system

Abstract

The system according to this embodiment aims to provide visually and hearing impaired individuals with information about their surrounding environment and support their safe movement. [Solution] The system according to the embodiment comprises an analysis unit, an audio guide unit, a visual information provision unit, and VR goggles. The analysis unit analyzes the environment. The audio guide unit provides audio guidance to visually impaired persons based on the information analyzed by the analysis unit. The visual information provision unit provides visual information to hearing impaired persons based on the information analyzed by the analysis unit.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor and includes steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance 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] In the conventional technology, it is difficult for visually and hearing impaired persons to recognize the surrounding environment, and there is room for improvement in supporting safe movement.

[0005] The system according to the embodiment aims to provide surrounding environmental information to visually and hearing impaired persons and support safe movement.

Means for Solving the Problems

[0006] The system according to this embodiment comprises an analysis unit, an audio guidance unit, a visual information provision unit, and VR goggles. The analysis unit analyzes the environment. The audio guidance unit provides audio guidance to visually impaired persons based on the information analyzed by the analysis unit. The visual information provision unit provides visual information to hearing-impaired persons based on the information analyzed by the analysis unit. [Effects of the Invention]

[0007] The system according to this embodiment can provide visually and hearing impaired individuals with information about their surroundings and support their safe movement. [Brief explanation of the drawing]

[0008] [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] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This 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] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This 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] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This 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] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Modes for carrying out the invention]

[0009] Hereinafter, an example of an embodiment of the system relating to the technology of this disclosure will be described with reference to the attached drawings.

[0010] First, let's explain the terminology used in the following explanation.

[0011] In the following embodiments, the signed processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Furthermore, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include CPU (Central Processing Unit), GPU (Graphics Processing Unit), GPGPU (General-Purpose computing on Graphics Processing Units), APU (Accelerated Processing Unit), or TPU (Tensor Processing Unit).

[0012] In the following embodiments, signed RAM (Random Access Memory) is a memory that temporarily stores information and is used as work memory by the processor.

[0013] In the following embodiments, the signed storage is one or more non-volatile storage devices that store various programs and various parameters. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes.

[0014] In the following embodiments, the labeled communication I / F (Interface) is an interface including a communication processor, an antenna, etc. The communication I / F manages communication between a plurality of 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).

[0015] 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 only A, only B, or a combination of A and B. Also, in this specification, when expressing three or more matters connected by "and / or", the same concept as "A and / or B" is applied.

[0016] [First Embodiment] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0017] As shown in FIG. 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.

[0018] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. Also, the database 24 and the communication I / F 26 are connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0019] The smart device 14 comprises a computer 36, a receiving 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 receiving device 38, output device 40, and camera 42 are also connected to the bus 52.

[0020] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, and accepts user input. The touch panel 38A accepts user input via touch by detecting contact with an object (e.g., a pen or finger). The microphone 38B accepts user input via voice 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 unit 12. In the data processing unit 12, the specific processing unit 290 (see Figure 2) acquires the data indicating the user input.

[0021] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user by outputting the data in a form perceptible to the user (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.

[0022] 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.

[0023] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0024] 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.

[0025] 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. The identification processing unit 290 can estimate the user's emotions using the emotion identification model 59 and perform identification processing using the user's emotions. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotions, including but not limited to these examples. Furthermore, emotion estimation and prediction also include, for example, emotion analysis.

[0026] In the smart device 14, specific processing is performed by the processor 46. The storage 50 stores a specific processing program 60. The specific processing program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as a control unit 46A according to the specific processing program 60 executed on the RAM 48. The smart device 14 also has a data generation model 58 and an emotion identification model 59, similar to the data generation model and emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0027] Furthermore, other devices besides the data processing device 12 may also have the data generation model 58. For example, a server device (e.g., a generation server) may have the data generation model 58. In this case, the data processing device 12 obtains processing results (such as prediction results) using the data generation model 58 by communicating with the server device having the data generation model 58. The data processing device 12 may also be a server device or a terminal device owned by a user (e.g., a mobile phone, robot, home appliance, etc.). Next, an example of processing by the data processing system 10 according to the first embodiment will be described.

[0028] (Example of form 1) The system according to an embodiment of the present invention is a system that supports the recognition of the surrounding environment by visually and hearing impaired persons. This system supports safe movement and aims to improve independent living and safety by having an AI for analyzing the environment collect visual and auditory information and provide audio guidance to visually impaired persons and visual information to hearing impaired persons. For example, the system has an AI for analyzing the environment that collects visual information of the surroundings through a camera. For example, it collects information on the location of obstacles and the movement path. Next, the system analyzes the collected visual information and provides it to visually impaired persons as an audio guide. For example, it provides specific instructions by voice, such as "There is an obstacle ahead. Turn right." The system also collects audio information of the surroundings through a microphone and provides it as visual information to hearing impaired persons. For example, it converts surrounding audio into text and displays it on a screen. This allows hearing impaired persons to visually grasp the surrounding audio information. Furthermore, the system supports independent movement of people with physical disabilities by combining VR goggles and an electric wheelchair. For example, by wearing VR goggles, it becomes possible to provide information in a virtual space in addition to the real space, improving the user experience. By utilizing electric wheelchairs, freedom of movement is increased, and safer travel becomes possible. This system supports independent living and improves safety for people with visual and hearing impairments. For example, visually impaired individuals can move safely through audio guidance, and hearing-impaired individuals can understand their surroundings through visual information. Furthermore, by combining VR goggles with electric wheelchairs, the freedom of movement for people with physical disabilities is increased, enabling independent living. In this way, the system can support the perception of the surrounding environment for people with visual and hearing impairments and support safe travel.

[0029] The system according to the embodiment comprises an analysis unit, an audio guidance unit, a visual information provision unit, and VR goggles. The analysis unit is a part for analyzing the environment and includes AI processing. The analysis unit collects, for example, surrounding visual information through a camera. The analysis unit collects, for example, information on the location and movement path of obstacles. The analysis unit can collect surrounding visual information in real time using a camera. The audio guidance unit is a part that provides audio guidance to visually impaired people based on the information analyzed by the analysis unit and includes AI processing. The audio guidance unit provides audio guidance to visually impaired people based on the collected visual information. The audio guidance unit provides specific instructions by voice, for example, "There is an obstacle ahead. Turn right." The audio guidance unit can provide audio guidance in real time so that visually impaired people can move safely. The visual information provision unit is a part that provides visual information to hearing impaired people based on the information analyzed by the analysis unit and includes AI processing. The visual information provision unit collects surrounding audio information through a microphone and provides it as visual information. The visual information provider unit, for example, converts ambient sound into text and displays it on a screen. The visual information provider unit can provide real-time visual information, for example, so that a person with a hearing impairment can visually grasp ambient sound information. VR goggles provide information in both the real and virtual spaces. VR goggles, for example, provide information in both the real and virtual spaces when worn by the user. VR goggles can improve the user experience by providing visual information, for example. As a result, the system according to this embodiment can support the recognition of the surrounding environment by people with visual and hearing impairments and support safe movement.

[0030] The analysis unit is the part that analyzes the environment and includes AI processing. For example, the analysis unit collects surrounding visual information through cameras. Specifically, the analysis unit collects surrounding visual information in real time using high-resolution cameras and analyzes this data using AI algorithms. The AI ​​uses image recognition technology to identify information about the location and movement paths of obstacles. For example, the AI ​​identifies objects such as pedestrians, vehicles, and buildings from camera footage and analyzes their positional relationships and movements. Furthermore, the AI ​​can use past data and pattern recognition to predict the frequency of obstacle appearance and movement paths. In this way, the analysis unit builds a foundation for accurately understanding the surrounding environment and providing necessary information so that visually impaired and hearing impaired people can move safely. The analysis unit can also send the collected data to a cloud server and link with other systems and devices. This allows the analysis unit to always provide the latest information based on data that is updated in real time. In addition, the analysis unit can use anomaly detection algorithms to detect unusual patterns and abnormal data and issue warnings early. This allows the analysis unit to not only grasp the situation in real time, but also to handle long-term risk management and anomaly detection, thereby improving the reliability and safety of the entire system.

[0031] The audio guidance unit is the part that provides audio guidance to visually impaired individuals based on information analyzed by the analysis unit, and includes AI processing. For example, the audio guidance unit provides audio guidance to visually impaired individuals based on collected visual information. Specifically, the audio guidance unit receives location information of obstacles and information on movement paths sent from the analysis unit, and uses AI to generate appropriate audio guidance. The AI ​​uses natural language processing technology to provide specific instructions in language that is easy for visually impaired individuals to understand. For example, it provides specific instructions such as, "There is an obstacle ahead. Please turn right," in audio. Based on information that is updated in real time, the audio guidance unit can always provide the latest audio guidance to ensure that visually impaired individuals can move safely. Furthermore, the audio guidance unit can collect user feedback and continuously improve the content and delivery method of the audio guidance. For example, based on feedback from visually impaired individuals, it can adjust the timing and content of the audio guidance to provide more effective guidance. In addition, the audio guidance unit supports multiple languages ​​and can provide audio guidance in the appropriate language according to the user's language settings. As a result, the audio guidance unit can provide effective audio guidance to ensure that visually impaired individuals can move safely and comfortably.

[0032] The visual information provision unit is the part that provides visual information to the hearing impaired based on the information analyzed by the analysis unit, and includes AI processing. For example, the visual information provision unit collects ambient audio information through a microphone and provides it as visual information. Specifically, the visual information provision unit collects ambient audio using a high-sensitivity microphone and converts this audio into text using AI. The AI ​​utilizes speech recognition technology to accurately transcribe ambient audio into text and displays it on the display. For example, it converts ambient audio information such as conversations, warning sounds, and car horns into text in real time, enabling the hearing impaired to visually understand it. Furthermore, the visual information provision unit can analyze the collected audio information and highlight important information. For example, it can highlight emergency warning sounds and important conversations, enabling the hearing impaired to respond quickly. In addition, the visual information provision unit can collect user feedback and continuously improve the way visual information is provided. For example, based on feedback from the hearing impaired, it can adjust the text display method and font size to provide a more readable display. In this way, the visual information provision unit can provide effective visual information so that the hearing impaired can visually understand ambient audio information.

[0033] VR goggles provide information in both real and virtual spaces. Specifically, when worn by a user, VR goggles provide information in both the real and virtual worlds. Equipped with high-resolution displays and sensors, VR goggles can track the user's gaze and movements. This allows users to seamlessly move between real and virtual spaces to obtain necessary information. For example, visually impaired individuals can wear VR goggles to virtually recreate their surroundings, visually understanding the location of obstacles and their movement paths. Similarly, hearing-impaired individuals can wear VR goggles to visually display surrounding audio information, ensuring they don't miss important details. Furthermore, VR goggles can provide interactive content to enhance the user experience. For instance, users can touch specific objects in the virtual space to display detailed information or play audio guides. This allows VR goggles to support visually and hearing-impaired individuals in gaining a deeper understanding of their surroundings and navigating safely. Additionally, VR goggles can collect user feedback and continuously improve content and functionality. This allows VR goggles to constantly provide the latest technology and information, and offer optimal support tailored to the user's needs.

[0034] The analysis unit can collect surrounding visual information through a camera. For example, the analysis unit collects surrounding visual information in real time using a camera. For example, the analysis unit collects information on the location and movement paths of obstacles. For example, the analysis unit collects surrounding visual information using a camera and generates information to be provided to visually impaired individuals. This allows for the provision of appropriate information to visually impaired individuals by collecting surrounding visual information. Visual information includes, but is not limited to, images, videos, and the area to be collected. Some or all of the above-described processes in the analysis unit may be performed using AI or not. For example, the analysis unit can input visual information acquired by the camera into a generating AI and have the generating AI perform the analysis of the visual information.

[0035] The audio guidance unit can provide audio guidance to visually impaired persons based on collected visual information. For example, the audio guidance unit can provide audio guidance to visually impaired persons based on collected visual information. For example, the audio guidance unit can provide specific instructions by voice, such as, "There is an obstacle ahead. Turn right." The audio guidance unit can provide audio guidance in real time to help visually impaired persons move safely. In this way, safe movement can be supported by providing audio guidance to visually impaired persons. Visual information includes, but is not limited to, images, videos, and the area to be collected. Some or all of the processing described above in the audio guidance unit may be performed using AI or not. For example, the audio guidance unit can input collected visual information into a generating AI and have the generating AI perform the generation of audio guidance.

[0036] The visual information provider can collect ambient audio information through a microphone and provide it as visual information. For example, the visual information provider can collect ambient audio information through a microphone and provide it as visual information. For example, the visual information provider can convert ambient audio into text and display it on a screen. For example, the visual information provider can provide visual information in real time so that a person with a hearing impairment can visually grasp ambient audio information. This allows a person with a hearing impairment to understand their surroundings by providing them with visual information. Audio information includes, but is not limited to, the type of sound and the range to be collected. Some or all of the above processing in the visual information provider may be performed using AI or not. For example, the visual information provider can input audio information acquired by the microphone into a generating AI and have the generating AI perform the text conversion of the audio information.

[0037] The visual information provider can convert collected audio information into text and display it on a screen. For example, the visual information provider can convert collected audio information into text and display it on a screen. For example, the visual information provider can convert ambient sounds into text and display it on a screen. For example, the visual information provider can provide real-time visual information so that a person with a hearing impairment can visually grasp ambient audio information. This allows a person with a hearing impairment to visually grasp ambient audio information. Audio information includes, but is not limited to, the type of sound and the range to be collected. Some or all of the processing described above in the visual information provider may be performed using AI or not. For example, the visual information provider can input collected audio information into a generating AI and have the generating AI perform the conversion of the audio information into text.

[0038] The system includes electric wheelchairs. Electric wheelchairs are used, for example, to increase freedom of movement. Electric wheelchairs are designed, for example, to enable visually and hearing-impaired individuals to move safely. Electric wheelchairs feature, for example, intuitive operating interfaces to make them easy for users to operate. This allows for increased freedom of movement and safer mobility through the use of electric wheelchairs. Specific functions and specifications of electric wheelchairs include, but are not limited to, speed and operating methods.

[0039] VR goggles can provide information in both the real and virtual spaces. For example, when worn by a user, VR goggles provide information in both the real and virtual spaces. VR goggles can improve the user experience by providing visual information, for example. This enables information provision in the virtual space, thereby improving the user experience. The virtual space includes, but is not limited to, display content and interaction methods.

[0040] The analysis unit can select the optimal analysis method by referring to the user's past travel history during analysis. For example, the analysis unit may select the optimal analysis method based on routes the user has frequently traveled in the past. For example, the analysis unit may select an analysis method to avoid congestion from the user's past travel history. For example, the analysis unit may analyze the user's past travel history and select the most efficient analysis method. In this way, the optimal analysis method can be selected by referring to the user's past travel history. The optimal analysis method includes, but is not limited to, examples of how past data is used and analysis algorithms. Some or all of the above processing in the analysis unit may be performed using AI or not using AI. For example, the analysis unit can input the user's past travel history data into a generating AI and have the generating AI perform the selection of the optimal analysis method.

[0041] The analysis unit can detect changes in the surrounding environment in real time during analysis and reflect them in the analysis results. For example, the analysis unit can detect changes in ambient temperature in real time and reflect them in the analysis results. For example, the analysis unit can detect changes in ambient sound volume in real time and reflect them in the analysis results. For example, the analysis unit can detect changes in ambient light intensity in real time and reflect them in the analysis results. In this way, changes in the surrounding environment can be detected in real time and reflected in the analysis results. Methods for detecting environmental changes in real time include, but are not limited to, the sensors used and detection algorithms. Some or all of the above processing in the analysis unit may be performed using AI or not. For example, the analysis unit can input ambient environmental data into a generating AI and have the generating AI perform the detection of environmental changes.

[0042] The analysis unit can prioritize analyzing highly relevant information based on the user's geographical location information during analysis. For example, if the user is in a specific region, the analysis unit will prioritize analyzing information related to that region. For example, if the user is on the move, the analysis unit will prioritize analyzing information related to their destination. For example, if the user is in a specific facility, the analysis unit will prioritize analyzing information related to that facility. By prioritizing the analysis of highly relevant information based on the user's geographical location information, more appropriate information can be provided. Geographical location information includes, but is not limited to, GPS data and location accuracy. Some or all of the above processing in the analysis unit may be performed using AI or not. For example, the analysis unit can input the user's geographical location information into a generating AI and have the generating AI perform the analysis of highly relevant information.

[0043] The analysis unit can analyze a user's social media activity and related environmental information during the analysis process. For example, the analysis unit can analyze related environmental information based on the content a user posts on social media. For example, the analysis unit can analyze related environmental information based on information about accounts a user follows on social media. For example, the analysis unit can analyze related environmental information based on information about places a user has checked into on social media. In this way, by analyzing a user's social media activity, related environmental information can be analyzed. Social media activity includes, but is not limited to, the content of posts and activity frequency. Some or all of the above processing in the analysis unit may be performed using AI or not. For example, the analysis unit can input the user's social media activity data into a generating AI and have the generating AI perform the analysis of related environmental information.

[0044] The audio guide unit can select the most suitable guide content by referring to the user's past travel history when providing audio guidance. For example, the audio guide unit can select the most suitable guide content based on routes the user has frequently traveled in the past. For example, the audio guide unit can select guide content to avoid congestion based on the user's past travel history. For example, the audio guide unit can analyze the user's past travel history and select the most efficient guide content. In this way, the optimal guide content can be selected by referring to the user's past travel history. The optimal guide content includes, but is not limited to, how past data is used and details of the guide content. Some or all of the above processing in the audio guide unit may be performed using AI or not. For example, the audio guide unit can input the user's past travel history data into a generating AI and have the generating AI perform the selection of the optimal guide content.

[0045] The audio guide unit can detect changes in the surrounding environment in real time when providing audio guidance and reflect them in the guide content. For example, the audio guide unit can detect changes in ambient temperature in real time and reflect them in the guide content. For example, the audio guide unit can detect changes in ambient volume in real time and reflect them in the guide content. For example, the audio guide unit can detect changes in ambient light intensity in real time and reflect them in the guide content. In this way, changes in the surrounding environment can be detected in real time and reflected in the guide content. Methods for detecting environmental changes in real time include, but are not limited to, the sensors used and detection algorithms. Some or all of the above processing in the audio guide unit may be performed using AI or not. For example, the audio guide unit can input ambient environmental data into a generating AI and have the generating AI perform the detection of environmental changes.

[0046] The audio guide unit can prioritize providing highly relevant information based on the user's geographical location when providing audio guidance. For example, if the user is in a specific region, the audio guide unit will prioritize providing information related to that region. For example, if the user is on the move, the audio guide unit will prioritize providing information related to their destination. For example, if the user is in a specific facility, the audio guide unit will prioritize providing information related to that facility. By prioritizing the provision of highly relevant information based on the user's geographical location, a more appropriate guide can be provided. Geographical location information includes, but is not limited to, GPS data and location accuracy. Some or all of the above processing in the audio guide unit may be performed using AI or not. For example, the audio guide unit can input the user's geographical location information into a generating AI and have the generating AI perform the provision of highly relevant information.

[0047] The audio guide unit can analyze the user's social media activity when providing audio guides and reflect relevant information in the guide content. For example, the audio guide unit can reflect relevant information in the guide content based on the content the user has posted on social media. For example, the audio guide unit can reflect relevant information in the guide content based on the information of accounts the user follows on social media. For example, the audio guide unit can reflect relevant information in the guide content based on the information of places the user has checked into on social media. In this way, by analyzing the user's social media activity, relevant information can be reflected in the guide content. Social media activity includes, but is not limited to, the content of posts and activity frequency. Some or all of the above processing in the audio guide unit may be performed using AI or not. For example, the audio guide unit can input the user's social media activity data into a generating AI and have the generating AI provide relevant information.

[0048] The visual information provider can select the optimal information display method by referring to the user's past travel history when providing visual information. For example, the visual information provider can select the optimal information display method based on routes the user has frequently traveled in the past. For example, the visual information provider can select an information display method to avoid congestion based on the user's past travel history. For example, the visual information provider can analyze the user's past travel history and select the most efficient information display method. In this way, the optimal information display method can be selected by referring to the user's past travel history. The optimal information display method includes, but is not limited to, the use of past data and details of the display method. Some or all of the above processing in the visual information provider may be performed using AI or not. For example, the visual information provider can input the user's past travel history data into a generating AI and have the generating AI perform the selection of the optimal information display method.

[0049] The visual information provider can detect changes in the surrounding environment in real time when providing visual information and reflect them in the displayed content. For example, the visual information provider can detect changes in ambient temperature in real time and reflect them in the displayed content. For example, the visual information provider can detect changes in ambient volume in real time and reflect them in the displayed content. For example, the visual information provider can detect changes in ambient light intensity in real time and reflect them in the displayed content. In this way, changes in the surrounding environment can be detected in real time and reflected in the displayed content. Methods for detecting environmental changes in real time include, but are not limited to, the sensors used and detection algorithms. Some or all of the above processing in the visual information provider may be performed using AI or not. For example, the visual information provider can input ambient environmental data into a generating AI and have the generating AI perform the detection of environmental changes.

[0050] The visual information provider can prioritize displaying highly relevant information based on the user's geographical location when providing visual information. For example, if the user is in a specific region, the visual information provider will prioritize displaying information related to that region. For example, if the user is on the move, the visual information provider will prioritize displaying information related to their destination. For example, if the user is in a specific facility, the visual information provider will prioritize displaying information related to that facility. This allows for the provision of more appropriate information by prioritizing the display of highly relevant information based on the user's geographical location. Geographical location information includes, but is not limited to, GPS data and location accuracy. Some or all of the above processing in the visual information provider may be performed using AI or not. For example, the visual information provider can input the user's geographical location information into a generating AI and have the generating AI display highly relevant information.

[0051] The visual information provider can analyze the user's social media activity and reflect relevant information in the displayed content when providing visual information. For example, the visual information provider can reflect relevant information in the displayed content based on the content the user has posted on social media. For example, the visual information provider can reflect relevant information in the displayed content based on information about accounts the user follows on social media. For example, the visual information provider can reflect relevant information in the displayed content based on information about places the user has checked into on social media. In this way, by analyzing the user's social media activity, relevant information can be reflected in the displayed content. Social media activity includes, but is not limited to, posts and activity frequency. Some or all of the above processing in the visual information provider may be performed using AI or not. For example, the visual information provider can input the user's social media activity data into a generating AI and have the generating AI display relevant information.

[0052] VR goggles can generate an optimal virtual space by referencing the user's past travel history when the VR goggles are in use. For example, VR goggles can generate an optimal virtual space based on places the user has visited in the past. For example, VR goggles can generate a virtual space to avoid congestion based on the user's past travel history. For example, VR goggles can analyze the user's past travel history and generate the most efficient virtual space. In this way, an optimal virtual space can be generated by referring to the user's past travel history. An optimal virtual space includes, but is not limited to, how past data is used and details of the virtual space. Some or all of the above processing in VR goggles may be performed using AI or not. For example, VR goggles can input the user's past travel history data into a generating AI and have the generating AI perform the generation of an optimal virtual space.

[0053] VR goggles can detect changes in the surrounding environment in real time when the VR goggles are in use and reflect them in the virtual space. For example, VR goggles can detect changes in ambient temperature in real time and reflect them in the virtual space. For example, VR goggles can detect changes in ambient volume in real time and reflect them in the virtual space. For example, VR goggles can detect changes in ambient light intensity in real time and reflect them in the virtual space. In this way, changes in the surrounding environment can be detected in real time and reflected in the virtual space. Methods for detecting environmental changes in real time include, but are not limited to, the sensors used and detection algorithms. Some or all of the above processing in VR goggles may be performed using AI or not. For example, VR goggles can input ambient environmental data into a generating AI and have the generating AI perform the detection of environmental changes.

[0054] VR goggles can generate highly relevant virtual spaces based on the user's geographical location information when the VR goggles are in use. For example, if the user is in a specific region, the VR goggles will generate a virtual space related to that region. For example, if the user is on the move, the VR goggles will generate a virtual space related to the destination. For example, if the user is in a specific facility, the VR goggles will generate a virtual space related to that facility. This allows for the provision of more appropriate information by generating highly relevant virtual spaces based on the user's geographical location information. Geographical location information includes, but is not limited to, GPS data and location accuracy. Some or all of the above processing in VR goggles may be performed using AI or not. For example, the VR goggles can input the user's geographical location information into a generating AI and have the generating AI perform the generation of highly relevant virtual spaces.

[0055] VR goggles can analyze a user's social media activity while they are in use and reflect relevant information in the virtual space. For example, VR goggles can reflect relevant information in the virtual space based on the content a user has posted on social media. For example, VR goggles can reflect relevant information in the virtual space based on information about accounts a user follows on social media. For example, VR goggles can reflect relevant information in the virtual space based on information about places a user has checked into on social media. In this way, by analyzing a user's social media activity, relevant information can be reflected in the virtual space. Social media activity includes, but is not limited to, the content of posts and activity frequency. Some or all of the above processing in VR goggles may be performed using AI or not. For example, VR goggles can input the user's social media activity data into a generating AI and have the generating AI perform the reflection of relevant information.

[0056] An electric wheelchair can select the optimal travel route by referring to the user's past travel history when using the electric wheelchair. For example, the electric wheelchair can select the optimal travel route based on routes the user has frequently traveled in the past. For example, the electric wheelchair can select a travel route to avoid congestion based on the user's past travel history. For example, the electric wheelchair can analyze the user's past travel history and select the most efficient travel route. In this way, the optimal travel route can be selected by referring to the user's past travel history. The optimal travel route includes, but is not limited to, how past data is used and details of route selection. Some or all of the above processing in an electric wheelchair may be performed using AI or not. For example, the electric wheelchair can input the user's past travel history data into a generating AI and have the generating AI perform the selection of the optimal travel route.

[0057] An electric wheelchair can detect changes in the surrounding environment in real time while in use and reflect them in its movement path. For example, an electric wheelchair can detect changes in ambient temperature in real time and reflect them in its movement path. For example, an electric wheelchair can detect changes in ambient noise in real time and reflect them in its movement path. For example, an electric wheelchair can detect changes in ambient light intensity in real time and reflect them in its movement path. In this way, changes in the surrounding environment can be detected in real time and reflected in the movement path. Methods for detecting environmental changes in real time include, but are not limited to, the sensors used and detection algorithms. Some or all of the above processing in an electric wheelchair may be performed using AI or not. For example, an electric wheelchair can input ambient environmental data into a generating AI and have the generating AI perform the detection of environmental changes.

[0058] An electric wheelchair can select a highly relevant travel route based on the user's geographical location information when using the electric wheelchair. For example, if the user is in a specific area, the electric wheelchair will select a travel route relevant to that area. For example, if the user is on the move, the electric wheelchair will select a travel route relevant to the destination. For example, if the user is in a specific facility, the electric wheelchair will select a travel route relevant to that facility. By selecting a highly relevant travel route based on the user's geographical location information, a more appropriate travel route can be provided. Geographical location information includes, but is not limited to, GPS data and location accuracy. Some or all of the above processing in the electric wheelchair may be performed using AI or not. For example, the electric wheelchair can input the user's geographical location information into a generating AI and have the generating AI perform the selection of a highly relevant travel route.

[0059] An electric wheelchair can analyze a user's social media activity while they are using it and reflect relevant information in their travel route. For example, the electric wheelchair can reflect relevant information in its travel route based on the content the user has posted on social media. For example, the electric wheelchair can reflect relevant information in its travel route based on the information of accounts the user follows on social media. For example, the electric wheelchair can reflect relevant information in its travel route based on the information of places the user has checked into on social media. In this way, by analyzing the user's social media activity, relevant information can be reflected in their travel route. Social media activity includes, but is not limited to, the content of posts and activity frequency. Some or all of the above processing in the electric wheelchair may be performed using AI or not. For example, the electric wheelchair can input the user's social media activity data into a generating AI and have the generating AI perform the reflection of relevant information.

[0060] The system according to the embodiment is not limited to the example described above, and various modifications are possible, for example, as follows.

[0061] The analysis unit can monitor the user's health status and adjust the accuracy of the analysis based on that status. For example, if the user's heart rate is high, the analysis unit can ensure the user's safety by providing detailed information. Conversely, if the user's heart rate is stable, the analysis unit can reduce the user's burden by providing only the minimum necessary information. Furthermore, if the user's blood pressure is high, the analysis unit can prioritize providing information to reduce stress. This enables the provision of appropriate information tailored to the user's health status.

[0062] The audio guide unit can automatically switch the language of the audio guide based on the user's language settings. For example, if the user selects English, the audio guide unit will provide the guide in English. If the user selects Japanese, the guide will provide the guide in Japanese. Furthermore, if the user uses multiple languages, the audio guide unit can provide the guide in the appropriate language according to the user's language settings. This enables flexible audio guidance that adapts to the user's language settings.

[0063] The visual information provider can adjust how information is displayed according to the user's degree of visual impairment. For example, if the user is completely blind, the visual information provider will prioritize providing audio guidance. If the user has low vision, the visual information provider will improve visibility by increasing the font size or enhancing the contrast. Furthermore, if the user has color vision deficiency, the visual information provider can adjust the use of colors to provide information. This makes it possible to provide appropriate information according to the user's degree of visual impairment.

[0064] VR goggles can change the theme of the virtual space according to the user's preferences. For example, if a user prefers nature, the VR goggles can provide a virtual space of a forest or the sea. If a user prefers cities, it can provide a virtual space that recreates a city landscape. Furthermore, if a user has a specific hobby, it can provide a virtual space related to that hobby. This provides a customized virtual space that suits the user's preferences, improving the user experience.

[0065] Electric wheelchairs can adjust their operation according to the user's weight. For example, if the user is light, the electric wheelchair provides smooth operation. If the user is heavy, the electric wheelchair provides stable operation. Furthermore, if the user's weight changes, the electric wheelchair can automatically adjust its operation to provide optimal mobility. This ensures that appropriate operation is provided according to the user's weight, enabling safe and comfortable movement.

[0066] The following briefly describes the processing flow for example form 1.

[0067] Step 1: The analysis unit is the part that analyzes the environment and includes AI processing. For example, the analysis unit collects surrounding visual information through a camera and collects information on the location and movement paths of obstacles. The analysis unit can collect surrounding visual information in real time using a camera. Step 2: The audio guidance unit is the part that provides audio guidance to visually impaired individuals based on the information analyzed by the analysis unit, and includes AI processing. For example, the audio guidance unit provides audio guidance to visually impaired individuals based on the collected visual information. The audio guidance unit can provide specific instructions in voice, such as "There is an obstacle ahead. Turn right," and can provide real-time audio guidance to enable visually impaired individuals to move safely. Step 3: The visual information provision unit is the part that provides visual information to the hearing impaired based on the information analyzed by the analysis unit, and includes AI processing. For example, the visual information provision unit collects ambient audio information through a microphone and provides it as visual information. The visual information provision unit converts ambient audio into text and displays it on the screen. The visual information provision unit can provide visual information in real time so that the hearing impaired can visually grasp the ambient audio information. Step 4: VR goggles provide information in both the real and virtual spaces. When worn by the user, VR goggles provide information in both the real and virtual spaces. VR goggles can improve the user experience by providing visual information.

[0068] (Example of form 2) The system according to an embodiment of the present invention is a system that supports the recognition of the surrounding environment by visually and hearing impaired persons. This system supports safe movement and aims to improve independent living and safety by having an AI for analyzing the environment collect visual and auditory information and provide audio guidance to visually impaired persons and visual information to hearing impaired persons. For example, the system has an AI for analyzing the environment that collects visual information of the surroundings through a camera. For example, it collects information on the location of obstacles and the movement path. Next, the system analyzes the collected visual information and provides it to visually impaired persons as an audio guide. For example, it provides specific instructions by voice, such as "There is an obstacle ahead. Turn right." The system also collects audio information of the surroundings through a microphone and provides it as visual information to hearing impaired persons. For example, it converts surrounding audio into text and displays it on a screen. This allows hearing impaired persons to visually grasp the surrounding audio information. Furthermore, the system supports independent movement of people with physical disabilities by combining VR goggles and an electric wheelchair. For example, by wearing VR goggles, it becomes possible to provide information in a virtual space in addition to the real space, improving the user experience. By utilizing electric wheelchairs, freedom of movement is increased, and safer travel becomes possible. This system supports independent living and improves safety for people with visual and hearing impairments. For example, visually impaired individuals can move safely through audio guidance, and hearing-impaired individuals can understand their surroundings through visual information. Furthermore, by combining VR goggles with electric wheelchairs, the freedom of movement for people with physical disabilities is increased, enabling independent living. In this way, the system can support the perception of the surrounding environment for people with visual and hearing impairments and support safe travel.

[0069] The system according to the embodiment comprises an analysis unit, an audio guidance unit, a visual information provision unit, and VR goggles. The analysis unit is a part for analyzing the environment and includes AI processing. The analysis unit collects, for example, surrounding visual information through a camera. The analysis unit collects, for example, information on the location and movement path of obstacles. The analysis unit can collect surrounding visual information in real time using a camera. The audio guidance unit is a part that provides audio guidance to visually impaired people based on the information analyzed by the analysis unit and includes AI processing. The audio guidance unit provides audio guidance to visually impaired people based on the collected visual information. The audio guidance unit provides specific instructions by voice, for example, "There is an obstacle ahead. Turn right." The audio guidance unit can provide audio guidance in real time so that visually impaired people can move safely. The visual information provision unit is a part that provides visual information to hearing impaired people based on the information analyzed by the analysis unit and includes AI processing. The visual information provision unit collects surrounding audio information through a microphone and provides it as visual information. The visual information provider unit, for example, converts ambient sound into text and displays it on a screen. The visual information provider unit can provide real-time visual information, for example, so that a person with a hearing impairment can visually grasp ambient sound information. VR goggles provide information in both the real and virtual spaces. VR goggles, for example, provide information in both the real and virtual spaces when worn by the user. VR goggles can improve the user experience by providing visual information, for example. As a result, the system according to this embodiment can support the recognition of the surrounding environment by people with visual and hearing impairments and support safe movement.

[0070] The analysis unit is the part that analyzes the environment and includes AI processing. For example, the analysis unit collects surrounding visual information through cameras. Specifically, the analysis unit collects surrounding visual information in real time using high-resolution cameras and analyzes this data using AI algorithms. The AI ​​uses image recognition technology to identify information about the location and movement paths of obstacles. For example, the AI ​​identifies objects such as pedestrians, vehicles, and buildings from camera footage and analyzes their positional relationships and movements. Furthermore, the AI ​​can use past data and pattern recognition to predict the frequency of obstacle appearance and movement paths. In this way, the analysis unit builds a foundation for accurately understanding the surrounding environment and providing necessary information so that visually impaired and hearing impaired people can move safely. The analysis unit can also send the collected data to a cloud server and link with other systems and devices. This allows the analysis unit to always provide the latest information based on data that is updated in real time. In addition, the analysis unit can use anomaly detection algorithms to detect unusual patterns and abnormal data and issue warnings early. This allows the analysis unit to not only grasp the situation in real time, but also to handle long-term risk management and anomaly detection, thereby improving the reliability and safety of the entire system.

[0071] The audio guidance unit is the part that provides audio guidance to visually impaired individuals based on information analyzed by the analysis unit, and includes AI processing. For example, the audio guidance unit provides audio guidance to visually impaired individuals based on collected visual information. Specifically, the audio guidance unit receives location information of obstacles and information on movement paths sent from the analysis unit, and uses AI to generate appropriate audio guidance. The AI ​​uses natural language processing technology to provide specific instructions in language that is easy for visually impaired individuals to understand. For example, it provides specific instructions such as, "There is an obstacle ahead. Please turn right," in audio. Based on information that is updated in real time, the audio guidance unit can always provide the latest audio guidance to ensure that visually impaired individuals can move safely. Furthermore, the audio guidance unit can collect user feedback and continuously improve the content and delivery method of the audio guidance. For example, based on feedback from visually impaired individuals, it can adjust the timing and content of the audio guidance to provide more effective guidance. In addition, the audio guidance unit supports multiple languages ​​and can provide audio guidance in the appropriate language according to the user's language settings. As a result, the audio guidance unit can provide effective audio guidance to ensure that visually impaired individuals can move safely and comfortably.

[0072] The visual information provision unit is the part that provides visual information to the hearing impaired based on the information analyzed by the analysis unit, and includes AI processing. For example, the visual information provision unit collects ambient audio information through a microphone and provides it as visual information. Specifically, the visual information provision unit collects ambient audio using a high-sensitivity microphone and converts this audio into text using AI. The AI ​​utilizes speech recognition technology to accurately transcribe ambient audio into text and displays it on the display. For example, it converts ambient audio information such as conversations, warning sounds, and car horns into text in real time, enabling the hearing impaired to visually understand it. Furthermore, the visual information provision unit can analyze the collected audio information and highlight important information. For example, it can highlight emergency warning sounds and important conversations, enabling the hearing impaired to respond quickly. In addition, the visual information provision unit can collect user feedback and continuously improve the way visual information is provided. For example, based on feedback from the hearing impaired, it can adjust the text display method and font size to provide a more readable display. In this way, the visual information provision unit can provide effective visual information so that the hearing impaired can visually understand ambient audio information.

[0073] VR goggles provide information in both real and virtual spaces. Specifically, when worn by a user, VR goggles provide information in both the real and virtual worlds. Equipped with high-resolution displays and sensors, VR goggles can track the user's gaze and movements. This allows users to seamlessly move between real and virtual spaces to obtain necessary information. For example, visually impaired individuals can wear VR goggles to virtually recreate their surroundings, visually understanding the location of obstacles and their movement paths. Similarly, hearing-impaired individuals can wear VR goggles to visually display surrounding audio information, ensuring they don't miss important details. Furthermore, VR goggles can provide interactive content to enhance the user experience. For instance, users can touch specific objects in the virtual space to display detailed information or play audio guides. This allows VR goggles to support visually and hearing-impaired individuals in gaining a deeper understanding of their surroundings and navigating safely. Additionally, VR goggles can collect user feedback and continuously improve content and functionality. This allows VR goggles to constantly provide the latest technology and information, and offer optimal support tailored to the user's needs.

[0074] The analysis unit can collect surrounding visual information through a camera. For example, the analysis unit collects surrounding visual information in real time using a camera. For example, the analysis unit collects information on the location and movement paths of obstacles. For example, the analysis unit collects surrounding visual information using a camera and generates information to be provided to visually impaired individuals. This allows for the provision of appropriate information to visually impaired individuals by collecting surrounding visual information. Visual information includes, but is not limited to, images, videos, and the area to be collected. Some or all of the above-described processes in the analysis unit may be performed using AI or not. For example, the analysis unit can input visual information acquired by the camera into a generating AI and have the generating AI perform the analysis of the visual information.

[0075] The audio guidance unit can provide audio guidance to visually impaired persons based on collected visual information. For example, the audio guidance unit can provide audio guidance to visually impaired persons based on collected visual information. For example, the audio guidance unit can provide specific instructions by voice, such as, "There is an obstacle ahead. Turn right." The audio guidance unit can provide audio guidance in real time to help visually impaired persons move safely. In this way, safe movement can be supported by providing audio guidance to visually impaired persons. Visual information includes, but is not limited to, images, videos, and the area to be collected. Some or all of the processing described above in the audio guidance unit may be performed using AI or not. For example, the audio guidance unit can input collected visual information into a generating AI and have the generating AI perform the generation of audio guidance.

[0076] The visual information provider can collect ambient audio information through a microphone and provide it as visual information. For example, the visual information provider can collect ambient audio information through a microphone and provide it as visual information. For example, the visual information provider can convert ambient audio into text and display it on a screen. For example, the visual information provider can provide visual information in real time so that a person with a hearing impairment can visually grasp ambient audio information. This allows a person with a hearing impairment to understand their surroundings by providing them with visual information. Audio information includes, but is not limited to, the type of sound and the range to be collected. Some or all of the above processing in the visual information provider may be performed using AI or not. For example, the visual information provider can input audio information acquired by the microphone into a generating AI and have the generating AI perform the text conversion of the audio information.

[0077] The visual information provider can convert collected audio information into text and display it on a screen. For example, the visual information provider can convert collected audio information into text and display it on a screen. For example, the visual information provider can convert ambient sounds into text and display it on a screen. For example, the visual information provider can provide real-time visual information so that a person with a hearing impairment can visually grasp ambient audio information. This allows a person with a hearing impairment to visually grasp ambient audio information. Audio information includes, but is not limited to, the type of sound and the range to be collected. Some or all of the processing described above in the visual information provider may be performed using AI or not. For example, the visual information provider can input collected audio information into a generating AI and have the generating AI perform the conversion of the audio information into text.

[0078] The system includes electric wheelchairs. Electric wheelchairs are used, for example, to increase freedom of movement. Electric wheelchairs are designed, for example, to enable visually and hearing-impaired individuals to move safely. Electric wheelchairs feature, for example, intuitive operating interfaces to make them easy for users to operate. This allows for increased freedom of movement and safer mobility through the use of electric wheelchairs. Specific functions and specifications of electric wheelchairs include, but are not limited to, speed and operating methods.

[0079] VR goggles can provide information in both the real and virtual spaces. For example, when worn by a user, VR goggles provide information in both the real and virtual spaces. VR goggles can improve the user experience by providing visual information, for example. This enables information provision in the virtual space, thereby improving the user experience. The virtual space includes, but is not limited to, display content and interaction methods.

[0080] The analysis unit can estimate the user's emotions and adjust the accuracy of the analysis based on the estimated emotions. For example, if the user is tense, the analysis unit can increase the accuracy of the analysis to provide more detailed information. For example, if the user is relaxed, the analysis unit can adjust the accuracy of the analysis to provide only the minimum necessary information. For example, if the user is in a hurry, the analysis unit can adjust the accuracy of the analysis to provide information quickly. In this way, by adjusting the accuracy of the analysis according to the user's emotions, more appropriate information can be provided. Emotion estimation is achieved using an emotion estimation function, for example, using an emotion engine or a generative AI. The generative AI is a text generation AI (e.g., LLM) or a multimodal generation AI, but is not limited to such examples. Some or all of the above processing in the analysis unit may be performed using AI or not using AI. For example, the analysis unit can input user emotion data into a generative AI and have the generative AI perform emotion estimation.

[0081] The analysis unit can select the optimal analysis method by referring to the user's past travel history during analysis. For example, the analysis unit may select the optimal analysis method based on routes the user has frequently traveled in the past. For example, the analysis unit may select an analysis method to avoid congestion from the user's past travel history. For example, the analysis unit may analyze the user's past travel history and select the most efficient analysis method. In this way, the optimal analysis method can be selected by referring to the user's past travel history. The optimal analysis method includes, but is not limited to, examples of how past data is used and analysis algorithms. Some or all of the above processing in the analysis unit may be performed using AI or not using AI. For example, the analysis unit can input the user's past travel history data into a generating AI and have the generating AI perform the selection of the optimal analysis method.

[0082] The analysis unit can detect changes in the surrounding environment in real time during analysis and reflect them in the analysis results. For example, the analysis unit can detect changes in ambient temperature in real time and reflect them in the analysis results. For example, the analysis unit can detect changes in ambient sound volume in real time and reflect them in the analysis results. For example, the analysis unit can detect changes in ambient light intensity in real time and reflect them in the analysis results. In this way, changes in the surrounding environment can be detected in real time and reflected in the analysis results. Methods for detecting environmental changes in real time include, but are not limited to, the sensors used and detection algorithms. Some or all of the above processing in the analysis unit may be performed using AI or not. For example, the analysis unit can input ambient environmental data into a generating AI and have the generating AI perform the detection of environmental changes.

[0083] The analysis unit can estimate the user's emotions and determine the priority of the analysis results based on the estimated user emotions. For example, if the user is tense, the analysis unit will prioritize providing important information. For example, if the user is relaxed, the analysis unit will prioritize providing detailed information. For example, if the user is in a hurry, the analysis unit will prioritize providing information that needs to be provided quickly. In this way, by determining the priority of the analysis results according to the user's emotions, important information can be provided preferentially. Emotion estimation is achieved using an emotion estimation function, for example, using an emotion engine or generative AI. Generative AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the analysis unit may be performed using AI or not using AI. For example, the analysis unit can input user emotion data into a generative AI and have the generative AI perform emotion estimation.

[0084] The analysis unit can prioritize analyzing highly relevant information based on the user's geographical location information during analysis. For example, if the user is in a specific region, the analysis unit will prioritize analyzing information related to that region. For example, if the user is on the move, the analysis unit will prioritize analyzing information related to their destination. For example, if the user is in a specific facility, the analysis unit will prioritize analyzing information related to that facility. By prioritizing the analysis of highly relevant information based on the user's geographical location information, more appropriate information can be provided. Geographical location information includes, but is not limited to, GPS data and location accuracy. Some or all of the above processing in the analysis unit may be performed using AI or not. For example, the analysis unit can input the user's geographical location information into a generating AI and have the generating AI perform the analysis of highly relevant information.

[0085] The analysis unit can analyze a user's social media activity and related environmental information during the analysis process. For example, the analysis unit can analyze related environmental information based on the content a user posts on social media. For example, the analysis unit can analyze related environmental information based on information about accounts a user follows on social media. For example, the analysis unit can analyze related environmental information based on information about places a user has checked into on social media. In this way, by analyzing a user's social media activity, related environmental information can be analyzed. Social media activity includes, but is not limited to, the content of posts and activity frequency. Some or all of the above processing in the analysis unit may be performed using AI or not. For example, the analysis unit can input the user's social media activity data into a generating AI and have the generating AI perform the analysis of related environmental information.

[0086] The voice guidance unit can estimate the user's emotions and adjust the tone and speed of the voice guidance based on the estimated emotions. For example, if the user is nervous, the voice guidance unit will provide a calm and slow voice guidance. For example, if the user is relaxed, the voice guidance unit will provide a bright voice guidance. For example, if the user is in a hurry, the voice guidance unit will provide a fast voice guidance. By adjusting the tone and speed of the voice guidance according to the user's emotions, a more appropriate guidance can be provided. Emotion estimation is achieved using an emotion estimation function, for example, using an emotion engine or generative AI. Generative AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the voice guidance unit may be performed using AI or not using AI. For example, the voice guidance unit can input user emotion data into a generative AI and have the generative AI perform emotion estimation.

[0087] The audio guide unit can select the most suitable guide content by referring to the user's past travel history when providing audio guidance. For example, the audio guide unit can select the most suitable guide content based on routes the user has frequently traveled in the past. For example, the audio guide unit can select guide content to avoid congestion based on the user's past travel history. For example, the audio guide unit can analyze the user's past travel history and select the most efficient guide content. In this way, the optimal guide content can be selected by referring to the user's past travel history. The optimal guide content includes, but is not limited to, how past data is used and details of the guide content. Some or all of the above processing in the audio guide unit may be performed using AI or not. For example, the audio guide unit can input the user's past travel history data into a generating AI and have the generating AI perform the selection of the optimal guide content.

[0088] The audio guide unit can detect changes in the surrounding environment in real time when providing audio guidance and reflect them in the guide content. For example, the audio guide unit can detect changes in ambient temperature in real time and reflect them in the guide content. For example, the audio guide unit can detect changes in ambient volume in real time and reflect them in the guide content. For example, the audio guide unit can detect changes in ambient light intensity in real time and reflect them in the guide content. In this way, changes in the surrounding environment can be detected in real time and reflected in the guide content. Methods for detecting environmental changes in real time include, but are not limited to, the sensors used and detection algorithms. Some or all of the above processing in the audio guide unit may be performed using AI or not. For example, the audio guide unit can input ambient environmental data into a generating AI and have the generating AI perform the detection of environmental changes.

[0089] The voice guide unit can estimate the user's emotions and customize the content of the voice guide based on the estimated emotions. For example, if the user is nervous, the voice guide unit can provide a reassuring voice guide. For example, if the user is relaxed, the voice guide unit can provide a pleasant voice guide. For example, if the user is in a hurry, the voice guide unit can provide a voice guide that encourages quick action. By customizing the content of the voice guide according to the user's emotions, a more appropriate guide can be provided. Emotion estimation is achieved using an emotion estimation function, for example, using an emotion engine or generative AI. The generative AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the voice guide unit may be performed using AI or not. For example, the voice guide unit can input user emotion data into the generative AI and have the generative AI perform emotion estimation.

[0090] The audio guide unit can prioritize providing highly relevant information based on the user's geographical location when providing audio guidance. For example, if the user is in a specific region, the audio guide unit will prioritize providing information related to that region. For example, if the user is on the move, the audio guide unit will prioritize providing information related to their destination. For example, if the user is in a specific facility, the audio guide unit will prioritize providing information related to that facility. By prioritizing the provision of highly relevant information based on the user's geographical location, a more appropriate guide can be provided. Geographical location information includes, but is not limited to, GPS data and location accuracy. Some or all of the above processing in the audio guide unit may be performed using AI or not. For example, the audio guide unit can input the user's geographical location information into a generating AI and have the generating AI perform the provision of highly relevant information.

[0091] The audio guide unit can analyze the user's social media activity when providing audio guides and reflect relevant information in the guide content. For example, the audio guide unit can reflect relevant information in the guide content based on the content the user has posted on social media. For example, the audio guide unit can reflect relevant information in the guide content based on the information of accounts the user follows on social media. For example, the audio guide unit can reflect relevant information in the guide content based on the information of places the user has checked into on social media. In this way, by analyzing the user's social media activity, relevant information can be reflected in the guide content. Social media activity includes, but is not limited to, the content of posts and activity frequency. Some or all of the above processing in the audio guide unit may be performed using AI or not. For example, the audio guide unit can input the user's social media activity data into a generating AI and have the generating AI provide relevant information.

[0092] The visual information provider can estimate the user's emotions and adjust the display method of visual information based on the estimated user emotions. For example, if the user is tense, the visual information provider can provide a simple and highly visible display method. For example, if the user is relaxed, the visual information provider can provide a display method that includes detailed information. For example, if the user is in a hurry, the visual information provider can provide a display method that gets straight to the point. In this way, by adjusting the display method of visual information according to the user's emotions, more appropriate information can be provided. Emotion estimation is achieved using an emotion estimation function, for example, using an emotion engine or a generative AI. The generative AI is, but is not limited to, a text generation AI (e.g., LLM) or a multimodal generation AI. Some or all of the above processing in the visual information provider may be performed using AI or not using AI. For example, the visual information provider can input user emotion data into a generative AI and have the generative AI perform emotion estimation.

[0093] The visual information provider can select the optimal information display method by referring to the user's past travel history when providing visual information. For example, the visual information provider can select the optimal information display method based on routes the user has frequently traveled in the past. For example, the visual information provider can select an information display method to avoid congestion based on the user's past travel history. For example, the visual information provider can analyze the user's past travel history and select the most efficient information display method. In this way, the optimal information display method can be selected by referring to the user's past travel history. The optimal information display method includes, but is not limited to, the use of past data and details of the display method. Some or all of the above processing in the visual information provider may be performed using AI or not. For example, the visual information provider can input the user's past travel history data into a generating AI and have the generating AI perform the selection of the optimal information display method.

[0094] The visual information provider can detect changes in the surrounding environment in real time when providing visual information and reflect them in the displayed content. For example, the visual information provider can detect changes in ambient temperature in real time and reflect them in the displayed content. For example, the visual information provider can detect changes in ambient volume in real time and reflect them in the displayed content. For example, the visual information provider can detect changes in ambient light intensity in real time and reflect them in the displayed content. In this way, changes in the surrounding environment can be detected in real time and reflected in the displayed content. Methods for detecting environmental changes in real time include, but are not limited to, the sensors used and detection algorithms. Some or all of the above processing in the visual information provider may be performed using AI or not. For example, the visual information provider can input ambient environmental data into a generating AI and have the generating AI perform the detection of environmental changes.

[0095] The visual information provider can estimate the user's emotions and prioritize visual information based on the estimated emotions. For example, if the user is tense, the visual information provider will prioritize displaying important information. For example, if the user is relaxed, the visual information provider will prioritize displaying detailed information. For example, if the user is in a hurry, the visual information provider will prioritize displaying information that needs to be provided quickly. In this way, by prioritizing visual information according to the user's emotions, important information can be provided preferentially. Emotion estimation is achieved using an emotion estimation function, for example, using an emotion engine or generative AI. Generative AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the visual information provider may be performed using AI or not. For example, the visual information provider can input user emotion data into a generative AI and have the generative AI perform emotion estimation.

[0096] The visual information provider can prioritize displaying highly relevant information based on the user's geographical location when providing visual information. For example, if the user is in a specific region, the visual information provider will prioritize displaying information related to that region. For example, if the user is on the move, the visual information provider will prioritize displaying information related to their destination. For example, if the user is in a specific facility, the visual information provider will prioritize displaying information related to that facility. This allows for the provision of more appropriate information by prioritizing the display of highly relevant information based on the user's geographical location. Geographical location information includes, but is not limited to, GPS data and location accuracy. Some or all of the above processing in the visual information provider may be performed using AI or not. For example, the visual information provider can input the user's geographical location information into a generating AI and have the generating AI display highly relevant information.

[0097] The visual information provider can analyze the user's social media activity and reflect relevant information in the displayed content when providing visual information. For example, the visual information provider can reflect relevant information in the displayed content based on the content the user has posted on social media. For example, the visual information provider can reflect relevant information in the displayed content based on information about accounts the user follows on social media. For example, the visual information provider can reflect relevant information in the displayed content based on information about places the user has checked into on social media. In this way, by analyzing the user's social media activity, relevant information can be reflected in the displayed content. Social media activity includes, but is not limited to, posts and activity frequency. Some or all of the above processing in the visual information provider may be performed using AI or not. For example, the visual information provider can input the user's social media activity data into a generating AI and have the generating AI display relevant information.

[0098] VR goggles can estimate the user's emotions and adjust the displayed content of the virtual space based on the estimated emotions. For example, if the user is tense, the VR goggles can display a calm virtual space. For example, if the user is relaxed, the VR goggles can display a bright virtual space. For example, if the user is excited, the VR goggles can display a visually stimulating virtual space. By adjusting the displayed content of the virtual space according to the user's emotions, more appropriate information can be provided. Emotion estimation is achieved using an emotion estimation function, for example, using an emotion engine or generative AI. Generative AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in VR goggles may be performed using AI or not. For example, VR goggles can input user emotion data into a generative AI and have the generative AI perform emotion estimation.

[0099] VR goggles can generate an optimal virtual space by referencing the user's past travel history when the VR goggles are in use. For example, VR goggles can generate an optimal virtual space based on places the user has visited in the past. For example, VR goggles can generate a virtual space to avoid congestion based on the user's past travel history. For example, VR goggles can analyze the user's past travel history and generate the most efficient virtual space. In this way, an optimal virtual space can be generated by referring to the user's past travel history. An optimal virtual space includes, but is not limited to, how past data is used and details of the virtual space. Some or all of the above processing in VR goggles may be performed using AI or not. For example, VR goggles can input the user's past travel history data into a generating AI and have the generating AI perform the generation of an optimal virtual space.

[0100] VR goggles can detect changes in the surrounding environment in real time when the VR goggles are in use and reflect them in the virtual space. For example, VR goggles can detect changes in ambient temperature in real time and reflect them in the virtual space. For example, VR goggles can detect changes in ambient volume in real time and reflect them in the virtual space. For example, VR goggles can detect changes in ambient light intensity in real time and reflect them in the virtual space. In this way, changes in the surrounding environment can be detected in real time and reflected in the virtual space. Methods for detecting environmental changes in real time include, but are not limited to, the sensors used and detection algorithms. Some or all of the above processing in VR goggles may be performed using AI or not. For example, VR goggles can input ambient environmental data into a generating AI and have the generating AI perform the detection of environmental changes.

[0101] VR goggles can estimate the user's emotions and prioritize virtual spaces based on those emotions. For example, if the user is tense, the VR goggles will prioritize displaying relaxing virtual spaces. If the user is relaxed, the VR goggles will prioritize displaying enjoyable virtual spaces. If the user is excited, the VR goggles will prioritize displaying visually stimulating virtual spaces. By prioritizing virtual spaces according to the user's emotions, important information can be provided preferentially. Emotion estimation is achieved using an emotion estimation function, for example, with an emotion engine or generative AI. Generative AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in VR goggles may be performed using AI or not. For example, VR goggles can input user emotion data into a generative AI and have the generative AI perform emotion estimation.

[0102] VR goggles can generate highly relevant virtual spaces based on the user's geographical location information when the VR goggles are in use. For example, if the user is in a specific region, the VR goggles will generate a virtual space related to that region. For example, if the user is on the move, the VR goggles will generate a virtual space related to the destination. For example, if the user is in a specific facility, the VR goggles will generate a virtual space related to that facility. This allows for the provision of more appropriate information by generating highly relevant virtual spaces based on the user's geographical location information. Geographical location information includes, but is not limited to, GPS data and location accuracy. Some or all of the above processing in VR goggles may be performed using AI or not. For example, the VR goggles can input the user's geographical location information into a generating AI and have the generating AI perform the generation of highly relevant virtual spaces.

[0103] VR goggles can analyze a user's social media activity while they are in use and reflect relevant information in the virtual space. For example, VR goggles can reflect relevant information in the virtual space based on the content a user has posted on social media. For example, VR goggles can reflect relevant information in the virtual space based on information about accounts a user follows on social media. For example, VR goggles can reflect relevant information in the virtual space based on information about places a user has checked into on social media. In this way, by analyzing a user's social media activity, relevant information can be reflected in the virtual space. Social media activity includes, but is not limited to, the content of posts and activity frequency. Some or all of the above processing in VR goggles may be performed using AI or not. For example, VR goggles can input the user's social media activity data into a generating AI and have the generating AI perform the reflection of relevant information.

[0104] An electric wheelchair can estimate the user's emotions and adjust its operation based on those emotions. For example, if the user is tense, the electric wheelchair will adjust its operation slowly. If the user is relaxed, the electric wheelchair will adjust its operation smoothly. If the user is in a hurry, the electric wheelchair will adjust its operation quickly. By adjusting the electric wheelchair's operation according to the user's emotions, it can provide more appropriate operation. Emotion estimation is achieved using an emotion estimation function, such as an emotion engine or generative AI. Generative AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in an electric wheelchair may be performed using AI or not. For example, the electric wheelchair can input user emotion data into a generative AI and have the generative AI perform emotion estimation.

[0105] An electric wheelchair can select the optimal travel route by referring to the user's past travel history when using the electric wheelchair. For example, the electric wheelchair can select the optimal travel route based on routes the user has frequently traveled in the past. For example, the electric wheelchair can select a travel route to avoid congestion based on the user's past travel history. For example, the electric wheelchair can analyze the user's past travel history and select the most efficient travel route. In this way, the optimal travel route can be selected by referring to the user's past travel history. The optimal travel route includes, but is not limited to, how past data is used and details of route selection. Some or all of the above processing in an electric wheelchair may be performed using AI or not. For example, the electric wheelchair can input the user's past travel history data into a generating AI and have the generating AI perform the selection of the optimal travel route.

[0106] An electric wheelchair can detect changes in the surrounding environment in real time while in use and reflect them in its movement path. For example, an electric wheelchair can detect changes in ambient temperature in real time and reflect them in its movement path. For example, an electric wheelchair can detect changes in ambient noise in real time and reflect them in its movement path. For example, an electric wheelchair can detect changes in ambient light intensity in real time and reflect them in its movement path. In this way, changes in the surrounding environment can be detected in real time and reflected in the movement path. Methods for detecting environmental changes in real time include, but are not limited to, the sensors used and detection algorithms. Some or all of the above processing in an electric wheelchair may be performed using AI or not. For example, an electric wheelchair can input ambient environmental data into a generating AI and have the generating AI perform the detection of environmental changes.

[0107] An electric wheelchair can estimate the user's emotions and determine the priority of its actions based on those emotions. For example, if the user is tense, the electric wheelchair will prioritize important actions. If the user is relaxed, the electric wheelchair will prioritize comfortable actions. If the user is in a hurry, the electric wheelchair will prioritize quick actions. This allows the electric wheelchair to prioritize important actions by determining the priority of its actions according to the user's emotions. Emotion estimation is achieved using an emotion estimation function, for example, using an emotion engine or generative AI. Generative AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in an electric wheelchair may be performed using AI or not. For example, the electric wheelchair can input user emotion data into a generative AI and have the generative AI perform emotion estimation.

[0108] An electric wheelchair can select a highly relevant travel route based on the user's geographical location information when using the electric wheelchair. For example, if the user is in a specific area, the electric wheelchair will select a travel route relevant to that area. For example, if the user is on the move, the electric wheelchair will select a travel route relevant to the destination. For example, if the user is in a specific facility, the electric wheelchair will select a travel route relevant to that facility. By selecting a highly relevant travel route based on the user's geographical location information, a more appropriate travel route can be provided. Geographical location information includes, but is not limited to, GPS data and location accuracy. Some or all of the above processing in the electric wheelchair may be performed using AI or not. For example, the electric wheelchair can input the user's geographical location information into a generating AI and have the generating AI perform the selection of a highly relevant travel route.

[0109] An electric wheelchair can analyze a user's social media activity while they are using it and reflect relevant information in their travel route. For example, the electric wheelchair can reflect relevant information in its travel route based on the content the user has posted on social media. For example, the electric wheelchair can reflect relevant information in its travel route based on the information of accounts the user follows on social media. For example, the electric wheelchair can reflect relevant information in its travel route based on the information of places the user has checked into on social media. In this way, by analyzing the user's social media activity, relevant information can be reflected in their travel route. Social media activity includes, but is not limited to, the content of posts and activity frequency. Some or all of the above processing in the electric wheelchair may be performed using AI or not. For example, the electric wheelchair can input the user's social media activity data into a generating AI and have the generating AI perform the reflection of relevant information.

[0110] The system according to the embodiment is not limited to the example described above, and various modifications are possible, for example, as follows.

[0111] The analysis unit can monitor the user's health status and adjust the accuracy of the analysis based on that status. For example, if the user's heart rate is high, the analysis unit can ensure the user's safety by providing detailed information. Conversely, if the user's heart rate is stable, the analysis unit can reduce the user's burden by providing only the minimum necessary information. Furthermore, if the user's blood pressure is high, the analysis unit can prioritize providing information to reduce stress. This enables the provision of appropriate information tailored to the user's health status.

[0112] The audio guide unit can automatically switch the language of the audio guide based on the user's language settings. For example, if the user selects English, the audio guide unit will provide the guide in English. If the user selects Japanese, the guide will provide the guide in Japanese. Furthermore, if the user uses multiple languages, the audio guide unit can provide the guide in the appropriate language according to the user's language settings. This enables flexible audio guidance that adapts to the user's language settings.

[0113] The visual information provider can adjust how information is displayed according to the user's degree of visual impairment. For example, if the user is completely blind, the visual information provider will prioritize providing audio guidance. If the user has low vision, the visual information provider will improve visibility by increasing the font size or enhancing the contrast. Furthermore, if the user has color vision deficiency, the visual information provider can adjust the use of colors to provide information. This makes it possible to provide appropriate information according to the user's degree of visual impairment.

[0114] VR goggles can change the theme of the virtual space according to the user's preferences. For example, if a user prefers nature, the VR goggles can provide a virtual space of a forest or the sea. If a user prefers cities, it can provide a virtual space that recreates a city landscape. Furthermore, if a user has a specific hobby, it can provide a virtual space related to that hobby. This provides a customized virtual space that suits the user's preferences, improving the user experience.

[0115] Electric wheelchairs can adjust their operation according to the user's weight. For example, if the user is light, the electric wheelchair provides smooth operation. If the user is heavy, the electric wheelchair provides stable operation. Furthermore, if the user's weight changes, the electric wheelchair can automatically adjust its operation to provide optimal mobility. This ensures that appropriate operation is provided according to the user's weight, enabling safe and comfortable movement.

[0116] The analysis unit can estimate the user's emotions and adjust the display method of the analysis results based on the estimated emotions. For example, if the user is nervous, the analysis unit provides a simple and highly visible display method. If the user is relaxed, it provides a display method that includes detailed information. Furthermore, if the user is in a hurry, it can provide a display method that gets straight to the point. This makes it possible to provide appropriate information according to the user's emotions.

[0117] The audio guide unit can estimate the user's emotions and customize the content of the audio guide based on those emotions. For example, if the user is nervous, it can provide an audio guide that provides a sense of reassurance. If the user is relaxed, it can provide an audio guide that makes them feel happy. Furthermore, if the user is in a hurry, it can provide an audio guide that encourages quick action. This ensures that the audio guide is appropriate to the user's emotions.

[0118] The visual information provider can estimate the user's emotions and adjust the display method of visual information based on those emotions. For example, if the user is tense, it can provide a simple and highly visible display method. If the user is relaxed, it can provide a display method that includes detailed information. Furthermore, if the user is in a hurry, it can provide a display method that gets straight to the point. This makes it possible to provide appropriate information according to the user's emotions.

[0119] VR goggles can estimate the user's emotions and adjust the displayed content of the virtual space based on those emotions. For example, if the user is tense, a calm virtual space can be displayed. If the user is relaxed, a bright virtual space can be displayed. Furthermore, if the user is excited, a visually stimulating virtual space can be displayed. This provides an appropriate virtual space that matches the user's emotions.

[0120] The electric wheelchair can estimate the user's emotions and adjust its operation based on those emotions. For example, if the user is tense, the electric wheelchair's operation will be adjusted slowly. If the user is relaxed, the electric wheelchair's operation will be adjusted smoothly. Furthermore, if the user is in a hurry, the electric wheelchair's operation can be adjusted quickly. This provides appropriate operation according to the user's emotions.

[0121] The following briefly describes the processing flow for example form 2.

[0122] Step 1: The analysis unit is the part that analyzes the environment and includes AI processing. For example, the analysis unit collects surrounding visual information through a camera and collects information on the location and movement paths of obstacles. The analysis unit can collect surrounding visual information in real time using a camera. Step 2: The audio guidance unit is the part that provides audio guidance to visually impaired individuals based on the information analyzed by the analysis unit, and includes AI processing. For example, the audio guidance unit provides audio guidance to visually impaired individuals based on the collected visual information. The audio guidance unit can provide specific instructions in voice, such as "There is an obstacle ahead. Turn right," and can provide real-time audio guidance to enable visually impaired individuals to move safely. Step 3: The visual information provision unit is the part that provides visual information to the hearing impaired based on the information analyzed by the analysis unit, and includes AI processing. For example, the visual information provision unit collects ambient audio information through a microphone and provides it as visual information. The visual information provision unit converts ambient audio into text and displays it on the screen. The visual information provision unit can provide visual information in real time so that the hearing impaired can visually grasp the ambient audio information. Step 4: VR goggles provide information in both the real and virtual spaces. When worn by the user, VR goggles provide information in both the real and virtual spaces. VR goggles can improve the user experience by providing visual information.

[0123] 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.

[0124] Data generation model 58 is a form of 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> Examples of generative AI include text generation AI, image generation AI, and multimodal generation AI. 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 (e.g., still image data or video data). The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference result in one or more data formats from audio data, text data, and image data. The data generation model 58 includes, for example, text generation AI, image generation AI, and multimodal generation AI. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specific processing unit 290 performs the specific processing described above using the data generation model 58. The data generation model 58 may be a fine-tuned model that outputs inference results from prompts that do not contain instructions, in which case the data generation model 58 can output inference results from prompts that do not contain instructions. In the data processing device 12, etc., there are multiple types of data generation models 58, and the data generation model 58 includes AI other than generative AI. AI other than generative AI includes, for example, linear regression, logistic regression, decision trees, random forests, support vector machines (SVMs), k-means clustering, convolutional neural networks (CNNs), recurrent neural networks (RNNs), generative adversarial networks (GANs), or naive Bayes, and can perform various processes, but is not limited to these examples. Also, the AI ​​may be an AI agent. Furthermore, when the processing of each of the above parts is performed by the AI, the processing may be performed by the AI ​​in part or in whole, but is not limited to this example.Furthermore, processing performed by AI, including generative AI, may be replaced with rule-based processing, and rule-based processing may be replaced with processing performed by AI, including generative AI.

[0125] Furthermore, the processing performed by the data processing system 10 described above is carried out by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart device 14, but it may also be carried out by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart device 14. In addition, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the smart device 14 or an external device, and the smart device 14 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0126] Each of the multiple elements described above, including the analysis unit, voice guidance unit, visual information provision unit, VR goggles, and electric wheelchair, is implemented, for example, by at least one of the smart device 14 and the data processing device 12. For example, the analysis unit collects surrounding visual information using the camera 42 of the smart device 14 and analyzes it using the specific processing unit 290 of the data processing device 12. The voice guidance unit is implemented, for example, by the control unit 46A of the smart device 14 and provides voice guidance to visually impaired people based on the analyzed information. The visual information provision unit collects surrounding audio information using the microphone 38B of the smart device 14, converts it into text using the specific processing unit 290 of the data processing device 12, and displays it on the display 40A of the smart device 14. The VR goggles provide information in real and virtual space, for example, by the control unit 46A of the smart device 14. The electric wheelchair is operated, for example, by the control unit 46A of the smart device 14 and supports the user's movement. The correspondence between each unit and the device or control unit is not limited to the example described above and can be modified in various ways.

[0127] [Second Embodiment] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0128] 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.

[0129] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. 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 and / or LAN.

[0130] 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.

[0131] The microphone 238 receives voice signals from the user and accepts instructions from the user. The microphone 238 captures the voice signals from the user, 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.

[0132] 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, which captures images of the area around the user (for example, an imaging range defined by a field of view equivalent to the field of vision of a typical healthy person).

[0133] 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.

[0134] 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 by the processor 28. The storage 32 stores the specific processing program 56.

[0135] The processor 28 reads a 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 acting as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0136] 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. The identification processing unit 290 can estimate the user's emotions using the emotion identification model 59 and perform identification processing using the user's emotions. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotions, including but not limited to these examples. Furthermore, emotion estimation and prediction also include, for example, emotion analysis.

[0137] In the smart glasses 214, specific processing is performed by the processor 46. The storage 50 stores a specific processing program 60. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 acting as a control unit 46A according to the specific processing program 60 executed on the RAM 48. The smart glasses 214 also have a data generation model 58 and an emotion identification model 59, similar to the data generation model and emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0138] Furthermore, other devices besides the data processing device 12 may also have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 obtains processing results (such as prediction results) using the data generation model 58 by communicating with the server device that has the data generation model 58. Also, the data processing device 12 may be a server device or a terminal device owned by the user (for example, a mobile phone, robot, home appliance, etc.).

[0139] 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.

[0140] The data generation model 58 is a so-called generative AI. An example of a data generation model 58 is a generative AI such as ChatGPT. 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 inference data such as audio data representing speech, text data representing text, and image data representing images (e.g., still image data or video data). The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference result in one or more data formats such as audio data, text data, and image data. The data generation model 58 includes, for example, text generation AI, image generation AI, and multimodal generation AI. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specific processing unit 290 performs the specific processing described above using the data generation model 58. The data generation model 58 may be a fine-tuned model that outputs inference results from prompts that do not contain instructions, in which case the data generation model 58 can output inference results from prompts that do not contain instructions. In the data processing device 12, etc., there are multiple types of data generation models 58, and the data generation model 58 includes AI other than generative AI. AI other than generative AI includes, for example, linear regression, logistic regression, decision trees, random forests, support vector machines (SVM), k-means clustering, convolutional neural networks (CNN), recurrent neural networks (RNN), generative adversarial networks (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. Also, the AI ​​may be an AI agent. Furthermore, when the processing of each part described above is performed by the AI, the processing may be performed by the AI ​​in part or in whole, but is not limited to this example. Also, processing performed by an AI including a generative AI may be replaced by rule-based processing, and rule-based processing may be replaced by processing performed by an AI including a generative AI.

[0141] The data processing system 210 according to the second embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 210 is performed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart glasses 214, but it may also be performed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart glasses 214. In addition, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the smart glasses 214 or an external device, and the smart glasses 214 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0142] Each of the multiple elements described above, including the analysis unit, voice guidance unit, visual information provision unit, VR goggles, and electric wheelchair, is implemented, for example, in at least one of the smart glasses 214 and the data processing unit 12. For example, the analysis unit collects ambient visual information using the camera 42 of the smart glasses 214 and analyzes it using the identification processing unit 290 of the data processing unit 12. The voice guidance unit is implemented, for example, by the control unit 46A of the smart glasses 214 and provides voice guidance to the visually impaired based on the analyzed information. The visual information provision unit collects ambient audio information using the microphone 238 of the smart glasses 214, converts it into text using the identification processing unit 290 of the data processing unit 12, and displays it on the display of the smart glasses 214. The VR goggles provide information in real and virtual space, for example, by the control unit 46A of the smart glasses 214. The electric wheelchair is operated, for example, by the control unit 46A of the smart glasses 214 and supports the user's movement. The correspondence between each unit and the device or control unit is not limited to the examples described above and can be modified in various ways.

[0143] [Third Embodiment] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0144] 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.

[0145] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. 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 and / or LAN.

[0146] 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.

[0147] The microphone 238 receives voice signals from the user and accepts instructions from the user. The microphone 238 captures the voice signals from the user, 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.

[0148] 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, which captures images of the area around the user (for example, an imaging range defined by a field of view equivalent to the field of vision of a typical healthy person).

[0149] 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.

[0150] 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.

[0151] The processor 28 reads a 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 acting as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0152] 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. The identification processing unit 290 can estimate the user's emotions using the emotion identification model 59 and perform identification processing using the user's emotions. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotions, including but not limited to these examples. Furthermore, emotion estimation and prediction also include, for example, emotion analysis.

[0153] In the headset terminal 314, specific processing is performed by the processor 46. The storage 50 stores a specific program 60. The processor 46 reads the specific program 60 from the storage 50 and executes the read specific program 60 on the RAM 48. The specific processing is realized by the processor 46 acting as a control unit 46A according to the specific program 60 executed on the RAM 48. The headset terminal 314 also has a data generation model 58 and an emotion identification model 59, similar to the data generation model and emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0154] Furthermore, other devices besides the data processing device 12 may also have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 obtains processing results (such as prediction results) using the data generation model 58 by communicating with the server device that has the data generation model 58. Also, the data processing device 12 may be a server device or a terminal device owned by the user (for example, a mobile phone, robot, home appliance, etc.).

[0155] 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.

[0156] The data generation model 58 is a so-called generative AI. An example of a data generation model 58 is a generative AI such as ChatGPT. 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 inference data such as audio data representing speech, text data representing text, and image data representing images (e.g., still image data or video data). The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference result in one or more data formats such as audio data, text data, and image data. The data generation model 58 includes, for example, text generation AI, image generation AI, and multimodal generation AI. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specific processing unit 290 performs the specific processing described above using the data generation model 58. The data generation model 58 may be a fine-tuned model that outputs inference results from prompts that do not contain instructions, in which case the data generation model 58 can output inference results from prompts that do not contain instructions. In the data processing device 12, etc., there are multiple types of data generation models 58, and the data generation model 58 includes AI other than generative AI. AI other than generative AI includes, for example, linear regression, logistic regression, decision trees, random forests, support vector machines (SVM), k-means clustering, convolutional neural networks (CNN), recurrent neural networks (RNN), generative adversarial networks (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. Also, the AI ​​may be an AI agent. Furthermore, when the processing of each part described above is performed by the AI, the processing may be performed by the AI ​​in part or in whole, but is not limited to this example. Also, processing performed by an AI including a generative AI may be replaced by rule-based processing, and rule-based processing may be replaced by processing performed by an AI including a generative AI.

[0157] The data processing system 310 according to the third embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 310 is performed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the headset terminal 314, but may also be performed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the headset terminal 314. In addition, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the headset terminal 314 or an external device, and the headset terminal 314 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0158] Each of the multiple elements described above, including the analysis unit, voice guidance unit, visual information provision unit, VR goggles, and electric wheelchair, is implemented, for example, by at least one of the headset terminal 314 and the data processing unit 12. For example, the analysis unit collects ambient visual information using the camera 42 of the headset terminal 314 and analyzes it using the specific processing unit 290 of the data processing unit 12. The voice guidance unit is implemented, for example, by the control unit 46A of the headset terminal 314 and provides voice guidance to the visually impaired based on the analyzed information. The visual information provision unit collects ambient audio information using the microphone 238 of the headset terminal 314, converts it into text using the specific processing unit 290 of the data processing unit 12, and displays it on the display 343 of the headset terminal 314. The VR goggles provide information in real and virtual space, for example, by the control unit 46A of the headset terminal 314. The electric wheelchair is operated, for example, by the control unit 46A of the headset terminal 314 and supports the user's movement. The correspondence between each part and the device or control unit is not limited to the examples described above, and various modifications are possible.

[0159] [Fourth Embodiment] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0160] 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.

[0161] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. 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 and / or LAN.

[0162] 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.

[0163] The microphone 238 receives voice signals from the user and accepts instructions from the user. The microphone 238 captures the voice signals from the user, 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.

[0164] 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 image sensor or CCD image sensor, which captures images of the area around the user (for example, an imaging range defined by a field of view equivalent to the field of vision of a typical healthy person).

[0165] 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.

[0166] 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. The robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0167] 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.

[0168] The processor 28 reads a 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 acting as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0169] 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. The identification processing unit 290 can estimate the user's emotions using the emotion identification model 59 and perform identification processing using the user's emotions. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotions, including but not limited to these examples. Furthermore, emotion estimation and prediction also include, for example, emotion analysis.

[0170] In robot 414, specific processing is performed by processor 46. A specific program 60 is stored in storage 50. Processor 46 reads the specific program 60 from storage 50 and executes it on RAM 48. The specific processing is achieved by processor 46 acting as a control unit 46A according to the specific program 60 executed on RAM 48. Robot 414 also has data generation model 58 and emotion identification model 59, similar to those of the robot, and can perform processing similar to that of the specific processing unit 290 using these models.

[0171] Furthermore, other devices besides the data processing device 12 may also have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 obtains processing results (such as prediction results) using the data generation model 58 by communicating with the server device that has the data generation model 58. Also, the data processing device 12 may be a server device or a terminal device owned by the user (for example, a mobile phone, robot, home appliance, etc.).

[0172] 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.

[0173] The data generation model 58 is a so-called generative AI. An example of a data generation model 58 is a generative AI such as ChatGPT. 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 inference data such as audio data representing speech, text data representing text, and image data representing images (e.g., still image data or video data). The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference result in one or more data formats such as audio data, text data, and image data. The data generation model 58 includes, for example, text generation AI, image generation AI, and multimodal generation AI. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specific processing unit 290 performs the specific processing described above using the data generation model 58. The data generation model 58 may be a fine-tuned model that outputs inference results from prompts that do not contain instructions, in which case the data generation model 58 can output inference results from prompts that do not contain instructions. In the data processing device 12, etc., there are multiple types of data generation models 58, and the data generation model 58 includes AI other than generative AI. AI other than generative AI includes, for example, linear regression, logistic regression, decision trees, random forests, support vector machines (SVM), k-means clustering, convolutional neural networks (CNN), recurrent neural networks (RNN), generative adversarial networks (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. Also, the AI ​​may be an AI agent. Furthermore, when the processing of each part described above is performed by the AI, the processing may be performed by the AI ​​in part or in whole, but is not limited to this example. Also, processing performed by an AI including a generative AI may be replaced by rule-based processing, and rule-based processing may be replaced by processing performed by an AI including a generative AI.

[0174] The data processing system 410 according to the fourth embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 410 is performed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the robot 414, but it may also be performed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the robot 414. In addition, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the robot 414 or an external device, and the robot 414 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0175] Each of the multiple elements described above, including the analysis unit, voice guidance unit, visual information provision unit, VR goggles, and electric wheelchair, is implemented, for example, in at least one of the robot 414 and the data processing unit 12. For example, the analysis unit collects visual information of the surroundings using the camera 42 of the robot 414 and analyzes it using the specific processing unit 290 of the data processing unit 12. The voice guidance unit is implemented, for example, by the control unit 46A of the robot 414 and provides voice guidance to visually impaired people based on the analyzed information. The visual information provision unit collects audio information of the surroundings using the microphone 238 of the robot 414, converts it into text using the specific processing unit 290 of the data processing unit 12, and displays it on the display of the robot 414. The VR goggles provide information in real and virtual space, for example, by the control unit 46A of the robot 414. The electric wheelchair is operated, for example, by the control unit 46A of the robot 414 and supports the user's movement. The correspondence between each unit and the devices and control units is not limited to the examples described above and can be modified in various ways.

[0176] 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.

[0177] Figure 9 shows the 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.

[0178] 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.

[0179] 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.

[0180] 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, and motorcycles, 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 based, for example, 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.

[0181] 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."

[0182] 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.

[0183] 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 method for the specific process may be used, which includes computer 22 and multiple other computers.

[0184] 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.

[0185] 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.

[0186] 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.

[0187] 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.

[0188] 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.

[0189] 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.

[0190] 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.

[0191] Furthermore, although the above-described examples were divided into four embodiments, some or all of these embodiments may be combined. Also, the smart device 14, smart glasses 214, headset terminal 314, and robot 414 are just examples, and they may be combined, or other devices may be used. Also, although the above-described examples were divided into two embodiments, Embodiment 1 and Embodiment 2, these may be combined.

[0192] 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 other things 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.

[0193] 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 to be incorporated by reference.

[0194] (Note 1) An analysis unit for analyzing the environment, An audio guide unit provides audio guidance to visually impaired persons based on the information analyzed by the aforementioned analysis unit, A visual information providing unit provides visual information to a person with a hearing impairment based on the information analyzed by the aforementioned analysis unit, Equipped with VR goggles, A system characterized by the following features. (Note 2) The aforementioned analysis unit, The camera collects visual information about the surroundings. The system described in Appendix 1, characterized by the features described herein. (Note 3) The aforementioned audio guide unit is Provide audio guides to visually impaired individuals based on collected visual information. The system described in Appendix 1, characterized by the features described herein. (Note 4) The aforementioned visual information providing unit is It collects ambient audio information through a microphone and presents it as visual information. The system described in Appendix 1, characterized by the features described herein. (Note 5) The aforementioned visual information providing unit is The collected audio information is converted into text and displayed on the screen. The system described in Appendix 1, characterized by the features described herein. (Note 6) Equipped with electric wheelchairs The system described in Appendix 1, characterized by the features described herein. (Note 7) The aforementioned VR goggles are In addition to providing information in real-world spaces, we also provide information in virtual spaces. The system described in Appendix 1, characterized by the features described herein. (Note 8) The aforementioned analysis unit, It estimates the user's emotions and adjusts the accuracy of the analysis based on the estimated user emotions. The system described in Appendix 1, characterized by the features described herein. (Note 9) The aforementioned analysis unit, During analysis, the system selects the optimal analysis method by referring to the user's past movement history. The system described in Appendix 1, characterized by the features described herein. (Note 10) The aforementioned analysis unit, During analysis, changes in the surrounding environment are detected in real time and reflected in the analysis results. The system described in Appendix 1, characterized by the features described herein. (Note 11) The aforementioned analysis unit, It estimates the user's emotions and prioritizes the analysis results based on the estimated user emotions. The system described in Appendix 1, characterized by the features described herein. (Note 12) The aforementioned analysis unit, During analysis, the system prioritizes analyzing information that is highly relevant based on the user's geographical location. The system described in Appendix 1, characterized by the features described herein. (Note 13) The aforementioned analysis unit, During the analysis, the user's social media activity is analyzed, and related environmental information is also analyzed. The system described in Appendix 1, characterized by the features described herein. (Note 14) The aforementioned audio guide unit is It estimates the user's emotions and adjusts the tone and speed of the voice guide based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 15) The aforementioned audio guide unit is When providing audio guides, the system selects the most appropriate guide content by referring to the user's past travel history. The system described in Appendix 1, characterized by the features described herein. (Note 16) The aforementioned audio guide unit is When providing audio guides, the system detects changes in the surrounding environment in real time and reflects them in the guide content. The system described in Appendix 1, characterized by the features described herein. (Note 17) The aforementioned audio guide unit is It estimates the user's emotions and customizes the content of the voice guide based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 18) The aforementioned audio guide unit is When providing audio guides, the system prioritizes providing highly relevant information based on the user's geographical location. The system described in Appendix 1, characterized by the features described herein. (Note 19) The aforementioned audio guide unit is When providing audio guides, analyze users' social media activity and incorporate relevant information into the guide content. The system described in Appendix 1, characterized by the features described herein. (Note 20) The aforementioned visual information providing unit is It estimates the user's emotions and adjusts how visual information is displayed based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 21) The aforementioned visual information providing unit is When providing visual information, the system selects the optimal information display method by referring to the user's past movement history. The system described in Appendix 1, characterized by the features described herein. (Note 22) The aforementioned visual information providing unit is When providing visual information, the system detects changes in the surrounding environment in real time and reflects them in the displayed content. The system described in Appendix 1, characterized by the features described herein. (Note 23) The aforementioned visual information providing unit is It estimates the user's emotions and prioritizes visual information based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 24) The aforementioned visual information providing unit is When providing visual information, the system prioritizes displaying information that is highly relevant based on the user's geographical location. The system described in Appendix 1, characterized by the features described herein. (Note 25) The aforementioned visual information providing unit is When providing visual information, analyze the user's social media activity and reflect relevant information in the displayed content. The system described in Appendix 1, characterized by the features described herein. (Note 26) The aforementioned VR goggles are It estimates the user's emotions and adjusts the display content in the virtual space based on the estimated user emotions. The system described in Appendix 1, characterized by the features described herein. (Note 27) The aforementioned VR goggles are When using VR goggles, the system generates an optimal virtual space by referencing the user's past movement history. The system described in Appendix 1, characterized by the features described herein. (Note 28) The aforementioned VR goggles are When using VR goggles, the system detects changes in the surrounding environment in real time and reflects them in the virtual space. The system described in Appendix 1, characterized by the features described herein. (Note 29) The aforementioned VR goggles are It estimates the user's emotions and determines the priority of the virtual space based on the estimated user emotions. The system described in Appendix 1, characterized by the features described herein. (Note 30) The aforementioned VR goggles are When using VR goggles, a highly relevant virtual space is generated based on the user's geographical location information. The system described in Appendix 1, characterized by the features described herein. (Note 31) The aforementioned VR goggles are When using VR goggles, the system analyzes the user's social media activity and reflects relevant information in the virtual space. The system described in Appendix 1, characterized by the features described herein. (Note 32) The aforementioned electric wheelchair is The system estimates the user's emotions and adjusts the operation of the electric wheelchair based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 33) The aforementioned electric wheelchair is When using an electric wheelchair, the system selects the optimal travel route by referring to the user's past travel history. The system described in Appendix 1, characterized by the features described herein. (Note 34) The aforementioned electric wheelchair is When using an electric wheelchair, the system detects changes in the surrounding environment in real time and reflects them in the movement path. The system described in Appendix 1, characterized by the features described herein. (Note 35) The aforementioned electric wheelchair is The system estimates the user's emotions and determines the operational priorities of the electric wheelchair based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 36) The aforementioned electric wheelchair is When using an electric wheelchair, the system selects the most relevant travel route based on the user's geographical location. The system described in Appendix 1, characterized by the features described herein. (Note 37) The aforementioned electric wheelchair is When using an electric wheelchair, analyze the user's social media activity and reflect relevant information in their travel route. The system described in Appendix 1, characterized by the features described herein. [Explanation of Symbols]

[0195] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots

Claims

1. An analysis unit for analyzing the environment, An audio guide unit provides audio guidance to visually impaired persons based on the information analyzed by the aforementioned analysis unit, A visual information providing unit provides visual information to a person with a hearing impairment based on the information analyzed by the aforementioned analysis unit, Equipped with VR goggles, A system characterized by the following features.

2. The aforementioned analysis unit, The camera collects visual information about the surroundings. The system according to feature 1.

3. The aforementioned audio guide unit is Provide audio guides to visually impaired individuals based on collected visual information. The system according to feature 1.

4. The aforementioned visual information providing unit is It collects ambient audio information through a microphone and presents it as visual information. The system according to feature 1.

5. The aforementioned visual information providing unit is The collected audio information is converted into text and displayed on the screen. The system according to feature 1.

6. Equipped with electric wheelchairs The system according to feature 1.

7. The aforementioned VR goggles are In addition to providing information in real-world spaces, we also provide information in virtual spaces. The system according to feature 1.

8. The aforementioned analysis unit, It estimates the user's emotions and adjusts the accuracy of the analysis based on the estimated user emotions. The system according to feature 1.

9. The aforementioned analysis unit, During analysis, the system selects the optimal analysis method by referring to the user's past movement history. The system according to feature 1.

10. The aforementioned analysis unit, During analysis, changes in the surrounding environment are detected in real time and reflected in the analysis results. The system according to feature 1.

Images