system

Abstract

An object of a system according to an embodiment is to enable an individual to take an appropriate action in a disaster or an emergency situation.SOLUTION: A system according to an embodiment includes smart devices equipped with a generation AI and an application. The smart device includes a disaster information providing unit, a rescue procedure providing unit, an evacuation route guiding unit, and an emergency call support unit. The disaster information providing unit provides disaster information. The rescue procedure providing unit provides a rescue procedure for the injured person. The evacuation route guidance unit guides a safe evacuation route based on the GPS information of the user. The emergency call support unit supports an emergency call.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] With conventional technology, it is difficult for individuals to take appropriate action during disasters or emergencies, and there is room for improvement in information gathering and decision-making in situations where a rapid response is required.

[0005] The system according to the embodiment aims to enable individuals to take appropriate actions in the event of a disaster or emergency. [Means for solving the problem]

[0006] The system according to the embodiment includes a smart device equipped with a generation AI and an app. The smart device includes a disaster information providing unit, a rescue procedure providing unit, an evacuation route guidance unit, and an emergency call support unit. The disaster information providing unit provides disaster information. The rescue procedure providing unit provides rescue procedures for injured people. The evacuation route guidance unit guides users to a safe evacuation route based on their GPS information. The emergency call support unit supports emergency calls. [Effects of the Invention]

[0007] The system according to the embodiment enables individuals to take appropriate action in the event of a disaster or emergency. [Brief explanation of the drawings]

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

[0025] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0026] In the smart device 14, the specific processing is performed by the processor 46. The storage 50 stores a specific processing program 60. The specific processing program 60 is used together with the specific processing program 56 by the data processing system 10. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. Note that the smart device 14 may have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59.

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

[0028] (Example 1) The lifesaving AI assistant system according to an embodiment of the present invention supports individuals in taking appropriate actions during disasters and emergencies. This system utilizes a smart device and app equipped with a generative AI to provide disaster information, rescue procedures for injured people, guide safe evacuation routes, and support emergency calls. This allows the lifesaving AI assistant system to improve individuals' disaster response capabilities and contribute to saving lives.

[0029] A lifesaving AI assistant system according to an embodiment includes a disaster information providing unit, a rescue procedure providing unit, an evacuation route guidance unit, and an emergency call support unit. The disaster information providing unit provides disaster information. For example, the generation AI collects the latest information on disasters such as earthquakes, floods, and fires and provides it to the user. The generation AI analyzes the information based on prompts containing disaster information and provides appropriate information to the user. For example, when a prompt such as "Please tell me the latest information on disasters occurring in my current location" is input, the generation AI analyzes the information and provides it to the user. The rescue procedure providing unit provides rescue procedures for injured people. For example, the generation AI analyzes rescue procedures based on prompts containing information about the injured person's condition and provides them to the user. For example, when a prompt such as "Please tell me what to do if the injured person is bleeding" is input, the generation AI analyzes the information and provides appropriate rescue procedures to the user. The evacuation route guidance unit guides the user to a safe evacuation route based on the user's GPS information. For example, the generation AI determines the user's current location and guides the user to the safest evacuation route. The generation AI analyzes an evacuation route based on prompts containing information about the user's current location and provides it to the user. For example, when a user inputs a prompt such as "What is the safest evacuation route from my current location?", the generation AI analyzes the information and provides the user with an appropriate evacuation route. The emergency call support unit supports emergency calls. For example, the generation AI analyzes the reporting procedure based on a prompt containing emergency information and provides it to the user. For example, when a user inputs a prompt such as "What should I report to in case of an emergency?", the generation AI analyzes the information and provides the user with an appropriate reporting destination. As a result, the lifesaving AI assistant system according to the embodiment can assist individuals in taking appropriate actions during disasters and emergencies, thereby improving personal safety. For example, by providing disaster information, the user can grasp the latest information and take appropriate actions. By providing rescue procedures for injured people, the user can provide appropriate rescue to the injured. By providing guidance on safe evacuation routes, the user can evacuate via the safest route. By supporting emergency calls, the user can quickly and appropriately report an emergency.

[0030] The disaster information provision unit can analyze the user's past behavioral history and provide individually optimized disaster information. For example, the generation AI in the disaster information provision unit analyzes the user's past evacuation behavior and behavioral history during disasters and provides individually optimized disaster information. For example, the optimal evacuation destination is suggested based on information about past evacuation routes and evacuation shelters. The disaster information provision unit also customizes disaster information based on the user's past behavioral history. For example, the optimal evacuation method is suggested taking into account information about transportation methods and evacuation shelters used in the past. The disaster information provision unit also analyzes the user's past behavioral history and individually optimizes disaster information. For example, the optimal evacuation plan is suggested based on problems and success stories from past evacuations. This makes it possible to provide optimal disaster information based on the user's past behavioral history.

[0031] The evacuation route guidance unit can provide information that allows everyone to evacuate safely, taking into account the location information of the user's family or friends. For example, the generation AI of the evacuation route guidance unit analyzes the location information of the user's family and friends and provides information that allows everyone to evacuate safely. For example, it can suggest an evacuation location where the whole family can meet up. The evacuation route guidance unit also considers the location information of the user's family and friends and suggests the optimal evacuation route. For example, it can provide a route that allows everyone to evacuate safely. The evacuation route guidance unit also analyzes the location information of the user's family and friends and provides information that allows everyone to evacuate safely. For example, it can update evacuation locations and evacuation routes in real time. This makes it possible to provide information that allows everyone to evacuate safely, taking into account the location information of the user's family and friends.

[0032] The evacuation route guidance unit can also consider the safety of the user's pet and suggest evacuation methods for the pet. For example, the generation AI analyzes the location information and status of the user's pet and suggests evacuation methods for the pet. For example, it provides a location and method where the pet can evacuate safely. The evacuation route guidance unit also considers the safety of the user's pet and suggests the optimal evacuation method. For example, it suggests an evacuation location where the pet can be evacuated together. The evacuation route guidance unit also considers the safety of the user's pet and suggests an evacuation method for the pet. For example, it provides items and procedures necessary for the pet's evacuation. This makes it possible to suggest evacuation methods that take the safety of the user's pet into consideration.

[0033] The rescue procedure providing unit can analyze the user's level of medical knowledge and provide procedures in an easy-to-understand format. For example, the generation AI in the rescue procedure providing unit analyzes the user's level of medical knowledge and provides rescue procedures in an easy-to-understand format. For example, it provides simple procedures for beginners and explanations that avoid technical jargon. The rescue procedure providing unit also provides appropriate rescue procedures through the generation AI based on the user's level of medical knowledge. For example, it provides detailed procedures for users with extensive medical knowledge and simple procedures for beginners. The rescue procedure providing unit also analyzes the user's level of medical knowledge and provides procedures in an easy-to-understand format. For example, it provides procedures that are visually easy to understand using diagrams and videos. This makes it possible to provide easy-to-understand procedures according to the user's level of medical knowledge.

[0034] The rescue procedure providing unit can analyze surrounding environmental information and propose the optimal rescue method. In the rescue procedure providing unit, for example, the generating AI analyzes surrounding environmental information in real time and proposes the optimal rescue method. For example, it proposes rescue procedures that take into account surrounding obstacles and dangerous areas. In addition, the rescue procedure providing unit proposes the optimal rescue method based on the user's current location and surrounding environmental information. For example, it provides the tools and procedures necessary for rescue. In addition, the rescue procedure providing unit proposes the optimal rescue method based on the surrounding environmental information using the generating AI. For example, it proposes rescue procedures that take into account weather and terrain. This makes it possible to propose the optimal rescue method based on surrounding environmental information.

[0035] The rescue procedure providing unit can analyze the contents of the user's medical kit and propose procedures using available tools. In the rescue procedure providing unit, for example, the generation AI analyzes the contents of the user's medical kit and proposes rescue procedures using available tools. For example, specific procedures using bandages and disinfectant are provided. In addition, the rescue procedure providing unit proposes optimal rescue procedures based on the contents of the user's medical kit. For example, a procedure that makes maximum use of available tools is provided. In addition, the rescue procedure providing unit analyzes the contents of the user's medical kit and proposes procedures using available tools. For example, detailed instructions on how to use the tools included in the medical kit are provided. This makes it possible to propose optimal procedures based on the contents of the user's medical kit.

[0036] The rescue procedure providing unit can propose a method for coordinating with other nearby users to carry out rescue operations in cooperation. For example, the rescue procedure providing unit has the generating AI analyze the location information of other nearby users and propose a method for coordinating rescue operations. For example, it provides a procedure for coordinating with nearby users to transport injured people. The rescue procedure providing unit also proposes a method for the generating AI to cooperate in rescue operations based on information about the user and nearby users. For example, it specifically proposes a division of roles and a method of cooperation. The rescue procedure providing unit also proposes a method for the generating AI to cooperate with other nearby users to carry out rescue operations in cooperation. For example, it provides a procedure for contacting nearby users and coordinating rescue operations. This makes it possible to propose a method for coordinating with other nearby users to carry out rescue operations.

[0037] The emergency call support unit can analyze the user's past call history and suggest the optimal contact to call. In the emergency call support unit, for example, the generation AI analyzes the user's past call history and suggests the optimal contact to call. For example, it suggests the optimal contact to call based on emergency contacts that have been called in the past. In addition, the emergency call support unit can have the generation AI suggest the optimal contact to call based on the user's call history. For example, it can make suggestions taking into consideration the content of past calls and the contact to call. In addition, the emergency call support unit can have the generation AI analyze the user's past call history and suggest the optimal contact to call. For example, it can automatically select an emergency contact based on the past call history. This makes it possible to suggest the optimal contact to call based on the user's past call history.

[0038] The emergency call support unit can simultaneously notify the user's family or friends and encourage their cooperation. For example, the generation AI analyzes the contact information of the user's family and friends and notifies them at the same time as the emergency call. For example, it notifies family and friends that an emergency has occurred. The emergency call support unit also simultaneously notifies the user's family and friends based on their contact information and encourages their cooperation. For example, it provides details of the emergency to family and friends. The emergency call support unit also simultaneously notifies the user's family and friends and encourages their cooperation. For example, it notifies them of the occurrence of an emergency and requests their cooperation. This allows the generation AI to simultaneously notify the user's family and friends and encourage their cooperation.

[0039] The emergency call support unit can analyze the user's medical information and notify the appropriate medical institution. In the emergency call support unit, for example, the generation AI analyzes the user's medical information and notifies the appropriate medical institution. For example, it selects the most appropriate medical institution based on the user's medical history and allergy information. In addition, the emergency call support unit uses the generation AI to notify the appropriate medical institution based on the user's medical information. For example, it creates the content of the call taking into account the user's current symptoms and condition. In addition, the emergency call support unit uses the generation AI to analyze the user's medical information and notify the appropriate medical institution. For example, it creates the content of the call based on the user's emergency contact information and medical information. This allows it to notify the appropriate medical institution based on the user's medical information.

[0040] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0041] The lifesaving AI assistant system can also be equipped with a health management unit that monitors the user's health condition and provides appropriate advice. For example, the generative AI can monitor the user's heart rate and blood pressure in real time and suggest appropriate measures if abnormalities are detected. The health management unit can also analyze the user's past health data and provide preventive advice. For example, it can suggest regular exercise and dietary improvements. Furthermore, the health management unit can provide a customized health plan based on the user's health condition. This allows users to receive support for maintaining their health not only during disasters but also in their daily lives.

[0042] The lifesaving AI assistant system can also be equipped with a multilingual support unit that provides information in multiple languages ​​according to the user's language settings. For example, the generation AI can analyze the user's language settings and provide disaster information and rescue procedures in the user's native language. The multilingual support unit can also perform real-time translation when the user communicates with family and friends who speak different languages. For example, it supports smooth communication between people who speak different languages ​​when providing evacuation route guidance or making emergency calls. Furthermore, the multilingual support unit can provide learning content to the generation AI to improve the user's language skills. This allows users to receive appropriate information without experiencing language barriers, even during disasters.

[0043] The lifesaving AI assistant system can also be equipped with a communication support unit that supports communication with the user's family and friends. For example, the generating AI can analyze the contact information of the user's family and friends and suggest ways to quickly contact them in the event of a disaster. The communication support unit can also provide a function that allows the user to share location information with family and friends in real time. For example, when providing evacuation route guidance, the unit can coordinate so that all family members head to the same evacuation site. Furthermore, the communication support unit can provide advice to the generating AI to facilitate communication with the user's family and friends. This makes it easier for the user to cooperate with family and friends even in the event of a disaster.

[0044] The life-saving AI assistant system can also include a pet care module that monitors the user's pet's health and provides appropriate advice. For example, the generative AI can monitor the user's pet's heart rate and body temperature in real time and suggest appropriate measures if an abnormality is detected. The pet care module can also analyze the user's pet's past health data and provide preventative advice. For example, it can suggest regular exercise and improved diet. Furthermore, the pet care module can provide customized care plans based on the user's pet's health condition. This allows users to receive support for maintaining their pet's health not only during disasters but also in everyday life.

[0045] The lifesaving AI assistant system can also be equipped with an education support unit that analyzes the user's level of medical knowledge and provides procedures in an easy-to-understand format. For example, the generation AI can analyze the user's level of medical knowledge and provide simple procedures for beginners and explanations that avoid technical jargon. The education support unit can also provide visually easy-to-understand procedures using diagrams and videos, depending on the user's level of medical knowledge. For example, showing rescue procedures in videos makes it easier for the user to actually perform the procedures. Furthermore, the education support unit can also use the generation AI to analyze the user's level of medical knowledge and provide procedures in an easy-to-understand format. This allows the user to receive appropriate rescue procedures according to their level of medical knowledge.

[0046] The lifesaving AI assistant system can also be equipped with an environmental analysis unit that analyzes surrounding environmental information and proposes the optimal rescue method. For example, the generating AI can analyze surrounding obstacles and dangerous areas in real time and propose the optimal rescue procedure. The environmental analysis unit can also provide the tools and procedures necessary for rescue based on the user's current location and surrounding environmental information. For example, it can propose rescue procedures that take weather and terrain into consideration. Furthermore, the environmental analysis unit can also enable the generating AI to analyze surrounding environmental information and propose the optimal rescue method. This allows the user to receive the optimal rescue method based on the surrounding environmental information.

[0047] The processing flow of the first embodiment will be briefly explained below.

[0048] Step 1: The disaster information provider provides disaster information. For example, the generation AI collects the latest information on disasters such as earthquakes, floods, and fires and provides it to the user. The generation AI analyzes the information based on prompts containing information about the disaster and provides appropriate information to the user. For example, if the user inputs the prompt, "Please tell me the latest information on disasters occurring in my current location," the generation AI analyzes the information and provides it to the user. Step 2: The rescue procedure provider provides rescue procedures for the injured person. For example, the generation AI analyzes rescue procedures based on prompts containing information about the injured person's condition and provides them to the user. For example, if the prompt is input, "Please tell me what to do if the injured person is bleeding," the generation AI analyzes the information and provides the user with appropriate rescue procedures. Step 3: The evacuation route guidance unit guides the user to a safe evacuation route based on the user's GPS information. For example, the generation AI determines the user's current location and guides them to the safest evacuation route. The generation AI analyzes an evacuation route based on a prompt containing information about the user's current location and provides it to the user. For example, if the user inputs the prompt, "Please tell me the safest evacuation route from my current location," the generation AI analyzes that information and provides the user with an appropriate evacuation route. Step 4: The emergency call support unit supports emergency calls. For example, the generation AI analyzes the call procedure based on a prompt containing information about the emergency situation and provides it to the user. For example, if the user inputs the prompt "Please tell me who to call in the event of an emergency," the generation AI analyzes the information and provides the user with the appropriate contact information.

[0049] (Example 2) The lifesaving AI assistant system according to an embodiment of the present invention supports individuals in taking appropriate actions during disasters and emergencies. This system utilizes a smart device and app equipped with a generative AI to provide disaster information, rescue procedures for injured people, guide safe evacuation routes, and support emergency calls. This allows the lifesaving AI assistant system to improve individuals' disaster response capabilities and contribute to saving lives.

[0050] A lifesaving AI assistant system according to an embodiment includes a disaster information providing unit, a rescue procedure providing unit, an evacuation route guidance unit, and an emergency call support unit. The disaster information providing unit provides disaster information. For example, the generation AI collects the latest information on disasters such as earthquakes, floods, and fires and provides it to the user. The generation AI analyzes the information based on prompts containing disaster information and provides appropriate information to the user. For example, when a prompt such as "Please tell me the latest information on disasters occurring in my current location" is input, the generation AI analyzes the information and provides it to the user. The rescue procedure providing unit provides rescue procedures for injured people. For example, the generation AI analyzes rescue procedures based on prompts containing information about the injured person's condition and provides them to the user. For example, when a prompt such as "Please tell me what to do if the injured person is bleeding" is input, the generation AI analyzes the information and provides appropriate rescue procedures to the user. The evacuation route guidance unit guides the user to a safe evacuation route based on the user's GPS information. For example, the generation AI determines the user's current location and guides the user to the safest evacuation route. The generation AI analyzes an evacuation route based on prompts containing information about the user's current location and provides it to the user. For example, when a user inputs a prompt such as "What is the safest evacuation route from my current location?", the generation AI analyzes the information and provides the user with an appropriate evacuation route. The emergency call support unit supports emergency calls. For example, the generation AI analyzes the reporting procedure based on a prompt containing emergency information and provides it to the user. For example, when a user inputs a prompt such as "What should I report to in case of an emergency?", the generation AI analyzes the information and provides the user with an appropriate reporting destination. As a result, the lifesaving AI assistant system according to the embodiment can assist individuals in taking appropriate actions during disasters and emergencies, thereby improving personal safety. For example, by providing disaster information, the user can grasp the latest information and take appropriate actions. By providing rescue procedures for injured people, the user can provide appropriate rescue to the injured. By providing guidance on safe evacuation routes, the user can evacuate via the safest route. By supporting emergency calls, the user can quickly and appropriately report an emergency.

[0051] The disaster information provision unit can analyze the user's past behavioral history and provide individually optimized disaster information. For example, the generation AI in the disaster information provision unit analyzes the user's past evacuation behavior and behavioral history during disasters and provides individually optimized disaster information. For example, the optimal evacuation destination is suggested based on information about past evacuation routes and evacuation shelters. The disaster information provision unit also customizes disaster information based on the user's past behavioral history. For example, the optimal evacuation method is suggested taking into account information about transportation methods and evacuation shelters used in the past. The disaster information provision unit also analyzes the user's past behavioral history and individually optimizes disaster information. For example, the optimal evacuation plan is suggested based on problems and success stories from past evacuations. This makes it possible to provide optimal disaster information based on the user's past behavioral history.

[0052] The disaster information provision unit can estimate the user's psychological state and simultaneously provide advice to reduce stress. For example, the generation AI in the disaster information provision unit analyzes the user's psychological state in real time and provides advice to reduce stress. For example, it suggests deep breathing or relaxation methods. The disaster information provision unit can also estimate the user's psychological state and the generation AI can provide advice to reduce stress. For example, it can provide music or videos for relaxation along with disaster information. The disaster information provision unit can also analyze the user's psychological state and provide specific advice to reduce stress. For example, it can suggest mental health care methods along with disaster information. This allows the generation AI to provide advice according to the user's psychological state and reduce stress.

[0053] The disaster information provision unit can use the emotion estimation function to analyze the emotional response of a user when receiving disaster information and provide information that elicits positive emotions. The disaster information provision unit, for example, uses the emotion estimation function to analyze the emotional response of a user when receiving disaster information in real time and provide information that elicits positive emotions. For example, it sends a message that gives a sense of security. The disaster information provision unit also analyzes the user's emotional response and provides information that the generation AI uses to elicit positive emotions. For example, it sends an encouraging message along with the disaster information. The disaster information provision unit also uses the emotion estimation function to analyze the user's emotional response and provide information that elicits positive emotions. For example, it provides success stories and positive news along with the disaster information. This makes it possible to provide information that elicits positive emotions based on the user's emotional response.

[0054] The evacuation route guidance unit can provide information that allows everyone to evacuate safely, taking into account the location information of the user's family or friends. For example, the generation AI of the evacuation route guidance unit analyzes the location information of the user's family and friends and provides information that allows everyone to evacuate safely. For example, it can suggest an evacuation location where the whole family can meet up. The evacuation route guidance unit also considers the location information of the user's family and friends and suggests the optimal evacuation route. For example, it can provide a route that allows everyone to evacuate safely. The evacuation route guidance unit also analyzes the location information of the user's family and friends and provides information that allows everyone to evacuate safely. For example, it can update evacuation locations and evacuation routes in real time. This makes it possible to provide information that allows everyone to evacuate safely, taking into account the location information of the user's family and friends.

[0055] The evacuation route guidance unit can also consider the safety of the user's pet and suggest evacuation methods for the pet. For example, the generation AI analyzes the location information and status of the user's pet and suggests evacuation methods for the pet. For example, it provides a location and method where the pet can evacuate safely. The evacuation route guidance unit also considers the safety of the user's pet and suggests the optimal evacuation method. For example, it suggests an evacuation location where the pet can be evacuated together. The evacuation route guidance unit also considers the safety of the user's pet and suggests an evacuation method for the pet. For example, it provides items and procedures necessary for the pet's evacuation. This makes it possible to suggest evacuation methods that take the safety of the user's pet into consideration.

[0056] The evacuation route guidance unit uses the emotion estimation function to monitor the user's emotions in real time when they are guided along the evacuation route, and can send encouraging messages as needed. The evacuation route guidance unit, for example, uses the emotion estimation function to monitor the user's emotions in real time when they receive disaster information, and can send encouraging messages as needed. For example, it sends a message that gives the user a sense of security when the user feels anxious. The evacuation route guidance unit also monitors the user's emotions in real time, and the generation AI sends encouraging messages. For example, it sends a positive message along with the disaster information. The evacuation route guidance unit also uses the emotion estimation function to monitor the user's emotions, and can send encouraging messages as needed. For example, it sends advice to help the user relax when they feel stressed. This makes it possible to monitor the user's emotions in real time, and can send encouraging messages as needed.

[0057] The rescue procedure providing unit can analyze the user's level of medical knowledge and provide procedures in an easy-to-understand format. For example, the generation AI in the rescue procedure providing unit analyzes the user's level of medical knowledge and provides rescue procedures in an easy-to-understand format. For example, it provides simple procedures for beginners and explanations that avoid technical jargon. The rescue procedure providing unit also provides appropriate rescue procedures through the generation AI based on the user's level of medical knowledge. For example, it provides detailed procedures for users with extensive medical knowledge and simple procedures for beginners. The rescue procedure providing unit also analyzes the user's level of medical knowledge and provides procedures in an easy-to-understand format. For example, it provides procedures that are visually easy to understand using diagrams and videos. This makes it possible to provide easy-to-understand procedures according to the user's level of medical knowledge.

[0058] The rescue procedure providing unit can analyze surrounding environmental information and propose the optimal rescue method. In the rescue procedure providing unit, for example, the generating AI analyzes surrounding environmental information in real time and proposes the optimal rescue method. For example, it proposes rescue procedures that take into account surrounding obstacles and dangerous areas. In addition, the rescue procedure providing unit proposes the optimal rescue method based on the user's current location and surrounding environmental information. For example, it provides the tools and procedures necessary for rescue. In addition, the rescue procedure providing unit proposes the optimal rescue method based on the surrounding environmental information using the generating AI. For example, it proposes rescue procedures that take into account weather and terrain. This makes it possible to propose the optimal rescue method based on surrounding environmental information.

[0059] The rescue procedure providing unit can analyze the contents of the user's medical kit and propose procedures using available tools. In the rescue procedure providing unit, for example, the generation AI analyzes the contents of the user's medical kit and proposes rescue procedures using available tools. For example, specific procedures using bandages and disinfectant are provided. In addition, the rescue procedure providing unit proposes optimal rescue procedures based on the contents of the user's medical kit. For example, a procedure that makes maximum use of available tools is provided. In addition, the rescue procedure providing unit analyzes the contents of the user's medical kit and proposes procedures using available tools. For example, detailed instructions on how to use the tools included in the medical kit are provided. This makes it possible to propose optimal procedures based on the contents of the user's medical kit.

[0060] The rescue procedure providing unit can propose a method for coordinating with other nearby users to carry out rescue operations in cooperation. For example, the rescue procedure providing unit has the generating AI analyze the location information of other nearby users and propose a method for coordinating rescue operations. For example, it provides a procedure for coordinating with nearby users to transport injured people. The rescue procedure providing unit also proposes a method for the generating AI to cooperate in rescue operations based on information about the user and nearby users. For example, it specifically proposes a division of roles and a method of cooperation. The rescue procedure providing unit also proposes a method for the generating AI to cooperate with other nearby users to carry out rescue operations in cooperation. For example, it provides a procedure for contacting nearby users and coordinating rescue operations. This makes it possible to propose a method for coordinating with other nearby users to carry out rescue operations.

[0061] The rescue procedure providing unit can use the emotion estimation function to monitor the user's emotions in real time when performing rescue procedures for an injured person, and send encouraging messages as needed. The rescue procedure providing unit can, for example, use the emotion estimation function to monitor the user's emotions in real time when performing rescue procedures for an injured person, and send encouraging messages as needed. For example, sending a message that gives the user a sense of security when the user feels anxious. The rescue procedure providing unit also monitors the user's emotions in real time, and the generation AI sends encouraging messages. For example, sending a positive message along with the rescue procedures. The rescue procedure providing unit also uses the emotion estimation function to monitor the user's emotions and send encouraging messages as needed. For example, sending advice to relax when the user feels stressed. In this way, the user's emotions can be monitored in real time, and encouraging messages can be sent as needed.

[0062] The emergency call support unit can analyze the user's past call history and suggest the optimal contact to call. In the emergency call support unit, for example, the generation AI analyzes the user's past call history and suggests the optimal contact to call. For example, it suggests the optimal contact to call based on emergency contacts that have been called in the past. In addition, the emergency call support unit can have the generation AI suggest the optimal contact to call based on the user's call history. For example, it can make suggestions taking into consideration the content of past calls and the contact to call. In addition, the emergency call support unit can have the generation AI analyze the user's past call history and suggest the optimal contact to call. For example, it can automatically select an emergency contact based on the past call history. This makes it possible to suggest the optimal contact to call based on the user's past call history.

[0063] The emergency call support unit can use the emotion estimation function to analyze the emotions of a user when making an emergency call and provide advice to help keep calm. For example, the emergency call support unit can use the emotion estimation function to analyze the emotions of a user when making an emergency call in real time and provide advice to help keep calm. For example, it can suggest deep breathing or relaxation techniques. The emergency call support unit can also analyze the user's emotions and provide advice to help keep calm using a generation AI. For example, it can provide mental health care methods along with the emergency call. The emergency call support unit can also use the emotion estimation function to analyze the user's emotions and provide specific advice to help keep calm. For example, it can provide relaxing music or videos along with the emergency call. This allows the user's emotions to be analyzed and advice to help keep calm to be provided.

[0064] The emergency call support unit can simultaneously notify the user's family or friends and encourage their cooperation. For example, the generation AI analyzes the contact information of the user's family and friends and notifies them at the same time as the emergency call. For example, it notifies family and friends that an emergency has occurred. The emergency call support unit also simultaneously notifies the user's family and friends based on their contact information and encourages their cooperation. For example, it provides details of the emergency to family and friends. The emergency call support unit also simultaneously notifies the user's family and friends and encourages their cooperation. For example, it notifies them of the occurrence of an emergency and requests their cooperation. This allows the generation AI to simultaneously notify the user's family and friends and encourage their cooperation.

[0065] The emergency call support unit can analyze the user's medical information and notify the appropriate medical institution. In the emergency call support unit, for example, the generation AI analyzes the user's medical information and notifies the appropriate medical institution. For example, it selects the most appropriate medical institution based on the user's medical history and allergy information. In addition, the emergency call support unit uses the generation AI to notify the appropriate medical institution based on the user's medical information. For example, it creates the content of the call taking into account the user's current symptoms and condition. In addition, the emergency call support unit uses the generation AI to analyze the user's medical information and notify the appropriate medical institution. For example, it creates the content of the call based on the user's emergency contact information and medical information. This allows it to notify the appropriate medical institution based on the user's medical information.

[0066] The emergency call support unit uses the emotion estimation function to monitor the user's emotions in real time when making an emergency call, and can send an encouraging message as needed. The emergency call support unit, for example, uses the emotion estimation function to monitor the user's emotions in real time when making an emergency call, and can send an encouraging message as needed. For example, a message that gives the user a sense of security is sent when the user feels anxious. The emergency call support unit also monitors the user's emotions in real time, and the generation AI sends an encouraging message. For example, a positive message is sent along with the emergency call. The emergency call support unit also uses the emotion estimation function to monitor the user's emotions, and can send an encouraging message as needed. For example, advice on how to relax is sent when the user feels stressed. This makes it possible to monitor the user's emotions in real time, and can send an encouraging message as needed.

[0067] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0068] The lifesaving AI assistant system can also be equipped with a health management unit that monitors the user's health condition and provides appropriate advice. For example, the generative AI can monitor the user's heart rate and blood pressure in real time and suggest appropriate measures if abnormalities are detected. The health management unit can also analyze the user's past health data and provide preventive advice. For example, it can suggest regular exercise and dietary improvements. Furthermore, the health management unit can provide a customized health plan based on the user's health condition. This allows users to receive support for maintaining their health not only during disasters but also in their daily lives.

[0069] The lifesaving AI assistant system can also be equipped with a multilingual support unit that provides information in multiple languages ​​according to the user's language settings. For example, the generation AI can analyze the user's language settings and provide disaster information and rescue procedures in the user's native language. The multilingual support unit can also perform real-time translation when the user communicates with family and friends who speak different languages. For example, it supports smooth communication between people who speak different languages ​​when providing evacuation route guidance or making emergency calls. Furthermore, the multilingual support unit can provide learning content to the generation AI to improve the user's language skills. This allows users to receive appropriate information without experiencing language barriers, even during disasters.

[0070] The lifesaving AI assistant system can also include a relaxation module that estimates the user's psychological state and suggests relaxation exercises. For example, the generation AI can analyze the user's psychological state in real time and suggest yoga or meditation methods to reduce stress. The relaxation module can also provide music or videos to help users relax, depending on the user's psychological state. For example, it can play natural sounds or videos with a relaxing effect. Furthermore, the relaxation module can analyze the user's psychological state and provide specific advice to reduce stress. This allows users to maintain psychological stability even during disasters and emergencies.

[0071] The lifesaving AI assistant system can also be equipped with an emotion response unit that estimates the user's emotions and provides customized messages based on those emotions. For example, the generation AI analyzes the user's emotions in real time and sends a reassuring message if the user is feeling anxious. The emotion response unit can also provide encouraging or comforting messages based on the user's emotions. For example, if the user is feeling stressed, it can send advice on how to relax. Furthermore, the emotion response unit can analyze the user's emotions and provide specific advice to elicit positive emotions. This allows users to receive emotional support even during disasters and emergencies.

[0072] The lifesaving AI assistant system can also be equipped with a communication support unit that supports communication with the user's family and friends. For example, the generating AI can analyze the contact information of the user's family and friends and suggest ways to quickly contact them in the event of a disaster. The communication support unit can also provide a function that allows the user to share location information with family and friends in real time. For example, when providing evacuation route guidance, the unit can coordinate so that all family members head to the same evacuation site. Furthermore, the communication support unit can provide advice to the generating AI to facilitate communication with the user's family and friends. This makes it easier for the user to cooperate with family and friends even in the event of a disaster.

[0073] The life-saving AI assistant system can also include a pet care module that monitors the user's pet's health and provides appropriate advice. For example, the generative AI can monitor the user's pet's heart rate and body temperature in real time and suggest appropriate measures if an abnormality is detected. The pet care module can also analyze the user's pet's past health data and provide preventative advice. For example, it can suggest regular exercise and improved diet. Furthermore, the pet care module can provide customized care plans based on the user's pet's health condition. This allows users to receive support for maintaining their pet's health not only during disasters but also in everyday life.

[0074] The lifesaving AI assistant system can also estimate the user's emotions and provide advice to reduce the anxiety and stress the user feels when receiving evacuation route guidance. For example, the generative AI can analyze the user's emotions in real time and suggest ways to relax while receiving evacuation route guidance. The emotion estimation function can also be used to monitor the user's emotions while receiving evacuation route guidance and send encouraging messages as needed. For example, a reassuring message can be sent if the user feels anxious. Furthermore, the emotion estimation function can be used to monitor the user's emotions and provide specific advice to elicit positive emotions while receiving evacuation route guidance. This allows the user to receive emotional support while receiving evacuation route guidance.

[0075] The lifesaving AI assistant system can also be equipped with an education support unit that analyzes the user's level of medical knowledge and provides procedures in an easy-to-understand format. For example, the generation AI can analyze the user's level of medical knowledge and provide simple procedures for beginners and explanations that avoid technical jargon. The education support unit can also provide visually easy-to-understand procedures using diagrams and videos, depending on the user's level of medical knowledge. For example, showing rescue procedures in videos makes it easier for the user to actually perform the procedures. Furthermore, the education support unit can also use the generation AI to analyze the user's level of medical knowledge and provide procedures in an easy-to-understand format. This allows the user to receive appropriate rescue procedures according to their level of medical knowledge.

[0076] The lifesaving AI assistant system can also be equipped with an environmental analysis unit that analyzes surrounding environmental information and proposes the optimal rescue method. For example, the generating AI can analyze surrounding obstacles and dangerous areas in real time and propose the optimal rescue procedure. The environmental analysis unit can also provide the tools and procedures necessary for rescue based on the user's current location and surrounding environmental information. For example, it can propose rescue procedures that take weather and terrain into consideration. Furthermore, the environmental analysis unit can also enable the generating AI to analyze surrounding environmental information and propose the optimal rescue method. This allows the user to receive the optimal rescue method based on the surrounding environmental information.

[0077] The lifesaving AI assistant system can also estimate the user's emotions, monitor their emotions in real time as they perform rescue procedures for injured people, and send encouraging messages as needed. For example, the generative AI analyzes the user's emotions in real time and sends a reassuring message if the user feels anxious. The emotion estimation function can also be used to monitor the user's emotions and send positive messages along with rescue procedures. For example, it can send advice on how to relax if the user feels stressed. The emotion estimation function can also be used to monitor the user's emotions and provide specific advice to elicit positive emotions when performing rescue procedures for injured people. This allows the user to receive emotional support when performing rescue procedures for injured people.

[0078] The processing flow of the second embodiment will be briefly explained below.

[0079] Step 1: The disaster information provider provides disaster information. For example, the generation AI collects the latest information on disasters such as earthquakes, floods, and fires and provides it to the user. The generation AI analyzes the information based on prompts containing information about the disaster and provides appropriate information to the user. For example, if the user inputs the prompt, "Please tell me the latest information on disasters occurring in my current location," the generation AI analyzes the information and provides it to the user. Step 2: The rescue procedure provider provides rescue procedures for the injured person. For example, the generation AI analyzes rescue procedures based on prompts containing information about the injured person's condition and provides them to the user. For example, if the prompt is input, "Please tell me what to do if the injured person is bleeding," the generation AI analyzes the information and provides the user with appropriate rescue procedures. Step 3: The evacuation route guidance unit guides the user to a safe evacuation route based on the user's GPS information. For example, the generation AI determines the user's current location and guides them to the safest evacuation route. The generation AI analyzes an evacuation route based on a prompt containing information about the user's current location and provides it to the user. For example, if the user inputs the prompt, "Please tell me the safest evacuation route from my current location," the generation AI analyzes that information and provides the user with an appropriate evacuation route. Step 4: The emergency call support unit supports emergency calls. For example, the generation AI analyzes the call procedure based on a prompt containing information about the emergency situation and provides it to the user. For example, if the user inputs the prompt "Please tell me who to call in the event of an emergency," the generation AI analyzes the information and provides the user with the appropriate contact information.

[0080] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0081] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> Examples of generative AIs include the data generation model 58, such as a neural network model (e.g., a neural network model), and a neural network model (e.g., a neural network model). The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating speech, text data indicating text, and image data indicating an image is also input to the data generation model 58. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specification processing unit 290 performs the above-mentioned specification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0082] Furthermore, the processing by the data processing system 10 described above is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart device 14, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart device 14. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the smart device 14 or an external device, and the smart device 14 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0083] [Second embodiment] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0084] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0085] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0086] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0087] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0088] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0089] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0090] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0091] The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0092] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0093] In the smart glasses 214, the specific processing is performed by the processor 46. A specific processing program 60 is stored in the storage 50. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. Note that the smart glasses 214 may have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59.

[0094] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0095] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0096] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0097] The data processing system 210 according to the second embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 210 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart glasses 214, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart glasses 214. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the smart glasses 214 or an external device, etc., and the smart glasses 214 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0098] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0099] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0100] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0101] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0102] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0103] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0104] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0105] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0106] The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0107] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0108] In the headset type terminal 314, the identification process is performed by the processor 46. A identification program 60 is stored in the storage 50. The processor 46 reads the identification program 60 from the storage 50 and executes the read identification program 60 on the RAM 48. The identification process is realized by the processor 46 operating as a control unit 46A in accordance with the identification program 60 executed on the RAM 48. Note that the headset type terminal 314 may also have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59.

[0109] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0110] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0111] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0112] The data processing system 310 according to the third embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 310 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the headset type terminal 314, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the headset type terminal 314. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the headset type terminal 314 or an external device, etc., and the headset type terminal 314 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0113] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0114] 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.

[0115] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0116] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[0117] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0118] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS image sensor or a CCD image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0119] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0120] The control object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[0121] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0122] The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0123] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0124] In the robot 414, the processor 46 performs the identification process. A identification program 60 is stored in the storage 50. The processor 46 reads the identification program 60 from the storage 50 and executes the read identification program 60 on the RAM 48. The identification process is realized by the processor 46 operating as a control unit 46A in accordance with the identification program 60 executed on the RAM 48. The robot 414 may have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59.

[0125] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0126] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[0127] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0128] The data processing system 410 according to the fourth embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 410 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the robot 414, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the robot 414. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the robot 414 or an external device, etc., and the robot 414 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0129] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0130] FIG. 9 illustrates an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and behaviors arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion encompasses both emotions and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[0131] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[0132] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[0133] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is expressed, and when they approach the ideal, a state of pleasure is expressed. Emotions can also be created for robots, cars, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is expressed, and when they approach the ideal, a state of pleasure is expressed. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on speech emotion recognition and brain physiological signal analysis systems for emotions, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the area called "reaction," where sensation is dominant. The right half of the emotion map lists emotions belonging to the area called "situation," where situational awareness is dominant.

[0134] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[0135] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[0136] In the above embodiment, an example was given in which a specific process is performed by one computer 22, but the technology disclosed herein is not limited to this, and distributed processing of the specific process may be performed by multiple computers including computer 22.

[0137] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[0138] 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.

[0139] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[0140] The hardware resource for executing a specific process can be any of the following types of processors: A processor, for example, is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. A processor also includes a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[0141] The hardware resource that executes the specific process may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific process may be a single processor.

[0142] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[0143] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[0144] In the above example, the first to fourth embodiments have been described separately, but some or all of these embodiments may be combined. The smart device 14, smart glasses 214, headset terminal 314, and robot 414 are merely examples, and they may be combined, or other devices may be used. In the above example, the first and second embodiments have been described separately, but they may be combined.

[0145] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[0146] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference. [Explanation of symbols]

[0147] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot

Claims

1. A smart device equipped with generative AI, With the app, Smart devices are a disaster information providing unit that provides disaster information; a rescue procedure providing unit that provides rescue procedures for injured persons; an evacuation route guidance unit that guides users to a safe evacuation route based on their GPS information; an emergency call support unit that supports emergency calls; A system characterized by:

2. The disaster information providing unit Analyzing the user's past behavior history and providing individually optimized disaster information 2. The system of claim 1.

3. The evacuation route guidance unit The system also takes into consideration the location information of the user's family or friends and provides information to help everyone evacuate safely.

2. The system of claim 1.

4. The rescue procedure providing unit Analyzing the user's level of medical knowledge and providing procedures in an easy-to-understand format 2. The system of claim 1.

5. The emergency call support unit Analyze the user's past reporting history and suggest the most appropriate reporting destination 2. The system of claim 1.

6. The disaster information providing unit The emotional response of the user when receiving the disaster information is analyzed, and information is provided that elicits positive emotions.

2. The system of claim 1.

7. The evacuation route guidance unit The emotions of the user are monitored in real time when the user is guided along the evacuation route, and an encouraging message is sent as needed.

2. The system of claim 1.

8. The rescue procedure providing unit Analyze the emotions of the user when receiving the rescue procedure for the injured person and provide advice to help them stay calm 2. The system of claim 1.

Images