system

Abstract

An object of a system according to an embodiment is to enable even elderly people and foreign travelers to easily obtain correct information in the event of a disaster.SOLUTION: A system according to an embodiment includes a UI structure unit, a disaster detection unit, an information providing unit, and a consultation unit. The UI structure provides a user interface. The disaster detection unit detects a disaster area. The information providing unit provides correct information based on the disaster area detected by the disaster detection unit. The consultation unit receives a consultation from a user at normal times.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] Conventional technology has made it difficult to quickly obtain accurate information during disasters, and has been difficult to use, particularly for elderly people and foreign tourists.

[0005] The system according to the embodiment aims to enable even elderly people and foreign tourists to easily obtain correct information in the event of a disaster. [Means for solving the problem]

[0006] The system according to the embodiment includes a UI structure unit, a disaster detection unit, an information provision unit, and a consultation unit. The UI structure unit provides a user interface. The disaster detection unit detects a disaster area. The information provision unit provides correct information based on the disaster area detected by the disaster detection unit. The consultation unit accepts consultations from users during normal times. [Effects of the Invention]

[0007] The system according to the embodiment can enable even elderly people and foreign tourists to easily obtain correct information in the event of a disaster. [Brief explanation of the drawings]

[0008] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. DETAILED DESCRIPTION OF THE INVENTION

[0009] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0010] First, the terms used in the following description will be explained.

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

[0012] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

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

[0014] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), and Bluetooth (registered trademark).

[0015] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

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

[0017] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[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, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0019] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0020] The reception device 38 includes a touch panel 38A and a microphone 38B, and receives user input. The touch panel 38A detects contact with a pointer (for example, a pen or a finger) to receive user input by the touch of the pointer. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 (see FIG. 2) acquires the data indicating the user input.

[0021] Output device 40 includes a display 40A and a speaker 40B, and presents data to a user by outputting the data in a form of expression that the user can perceive (e.g., audio and / or text). Display 40A displays visible information such as text and images in accordance with instructions from processor 46. Speaker 40B outputs audio in accordance with instructions from processor 46. Camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0022] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

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

[0024] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0025] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0026] In the smart device 14, the specific processing is performed by the processor 46. The storage 50 stores a specific processing program 60. The specific processing program 60 is used together 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 the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. Note that the smart device 14 has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can also perform processing similar to that of the specific processing unit 290 using these models.

[0027] Note that a device other than the data processing device 12 may 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 a processing result (prediction result, etc.) using the data generation model 58 by communicating with the server device having the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device owned by a user (e.g., a mobile phone, a robot, a home appliance, etc.). Next, an example of processing by the data processing system 10 according to the first embodiment will be described.

[0028] (Example 1) The disaster information provision system according to an embodiment of the present invention provides accurate information during disasters and is equipped with a UI that is easy to use for all users, including the elderly and foreign tourists. AI detects disaster areas and provides free, carefully selected, accurate information and advice. The system also has a function that allows people in need to consult with experts in the field or AI during normal times. This allows the disaster information provision system to improve user convenience by providing accurate information during disasters and a consultation function during normal times.

[0029] A disaster information provision system according to an embodiment includes a UI structure unit, a disaster detection unit, an information provision unit, and a consultation unit. The UI structure unit provides a user interface. For example, large icons and a simple menu structure are used to enable intuitive operation. The UI structure unit also supports multiple languages, allowing users to obtain information in their own language. For example, the UI structure unit supports major languages ​​such as English, Chinese, and Spanish. The disaster detection unit detects disaster areas. For example, in the event of an earthquake or flood, the UI structure unit guides users to evacuation sites and safe routes. The information provision unit provides accurate information based on the disaster areas detected by the disaster detection unit. For example, a generation AI analyzes disaster information and provides appropriate advice to users. The consultation unit accepts user consultations during normal times. For example, experts in various fields, such as medical consultations, legal consultations, and travel advice, are available. As a result, the disaster information provision system according to an embodiment can provide accurate information during disasters and provide consultation functions during normal times, thereby improving user convenience.

[0030] The UI structure unit can use large icons or a simple menu structure to enable intuitive operation. For example, the UI structure unit collects user operation history and analyzes frequently used functions and operation patterns. Based on this, it automatically generates a UI optimized for each user, improving usability. The UI structure unit also learns operation history and prioritizes displaying menus and buttons that the user uses frequently. For example, for a user who frequently checks disaster information, it places a disaster information icon on the home screen. The UI structure unit also customizes the UI layout and color scheme based on the user's operation history. For example, it automatically adjusts color schemes and font sizes to make them easier to see. This makes it easy to use for elderly people and foreign tourists.

[0031] The UI structure unit supports multiple languages, allowing users to obtain information in their own language. For example, the UI structure unit tracks the user's gaze with a camera and displays important information according to gaze movements. For example, if the user is looking at a specific area, information related to that area is highlighted. The UI structure unit also uses gaze tracking technology to dynamically position menus and buttons according to the user's gaze. For example, if the user is looking at the right side of the screen, a menu is displayed on the right side. The UI structure unit also analyzes gaze movements and automatically displays information that the user is likely to miss. For example, if the user's gaze is not directed at an area where an important notification is displayed, the notification is displayed as a pop-up. This allows foreign tourists to obtain information in their own language.

[0032] The disaster detection unit can provide guidance on evacuation sites or safe routes in the event of an earthquake or flood. The disaster detection unit, for example, analyzes satellite data in real time and builds a system that provides geographic information of disaster areas. For example, the extent of damage caused by floods or earthquakes is displayed on a map. The disaster detection unit also analyzes drone footage to grasp the detailed situation of disaster areas. For example, it identifies areas with severe damage and suggests evacuation routes. The disaster detection unit also combines satellite data and drone footage to develop a system that updates geographic information of disaster areas in real time. For example, the information can be updated immediately if new damage occurs. This allows for quick guidance on evacuation sites in the event of a disaster.

[0033] The consultation unit can provide assistance from experts in multiple fields, such as medical consultations, legal consultations, and travel advice. For example, the consultation unit collects the user's past consultation history and analyzes the frequently consulted content and patterns. Based on this, a system is built to provide advice optimized for each user. For example, a user who has frequently consulted medically in the past is given priority in providing medical-related advice. The consultation unit also learns the consultation history and evaluates the effectiveness of the advice the user received in the past. This creates a feedback loop for providing effective advice. For example, if past advice was effective, similar advice is provided again. The consultation unit also develops a system that provides individually customized advice based on the user's consultation history. For example, it provides the latest information and expert opinions related to the content the user has consulted in the past. This allows experts in various fields to respond in peacetime.

[0034] The disaster detection unit can send emergency notifications to users when a disaster occurs. The disaster detection unit uses, for example, AR technology to build a system that visually displays disaster information. For example, it displays evacuation routes using a smartphone camera. The disaster detection unit also uses AR technology to allow users to intuitively understand evacuation routes in the real world. For example, it shows the route to an evacuation site with an arrow. The disaster detection unit also uses AR technology to display detailed information about the disaster area. For example, it displays areas with severe damage in red and evacuation routes in green. This allows users to be notified quickly when a disaster occurs.

[0035] The UI structure unit can learn the user's operation history and automatically generate a UI optimized for each individual user. For example, the UI structure unit collects the user's operation history and analyzes frequently used functions and operation patterns. Based on this, it automatically generates a UI optimized for each user, improving usability. The UI structure unit also learns the operation history and prioritizes displaying menus and buttons that the user uses frequently. For example, for a user who frequently checks disaster information, it places a disaster information icon on the home screen. The UI structure unit also customizes the UI layout and color based on the user's operation history. For example, it automatically adjusts the color scheme and font size to make it easier to see. This makes it possible to provide a UI optimized for each user.

[0036] The UI structure unit can dynamically change the UI layout according to the user's gaze using a user's gaze tracking technology. For example, the UI structure unit tracks the user's gaze with a camera and displays important information according to the gaze movement. For example, if the user is looking at a specific area, information related to that area is highlighted. The UI structure unit also uses gaze tracking technology to dynamically arrange menus and buttons according to the part the user is looking at. For example, if the user is looking at the right side of the screen, a menu is displayed on the right side. The UI structure unit also analyzes gaze movement and automatically displays information that the user is likely to miss. For example, if the user's gaze is not directed at an area where an important notification is displayed, the notification is displayed as a pop-up. This allows the UI to dynamically change according to the user's gaze.

[0037] The UI structure unit can incorporate voice and gesture operations to enable easy operation even for users with disabilities. For example, the UI structure unit uses voice recognition technology to add functions that users can operate by voice. For example, by simply saying, "Tell me where the evacuation site is," information about evacuation sites can be displayed. The UI structure unit can also introduce gesture recognition technology to design a UI that can be operated by hand movements. For example, it can be made possible to open a menu by simply waving your hand. The UI structure unit can also combine voice and gesture operations to provide a UI that users can operate intuitively. For example, instructions can be given by voice and detailed operations can be performed by gestures. This allows even users with disabilities to operate easily.

[0038] The UI structure unit can add a function to customize the UI according to the user's physical characteristics. For example, the UI structure unit adds a function to automatically adjust font size and contrast according to the user's eyesight. For example, a user with low eyesight can be provided with large fonts and high-contrast color schemes. The UI structure unit also introduces a function to adjust the volume and frequency of audio notifications according to hearing ability. For example, a user with low hearing can be provided with high-pitched audio notifications. The UI structure unit also registers the user's physical characteristics in advance and builds a system to customize the UI based on the registered information. For example, the system automatically applies optimal UI settings based on the information registered by the user. This allows the UI to be customized according to the user's physical characteristics.

[0039] The disaster detection unit can analyze satellite data or drone footage and provide detailed geographic information of disaster areas in real time. The disaster detection unit, for example, analyzes satellite data in real time and builds a system that provides geographic information of disaster areas. For example, the extent of damage caused by floods or earthquakes is displayed on a map. The disaster detection unit also analyzes drone footage to grasp the detailed situation of disaster areas. For example, it identifies areas with severe damage and suggests evacuation routes. The disaster detection unit also combines satellite data and drone footage to develop a system that updates geographic information of disaster areas in real time. For example, it updates information immediately if new damage occurs. This makes it possible to provide detailed geographic information of disaster areas in real time.

[0040] The disaster detection unit can combine the user's location information with past disaster data to propose an individually customized evacuation route. The disaster detection unit, for example, acquires the user's location information and combines it with past disaster data to build a system that proposes the optimal evacuation route. For example, when an earthquake occurs, it displays safe evacuation routes in real time. The disaster detection unit also analyzes past disaster data and provides customized evacuation routes based on the user's location information. For example, it proposes routes that avoid areas with a high risk of flooding. The disaster detection unit also combines the user's location information with past disaster data to develop a system that evaluates the safety of evacuation routes. For example, it notifies users of dangerous areas on evacuation routes in real time. This makes it possible to propose evacuation routes customized for each user.

[0041] The disaster detection unit can introduce AR technology to visually display disaster information, allowing users to intuitively understand evacuation routes in the real world. The disaster detection unit, for example, uses AR technology to build a system that visually displays disaster information. For example, evacuation routes are displayed through a smartphone camera. The disaster detection unit also utilizes AR technology to allow users to intuitively understand evacuation routes in the real world. For example, arrows are used to show the route to evacuation locations. The disaster detection unit also uses AR technology to display detailed information about disaster areas. For example, areas with severe damage are displayed in red, and evacuation routes are displayed in green. This allows users to intuitively understand evacuation routes in the real world.

[0042] The disaster detection unit can add a function to provide disaster information by voice, making it easier for visually impaired people or elderly people to obtain information. The disaster detection unit can add a function to provide disaster information by voice, making it easier for visually impaired people or elderly people to obtain information. For example, when an earthquake occurs, it can provide evacuation locations by voice. The disaster detection unit can also use voice recognition technology to build a system that allows users to obtain disaster information by voice. For example, by simply saying, "Tell me where the evacuation locations are," it can provide information by voice. The disaster detection unit can also introduce a function to provide disaster information by voice, making it easier for visually impaired people or elderly people to obtain information. For example, it can provide evacuation routes by voice, allowing the user to evacuate safely. This makes it easier for visually impaired people or elderly people to obtain information.

[0043] The consultation unit can learn the user's past consultation history and provide advice that is optimized for each individual user. For example, the consultation unit collects the user's past consultation history and analyzes the content and patterns of frequent consultations. Based on this, a system is built to provide advice that is optimized for each user. For example, a user who has frequently consulted medically in the past is given priority in receiving medical-related advice. The consultation unit also learns the consultation history and evaluates the effectiveness of advice that the user has received in the past. This creates a feedback loop for providing effective advice. For example, if past advice was effective, similar advice is provided again. The consultation unit also develops a system that provides individually customized advice based on the user's consultation history. For example, it provides the latest information and expert opinions related to the content that the user has consulted in the past. This makes it possible to provide advice that is optimized for each user.

[0044] The consultation department allows the generating AI to continuously learn the expert's knowledge and update advice based on the latest information. For example, the consultation department will build a system where the generating AI continuously learns the expert's knowledge and provides advice based on the latest information. For example, it will learn the latest research in the medical field and information on legal amendments and provide this to the user. The consultation department will also regularly update the expert's knowledge and the generating AI will provide advice based on the latest information. For example, it will learn the latest guidelines and best practices provided by experts. The consultation department will also develop a system where the generating AI continuously learns the expert's knowledge and provides the latest information according to the user's consultation content. For example, if a user seeks legal advice, it will provide the latest case law and information on legal amendments. This allows advice to be updated based on the latest information.

[0045] The consultation unit can add a function that allows users to input their consultation details by voice, making it easy for even users with disabilities to consult. The consultation unit adds a function that allows users to input their consultation details by voice, for example, using voice recognition technology. For example, the consultation details can be input by voice by simply saying, "I would like to consult a medical professional." The consultation unit also introduces a voice input function, making it easy for even users with disabilities to consult. For example, a question can be input by voice, and the generation AI will provide an answer by voice. The consultation unit also uses voice recognition technology to provide an interface that makes it easy for users to input their consultation details by voice. For example, a noise cancellation function can be added to improve the accuracy of voice input. This makes it easy for even users with disabilities to consult.

[0046] The consultation unit can add a function in which the generation AI automatically classifies the content of a user's consultation and transfers it to the most appropriate expert. For example, the consultation unit builds a system in which the generation AI analyzes the content of a user's consultation and automatically classifies it. For example, it could classify it into categories such as medical consultation, legal consultation, and travel consultation. The consultation unit also adds a function to automatically classify the content of a consultation and transfer it to the most appropriate expert. For example, medical consultations would be transferred to a doctor, and legal consultations would be transferred to a lawyer. The consultation unit also develops a system in which the generation AI analyzes the content of a user's consultation and transfers it to the most appropriate expert. For example, if a user asks for travel advice, it would be transferred to a travel expert. This makes it possible to automatically classify the content of a user's consultation and transfer it to the most appropriate expert.

[0047] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0048] The disaster information provision system may further include a route suggestion unit that acquires the user's location information and suggests an optimal evacuation route based on the disaster area. For example, when an earthquake occurs, the route from the user's current location to the safest evacuation site is displayed in real time. The route suggestion unit may also analyze past disaster data and suggest routes that avoid high-risk areas. For example, it may suggest routes that avoid areas with a high risk of flooding. The route suggestion unit may also dynamically update the optimal evacuation route, taking into account the user's movement speed and traffic conditions. This allows the user to evacuate quickly and safely.

[0049] The disaster information provision system can further include a health monitoring unit that monitors the user's health status and provides appropriate medical advice in the event of a disaster. For example, it can measure the user's heart rate and blood pressure in real time and provide medical advice if an abnormality is detected. The health monitoring unit can also provide individually customized medical advice taking into account the user's medical history and allergy information. For example, it can instruct the user to avoid certain medications. The health monitoring unit can also strengthen cooperation with medical institutions in the event of a disaster, enabling a rapid response in an emergency. This can help protect the user's health.

[0050] The disaster information provision system can further take into consideration the visual impairment of users and include an audio guidance unit that provides disaster information by voice. For example, when an earthquake occurs, evacuation sites are provided by voice. The audio guidance unit can also be used to create a system that allows users to obtain disaster information by voice. For example, by simply saying, "Tell me where the evacuation sites are," the information is provided by voice. The audio guidance unit can also incorporate a function to provide disaster information by voice, making it easier for visually impaired people and elderly people to obtain information. This allows visually impaired people and elderly people to obtain information easily.

[0051] The disaster information provision system can further include a route customization unit that combines the user's location information with past disaster data to propose an individually customized evacuation route. For example, when an earthquake occurs, the system displays a route from the user's current location to the safest evacuation site in real time. The route customization unit can also analyze past disaster data to propose a route that avoids high-risk areas. For example, it can provide a route that avoids areas with a high risk of flooding. The route customization unit can also dynamically update the optimal evacuation route, taking into account the user's movement speed and traffic conditions. This allows the user to evacuate quickly and safely.

[0052] The disaster information provision system can further include a health advice unit that monitors the user's health status and provides appropriate medical advice in the event of a disaster. For example, it can measure the user's heart rate and blood pressure in real time and provide medical advice if an abnormality is detected. The health advice unit can also provide individually customized medical advice taking into account the user's medical history and allergy information. For example, it can instruct the user to avoid certain medications. The health advice unit can also strengthen cooperation with medical institutions in the event of a disaster, enabling a rapid response in an emergency. This can help protect the user's health.

[0053] The disaster information provision system can further take into consideration the visual impairment of users and include an audio guidance unit that provides disaster information by voice. For example, when an earthquake occurs, evacuation sites are provided by voice. The audio guidance unit can also be used to create a system that allows users to obtain disaster information by voice. For example, by simply saying, "Tell me where the evacuation sites are," the information is provided by voice. The audio guidance unit can also incorporate a function to provide disaster information by voice, making it easier for visually impaired people and elderly people to obtain information. This allows visually impaired people and elderly people to obtain information easily.

[0054] The processing flow of the first embodiment will be briefly explained below.

[0055] Step 1: The UI structure provides the user interface. For example, it uses large icons and a simple menu structure to allow intuitive operation. The UI structure also supports multiple languages, allowing users to obtain information in their own language. For example, it supports major languages ​​such as English, Chinese, and Spanish. Step 2: The disaster detection unit detects disaster areas. For example, in the event of an earthquake or flood, the unit guides users to evacuation sites and safe routes. Step 3: The information provider provides accurate information based on the disaster area detected by the disaster detector. For example, the generator AI analyzes the disaster information and provides appropriate advice to the user. Step 4: The consultation department accepts user inquiries during normal times. For example, experts in various fields will respond, such as medical consultations, legal consultations, and travel advice.

[0056] (Example 2) The disaster information provision system according to an embodiment of the present invention provides accurate information during disasters and is equipped with a UI that is easy to use for all users, including the elderly and foreign tourists. AI detects disaster areas and provides free, carefully selected, accurate information and advice. The system also has a function that allows people in need to consult with experts in the field or AI during normal times. This allows the disaster information provision system to improve user convenience by providing accurate information during disasters and a consultation function during normal times.

[0057] A disaster information provision system according to an embodiment includes a UI structure unit, a disaster detection unit, an information provision unit, and a consultation unit. The UI structure unit provides a user interface. For example, large icons and a simple menu structure are used to enable intuitive operation. The UI structure unit also supports multiple languages, allowing users to obtain information in their own language. For example, the UI structure unit supports major languages ​​such as English, Chinese, and Spanish. The disaster detection unit detects disaster areas. For example, in the event of an earthquake or flood, the UI structure unit guides users to evacuation sites and safe routes. The information provision unit provides accurate information based on the disaster areas detected by the disaster detection unit. For example, a generation AI analyzes disaster information and provides appropriate advice to users. The consultation unit accepts user consultations during normal times. For example, experts in various fields, such as medical consultations, legal consultations, and travel advice, are available. As a result, the disaster information provision system according to an embodiment can provide accurate information during disasters and provide consultation functions during normal times, thereby improving user convenience.

[0058] The UI structure unit can use large icons or a simple menu structure to enable intuitive operation. For example, the UI structure unit collects user operation history and analyzes frequently used functions and operation patterns. Based on this, it automatically generates a UI optimized for each user, improving usability. The UI structure unit also learns operation history and prioritizes displaying menus and buttons that the user uses frequently. For example, for a user who frequently checks disaster information, it places a disaster information icon on the home screen. The UI structure unit also customizes the UI layout and color scheme based on the user's operation history. For example, it automatically adjusts color schemes and font sizes to make them easier to see. This makes it easy to use for elderly people and foreign tourists.

[0059] The UI structure unit supports multiple languages, allowing users to obtain information in their own language. For example, the UI structure unit tracks the user's gaze with a camera and displays important information according to gaze movements. For example, if the user is looking at a specific area, information related to that area is highlighted. The UI structure unit also uses gaze tracking technology to dynamically position menus and buttons according to the user's gaze. For example, if the user is looking at the right side of the screen, a menu is displayed on the right side. The UI structure unit also analyzes gaze movements and automatically displays information that the user is likely to miss. For example, if the user's gaze is not directed at an area where an important notification is displayed, the notification is displayed as a pop-up. This allows foreign tourists to obtain information in their own language.

[0060] The disaster detection unit can provide guidance on evacuation sites or safe routes in the event of an earthquake or flood. The disaster detection unit, for example, analyzes satellite data in real time and builds a system that provides geographic information of disaster areas. For example, the extent of damage caused by floods or earthquakes is displayed on a map. The disaster detection unit also analyzes drone footage to grasp the detailed situation of disaster areas. For example, it identifies areas with severe damage and suggests evacuation routes. The disaster detection unit also combines satellite data and drone footage to develop a system that updates geographic information of disaster areas in real time. For example, the information can be updated immediately if new damage occurs. This allows for quick guidance on evacuation sites in the event of a disaster.

[0061] The consultation unit can provide assistance from experts in multiple fields, such as medical consultations, legal consultations, and travel advice. For example, the consultation unit collects the user's past consultation history and analyzes the frequently consulted content and patterns. Based on this, a system is built to provide advice optimized for each user. For example, a user who has frequently consulted medically in the past is given priority in providing medical-related advice. The consultation unit also learns the consultation history and evaluates the effectiveness of the advice the user received in the past. This creates a feedback loop for providing effective advice. For example, if past advice was effective, similar advice is provided again. The consultation unit also develops a system that provides individually customized advice based on the user's consultation history. For example, it provides the latest information and expert opinions related to the content the user has consulted in the past. This allows experts in various fields to respond in peacetime.

[0062] The disaster detection unit can send emergency notifications to users when a disaster occurs. The disaster detection unit uses, for example, AR technology to build a system that visually displays disaster information. For example, it displays evacuation routes using a smartphone camera. The disaster detection unit also uses AR technology to allow users to intuitively understand evacuation routes in the real world. For example, it shows the route to an evacuation site with an arrow. The disaster detection unit also uses AR technology to display detailed information about the disaster area. For example, it displays areas with severe damage in red and evacuation routes in green. This allows users to be notified quickly when a disaster occurs.

[0063] The UI structure unit can learn the user's operation history and automatically generate a UI optimized for each individual user. For example, the UI structure unit collects the user's operation history and analyzes frequently used functions and operation patterns. Based on this, it automatically generates a UI optimized for each user, improving usability. The UI structure unit also learns the operation history and prioritizes displaying menus and buttons that the user uses frequently. For example, for a user who frequently checks disaster information, it places a disaster information icon on the home screen. The UI structure unit also customizes the UI layout and color based on the user's operation history. For example, it automatically adjusts the color scheme and font size to make it easier to see. This makes it possible to provide a UI optimized for each user.

[0064] The UI structure unit can dynamically change the UI layout according to the user's gaze using a user's gaze tracking technology. For example, the UI structure unit tracks the user's gaze with a camera and displays important information according to the gaze movement. For example, if the user is looking at a specific area, information related to that area is highlighted. The UI structure unit also uses gaze tracking technology to dynamically arrange menus and buttons according to the part the user is looking at. For example, if the user is looking at the right side of the screen, a menu is displayed on the right side. The UI structure unit also analyzes gaze movement and automatically displays information that the user is likely to miss. For example, if the user's gaze is not directed at an area where an important notification is displayed, the notification is displayed as a pop-up. This allows the UI to dynamically change according to the user's gaze.

[0065] The UI structure unit uses the emotion estimation function to change the color and design of the UI according to the user's emotional state, thereby reducing stress. The UI structure unit, for example, analyzes the user's facial expressions and voice to estimate the user's emotional state. For example, if the user is feeling stressed, the UI color is changed to a calming color. The UI structure unit also uses the emotion estimation function to automatically apply a design that helps the user relax. For example, if the user is feeling anxious, an animation with a relaxing effect is added to the UI. The UI structure unit also changes the UI layout according to the user's emotional state. For example, if the user is feeling anxious, important information is placed in a prominent position and operation is simplified. In this way, the UI can be adjusted according to the user's emotional state, reducing stress.

[0066] The UI structure unit can incorporate voice and gesture operations to enable easy operation even for users with disabilities. For example, the UI structure unit uses voice recognition technology to add functions that users can operate by voice. For example, by simply saying, "Tell me where the evacuation site is," information about evacuation sites can be displayed. The UI structure unit can also introduce gesture recognition technology to design a UI that can be operated by hand movements. For example, it can be made possible to open a menu by simply waving your hand. The UI structure unit can also combine voice and gesture operations to provide a UI that users can operate intuitively. For example, instructions can be given by voice and detailed operations can be performed by gestures. This allows even users with disabilities to operate easily.

[0067] The UI structure unit can add a function to customize the UI according to the user's physical characteristics. For example, the UI structure unit adds a function to automatically adjust font size and contrast according to the user's eyesight. For example, a user with low eyesight can be provided with large fonts and high-contrast color schemes. The UI structure unit also introduces a function to adjust the volume and frequency of audio notifications according to hearing ability. For example, a user with low hearing can be provided with high-pitched audio notifications. The UI structure unit also registers the user's physical characteristics in advance and builds a system to customize the UI based on the registered information. For example, the system automatically applies optimal UI settings based on the information registered by the user. This allows the UI to be customized according to the user's physical characteristics.

[0068] The UI structure unit can use the emotion estimation function to detect anxiety or confusion felt by the user during operation in real time and display appropriate help messages. The UI structure unit, for example, analyzes the user's facial expressions and voice to detect anxiety or confusion felt during operation in real time. For example, if the user is confused, it displays a help message in a pop-up. Furthermore, if the UI structure unit uses the emotion estimation function to determine that the user is having difficulty with an operation, it automatically displays an operation guide or tutorial. For example, if a specific operation does not work properly, it provides detailed explanations of the operation procedure. Furthermore, the UI structure unit customizes the content and display method of the help message according to the user's emotional state. For example, if the user is impatient, it displays a concise and easy-to-understand message. This allows the UI structure unit to detect anxiety or confusion felt by the user during operation in real time and display appropriate help messages.

[0069] The disaster detection unit can analyze satellite data or drone footage and provide detailed geographic information of disaster areas in real time. The disaster detection unit, for example, analyzes satellite data in real time and builds a system that provides geographic information of disaster areas. For example, the extent of damage caused by floods or earthquakes is displayed on a map. The disaster detection unit also analyzes drone footage to grasp the detailed situation of disaster areas. For example, it identifies areas with severe damage and suggests evacuation routes. The disaster detection unit also combines satellite data and drone footage to develop a system that updates geographic information of disaster areas in real time. For example, it updates information immediately if new damage occurs. This makes it possible to provide detailed geographic information of disaster areas in real time.

[0070] The disaster detection unit can combine the user's location information with past disaster data to propose an individually customized evacuation route. The disaster detection unit, for example, acquires the user's location information and combines it with past disaster data to build a system that proposes the optimal evacuation route. For example, when an earthquake occurs, it displays safe evacuation routes in real time. The disaster detection unit also analyzes past disaster data and provides customized evacuation routes based on the user's location information. For example, it proposes routes that avoid areas with a high risk of flooding. The disaster detection unit also combines the user's location information with past disaster data to develop a system that evaluates the safety of evacuation routes. For example, it notifies users of dangerous areas on evacuation routes in real time. This makes it possible to propose evacuation routes customized for each user.

[0071] The disaster detection unit uses the emotion estimation function to provide evacuation advice according to the user's emotional state, thereby preventing panic. The disaster detection unit, for example, analyzes the user's facial expressions and voice to estimate the user's emotional state. For example, if the user is in a panic, it provides advice to help them stay calm. The disaster detection unit also uses the emotion estimation function to customize evacuation advice according to the user's emotional state. For example, if the user is feeling anxious, it displays a message that gives a sense of security. The disaster detection unit also monitors the user's emotional state in real time, building a system that provides evacuation advice at the appropriate time. For example, if the user is feeling anxious, it provides advice to help them stay calm. This makes it possible to provide evacuation advice according to the user's emotional state, thereby preventing panic.

[0072] The disaster detection unit can introduce AR technology to visually display disaster information, allowing users to intuitively understand evacuation routes in the real world. The disaster detection unit, for example, uses AR technology to build a system that visually displays disaster information. For example, evacuation routes are displayed through a smartphone camera. The disaster detection unit also utilizes AR technology to allow users to intuitively understand evacuation routes in the real world. For example, arrows are used to show the route to evacuation locations. The disaster detection unit also uses AR technology to display detailed information about disaster areas. For example, areas with severe damage are displayed in red, and evacuation routes are displayed in green. This allows users to intuitively understand evacuation routes in the real world.

[0073] The disaster detection unit can add a function to provide disaster information by voice, making it easier for visually impaired people or elderly people to obtain information. The disaster detection unit can add a function to provide disaster information by voice, making it easier for visually impaired people or elderly people to obtain information. For example, when an earthquake occurs, it can provide evacuation locations by voice. The disaster detection unit can also use voice recognition technology to build a system that allows users to obtain disaster information by voice. For example, by simply saying, "Tell me where the evacuation locations are," it can provide information by voice. The disaster detection unit can also introduce a function to provide disaster information by voice, making it easier for visually impaired people or elderly people to obtain information. For example, it can provide evacuation routes by voice, allowing the user to evacuate safely. This makes it easier for visually impaired people or elderly people to obtain information.

[0074] The disaster detection unit can use the emotion estimation function to detect anxiety felt by a user during evacuation in real time and send a message that provides a sense of security. The disaster detection unit, for example, analyzes the user's facial expressions and voice to detect anxiety felt during evacuation in real time. For example, if the user is feeling anxious, it sends a message that provides a sense of security. The disaster detection unit also uses the emotion estimation function to detect anxiety felt by a user during evacuation and sends a message that provides a sense of security at an appropriate time. For example, it sends a message such as "It's okay, we'll arrive at the evacuation site soon." The disaster detection unit also monitors the user's emotional state in real time and builds a system that sends messages to reduce anxiety felt during evacuation. For example, if the user is feeling anxious, it sends a message to calm down. In this way, it is possible to detect anxiety felt by a user during evacuation in real time and send a message that provides a sense of security.

[0075] The consultation unit can learn the user's past consultation history and provide advice that is optimized for each individual user. For example, the consultation unit collects the user's past consultation history and analyzes the content and patterns of frequent consultations. Based on this, a system is built to provide advice that is optimized for each user. For example, a user who has frequently consulted medically in the past is given priority in receiving medical-related advice. The consultation unit also learns the consultation history and evaluates the effectiveness of advice that the user has received in the past. This creates a feedback loop for providing effective advice. For example, if past advice was effective, similar advice is provided again. The consultation unit also develops a system that provides individually customized advice based on the user's consultation history. For example, it provides the latest information and expert opinions related to the content that the user has consulted in the past. This makes it possible to provide advice that is optimized for each user.

[0076] The consultation department allows the generating AI to continuously learn the expert's knowledge and update advice based on the latest information. For example, the consultation department will build a system where the generating AI continuously learns the expert's knowledge and provides advice based on the latest information. For example, it will learn the latest research in the medical field and information on legal amendments and provide this to the user. The consultation department will also regularly update the expert's knowledge and the generating AI will provide advice based on the latest information. For example, it will learn the latest guidelines and best practices provided by experts. The consultation department will also develop a system where the generating AI continuously learns the expert's knowledge and provides the latest information according to the user's consultation content. For example, if a user seeks legal advice, it will provide the latest case law and information on legal amendments. This allows advice to be updated based on the latest information.

[0077] The consultation unit can add a function that allows users to input their consultation details by voice, making it easy for even users with disabilities to consult. The consultation unit adds a function that allows users to input their consultation details by voice, for example, using voice recognition technology. For example, the consultation details can be input by voice by simply saying, "I would like to consult a medical professional." The consultation unit also introduces a voice input function, making it easy for even users with disabilities to consult. For example, a question can be input by voice, and the generation AI will provide an answer by voice. The consultation unit also uses voice recognition technology to provide an interface that makes it easy for users to input their consultation details by voice. For example, a noise cancellation function can be added to improve the accuracy of voice input. This makes it easy for even users with disabilities to consult.

[0078] The consultation unit can add a function in which the generation AI automatically classifies the content of a user's consultation and transfers it to the most appropriate expert. For example, the consultation unit builds a system in which the generation AI analyzes the content of a user's consultation and automatically classifies it. For example, it could classify it into categories such as medical consultation, legal consultation, and travel consultation. The consultation unit also adds a function to automatically classify the content of a consultation and transfer it to the most appropriate expert. For example, medical consultations would be transferred to a doctor, and legal consultations would be transferred to a lawyer. The consultation unit also develops a system in which the generation AI analyzes the content of a user's consultation and transfers it to the most appropriate expert. For example, if a user asks for travel advice, it would be transferred to a travel expert. This makes it possible to automatically classify the content of a user's consultation and transfer it to the most appropriate expert.

[0079] The consultation unit can use the emotion estimation function to detect anxiety or confusion felt by the user during the consultation in real time and display an appropriate support message. The consultation unit, for example, analyzes the user's facial expressions and voice to detect anxiety or confusion felt by the user during the consultation in real time. For example, if the user is confused, a support message is displayed as a pop-up. The consultation unit can also use the emotion estimation function to detect anxiety felt by the user during the consultation and display a support message at an appropriate time. For example, a message such as "Don't worry, an expert will assist you" is displayed. The consultation unit can also monitor the user's emotional state in real time and build a system that displays a support message to reduce anxiety felt during the consultation. For example, if the user is impatient, a message to calm down is displayed. This makes it possible to detect anxiety or confusion felt by the user during the consultation in real time and display an appropriate support message.

[0080] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0081] The disaster information provision system may further include a route suggestion unit that acquires the user's location information and suggests an optimal evacuation route based on the disaster area. For example, when an earthquake occurs, the route from the user's current location to the safest evacuation site is displayed in real time. The route suggestion unit may also analyze past disaster data and suggest routes that avoid high-risk areas. For example, it may suggest routes that avoid areas with a high risk of flooding. The route suggestion unit may also dynamically update the optimal evacuation route, taking into account the user's movement speed and traffic conditions. This allows the user to evacuate quickly and safely.

[0082] The disaster information provision system can further include a health monitoring unit that monitors the user's health status and provides appropriate medical advice in the event of a disaster. For example, it can measure the user's heart rate and blood pressure in real time and provide medical advice if an abnormality is detected. The health monitoring unit can also provide individually customized medical advice taking into account the user's medical history and allergy information. For example, it can instruct the user to avoid certain medications. The health monitoring unit can also strengthen cooperation with medical institutions in the event of a disaster, enabling a rapid response in an emergency. This can help protect the user's health.

[0083] The disaster information provision system may further include an emotion advice unit that estimates the user's emotional state and provides appropriate evacuation advice based on the estimated emotion. For example, if the user is in a panic, the emotion advice unit may provide advice to help the user stay calm. The emotion advice unit may also customize an evacuation route according to the user's emotional state. For example, if the user is feeling anxious, the emotion advice unit may display a message that provides a sense of security. The emotion advice unit may also monitor the user's emotional state in real time and provide evacuation advice at an appropriate time. This allows the system to provide evacuation advice according to the user's emotional state and prevent panic.

[0084] The disaster information provision system can further take into consideration the visual impairment of users and include an audio guidance unit that provides disaster information by voice. For example, when an earthquake occurs, evacuation sites are provided by voice. The audio guidance unit can also be used to create a system that allows users to obtain disaster information by voice. For example, by simply saying, "Tell me where the evacuation sites are," the information is provided by voice. The audio guidance unit can also incorporate a function to provide disaster information by voice, making it easier for visually impaired people and elderly people to obtain information. This allows visually impaired people and elderly people to obtain information easily.

[0085] The disaster information provision system can further include an emotional help unit that estimates the user's emotional state and displays an appropriate help message based on the estimated emotion. For example, if the user is confused, a help message is displayed as a pop-up. The emotional help unit can also automatically display an operation guide or tutorial if it determines that the user is having difficulty with an operation. For example, if a specific operation does not work properly, it can provide detailed instructions on how to perform that operation. The emotional help unit can also customize the content and display method of the help message according to the user's emotional state. This makes it possible to detect in real time any anxiety or confusion the user feels while operating the system and display an appropriate help message.

[0086] The disaster information provision system can further include a route customization unit that combines the user's location information with past disaster data to propose an individually customized evacuation route. For example, when an earthquake occurs, the system displays a route from the user's current location to the safest evacuation site in real time. The route customization unit can also analyze past disaster data to propose a route that avoids high-risk areas. For example, it can provide a route that avoids areas with a high risk of flooding. The route customization unit can also dynamically update the optimal evacuation route, taking into account the user's movement speed and traffic conditions. This allows the user to evacuate quickly and safely.

[0087] The disaster information provision system may further include an emotional evacuation advice unit that estimates the user's emotional state and provides appropriate evacuation advice based on the estimated emotion. For example, if the user is in a panic, the emotional evacuation advice unit may provide advice to help the user stay calm. The emotional evacuation advice unit may also customize an evacuation route according to the user's emotional state. For example, if the user is feeling anxious, the emotional evacuation advice unit may display a message that provides a sense of security. The emotional evacuation advice unit may also monitor the user's emotional state in real time and provide evacuation advice at an appropriate time. This allows the user to provide evacuation advice according to their emotional state and prevent panic.

[0088] The disaster information provision system can further include a health advice unit that monitors the user's health status and provides appropriate medical advice in the event of a disaster. For example, it can measure the user's heart rate and blood pressure in real time and provide medical advice if an abnormality is detected. The health advice unit can also provide individually customized medical advice taking into account the user's medical history and allergy information. For example, it can instruct the user to avoid certain medications. The health advice unit can also strengthen cooperation with medical institutions in the event of a disaster, enabling a rapid response in an emergency. This can help protect the user's health.

[0089] The disaster information provision system may further include an emotional evacuation advice unit that estimates the user's emotional state and provides appropriate evacuation advice based on the estimated emotion. For example, if the user is in a panic, the emotional evacuation advice unit may provide advice to help the user stay calm. The emotional evacuation advice unit may also customize an evacuation route according to the user's emotional state. For example, if the user is feeling anxious, the emotional evacuation advice unit may display a message that provides a sense of security. The emotional evacuation advice unit may also monitor the user's emotional state in real time and provide evacuation advice at an appropriate time. This allows the user to provide evacuation advice according to their emotional state and prevent panic.

[0090] The disaster information provision system can further take into consideration the visual impairment of users and include an audio guidance unit that provides disaster information by voice. For example, when an earthquake occurs, evacuation sites are provided by voice. The audio guidance unit can also be used to create a system that allows users to obtain disaster information by voice. For example, by simply saying, "Tell me where the evacuation sites are," the information is provided by voice. The audio guidance unit can also incorporate a function to provide disaster information by voice, making it easier for visually impaired people and elderly people to obtain information. This allows visually impaired people and elderly people to obtain information easily.

[0091] The processing flow of the second embodiment will be briefly explained below.

[0092] Step 1: The UI structure provides the user interface. For example, it uses large icons and a simple menu structure to allow intuitive operation. The UI structure also supports multiple languages, allowing users to obtain information in their own language. For example, it supports major languages ​​such as English, Chinese, and Spanish. Step 2: The disaster detection unit detects disaster areas. For example, in the event of an earthquake or flood, the unit guides users to evacuation sites and safe routes. Step 3: The information provider provides accurate information based on the disaster area detected by the disaster detector. For example, the generator AI analyzes the disaster information and provides appropriate advice to the user. Step 4: The consultation department accepts user inquiries during normal times. For example, experts in various fields will respond, such as medical consultations, legal consultations, and travel advice.

[0093] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0094] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> Examples of generative AIs include the data generation model 58, such as a neural network model (e.g., a neural network model), and a neural network model (e.g., a neural network model). The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating speech, text data indicating text, and image data indicating an image is also input to the data generation model 58. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specification processing unit 290 performs the above-mentioned specification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0095] Furthermore, the processing by the data processing system 10 described above is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart device 14, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart device 14. Furthermore, 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.

[0096] [Second embodiment] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0097] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0098] 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, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0099] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0100] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0101] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0102] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0103] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0104] The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0105] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0106] In the smart glasses 214, the specific processing is performed by the processor 46. A specific processing program 60 is stored in the storage 50. 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 the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. The smart glasses 214 also have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0107] Note that a device other than the data processing device 12 may 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 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0108] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0109] The data generation model 58 is a so-called generative AI. An example of the 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 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AI other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0110] 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 executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart glasses 214, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart glasses 214. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the smart glasses 214 or an external device, etc., and the smart glasses 214 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0111] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0112] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0113] 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, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0114] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0115] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0116] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0117] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0118] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0119] The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0120] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0121] In the headset type terminal 314, the specific processing is performed by the processor 46. A specific processing program 60 is stored in the storage 50. 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 the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. Note that the headset type terminal 314 has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can also perform processing similar to that of the specific processing unit 290 using these models.

[0122] Note that a device other than the data processing device 12 may 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 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0123] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0124] The data generation model 58 is a so-called generative AI. An example of the 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 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AI other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0125] 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 executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the headset type terminal 314, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the headset type terminal 314. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the headset type terminal 314 or an external device, etc., and the headset type terminal 314 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0126] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0127] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0128] 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, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0129] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[0130] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0131] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS image sensor or a CCD image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0132] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0133] The control 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 emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[0134] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0135] The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0136] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0137] In the robot 414, the specific processing is performed by the processor 46. A specific processing program 60 is stored in the storage 50. 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 the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. The robot 414 also has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0138] Note that a device other than the data processing device 12 may 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 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0139] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[0140] The data generation model 58 is a so-called generative AI. An example of the 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 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AI other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0141] 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 executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the robot 414, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the robot 414. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the robot 414 or an external device, etc., and the robot 414 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0142] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0143] FIG. 9 illustrates an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and behaviors arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion encompasses both emotions and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[0144] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[0145] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[0146] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is expressed, and when they approach the ideal, a state of pleasure is expressed. Emotions can also be created for robots, cars, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is expressed, and when they approach the ideal, a state of pleasure is expressed. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on speech emotion recognition and brain physiological signal analysis systems for emotions, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[0147] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[0148] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[0149] In the above embodiment, an example was given in which a specific process is performed by one computer 22, but the technology disclosed herein is not limited to this, and distributed processing of the specific process may be performed by multiple computers including computer 22.

[0150] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[0151] 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.

[0152] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[0153] The hardware resource for executing a specific process can be any of the following types of processors: A processor, for example, is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. A processor also includes a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[0154] The hardware resource that executes the specific process may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific process may be a single processor.

[0155] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[0156] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[0157] In the above example, the first to fourth embodiments have been described separately, but some or all of these embodiments may be combined. The smart device 14, smart glasses 214, headset terminal 314, and robot 414 are merely examples, and they may be combined, or other devices may be used. In the above example, the first and second embodiments have been described separately, but they may be combined.

[0158] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[0159] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference. [Explanation of symbols]

[0160] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot

Claims

1. a UI structure that provides a user interface; a disaster detection unit that detects a disaster area; an information providing unit that provides correct information based on the disaster area detected by the disaster detection unit; A consultation unit that accepts consultations from users during normal times. A system characterized by:

2. The UI structure unit includes: Use large icons or a simple menu structure to make it intuitive to use.

2. The system of claim 1.

3. The UI structure unit includes: Multilingual support so users can get information in their own language 2. The system of claim 1.

4. The disaster detection unit Guiding evacuation shelters or safe routes in the event of an earthquake or flood 2. The system of claim 1.

5. The consultation department: Experts in multiple fields, including medical and legal advice and travel advice 2. The system of claim 1.

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