system

Abstract

The system according to this embodiment aims to provide information even without an internet connection in times of emergency. [Solution] The system according to this embodiment comprises a provisioning unit, an update unit, and an interface unit. The provisioning unit provides information. The update unit supplies the provisioning unit with the latest information. The interface unit interacts with the user.

Description

Technical Field

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

Background Art

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

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In the conventional technology, a system for providing information even without an Internet connection in an emergency is not sufficiently developed, and there is room for improvement.

[0005] The system according to the embodiment aims to provide information even without an Internet connection in an emergency.

Means for Solving the Problems

[0006] The system according to the embodiment includes a providing unit, an updating unit, and an interface unit. The providing unit provides information. The updating unit supplies the latest information to the providing unit. The interface unit communicates with the user.

Effects of the Invention

[0007] The system according to this embodiment can provide information even without an internet connection in the event of an emergency. [Brief explanation of the drawing]

[0008] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Modes for carrying out the invention]

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

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

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

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

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

[0014] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0015] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B". That is, "A and / or B" means that it may be only A, only B, or a combination of A and B. Also, in this specification, when expressing three or more matters connected by "and / or", the same concept as "A and / or B" is applied.

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

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

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

[0019] The smart device 14 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. Also, the reception device 38, the output device 40, and the camera 42 are connected to the bus 52.

[0020] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, and accepts user input. The touch panel 38A accepts user input via touch by detecting contact with an object (e.g., a pen or finger). The microphone 38B accepts user input via voice by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 (see Figure 2) acquires the data indicating the user input.

[0021] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user by outputting the data in a form perceptible to the user (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0022] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

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

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

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

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

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

[0028] (Example of form 1) The off-grid AI companion system according to an embodiment of the present invention is a system that operates even without an internet connection in situations where there is a possibility of living in a shelter for an extended period during emergencies such as war, terrorism, or natural disasters. This off-grid AI companion system provides survival skills, medical knowledge, and psychological support to support life in the shelter. During normal times, the AI ​​model can be regularly updated to incorporate the latest knowledge. First, it provides information necessary for the user to live in the shelter. For example, as survival skills, it provides information on how to preserve food, how to secure water, and first aid procedures. As medical knowledge, it provides information on how to deal with common illnesses and injuries, and how to use medicines. Furthermore, as psychological support, it provides advice and relaxation methods to reduce stress and anxiety. Because this off-grid AI companion system operates without an internet connection, it can be used with peace of mind even during emergencies. For example, even if life in the shelter lasts for an extended period, it can continue to provide necessary information. Also, because the AI ​​model can be regularly updated to incorporate the latest knowledge during normal times, it can always provide the most up-to-date information. This system can provide an environment where people can live with peace of mind even in times of emergency, contributing to the overall resilience of society. For example, even if life in a shelter lasts for an extended period, it can continue to provide necessary information, thereby reducing stress and anxiety. Furthermore, by providing survival skills and medical knowledge, it can compensate for any lack of specialized knowledge and skills necessary for survival. In this way, the off-grid AI companion system can provide users with an environment in which they can live with peace of mind within a shelter.

[0029] The off-grid AI companion system according to this embodiment comprises a provisioning unit, an update unit, and an interface unit. The provisioning unit provides information. For example, the provisioning unit provides survival skills, medical knowledge, and psychological support. For example, the provisioning unit can provide methods for preserving food, methods for securing water, and first-aid procedures. The provisioning unit can also provide methods for dealing with common illnesses and injuries, and how to use medicines. Furthermore, the provisioning unit can also provide advice and relaxation methods to reduce stress and anxiety. The update unit supplies the provisioning unit with the latest information. For example, the update unit periodically updates the AI ​​model during normal times to incorporate the latest knowledge. For example, the update unit can update the AI ​​model monthly to incorporate the latest medical knowledge and survival skills. The update unit can also incorporate the latest psychological support methods. The interface unit interacts with the user. For example, the interface unit interacts with the user by methods such as chat, voice, and video. For example, when the user enters a question, the interface unit displays information from the provisioning unit. Furthermore, the interface unit can accept voice input and respond with information from the information provider unit in voice. In addition, the interface unit can interact with the user in real time through video calls. As a result, the off-grid AI companion system according to this embodiment can provide the user with necessary information, supply the latest information, and interact with the user.

[0030] The service provider will provide information. For example, they will provide survival skills, medical knowledge, and psychological support. Specifically, they can provide detailed explanations on how to preserve food, how to secure water, and first aid procedures. For example, regarding food preservation, they will provide information on how to select and preserve foods that can be stored for a long time, as well as guidelines for storage periods. Regarding water acquisition, they will provide detailed explanations on how to collect water from the natural environment, how to purify it, and the necessary tools and procedures. Regarding first aid procedures, they will specifically show how to respond to injuries and illnesses initially, and how to use necessary medical equipment and medicines. Furthermore, the service provider can also provide information on how to deal with common illnesses and injuries, and how to use medicines. For example, they will provide detailed explanations on how to deal with symptoms of colds and influenza, first aid for fractures and sprains, and how to select and use common medicines. Regarding psychological support, they will provide advice and relaxation methods to reduce stress and anxiety. For example, they will provide relaxation methods such as deep breathing, meditation, and simple exercises, as well as specific advice for stress management. This allows the service provider to comprehensively provide users with a variety of information they need in emergencies and in their daily lives, thereby enhancing their sense of security and safety.

[0031] The update department supplies the service provider with the latest information. Specifically, the update department regularly updates the AI ​​model during normal operation, incorporating the latest knowledge. For example, the AI ​​model can be updated monthly to incorporate the latest medical knowledge and survival skills. The update department collects the latest databases, research papers, and expert opinions in an environment with internet connectivity and reflects them in the AI ​​model. This ensures that the service provider always provides users with information based on the latest data. Furthermore, the update department can also incorporate the latest psychological support methods. For example, by incorporating new relaxation techniques, stress management methods, and the latest research findings in psychotherapy, it can provide more effective support to users. To maintain the accuracy and reliability of the AI ​​model, the update department conducts regular tests and evaluations, and adjusts and improves the model as needed. This allows the update department to support the service provider in always providing the latest and most accurate information, improving the reliability and usefulness of the entire system.

[0032] The interface unit interacts with the user. Specifically, the interface unit interacts with the user through methods such as chat, voice, and video. For example, when a user enters a question, it displays information from the service provider. The interface unit can also accept voice input and provide information from the service provider in voice. This allows users to obtain information without using their hands, improving convenience. Furthermore, the interface unit can interact with the user in real time through video calls. For example, when a user is actually performing first aid procedures, they can proceed while receiving instructions from the service provider via video call. This allows users to receive more specific and practical support. The interface unit contributes to the improvement of the entire system by collecting user feedback and sending it to the service provider and update departments. For example, if a user points out questions or areas for improvement regarding the information provided, the update department can collect that information and reflect it in the next update. In this way, the interface unit can achieve smooth communication with users and improve the usability and effectiveness of the entire system.

[0033] The Survival Club provides survival skills. For example, it can provide methods for starting a fire. The Survival Club can also provide methods for procuring food. The Survival Club can also provide first aid procedures. In this way, the Survival Club enables users to acquire the skills necessary for survival.

[0034] The medical department provides medical knowledge. For example, the medical department provides information on disease prevention. The medical department can also provide information on first aid procedures. The medical department can also provide information on how to use medications. This allows the medical department to acquire the knowledge necessary for users to maintain their health.

[0035] The psychology department provides psychological support. For example, it offers counseling. The psychology department can also provide methods for stress management. The psychology department can also provide relaxation techniques. In this way, the psychology department can support the mental health of users.

[0036] The service provider offers survival skills, medical knowledge, and psychological support. For example, they can provide instructions on how to start a fire. They can also provide information on disease prevention. They can also provide information on stress management. This allows the service provider to meet the diverse needs of users by offering a variety of information.

[0037] The update department regularly updates the AI ​​model during normal operation to incorporate the latest knowledge. For example, the update department updates the AI ​​model monthly to incorporate the latest medical knowledge and survival skills. The update department can also incorporate the latest psychological support methods, for example. This ensures that the update department always provides the most up-to-date information.

[0038] The information provider dynamically changes the priority of the information it provides based on the user's current situation and needs. For example, if a user is injured, the provider will prioritize providing first-aid procedures. If a user is complaining of a food shortage, the provider may also prioritize providing information on food preservation methods and alternative ingredients. If a user is having trouble securing water, the provider may also prioritize providing information on water purification methods and how to secure water. In this way, the provider can provide more appropriate information by changing the priority of information according to the user's situation and needs.

[0039] The information provider customizes the format of the information provided according to the user's level of understanding and learning style. For example, if the user is a visual learner, the provider will provide information using diagrams and videos. If the user is an auditory learner, the provider can also provide information in the form of audio guides or podcasts. If the user is a hands-on learner, the provider can also provide step-by-step practical guides. By customizing the format of information according to the user's level of understanding and learning style, the provider can deliver information more effectively.

[0040] The service provider personalizes the information it provides based on the user's past behavior history and preferences. For example, it might prioritize providing survival skills that the user has previously enjoyed using. It could also prioritize providing medical knowledge that the user has previously shown interest in. It could also prioritize providing psychological support methods that the user has previously used. By personalizing information based on the user's past behavior history and preferences, the service provider can deliver more relevant information.

[0041] The service provider optimizes the information it provides based on the user's geographical location and environmental conditions. For example, if the user is in a cold region, the service provider can provide survival skills for dealing with the cold. For example, if the user is at a high altitude, the service provider can also provide medical knowledge for preventing altitude sickness. For example, if the user is in an isolated location, the service provider can also provide psychological support to alleviate feelings of loneliness. In this way, the service provider can provide more appropriate information by optimizing the information based on the user's geographical location and environmental conditions.

[0042] The update unit selects the optimal update content by referring to past data during the update process. For example, the update unit can select the optimal update content based on information the user has used in the past. The update unit can also analyze the user's past behavior history and prioritize updating necessary information. For example, the update unit can customize the update content by considering the user's past preferences. As a result, the update unit can perform more effective updates by selecting the optimal update content by referring to past data.

[0043] The update unit customizes the content of updates based on the user's current situation and needs. For example, if the user is injured, the update unit will prioritize updating with the latest information on first aid. For example, if the user is complaining of a food shortage, the update unit can also update with the latest information on food preservation methods. For example, if the user is feeling stressed, the update unit can also update with the latest information on relaxation methods. In this way, the update unit can provide more appropriate information by customizing the content of updates according to the user's situation and needs.

[0044] The update unit personalizes update content based on the user's past behavior history and preferences. For example, the update unit prioritizes updating the latest information on survival skills that the user has previously enjoyed using. It can also update the latest information on medical knowledge that the user has previously shown interest in. It can also update the latest information on psychological support methods that the user has previously used. In this way, the update unit can provide more relevant information by personalizing update content based on the user's past behavior history and preferences.

[0045] The update unit optimizes the content of updates based on the user's geographical location and environmental conditions. For example, if the user is in a cold region, the update unit will update with the latest information on cold weather countermeasures. For example, if the user is at a high altitude, the update unit can also update with the latest information on altitude sickness countermeasures. For example, if the user is in an isolated location, the update unit can also update with the latest information on alleviating feelings of loneliness. In this way, the update unit can provide more appropriate information by optimizing the content of updates based on the user's geographical location and environmental conditions.

[0046] The interface unit selects the optimal display method by referring to the user's past operation history when displaying the interface. For example, the interface unit prioritizes displaying interface designs that the user has previously preferred. The interface unit can also analyze the user's past operation history and select the most efficient display method. For example, the interface unit can suggest the optimal display method based on the operation procedures the user has used in the past. As a result, the interface unit can display more effectively by referring to the user's past operation history and selecting the optimal display method.

[0047] The interface unit customizes the operation procedures of the interface according to the user's level of understanding and learning style. For example, if the user is a visual learner, the interface unit provides operation procedures using diagrams and videos. If the user is an auditory learner, the interface unit can also provide operation procedures in the form of audio guides or podcasts. If the user is a hands-on learner, the interface unit can also provide step-by-step practical guides. In this way, the interface unit enables more effective operation by customizing the operation procedures according to the user's level of understanding and learning style.

[0048] The interface unit selects the optimal display method when displaying the interface, taking into account the user's device information. For example, if the user is using a smartphone, the interface unit provides a display method that matches the screen size. If the user is using a tablet, the interface unit can also provide a display method optimized for a larger screen. If the user is using a smartwatch, the interface unit can also provide a concise and highly visible display method. As a result, the interface unit can enable more effective display by selecting the optimal display method based on the user's device information.

[0049] The interface unit customizes the interface design based on the user's visual preferences. For example, the interface unit customizes the interface design based on the user's preferred colors and themes. The interface unit can also suggest the optimal design by referring to design options the user has previously selected. For example, the interface unit can adjust font size and icon placement according to the user's visual preferences. In this way, the interface unit enables a more comfortable user experience by customizing the design according to the user's visual preferences.

[0050] The Survival Department customizes the content of survival skills provided based on the user's current situation and needs. For example, if a user is experiencing food shortages, the Survival Department will prioritize providing information on food preservation methods and alternative ingredients. If a user is having trouble securing water, the Survival Department can also prioritize providing information on water purification and procurement methods. If a user is injured, the Survival Department can also prioritize providing first aid procedures. In this way, the Survival Department can provide more appropriate skills by customizing the content of survival skills according to the user's situation and needs.

[0051] The Survival Department optimizes the content of survival skills provided based on the user's geographical location and environmental conditions. For example, if the user is in a cold region, the Survival Department will provide survival skills to combat the cold. If the user is at a high altitude, the Survival Department can also provide survival skills to prevent altitude sickness. If the user is in an isolated location, the Survival Department can also provide survival skills to alleviate feelings of loneliness. By optimizing the content of survival skills based on the user's geographical location and environmental conditions, the Survival Department can provide more appropriate skills.

[0052] The medical department customizes the content of medical knowledge provided based on the user's current health condition and needs. For example, if a user is injured, the medical department will prioritize providing first aid procedures. If a user is complaining of symptoms of an illness, the medical department can also provide information on how to deal with those symptoms. If a user is having trouble using medication, the medical department can provide instructions and precautions for using the medication. In this way, the medical department can provide more appropriate knowledge by customizing the content of medical knowledge according to the user's health condition and needs.

[0053] The medical department optimizes the content of medical knowledge provided based on the user's geographical location and environmental conditions. For example, if the user is in a cold region, the medical department will provide medical knowledge on cold weather countermeasures. If the user is at a high altitude, the medical department can also provide medical knowledge on altitude sickness countermeasures. If the user is in an isolated location, the medical department can also provide medical knowledge to alleviate feelings of loneliness. By optimizing the content of medical knowledge based on the user's geographical location and environmental conditions, the medical department can provide more appropriate knowledge.

[0054] The psychology department customizes the content of psychological support provided based on the user's current psychological state and needs. For example, if a user is experiencing stress, the psychology department can provide advice on stress reduction. If a user is experiencing anxiety, the psychology department can also provide relaxation methods to alleviate that anxiety. If a user is feeling lonely, the psychology department can also provide psychological support to reduce feelings of loneliness. In this way, the psychology department can provide more appropriate support by customizing the content of psychological support according to the user's psychological state and needs.

[0055] The psychology department optimizes the content of psychological support based on the user's geographical location and environmental conditions. For example, if the user is in a cold region, the psychology department can provide psychological support to help them cope with the cold. If the user is at a high altitude, the psychology department can also provide psychological support to help them cope with altitude sickness. If the user is in an isolated location, the psychology department can also provide psychological support to alleviate feelings of loneliness. By optimizing the content of psychological support based on the user's geographical location and environmental conditions, the psychology department can provide more appropriate support.

[0056] The system according to the embodiment is not limited to the example described above, and various modifications are possible, for example, as follows.

[0057] The off-grid AI companion system can also be equipped with an energy management unit. This unit provides information to optimize energy consumption within the shelter. For example, it can suggest efficient ways to utilize the solar power system. It can also suggest optimal charging and discharging timings to extend battery life. Furthermore, it can monitor power consumption within the shelter in real time and suggest energy-saving methods. This allows the energy management unit to optimize energy consumption within the shelter and support long-term living.

[0058] The off-grid AI companion system can also include an education section. This education section supports learning activities within the shelter. For example, it can provide educational content for children. It can also provide skill-building courses and hobby-based learning content for adults. Furthermore, the education section can monitor users' learning progress and suggest appropriate learning plans. This allows the education section to effectively utilize time within the shelter and support the improvement of users' knowledge and skills.

[0059] The off-grid AI companion system can also be equipped with an agricultural department. This department can support food production within the shelter. For example, it can provide instructions on setting up and cultivating a vegetable garden. It can also monitor the user's cultivation progress and provide appropriate advice. Furthermore, it can suggest technologies and methods to improve the efficiency of food production within the shelter. This allows the agricultural department to increase food self-sufficiency within the shelter and support the user's diet.

[0060] The following briefly describes the processing flow for example form 1.

[0061] Step 1: The provider provides information. For example, the provider provides survival skills, medical knowledge, and psychological support. Specifically, they provide information on how to store food and secure water, first aid procedures, how to deal with common illnesses and injuries, how to use medicine, and advice and relaxation methods to reduce stress and anxiety. Step 2: The update department supplies the latest information to the provision department. For example, the update department regularly updates the AI ​​model during normal times to incorporate the latest knowledge. Specifically, the AI ​​model is updated monthly to incorporate the latest medical knowledge, survival skills, and psychological support methods. Step 3: The interface unit interacts with the user. The interface unit interacts with the user through methods such as chat, voice, and video. Specifically, when the user enters a question, it displays information from the service provider, accepts voice input and responds with information from the service provider via voice, and interacts in real time through video calls.

[0062] (Example of form 2) The off-grid AI companion system according to an embodiment of the present invention is a system that operates even without an internet connection in situations where there is a possibility of living in a shelter for an extended period during emergencies such as war, terrorism, or natural disasters. This off-grid AI companion system provides survival skills, medical knowledge, and psychological support to support life in the shelter. During normal times, the AI ​​model can be regularly updated to incorporate the latest knowledge. First, it provides information necessary for the user to live in the shelter. For example, as survival skills, it provides information on how to preserve food, how to secure water, and first aid procedures. As medical knowledge, it provides information on how to deal with common illnesses and injuries, and how to use medicines. Furthermore, as psychological support, it provides advice and relaxation methods to reduce stress and anxiety. Because this off-grid AI companion system operates without an internet connection, it can be used with peace of mind even during emergencies. For example, even if life in the shelter lasts for an extended period, it can continue to provide necessary information. Also, because the AI ​​model can be regularly updated to incorporate the latest knowledge during normal times, it can always provide the most up-to-date information. This system can provide an environment where people can live with peace of mind even in times of emergency, contributing to the overall resilience of society. For example, even if life in a shelter lasts for an extended period, it can continue to provide necessary information, thereby reducing stress and anxiety. Furthermore, by providing survival skills and medical knowledge, it can compensate for any lack of specialized knowledge and skills necessary for survival. In this way, the off-grid AI companion system can provide users with an environment in which they can live with peace of mind within a shelter.

[0063] The off-grid AI companion system according to this embodiment comprises a provisioning unit, an update unit, and an interface unit. The provisioning unit provides information. For example, the provisioning unit provides survival skills, medical knowledge, and psychological support. For example, the provisioning unit can provide methods for preserving food, methods for securing water, and first-aid procedures. The provisioning unit can also provide methods for dealing with common illnesses and injuries, and how to use medicines. Furthermore, the provisioning unit can also provide advice and relaxation methods to reduce stress and anxiety. The update unit supplies the provisioning unit with the latest information. For example, the update unit periodically updates the AI ​​model during normal times to incorporate the latest knowledge. For example, the update unit can update the AI ​​model monthly to incorporate the latest medical knowledge and survival skills. The update unit can also incorporate the latest psychological support methods. The interface unit interacts with the user. For example, the interface unit interacts with the user by methods such as chat, voice, and video. For example, when the user enters a question, the interface unit displays information from the provisioning unit. Furthermore, the interface unit can accept voice input and respond with information from the information provider unit in voice. In addition, the interface unit can interact with the user in real time through video calls. As a result, the off-grid AI companion system according to this embodiment can provide the user with necessary information, supply the latest information, and interact with the user.

[0064] The service provider will provide information. For example, they will provide survival skills, medical knowledge, and psychological support. Specifically, they can provide detailed explanations on how to preserve food, how to secure water, and first aid procedures. For example, regarding food preservation, they will provide information on how to select and preserve foods that can be stored for a long time, as well as guidelines for storage periods. Regarding water acquisition, they will provide detailed explanations on how to collect water from the natural environment, how to purify it, and the necessary tools and procedures. Regarding first aid procedures, they will specifically show how to respond to injuries and illnesses initially, and how to use necessary medical equipment and medicines. Furthermore, the service provider can also provide information on how to deal with common illnesses and injuries, and how to use medicines. For example, they will provide detailed explanations on how to deal with symptoms of colds and influenza, first aid for fractures and sprains, and how to select and use common medicines. Regarding psychological support, they will provide advice and relaxation methods to reduce stress and anxiety. For example, they will provide relaxation methods such as deep breathing, meditation, and simple exercises, as well as specific advice for stress management. This allows the service provider to comprehensively provide users with a variety of information they need in emergencies and in their daily lives, thereby enhancing their sense of security and safety.

[0065] The update department supplies the service provider with the latest information. Specifically, the update department regularly updates the AI ​​model during normal operation, incorporating the latest knowledge. For example, the AI ​​model can be updated monthly to incorporate the latest medical knowledge and survival skills. The update department collects the latest databases, research papers, and expert opinions in an environment with internet connectivity and reflects them in the AI ​​model. This ensures that the service provider always provides users with information based on the latest data. Furthermore, the update department can also incorporate the latest psychological support methods. For example, by incorporating new relaxation techniques, stress management methods, and the latest research findings in psychotherapy, it can provide more effective support to users. To maintain the accuracy and reliability of the AI ​​model, the update department conducts regular tests and evaluations, and adjusts and improves the model as needed. This allows the update department to support the service provider in always providing the latest and most accurate information, improving the reliability and usefulness of the entire system.

[0066] The interface unit interacts with the user. Specifically, the interface unit interacts with the user through methods such as chat, voice, and video. For example, when a user enters a question, it displays information from the service provider. The interface unit can also accept voice input and provide information from the service provider in voice. This allows users to obtain information without using their hands, improving convenience. Furthermore, the interface unit can interact with the user in real time through video calls. For example, when a user is actually performing first aid procedures, they can proceed while receiving instructions from the service provider via video call. This allows users to receive more specific and practical support. The interface unit contributes to the improvement of the entire system by collecting user feedback and sending it to the service provider and update departments. For example, if a user points out questions or areas for improvement regarding the information provided, the update department can collect that information and reflect it in the next update. In this way, the interface unit can achieve smooth communication with users and improve the usability and effectiveness of the entire system.

[0067] The Survival Club provides survival skills. For example, it can provide methods for starting a fire. The Survival Club can also provide methods for procuring food. The Survival Club can also provide first aid procedures. In this way, the Survival Club enables users to acquire the skills necessary for survival.

[0068] The medical department provides medical knowledge. For example, the medical department provides information on disease prevention. The medical department can also provide information on first aid procedures. The medical department can also provide information on how to use medications. This allows the medical department to acquire the knowledge necessary for users to maintain their health.

[0069] The psychology department provides psychological support. For example, it offers counseling. The psychology department can also provide methods for stress management. The psychology department can also provide relaxation techniques. In this way, the psychology department can support the mental health of users.

[0070] The service provider offers survival skills, medical knowledge, and psychological support. For example, they can provide instructions on how to start a fire. They can also provide information on disease prevention. They can also provide information on stress management. This allows the service provider to meet the diverse needs of users by offering a variety of information.

[0071] The update department regularly updates the AI ​​model during normal operation to incorporate the latest knowledge. For example, the update department updates the AI ​​model monthly to incorporate the latest medical knowledge and survival skills. The update department can also incorporate the latest psychological support methods, for example. This ensures that the update department always provides the most up-to-date information.

[0072] The service provider estimates the user's emotions and adjusts the content of the information provided based on the estimated emotions. For example, if the user is feeling anxious, the service provider will prioritize providing relaxation methods and stress reduction advice. If the user is excited, the service provider may also provide breathing exercises or meditation techniques to help them calm down. If the user is tired, the service provider may also provide information on the importance of rest and effective ways to rest. In this way, the service provider can provide more appropriate information by adjusting the content of the information according to the user's emotions. Emotion estimation is achieved using an emotion estimation function, such as an emotion engine or generative AI. Generative AI may include, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI.

[0073] The information provider dynamically changes the priority of the information it provides based on the user's current situation and needs. For example, if a user is injured, the provider will prioritize providing first-aid procedures. If a user is complaining of a food shortage, the provider may also prioritize providing information on food preservation methods and alternative ingredients. If a user is having trouble securing water, the provider may also prioritize providing information on water purification methods and how to secure water. In this way, the provider can provide more appropriate information by changing the priority of information according to the user's situation and needs.

[0074] The information provider customizes the format of the information provided according to the user's level of understanding and learning style. For example, if the user is a visual learner, the provider will provide information using diagrams and videos. If the user is an auditory learner, the provider can also provide information in the form of audio guides or podcasts. If the user is a hands-on learner, the provider can also provide step-by-step practical guides. By customizing the format of information according to the user's level of understanding and learning style, the provider can deliver information more effectively.

[0075] The information provider estimates the user's emotions and adjusts the frequency of information delivery based on the estimated emotions. For example, if the user is stressed, the information provider reduces the frequency of information delivery and increases the time for relaxation. For example, if the user is excited, the information provider may increase the frequency of information delivery and provide information to help them calm down. For example, if the user is tired, the information provider may reduce the frequency of information delivery and encourage rest. In this way, the information provider can deliver information at a more appropriate time by adjusting the frequency of information delivery according to the user's emotions. Emotion estimation is achieved using an emotion estimation function, such as an emotion engine or generative AI. Generative AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI.

[0076] The service provider personalizes the information it provides based on the user's past behavior history and preferences. For example, it might prioritize providing survival skills that the user has previously enjoyed using. It could also prioritize providing medical knowledge that the user has previously shown interest in. It could also prioritize providing psychological support methods that the user has previously used. By personalizing information based on the user's past behavior history and preferences, the service provider can deliver more relevant information.

[0077] The service provider optimizes the information it provides based on the user's geographical location and environmental conditions. For example, if the user is in a cold region, the service provider can provide survival skills for dealing with the cold. For example, if the user is at a high altitude, the service provider can also provide medical knowledge for preventing altitude sickness. For example, if the user is in an isolated location, the service provider can also provide psychological support to alleviate feelings of loneliness. In this way, the service provider can provide more appropriate information by optimizing the information based on the user's geographical location and environmental conditions.

[0078] The update unit estimates the user's emotions and adjusts the timing of updates based on the estimated emotions. For example, if the user is relaxed, the update unit will select a suitable time to perform an update. If the user is stressed, the update unit may prioritize relaxation time by postponing the update. If the user is excited, the update unit may perform an update quickly to provide the latest information. In this way, the update unit can perform updates at more appropriate times by adjusting the timing according to the user's emotions. Emotion estimation is achieved using an emotion estimation function, such as an emotion engine or generative AI. Generative AI includes, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI.

[0079] The update unit selects the optimal update content by referring to past data during the update process. For example, the update unit can select the optimal update content based on information the user has used in the past. The update unit can also analyze the user's past behavior history and prioritize updating necessary information. For example, the update unit can customize the update content by considering the user's past preferences. As a result, the update unit can perform more effective updates by selecting the optimal update content by referring to past data.

[0080] The update unit customizes the content of updates based on the user's current situation and needs. For example, if the user is injured, the update unit will prioritize updating with the latest information on first aid. For example, if the user is complaining of a food shortage, the update unit can also update with the latest information on food preservation methods. For example, if the user is feeling stressed, the update unit can also update with the latest information on relaxation methods. In this way, the update unit can provide more appropriate information by customizing the content of updates according to the user's situation and needs.

[0081] The update unit estimates the user's emotions and adjusts the update frequency based on the estimated emotions. For example, if the user is relaxed, the update unit increases the update frequency to provide the latest information. If the user is stressed, the update unit can also decrease the update frequency to allow for more time to relax. If the user is excited, the update unit can also increase the update frequency to provide the latest information quickly. In this way, the update unit can provide updates at a more appropriate time by adjusting the update frequency according to the user's emotions. Emotion estimation is achieved using an emotion estimation function, such as an emotion engine or generative AI. Generative AI includes, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI.

[0082] The update unit personalizes update content based on the user's past behavior history and preferences. For example, the update unit prioritizes updating the latest information on survival skills that the user has previously enjoyed using. It can also update the latest information on medical knowledge that the user has previously shown interest in. It can also update the latest information on psychological support methods that the user has previously used. In this way, the update unit can provide more relevant information by personalizing update content based on the user's past behavior history and preferences.

[0083] The update unit optimizes the content of updates based on the user's geographical location and environmental conditions. For example, if the user is in a cold region, the update unit will update with the latest information on cold weather countermeasures. For example, if the user is at a high altitude, the update unit can also update with the latest information on altitude sickness countermeasures. For example, if the user is in an isolated location, the update unit can also update with the latest information on alleviating feelings of loneliness. In this way, the update unit can provide more appropriate information by optimizing the content of updates based on the user's geographical location and environmental conditions.

[0084] The interface unit estimates the user's emotions and adjusts the interface display method based on the estimated emotions. For example, if the user is tense, the interface unit provides an interface with calming colors to reduce visual stress. For example, if the user is having fun, the interface unit can provide an interface with bright colors to make the input process more enjoyable. For example, if the user is tired, the interface unit can provide a simple and highly visible interface to facilitate the input process. In this way, the interface unit can provide a more appropriate display by adjusting the interface display method according to the user's emotions. Emotion estimation is achieved using an emotion estimation function, such as an emotion engine or generative AI. Generative AI includes, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI.

[0085] The interface unit selects the optimal display method by referring to the user's past operation history when displaying the interface. For example, the interface unit prioritizes displaying interface designs that the user has previously preferred. The interface unit can also analyze the user's past operation history and select the most efficient display method. For example, the interface unit can suggest the optimal display method based on the operation procedures the user has used in the past. As a result, the interface unit can display more effectively by referring to the user's past operation history and selecting the optimal display method.

[0086] The interface unit customizes the operation procedures of the interface according to the user's level of understanding and learning style. For example, if the user is a visual learner, the interface unit provides operation procedures using diagrams and videos. If the user is an auditory learner, the interface unit can also provide operation procedures in the form of audio guides or podcasts. If the user is a hands-on learner, the interface unit can also provide step-by-step practical guides. In this way, the interface unit enables more effective operation by customizing the operation procedures according to the user's level of understanding and learning style.

[0087] The interface unit estimates the user's emotions and adjusts the interface's operation procedures based on the estimated emotions. For example, if the user is tense, the interface unit provides simple and highly visible operation procedures. For example, if the user is relaxed, the interface unit can also provide detailed operation procedures. For example, if the user is in a hurry, the interface unit can provide concise operation procedures. In this way, the interface unit enables more appropriate operation by adjusting the operation procedures according to the user's emotions. Emotion estimation is achieved using an emotion estimation function, such as an emotion engine or generative AI. Generative AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI.

[0088] The interface unit selects the optimal display method when displaying the interface, taking into account the user's device information. For example, if the user is using a smartphone, the interface unit provides a display method that matches the screen size. If the user is using a tablet, the interface unit can also provide a display method optimized for a larger screen. If the user is using a smartwatch, the interface unit can also provide a concise and highly visible display method. As a result, the interface unit can enable more effective display by selecting the optimal display method based on the user's device information.

[0089] The interface unit customizes the interface design based on the user's visual preferences. For example, the interface unit customizes the interface design based on the user's preferred colors and themes. The interface unit can also suggest the optimal design by referring to design options the user has previously selected. For example, the interface unit can adjust font size and icon placement according to the user's visual preferences. In this way, the interface unit enables a more comfortable user experience by customizing the design according to the user's visual preferences.

[0090] The Survival Department estimates the user's emotions and adjusts how survival skills are provided based on those estimated emotions. For example, if the user is feeling anxious, the Survival Department will prioritize providing relaxation methods and stress reduction advice. If the user is excited, the Survival Department may also provide breathing exercises and meditation techniques to help them calm down. If the user is tired, the Survival Department may also provide information on the importance of rest and effective ways to rest. This allows the Survival Department to provide more appropriate skills by adjusting how survival skills are delivered according to the user's emotions. Emotion estimation is achieved using emotion estimation functions, such as an emotion engine or generative AI. Generative AI includes, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI.

[0091] The Survival Department customizes the content of survival skills provided based on the user's current situation and needs. For example, if a user is experiencing food shortages, the Survival Department will prioritize providing information on food preservation methods and alternative ingredients. If a user is having trouble securing water, the Survival Department can also prioritize providing information on water purification and procurement methods. If a user is injured, the Survival Department can also prioritize providing first aid procedures. In this way, the Survival Department can provide more appropriate skills by customizing the content of survival skills according to the user's situation and needs.

[0092] The Survival Unit estimates the user's emotions and adjusts the frequency of survival skill delivery based on the estimated emotions. For example, if the user is stressed, the Survival Unit reduces the frequency of information delivery and increases the time for relaxation. For example, if the user is excited, the Survival Unit can increase the frequency of information delivery and provide information to help them calm down. For example, if the user is tired, the Survival Unit can reduce the frequency of information delivery and encourage rest. In this way, the Survival Unit can provide skills at a more appropriate time by adjusting the frequency of survival skill delivery according to the user's emotions. Emotion estimation is achieved using an emotion estimation function, such as an emotion engine or generative AI. Generative AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI.

[0093] The Survival Department optimizes the content of survival skills provided based on the user's geographical location and environmental conditions. For example, if the user is in a cold region, the Survival Department will provide survival skills to combat the cold. If the user is at a high altitude, the Survival Department can also provide survival skills to prevent altitude sickness. If the user is in an isolated location, the Survival Department can also provide survival skills to alleviate feelings of loneliness. By optimizing the content of survival skills based on the user's geographical location and environmental conditions, the Survival Department can provide more appropriate skills.

[0094] The medical department estimates the user's emotions and adjusts how medical knowledge is delivered based on those estimates. For example, if the user is feeling anxious, the medical department prioritizes providing relaxation techniques and stress reduction advice. If the user is agitated, the medical department may also provide breathing exercises or meditation techniques to help them calm down. If the user is tired, the medical department may also provide information on the importance of rest and effective ways to rest. This allows the medical department to provide more appropriate knowledge by adjusting how medical knowledge is delivered according to the user's emotions. Emotion estimation is achieved using emotion estimation functions, such as emotion engines or generative AI. Generative AI includes, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI.

[0095] The medical department customizes the content of medical knowledge provided based on the user's current health condition and needs. For example, if a user is injured, the medical department will prioritize providing first aid procedures. If a user is complaining of symptoms of an illness, the medical department can also provide information on how to deal with those symptoms. If a user is having trouble using medication, the medical department can provide instructions and precautions for using the medication. In this way, the medical department can provide more appropriate knowledge by customizing the content of medical knowledge according to the user's health condition and needs.

[0096] The medical department estimates the user's emotions and adjusts the frequency of medical knowledge delivery based on the estimated emotions. For example, if the user is stressed, the medical department reduces the frequency of information delivery and increases the time for relaxation. For example, if the user is agitated, the medical department may increase the frequency of information delivery and provide information to help them calm down. For example, if the user is tired, the medical department may reduce the frequency of information delivery and encourage rest. In this way, the medical department can deliver knowledge at a more appropriate time by adjusting the frequency of medical knowledge delivery according to the user's emotions. Emotion estimation is achieved using emotion estimation functions, such as emotion engines or generative AI. Generative AI includes, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI.

[0097] The medical department optimizes the content of medical knowledge provided based on the user's geographical location and environmental conditions. For example, if the user is in a cold region, the medical department will provide medical knowledge on cold weather countermeasures. If the user is at a high altitude, the medical department can also provide medical knowledge on altitude sickness countermeasures. If the user is in an isolated location, the medical department can also provide medical knowledge to alleviate feelings of loneliness. By optimizing the content of medical knowledge based on the user's geographical location and environmental conditions, the medical department can provide more appropriate knowledge.

[0098] The psychology department estimates the user's emotions and adjusts the method of providing psychological support based on the estimated emotions. For example, if the user is feeling anxious, the psychology department will prioritize providing relaxation methods and stress reduction advice. If the user is agitated, the psychology department may also provide breathing exercises or meditation techniques to help them calm down. If the user is tired, the psychology department may also provide information on the importance of rest and effective ways to rest. This allows the psychology department to provide more appropriate support by adjusting the method of providing psychological support according to the user's emotions. Emotion estimation is achieved using emotion estimation functions, such as emotion engines or generative AI. Generative AI includes, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI.

[0099] The psychology department customizes the content of psychological support provided based on the user's current psychological state and needs. For example, if a user is experiencing stress, the psychology department can provide advice on stress reduction. If a user is experiencing anxiety, the psychology department can also provide relaxation methods to alleviate that anxiety. If a user is feeling lonely, the psychology department can also provide psychological support to reduce feelings of loneliness. In this way, the psychology department can provide more appropriate support by customizing the content of psychological support according to the user's psychological state and needs.

[0100] The psychology department estimates the user's emotions and adjusts the frequency of psychological support provided based on the estimated emotions. For example, if the user is stressed, the psychology department reduces the frequency of information provided and increases the time for relaxation. For example, if the user is agitated, the psychology department may increase the frequency of information provided and offer information to help them calm down. For example, if the user is tired, the psychology department may reduce the frequency of information provided and encourage rest. In this way, the psychology department can provide support at a more appropriate time by adjusting the frequency of psychological support provided according to the user's emotions. Emotion estimation is achieved using emotion estimation functions, such as emotion engines or generative AI. Generative AI includes, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI.

[0101] The psychology department optimizes the content of psychological support based on the user's geographical location and environmental conditions. For example, if the user is in a cold region, the psychology department can provide psychological support to help them cope with the cold. If the user is at a high altitude, the psychology department can also provide psychological support to help them cope with altitude sickness. If the user is in an isolated location, the psychology department can also provide psychological support to alleviate feelings of loneliness. By optimizing the content of psychological support based on the user's geographical location and environmental conditions, the psychology department can provide more appropriate support.

[0102] The system according to the embodiment is not limited to the example described above, and various modifications are possible, for example, as follows.

[0103] The off-grid AI companion system can also be equipped with an energy management unit. This unit provides information to optimize energy consumption within the shelter. For example, it can suggest efficient ways to utilize the solar power system. It can also suggest optimal charging and discharging timings to extend battery life. Furthermore, it can monitor power consumption within the shelter in real time and suggest energy-saving methods. This allows the energy management unit to optimize energy consumption within the shelter and support long-term living.

[0104] The off-grid AI companion system can also be equipped with a communication unit. This unit facilitates communication between users within the shelter. For example, it can support message exchange between users. It can also assist users in real-time communication through voice and video calls. Furthermore, it can estimate users' emotions and suggest appropriate communication methods. This allows the communication unit to reduce feelings of isolation within the shelter and strengthen bonds between users.

[0105] The off-grid AI companion system can also include an education section. This education section supports learning activities within the shelter. For example, it can provide educational content for children. It can also provide skill-building courses and hobby-based learning content for adults. Furthermore, the education section can monitor users' learning progress and suggest appropriate learning plans. This allows the education section to effectively utilize time within the shelter and support the improvement of users' knowledge and skills.

[0106] The off-grid AI companion system can also be equipped with an entertainment section. This section provides recreational activities within the shelter. For example, it can offer content such as movies, music, and games. Furthermore, the entertainment section can estimate the user's emotions and suggest appropriate entertainment content. For instance, if the user is feeling stressed, it can suggest relaxing music or movies. In this way, the entertainment section can make life within the shelter more enjoyable and support the user's mental well-being.

[0107] The off-grid AI companion system can also be equipped with a fitness function. This fitness function supports exercise activities within the shelter. For example, it can provide exercise programs tailored to the user's physical fitness and health condition. It can also estimate the user's emotions and suggest appropriate exercise methods. For instance, if the user is tired, it can suggest light stretching or relaxation exercises. In this way, the fitness function can support health maintenance within the shelter and improve the user's physical and mental well-being.

[0108] The off-grid AI companion system can also be equipped with an agricultural department. This department can support food production within the shelter. For example, it can provide instructions on setting up and cultivating a vegetable garden. It can also monitor the user's cultivation progress and provide appropriate advice. Furthermore, it can suggest technologies and methods to improve the efficiency of food production within the shelter. This allows the agricultural department to increase food self-sufficiency within the shelter and support the user's diet.

[0109] The off-grid AI companion system can also be equipped with a disaster prevention unit. This unit assists with safety measures within the shelter. For example, it can provide information on how to respond to disasters such as earthquakes and fires. It can also provide information on how to inspect and maintain safety equipment within the shelter. Furthermore, the unit can estimate the user's emotions and suggest appropriate disaster prevention measures. For instance, if the user is feeling anxious, it can provide reassuring disaster prevention information. This allows the disaster prevention unit to enhance safety measures within the shelter and improve the user's sense of security.

[0110] The off-grid AI companion system can also be equipped with a resource management unit. This unit assists with resource management within the shelter. For example, it can manage inventory of water, food, and medicine. It can also monitor resource consumption and suggest efficient usage methods. Furthermore, it can estimate the user's emotions and suggest appropriate resource management methods. For instance, if a user is feeling stressed, it can provide reassurance by suggesting ways to conserve resources. This allows the resource management unit to streamline resource management within the shelter and improve user confidence.

[0111] The off-grid AI companion system can also be equipped with an environmental monitoring unit. This unit monitors environmental conditions both inside and outside the shelter. For example, it can monitor temperature, humidity, and air quality inside the shelter in real time. It can also monitor external radiation levels and hazardous substance concentrations and issue warnings to the user. Furthermore, it can estimate the user's emotions and suggest appropriate environmental measures. For instance, if the user is feeling anxious, it can provide reassuring information about the environmental conditions. This allows the environmental monitoring unit to effectively manage environmental conditions inside and outside the shelter, thereby improving the user's sense of security.

[0112] The off-grid AI companion system can also include a maintenance unit. This unit assists with the maintenance and management of equipment and facilities within the shelter. For example, it can provide inspection schedules for equipment and facilities. It can also provide repair methods in case of malfunction and preventative maintenance methods. Furthermore, the maintenance unit can estimate the user's emotions and suggest appropriate maintenance methods. For instance, if the user is feeling anxious, it can provide maintenance information to reassure them. This allows the maintenance unit to streamline the maintenance and management of equipment and facilities within the shelter and improve user confidence.

[0113] The following briefly describes the processing flow for example form 2.

[0114] Step 1: The provider provides information. For example, the provider provides survival skills, medical knowledge, and psychological support. Specifically, they provide information on how to store food and secure water, first aid procedures, how to deal with common illnesses and injuries, how to use medicine, and advice and relaxation methods to reduce stress and anxiety. Step 2: The update department supplies the latest information to the provision department. For example, the update department regularly updates the AI ​​model during normal times to incorporate the latest knowledge. Specifically, the AI ​​model is updated monthly to incorporate the latest medical knowledge, survival skills, and psychological support methods. Step 3: The interface unit interacts with the user. The interface unit interacts with the user through methods such as chat, voice, and video. Specifically, when the user enters a question, it displays information from the service provider, accepts voice input and responds with information from the service provider via voice, and interacts in real time through video calls.

[0115] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0116] Data generation model 58 is a form of so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> Examples of generative AI include text generation AI, image generation AI, and multimodal generation AI. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images (e.g., still image data or video data). The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference result in one or more data formats from audio data, text data, and image data. The data generation model 58 includes, for example, text generation AI, image generation AI, and multimodal generation AI. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specific processing unit 290 performs the specific processing described above using the data generation model 58. The data generation model 58 may be a fine-tuned model that outputs inference results from prompts that do not contain instructions, in which case the data generation model 58 can output inference results from prompts that do not contain instructions. In the data processing device 12, etc., there are multiple types of data generation models 58, and the data generation model 58 includes AI other than generative AI. AI other than generative AI includes, for example, linear regression, logistic regression, decision trees, random forests, support vector machines (SVMs), k-means clustering, convolutional neural networks (CNNs), recurrent neural networks (RNNs), generative adversarial networks (GANs), or naive Bayes, and can perform various processes, but is not limited to these examples. Also, the AI ​​may be an AI agent. Furthermore, when the processing of each of the above parts is performed by the AI, the processing may be performed by the AI ​​in part or in whole, but is not limited to this example.Furthermore, processing performed by AI, including generative AI, may be replaced with rule-based processing, and rule-based processing may be replaced with processing performed by AI, including generative AI.

[0117] Furthermore, the processing performed by the data processing system 10 described above is carried out by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart device 14, but it may also be carried out by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart device 14. In addition, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the smart device 14 or an external device, and the smart device 14 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0118] Each of the multiple elements described above, including the provision unit, update unit, and interface unit, is implemented in at least one of the smart device 14 and the data processing unit 12. For example, the provision unit is implemented by the control unit 46A of the smart device 14 and provides survival skills, medical knowledge, and psychological support. The update unit is implemented by the specific processing unit 290 of the data processing unit 12 and periodically updates the AI ​​model during normal operation to incorporate the latest knowledge. The interface unit is implemented by the control unit 46A of the smart device 14 and interacts with the user in ways such as chat, voice, and video. The survival unit is implemented by the control unit 46A of the smart device 14 and provides methods for starting a fire and procuring food. The medical unit is implemented by the specific processing unit 290 of the data processing unit 12 and provides methods for preventing illness and using medicine. The psychological unit is implemented by the control unit 46A of the smart device 14 and provides methods for counseling and stress management. The correspondence between each part and the device or control unit is not limited to the examples described above, and various modifications are possible.

[0119] [Second Embodiment] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0120] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0121] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN and / or LAN.

[0122] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0123] The microphone 238 receives voice signals from the user and accepts instructions from the user. The microphone 238 captures the voice signals from the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0124] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, which captures images of the area around the user (for example, an imaging range defined by a field of view equivalent to the field of vision of a typical healthy person).

[0125] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0126] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing by the processor 28. The storage 32 stores the specific processing program 56.

[0127] The processor 28 reads a specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 acting as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0128] Storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotions using the emotion identification model 59 and perform identification processing using the user's emotions. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotions, including but not limited to these examples. Furthermore, emotion estimation and prediction also include, for example, emotion analysis.

[0129] In the smart glasses 214, specific processing is performed by the processor 46. The storage 50 stores a specific processing program 60. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 acting as a control unit 46A according to the specific processing program 60 executed on the RAM 48. The smart glasses 214 also have a data generation model 58 and an emotion identification model 59, similar to the data generation model and emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0130] Furthermore, other devices besides the data processing device 12 may also have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 obtains processing results (such as prediction results) using the data generation model 58 by communicating with the server device that has the data generation model 58. Also, the data processing device 12 may be a server device or a terminal device owned by the user (for example, a mobile phone, robot, home appliance, etc.).

[0131] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0132] The data generation model 58 is a so-called generative AI. An example of a data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and inference data such as audio data representing speech, text data representing text, and image data representing images (e.g., still image data or video data). The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference result in one or more data formats such as audio data, text data, and image data. The data generation model 58 includes, for example, text generation AI, image generation AI, and multimodal generation AI. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specific processing unit 290 performs the specific processing described above using the data generation model 58. The data generation model 58 may be a fine-tuned model that outputs inference results from prompts that do not contain instructions, in which case the data generation model 58 can output inference results from prompts that do not contain instructions. In the data processing device 12, etc., there are multiple types of data generation models 58, and the data generation model 58 includes AI other than generative AI. AI other than generative AI includes, for example, linear regression, logistic regression, decision trees, random forests, support vector machines (SVM), k-means clustering, convolutional neural networks (CNN), recurrent neural networks (RNN), generative adversarial networks (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. Also, the AI ​​may be an AI agent. Furthermore, when the processing of each part described above is performed by the AI, the processing may be performed by the AI ​​in part or in whole, but is not limited to this example. Also, processing performed by an AI including a generative AI may be replaced by rule-based processing, and rule-based processing may be replaced by processing performed by an AI including a generative AI.

[0133] The data processing system 210 according to the second embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 210 is performed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart glasses 214, but it may also be performed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart glasses 214. In addition, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the smart glasses 214 or an external device, and the smart glasses 214 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0134] Each of the multiple elements described above, including the provision unit, update unit, and interface unit, is implemented in at least one of the smart glasses 214 and the data processing unit 12. For example, the provision unit is implemented by the control unit 46A of the smart glasses 214 and provides survival skills, medical knowledge, and psychological support. The update unit is implemented by the specific processing unit 290 of the data processing unit 12 and periodically updates the AI ​​model during normal operation to incorporate the latest knowledge. The interface unit is implemented by the control unit 46A of the smart glasses 214 and interacts with the user in ways such as chat, voice, and video. The survival unit is implemented by the control unit 46A of the smart glasses 214 and provides methods for starting a fire and procuring food. The medical unit is implemented by the specific processing unit 290 of the data processing unit 12 and provides methods for preventing illness and using medicine. The psychological unit is implemented by the control unit 46A of the smart glasses 214 and provides methods for counseling and stress management. The correspondence between each part and the device or control unit is not limited to the examples described above, and various modifications are possible.

[0135] [Third Embodiment] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0136] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0137] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN and / or LAN.

[0138] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0139] The microphone 238 receives voice signals from the user and accepts instructions from the user. The microphone 238 captures the voice signals from the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0140] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, which captures images of the area around the user (for example, an imaging range defined by a field of view equivalent to the field of vision of a typical healthy person).

[0141] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0142] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0143] The processor 28 reads a specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 acting as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0144] Storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotions using the emotion identification model 59 and perform identification processing using the user's emotions. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotions, including but not limited to these examples. Furthermore, emotion estimation and prediction also include, for example, emotion analysis.

[0145] In the headset terminal 314, specific processing is performed by the processor 46. The storage 50 stores a specific program 60. The processor 46 reads the specific program 60 from the storage 50 and executes the read specific program 60 on the RAM 48. The specific processing is realized by the processor 46 acting as a control unit 46A according to the specific program 60 executed on the RAM 48. The headset terminal 314 also has a data generation model 58 and an emotion identification model 59, similar to the data generation model and emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0146] Furthermore, other devices besides the data processing device 12 may also have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 obtains processing results (such as prediction results) using the data generation model 58 by communicating with the server device that has the data generation model 58. Also, the data processing device 12 may be a server device or a terminal device owned by the user (for example, a mobile phone, robot, home appliance, etc.).

[0147] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0148] The data generation model 58 is a so-called generative AI. An example of a data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and inference data such as audio data representing speech, text data representing text, and image data representing images (e.g., still image data or video data). The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference result in one or more data formats such as audio data, text data, and image data. The data generation model 58 includes, for example, text generation AI, image generation AI, and multimodal generation AI. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specific processing unit 290 performs the specific processing described above using the data generation model 58. The data generation model 58 may be a fine-tuned model that outputs inference results from prompts that do not contain instructions, in which case the data generation model 58 can output inference results from prompts that do not contain instructions. In the data processing device 12, etc., there are multiple types of data generation models 58, and the data generation model 58 includes AI other than generative AI. AI other than generative AI includes, for example, linear regression, logistic regression, decision trees, random forests, support vector machines (SVM), k-means clustering, convolutional neural networks (CNN), recurrent neural networks (RNN), generative adversarial networks (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. Also, the AI ​​may be an AI agent. Furthermore, when the processing of each part described above is performed by the AI, the processing may be performed by the AI ​​in part or in whole, but is not limited to this example. Also, processing performed by an AI including a generative AI may be replaced by rule-based processing, and rule-based processing may be replaced by processing performed by an AI including a generative AI.

[0149] The data processing system 310 according to the third embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 310 is performed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the headset terminal 314, but may also be performed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the headset terminal 314. In addition, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the headset terminal 314 or an external device, and the headset terminal 314 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0150] Each of the multiple elements described above, including the provision unit, update unit, and interface unit, is implemented in at least one of the headset terminal 314 and the data processing unit 12. For example, the provision unit is implemented by the control unit 46A of the headset terminal 314 and provides survival skills, medical knowledge, and psychological support. The update unit is implemented by the specific processing unit 290 of the data processing unit 12 and periodically updates the AI ​​model during normal operation to incorporate the latest knowledge. The interface unit is implemented by the control unit 46A of the headset terminal 314 and interacts with the user in ways such as chat, voice, and video. The survival unit is implemented by the control unit 46A of the headset terminal 314 and provides methods for starting a fire and procuring food. The medical unit is implemented by the specific processing unit 290 of the data processing unit 12 and provides methods for preventing illness and using medicine. The psychological unit is implemented by the control unit 46A of the headset terminal 314 and provides methods for counseling and stress management. The correspondence between each part and the device or control unit is not limited to the examples described above, and various modifications are possible.

[0151] [Fourth Embodiment] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0152] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0153] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN and / or LAN.

[0154] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0155] The microphone 238 receives voice signals from the user and accepts instructions from the user. The microphone 238 captures the voice signals from the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0156] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS image sensor or CCD image sensor, which captures images of the area around the user (for example, an imaging range defined by a field of view equivalent to the field of vision of a typical healthy person).

[0157] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0158] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. The robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0159] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0160] The processor 28 reads a specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 acting as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0161] Storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotions using the emotion identification model 59 and perform identification processing using the user's emotions. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotions, including but not limited to these examples. Furthermore, emotion estimation and prediction also include, for example, emotion analysis.

[0162] In robot 414, specific processing is performed by processor 46. A specific program 60 is stored in storage 50. Processor 46 reads the specific program 60 from storage 50 and executes it on RAM 48. The specific processing is achieved by processor 46 acting as a control unit 46A according to the specific program 60 executed on RAM 48. Robot 414 also has data generation model 58 and emotion identification model 59, similar to those of the robot, and can perform processing similar to that of the specific processing unit 290 using these models.

[0163] Furthermore, other devices besides the data processing device 12 may also have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 obtains processing results (such as prediction results) using the data generation model 58 by communicating with the server device that has the data generation model 58. Also, the data processing device 12 may be a server device or a terminal device owned by the user (for example, a mobile phone, robot, home appliance, etc.).

[0164] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0165] The data generation model 58 is a so-called generative AI. An example of a data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and inference data such as audio data representing speech, text data representing text, and image data representing images (e.g., still image data or video data). The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference result in one or more data formats such as audio data, text data, and image data. The data generation model 58 includes, for example, text generation AI, image generation AI, and multimodal generation AI. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specific processing unit 290 performs the specific processing described above using the data generation model 58. The data generation model 58 may be a fine-tuned model that outputs inference results from prompts that do not contain instructions, in which case the data generation model 58 can output inference results from prompts that do not contain instructions. In the data processing device 12, etc., there are multiple types of data generation models 58, and the data generation model 58 includes AI other than generative AI. AI other than generative AI includes, for example, linear regression, logistic regression, decision trees, random forests, support vector machines (SVM), k-means clustering, convolutional neural networks (CNN), recurrent neural networks (RNN), generative adversarial networks (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. Also, the AI ​​may be an AI agent. Furthermore, when the processing of each part described above is performed by the AI, the processing may be performed by the AI ​​in part or in whole, but is not limited to this example. Also, processing performed by an AI including a generative AI may be replaced by rule-based processing, and rule-based processing may be replaced by processing performed by an AI including a generative AI.

[0166] The data processing system 410 according to the fourth embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 410 is performed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the robot 414, but it may also be performed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the robot 414. In addition, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the robot 414 or an external device, and the robot 414 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0167] Each of the multiple elements described above, including the provision unit, update unit, and interface unit, is implemented in at least one of the robot 414 and the data processing unit 12. For example, the provision unit is implemented by the control unit 46A of the robot 414 and provides survival skills, medical knowledge, and psychological support. The update unit is implemented by the specific processing unit 290 of the data processing unit 12 and periodically updates the AI ​​model during normal operation to incorporate the latest knowledge. The interface unit is implemented by the control unit 46A of the robot 414 and interacts with the user in ways such as chat, voice, and video. The survival unit is implemented by the control unit 46A of the robot 414 and provides methods for starting a fire and procuring food. The medical unit is implemented by the specific processing unit 290 of the data processing unit 12 and provides methods for preventing illness and using medicine. The psychological unit is implemented by the control unit 46A of the robot 414 and provides methods for counseling and stress management. The correspondence between each part and the device or control unit is not limited to the examples described above, and various modifications are possible.

[0168] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0169] Figure 9 shows the emotion map 400, in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0170] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0171] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0172] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, and motorcycles, emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated based, for example, on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0173] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0174] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0175] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing method for the specific process may be used, which includes computer 22 and multiple other computers.

[0176] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0177] 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.

[0178] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0179] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0180] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0181] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0182] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0183] Furthermore, although the above-described examples were divided into four embodiments, some or all of these embodiments may be combined. Also, the smart device 14, smart glasses 214, headset terminal 314, and robot 414 are just examples, and they may be combined, or other devices may be used. Also, although the above-described examples were divided into two embodiments, Embodiment 1 and Embodiment 2, these may be combined.

[0184] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and other things that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0185] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0186] (Note 1) Information provision department, An update unit that supplies the latest information to the aforementioned supply unit, It comprises an interface unit for interacting with the user. A system characterized by the following features. (Note 2) It features a survival section that provides survival skills. The system described in Appendix 1, characterized by the features described herein. (Note 3) Equipped with a medical department to provide medical knowledge. The system described in Appendix 1, characterized by the features described herein. (Note 4) The facility includes a psychology department that provides psychological support. The system described in Appendix 1, characterized by the features described herein. (Note 5) The aforementioned supply unit is, We provide survival skills, medical knowledge, and psychological support. The system described in Appendix 1, characterized by the features described herein. (Note 6) The aforementioned update section is, Regularly update the AI ​​model during normal times to incorporate the latest knowledge. The system described in Appendix 1, characterized by the features described herein. (Note 7) The aforementioned supply unit is, It estimates the user's emotions and adjusts the content of the information provided based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 8) The aforementioned supply unit is, The priority of the information provided is dynamically changed based on the user's current situation and needs. The system described in Appendix 1, characterized by the features described herein. (Note 9) The aforementioned supply unit is, Customize the format of the information provided according to the user's level of understanding and learning style. The system described in Appendix 1, characterized by the features described herein. (Note 10) The aforementioned supply unit is, It estimates the user's emotions and adjusts the frequency of information delivery based on the estimated user emotions. The system described in Appendix 1, characterized by the features described herein. (Note 11) The aforementioned supply unit is, The information provided is personalized based on the user's past behavior history and preferences. The system described in Appendix 1, characterized by the features described herein. (Note 12) The aforementioned supply unit is, The information provided is optimized based on the user's geographical location and environmental conditions. The system described in Appendix 1, characterized by the features described herein. (Note 13) The aforementioned update section is, We estimate user sentiment and adjust the timing of updates based on that estimated sentiment. The system described in Appendix 1, characterized by the features described herein. (Note 14) The aforementioned update section is, During updates, the system references past data to select the most suitable update content. The system described in Appendix 1, characterized by the features described herein. (Note 15) The aforementioned update section is, Customize the update content based on the user's current situation and needs. The system described in Appendix 1, characterized by the features described herein. (Note 16) The aforementioned update section is, It estimates user sentiment and adjusts the update frequency based on that estimated sentiment. The system described in Appendix 1, characterized by the features described herein. (Note 17) The aforementioned update section is, During updates, the update content is personalized based on the user's past behavior history and preferences. The system described in Appendix 1, characterized by the features described herein. (Note 18) The aforementioned update section is, The update content will be optimized based on the user's geographical location and environmental conditions. The system described in Appendix 1, characterized by the features described herein. (Note 19) The interface unit is It estimates the user's emotions and adjusts the interface display based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 20) The interface unit is When displaying the interface, the system selects the optimal display method by referring to the user's past operation history. The system described in Appendix 1, characterized by the features described herein. (Note 21) The interface unit is Customize the interface operation procedures according to the user's level of understanding and learning style. The system described in Appendix 1, characterized by the features described herein. (Note 22) The interface unit is It estimates the user's emotions and adjusts the interface operation procedures based on the estimated user emotions. The system described in Appendix 1, characterized by the features described herein. (Note 23) The interface unit is When displaying the interface, the optimal display method is selected considering the user's device information. The system described in Appendix 1, characterized by the features described herein. (Note 24) The interface unit is Customize the interface design based on the user's visual preferences. The system described in Appendix 1, characterized by the features described herein. (Note 25) The aforementioned survival section is, It estimates the user's emotions and adjusts how survival skills are delivered based on those estimated emotions. The system described in Appendix 2, characterized by the features described herein. (Note 26) The aforementioned survival section is, When providing survival skills, customize the content based on the user's current situation and needs. The system described in Appendix 2, characterized by the features described herein. (Note 27) The aforementioned survival section is, It estimates the user's emotions and adjusts the frequency of providing survival skills based on those estimated emotions. The system described in Appendix 2, characterized by the features described herein. (Note 28) The aforementioned survival section is, When providing survival skills, the content is optimized based on the user's geographical location and environmental conditions. The system described in Appendix 2, characterized by the features described herein. (Note 29) The aforementioned medical department, The system estimates the user's emotions and adjusts the way medical knowledge is delivered based on those estimated emotions. The system described in Appendix 3, characterized by the features described herein. (Note 30) The aforementioned medical department, When providing medical knowledge, the content is customized based on the user's current health status and needs. The system described in Appendix 3, characterized by the features described herein. (Note 31) The aforementioned medical department, The system estimates the user's emotions and adjusts the frequency of medical information provision based on those emotions. The system described in Appendix 3, characterized by the features described herein. (Note 32) The aforementioned medical department, When providing medical knowledge, the content is optimized based on the user's geographical location and environmental conditions. The system described in Appendix 3, characterized by the features described herein. (Note 33) The aforementioned psychology department, It estimates the user's emotions and adjusts the way psychological support is provided based on the estimated emotions. The system described in Appendix 4, characterized by the features described herein. (Note 34) The aforementioned psychology department, When providing psychological support, customize the content based on the user's current psychological state and needs. The system described in Appendix 4, characterized by the features described herein. (Note 35) The aforementioned psychology department, The system estimates the user's emotions and adjusts the frequency of psychological support provided based on those emotions. The system described in Appendix 4, characterized by the features described herein. (Note 36) The aforementioned psychology department, When providing psychological support, the content is optimized based on the user's geographical location and environmental conditions. The system described in Appendix 4, characterized by the features described herein. [Explanation of Symbols]

[0187] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots

Claims

1. Information provision department, An update unit that supplies the latest information to the aforementioned supply unit, It comprises an interface unit for interacting with the user. A system characterized by the following features.

2. It features a survival section that provides survival skills. The system according to feature 1.

3. Equipped with a medical department to provide medical knowledge. The system according to feature 1.

4. The facility includes a psychology department that provides psychological support. The system according to feature 1.

5. The aforementioned supply unit is, We provide survival skills, medical knowledge, and psychological support. The system according to feature 1.

6. The aforementioned update section is, During normal times, the AI ​​model is regularly updated to incorporate the latest knowledge. The system according to feature 1.

7. The aforementioned supply unit is, It estimates the user's emotions and adjusts the content of the information provided based on those estimated emotions. The system according to feature 1.

8. The aforementioned supply unit is, The priority of the information provided is dynamically changed based on the user's current situation and needs. The system according to feature 1.

9. The aforementioned supply unit is, Customize the format of the information provided according to the user's level of understanding and learning style. The system according to feature 1.

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