object recognition and obstacle detection.

[0795] (Claim 3)

[0796] The system according to claim 1, wherein the information transfer via the aforementioned acoustic signal is performed using speech synthesis technology at the terminal.

[0797] "Application Example 1"

[0798] (Claim 1)

[0799] A means for receiving surrounding information from a video acquisition device and a position acquisition device that can be worn by the user,

[0800] A means of analyzing received ambient information and using a generative AI model to determine the movement environment,

[0801] A means of providing users with navigation guidance information via voice based on the identified situation,

[0802] A means for transmitting data from an information acquisition device mounted on a mobile vehicle to a cloud server,

[0803] A means of transmitting the generated guidance information to users in real time,

[0804] A system that includes this.

[0805] (Claim 2)

[0806] The system according to claim 1, wherein the generating AI model includes means for detecting obstacles and analyzing traffic conditions, and uses prompt sentences to generate voice guidance information.

[0807] (Claim 3)

[0808] The system according to claim 1, wherein the voice information provision is performed inside the mobile device, and high-speed wireless communication technology is used to process the data in order to perform real-time communication.

[0809] "Example 2 of combining an emotion engine"

[0810] (Claim 1)

[0811] A means for receiving video data from a video acquisition device that can be worn by the user and location information from a location acquisition device,

[0812] A means of analyzing received video data and location information, and using an artificial intelligence algorithm to recognize surrounding objects and detect obstacles,

[0813] Analytical methods for understanding the characteristics of user voices and their emotional states,

[0814] A natural language generation means for providing voice guidance that gives users a sense of security, based on the identified situation and emotional state,

[0815] A means for providing real-time voice feedback to the user,

[0816] A system that includes this.

[0817] (Claim 2)

[0818] The system according to claim 1, wherein the artificial intelligence algorithm includes means for creating voice feedback using a generation algorithm.

[0819] (Claim 3)

[0820] The system according to claim 1, wherein the provision of information by voice is performed using digital communication technology for real-time communication.

[0821] "Application example 2 when combining with an emotional engine"

[0822] (Claim 1)

[0823] A technology for receiving image data from a wearable visual information acquisition device and location information from a location acquisition device,

[0824] A technology that uses an intelligent model to analyze received image data and location information and determine the surrounding environment,

[0825] A technology that allows robots to monitor their operation in an industrial setting and, when errors or hazards are detected, to provide instructions and warnings to workers via voice,

[0826] This technology analyzes emotions, evaluates the stress and load on robot movements, and provides advice for efficient movement.

[0827] A system that includes this.

[0828] (Claim 2)

[0829] The system according to claim 1, wherein the intelligent model includes techniques for object recognition and obstacle detection.

[0830] (Claim 3)

[0831] The system according to claim 1, wherein the voice instructions and warnings are provided using high-speed wireless communication technology for real-time communication. [Explanation of symbols]

[0832] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A means for receiving video data from a video acquisition device that can be worn by the user and location information from a location acquisition device, A means of analyzing received video data and location information and using an artificial intelligence model to determine the surrounding situation, Based on the identified situation, a means of providing users with important information about their surroundings via voice, A system that includes this.

2. The system according to claim 1, wherein the artificial intelligence model includes means for performing object recognition and obstacle detection.

3. The system according to claim 1, wherein the provision of information by voice is performed using high-speed wireless communication technology for real-time communication.

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