System

Abstract

An object of a system according to an embodiment is to prevent an elderly person from being isolated and to make it easy to respond to an emergency and acquire regional information.SOLUTION: A system includes a voice recognition unit, an information providing unit, a physical condition management unit, and an emergency notification unit. The voice recognition unit recognizes a voice of a user using a voice recognition technique. The information providing unit provides useful local information on the basis of the voice recognized by the voice recognition unit. The physical condition management unit performs physical condition management on the basis of the voice recognized by the voice recognition unit. The emergency report unit reports in an emergency on the basis of the voice recognized by the voice recognition unit.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] Conventional technology has had the problem that elderly people are prone to isolation and have difficulty responding to emergencies and obtaining local information.

[0005] The system according to the embodiment aims to prevent elderly people from becoming isolated and to facilitate emergency response and acquisition of local information. [Means for solving the problem]

[0006] The system according to the embodiment includes a voice recognition unit, an information provision unit, a health management unit, and an emergency notification unit. The voice recognition unit recognizes the user's voice using voice recognition technology. The information provision unit provides useful local information based on the voice recognized by the voice recognition unit. The health management unit manages the user's health based on the voice recognized by the voice recognition unit. The emergency notification unit notifies the user in an emergency based on the voice recognized by the voice recognition unit. [Effects of the Invention]

[0007] The system according to the embodiment prevents elderly people from becoming isolated and makes it easier to respond to emergencies and obtain local information. [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 voice recognition IoT device according to an embodiment of the present invention is a system that allows elderly people to live their daily lives with peace of mind. This system uses voice recognition technology to provide useful information about the area where they live, support for health management and daily life, and emergency notification functions. As a result, the voice recognition IoT device helps elderly people to alleviate feelings of isolation and social loneliness, prevent frailty, and quickly notify emergency situations. It also promotes communication with family members who live far away, reducing the digital divide.

[0029] A voice recognition IoT device according to an embodiment includes a voice recognition unit, an information providing unit, a health management unit, and an emergency notification unit. The voice recognition unit recognizes a user's voice using voice recognition technology. For example, when a user asks, "What's the weather like today?", the voice recognition unit can analyze the voice and respond with, "It's sunny today." The voice recognition unit can also analyze the tone and speed of the user's voice and respond according to the user's emotional state. For example, if a user says, "I'm tired today," the voice recognition unit analyzes the tone and speed of the voice and responds with, "I'll play some relaxing music." The information providing unit provides useful local information based on the voice recognized by the voice recognition unit. For example, the information providing unit can provide voice notification of local event information, garbage collection schedules, information about nearby medical facilities, and the like. The information providing unit can also predict and suggest the next song to play based on the user's past music selection history. For example, when a user says, "Play some music," the information providing unit analyzes the user's past music selection history and responds with, "I'll play some jazz that I've been listening to a lot lately." The health management unit manages the user's health based on the voice recognition unit. For example, the health management unit can collect the user's health data, predict their health status using AI, and provide appropriate advice. If the user says, "I'm not feeling well," the health management unit can predict their health status based on past health data and respond, "I recommend you take a rest today." The health management unit can also record the user's meals and calculate calories via voice, supporting a healthy diet. For example, if the user says, "Record today's meals," the health management unit records the meal contents via voice and responds, "The calories are 300 kcal." The emergency notification unit can notify an emergency based on the voice recognition unit. For example, if the user yells "help," the emergency notification unit can automatically obtain location information and send it to emergency contacts. The emergency notification unit can also save emergency call history, analyze patterns of past emergencies, and suggest preventive measures. For example, if the user yells, "help," the emergency notification unit saves the call history and responds, "Based on your past history, you are at high risk of falling."As a result, the voice recognition IoT device according to the embodiment allows elderly people to live their daily lives with peace of mind. For example, by being able to easily obtain local information, connections with the local community are strengthened. In addition, health management and emergency notification functions help protect the health and safety of elderly people. Furthermore, by promoting communication with family members, feelings of isolation are reduced.

[0030] The information providing unit can predict and suggest the next song to be played based on the user's past music selection history. For example, when the user says, "Play some music," the information providing unit analyzes the user's past music selection history and suggests songs in the user's favorite genre. For example, the information providing unit may respond, "I'll play the jazz you've been listening to a lot lately." When the user says, "I want to listen to a new song," the information providing unit may suggest a new song based on the user's past music selection history. For example, the information providing unit may respond, "Try listening to this new song." When the user says, "Play some relaxing music," the information providing unit may suggest a relaxing song based on the user's past music selection history. For example, the information providing unit may respond, "I'll play this relaxing song." This makes it possible to suggest music that suits the user's preferences.

[0031] The health management unit collects the user's health data, uses AI to predict their health condition, and provides appropriate advice. For example, if the user says, "I'm not feeling well," the health management unit predicts their health condition based on past health data and provides appropriate advice. For example, it may respond, "I recommend you take a rest today." If the user says, "Give me some exercise advice," the health management unit provides exercise advice based on past health data. For example, it may respond, "It would be good to do some light stretching today." If the user says, "Give me some dietary advice," the health management unit provides dietary advice based on past health data. For example, it may respond, "It would be good to eat more vegetables today." This allows the user's health to be managed efficiently.

[0032] The emergency notification unit can automatically acquire location information in an emergency and send it to an emergency contact. For example, when a user yells "help," the emergency notification unit automatically acquires location information and sends it to an emergency contact. For example, the emergency notification unit responds with "Location information has been sent to an emergency contact." Furthermore, when a user says "I have fallen," the emergency notification unit automatically acquires location information and sends it to an emergency contact. For example, the emergency notification unit responds with "Location information has been sent to an emergency contact." Furthermore, when a user says "I am feeling unwell," the emergency notification unit automatically acquires location information and sends it to an emergency contact. For example, the emergency notification unit responds with "Location information has been sent to an emergency contact." This enables a rapid response in an emergency.

[0033] The information providing unit can suggest an optimal medical institution based on the user's health condition and past medical history. For example, when the user says, "Tell me about a nearby hospital," the information providing unit suggests an optimal hospital taking into consideration the user's health condition and past medical history. For example, the information providing unit may respond with, "This is the best hospital for you." Furthermore, when the user says, "I'm looking for a specialist," the information providing unit suggests an optimal specialist taking into consideration the user's health condition and past medical history. For example, the information providing unit may respond with, "This specialist is suitable." Furthermore, when the user says, "Tell me about a medical department," the information providing unit suggests an optimal medical department taking into consideration the user's health condition and past medical history. For example, the information providing unit may respond with, "This medical department is suitable." This makes it possible to suggest an optimal medical institution for the user.

[0034] The health management unit can support a healthy diet by recording the user's meals or calculating calories through voice. For example, when the user says, "Record what I eat today," the health management unit records the meal details through voice and calculates the calories. For example, when the user says, "I had bread and eggs for breakfast," the health management unit responds, "That's 300 kilocalories." When the user says, "Calculate the calories," the health management unit records the meal details through voice and calculates the calories. For example, when the user says, "I had salad and chicken for lunch," the health management unit responds, "That's 400 kilocalories." When the user says, "Give me some dietary advice," the health management unit records the meal details through voice, calculates the calories, and provides appropriate advice. For example, the health management unit responds, "It would be good to eat fish for dinner." This makes it possible to support the user's healthy diet.

[0035] The emergency notification unit stores emergency notification history, analyzes patterns of past emergency situations, and can propose preventive measures. For example, when a user yells "help," the emergency notification unit stores the notification history and analyzes patterns of past emergency situations. For example, the emergency notification unit responds with, "Based on past history, there is a high risk of falling." When a user says, "I fell," the emergency notification unit stores the notification history and analyzes patterns of past emergency situations. For example, the emergency notification unit responds with, "Based on past history, there is a high risk of falling." When a user says, "I feel unwell," the emergency notification unit stores the notification history and analyzes patterns of past emergency situations. For example, the emergency notification unit responds with, "Based on past history, there is a high risk of feeling unwell." In this way, by analyzing patterns of past emergency situations and proposing preventive measures, it is possible to prevent emergencies from occurring.

[0036] The information providing unit can add a function to promote participation in local volunteer activities and community events, thereby strengthening social connections. For example, when a user says, "I'm looking for volunteer activities," the information providing unit suggests local volunteer activities. For example, it responds with, "This volunteer activity is available." Also, when a user says, "I want to participate in a community event," the information providing unit suggests local community events. For example, it responds with, "This community event is available." Also, when a user says, "I want to have social connections," the information providing unit suggests local volunteer activities and community events. For example, it responds with, "Try participating in this volunteer activity or community event." In this way, the user's social connections are strengthened by promoting participation in local volunteer activities and community events.

[0037] The health management unit cooperates with the wearable device to acquire health data in real time and perform health management. For example, when a user says, "Tell me how many steps I took today," the health management unit acquires step count data from the wearable device in real time and provides the result. For example, the health management unit may respond, "I walked 5,000 steps today." When a user says, "Tell me my heart rate," the health management unit acquires heart rate data from the wearable device in real time and provides the result. For example, the health management unit may respond, "My current heart rate is 70." When a user says, "Tell me the quality of my sleep," the health management unit acquires sleep data from the wearable device in real time and provides the result. For example, the health management unit may respond, "The quality of my sleep last night was good." This enables real-time health management by cooperating with the wearable device.

[0038] The information providing unit can suggest conversation topics based on the user's hobbies and interests, and promote dialogue. For example, when a user says, "What shall we talk about today?", the information providing unit suggests conversation topics based on the user's hobbies and interests. For example, the information providing unit responds with, "Shall we talk about recent movies?". Also, when a user says, "I want to talk about my hobbies," the information providing unit suggests conversation topics based on the user's hobbies. For example, the information providing unit responds with, "Shall we talk about recent sports news?". Also, when a user says, "I want to talk about things that interest me," the information providing unit suggests conversation topics based on the user's interests. For example, the information providing unit responds with, "Shall we talk about recent science news?". In this way, by suggesting conversation topics based on the user's hobbies and interests, dialogue is promoted and a sense of isolation is reduced.

[0039] The information providing unit can form an online community with other elderly people and promote interaction with people who share common hobbies and interests. For example, when a user says, "I want to talk to other people," the information providing unit suggests an online community and promotes interaction with people who share common hobbies and interests. For example, the information providing unit responds with, "Please try joining this online community." Also, when a user says, "I'm looking for people who share my hobbies," the information providing unit suggests an online community and promotes interaction with people who share common hobbies. For example, the information providing unit responds with, "Please try joining an online community for this hobby." Also, when a user says, "I want to talk about things that interest me," the information providing unit suggests an online community and promotes interaction with people who share common interests. For example, the information providing unit responds with, "Please try joining an online community for this interest." In this way, an online community can be formed with other elderly people, promoting interaction with people who share common hobbies and interests, thereby reducing a sense of isolation.

[0040] The information provision unit allows the AI ​​to analyze the content of conversations during video calls with family members and suggest appropriate topics. For example, when a user says, "What should we talk about?" during a video call with family members, the AI ​​analyzes the content of the conversation and suggests appropriate topics. For example, the information provision unit may respond with, "Shall we talk about our recent trip?". Also, when a user says, "I don't have anything to talk about," during a video call with family members, the AI ​​analyzes the content of the conversation and suggests appropriate topics. For example, the information provision unit may respond with, "Shall we talk about your recent hobbies?". Also, when a user says, "Suggest a topic," during a video call with family members, the AI ​​analyzes the content of the conversation and suggests appropriate topics. For example, the information provision unit may respond with, "Shall we talk about the latest news?". This allows for smoother communication by suggesting appropriate topics during video calls with family members.

[0041] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0042] In addition to the user's voice recognition function, a voice recognition IoT device can be equipped with a motion sensor that detects the user's movements. For example, if the user says, "I'm going to start exercising," the motion sensor detects the user's movements and monitors the progress of the exercise in real time. If the user says, "I'm going to take a break," the motion sensor detects the cessation of movement and records the timing of the break. Furthermore, if the user says, "I fell," the motion sensor detects the fall and notifies the emergency reporting department. This allows for safer and more effective support by monitoring the user's movements in real time.

[0043] In addition to the user's voice recognition function, voice recognition IoT devices can also be equipped with a GPS function that uses the user's location information. For example, if a user says, "Tell me where the nearest park is," the GPS function will identify the user's current location and provide information on the nearest park. If the user says, "I'm going for a walk," the GPS function will record the user's route so that it can be viewed later. Furthermore, if the user says, "I'm lost," the GPS function will identify the user's current location and notify emergency contacts. This makes it possible to provide more convenient and safer support by utilizing the user's location information.

[0044] In addition to the ability to recognize a user's voice, voice recognition IoT devices can also be equipped with the ability to store the user's health data in the cloud and share it with a doctor in a remote location. For example, if a user says, "Send my health data," the health data stored in the cloud can be sent to a doctor, allowing for remote medical treatment. If the user says, "Tell me the diagnosis results," the doctor's diagnosis results will be provided via voice. Furthermore, if the user says, "Give me some medication advice," the doctor's advice will be provided via voice. This makes it possible to collaborate with doctors in remote locations by utilizing the cloud, allowing for faster and more appropriate medical support.

[0045] In addition to the user's voice recognition function, a voice-recognition IoT device can also have a smart home function that controls the user's home appliances. For example, if the user says "Turn on the lights," the smart home function will turn on the lights. If the user says "Turn on the air conditioner," the smart home function will turn on the air conditioner. If the user says "Turn on the TV," the smart home function will turn on the TV. This allows for voice control of home appliances, providing a more convenient and comfortable living environment.

[0046] In addition to the user's voice recognition function, a voice-recognition IoT device can also have a calendar function that manages the user's schedule. For example, if the user says, "Tell me what's on my schedule for tomorrow," the calendar function will provide the next day's schedule via voice. If the user says, "Add an event," the calendar function will add a new event. Furthermore, if the user says, "Set a reminder," the calendar function will set a reminder and notify the user at the specified time. This allows for more efficient time management by managing schedules via voice.

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

[0048] Step 1: The voice recognition unit uses voice recognition technology to recognize the user's voice. For example, if the user asks, "What's the weather like today?", the voice can be analyzed and the answer can be, "The weather is sunny today." The voice recognition unit can also analyze the tone and speed of the user's voice and respond according to their emotional state. For example, if the user says, "I'm tired today," the voice recognition unit can analyze the tone and speed of the voice and respond, "I'll play some relaxing music." Step 2: The information providing unit provides useful local information based on the voice recognized by the voice recognition unit. For example, it can provide information about local events, garbage collection schedules, and information about nearby medical facilities through voice. The information providing unit can also predict and suggest the next song to play based on the user's past music selection history. For example, if the user says, "Play some music," the information providing unit will analyze the user's past music selection history and respond with, "I'll play some jazz, which I've been listening to a lot lately." Step 3: The health management unit manages the user's health based on the voice recognized by the voice recognition unit. For example, it can collect the user's health data, predict their health condition using AI, and provide appropriate advice. If the user says, "I'm not feeling well," the health management unit predicts their health condition based on past health data and responds, "I recommend you take a rest today." The health management unit can also record the user's meals and calculate calories via voice, supporting a healthy diet. For example, if the user says, "Record today's meals," the health management unit will record the meal contents via voice and respond, "The calories are 300 kcal." Step 4: The emergency notification unit makes an emergency call based on the voice recognized by the voice recognition unit. For example, if the user calls out "help," the emergency notification unit can automatically obtain location information and send it to an emergency contact. The emergency notification unit can also save emergency call history and analyze patterns of past emergency situations to suggest preventive measures. For example, if the user calls out "help," the emergency notification unit saves the call history and responds by saying, "Based on your past history, you are at high risk of falling."

[0049] (Example 2) The voice recognition IoT device according to an embodiment of the present invention is a system that allows elderly people to live their daily lives with peace of mind. This system uses voice recognition technology to provide useful information about the area where they live, support for health management and daily life, and emergency notification functions. As a result, the voice recognition IoT device helps elderly people to alleviate feelings of isolation and social loneliness, prevent frailty, and quickly notify emergency situations. It also promotes communication with family members who live far away, reducing the digital divide.

[0050] A voice recognition IoT device according to an embodiment includes a voice recognition unit, an information providing unit, a health management unit, and an emergency notification unit. The voice recognition unit recognizes a user's voice using voice recognition technology. For example, when a user asks, "What's the weather like today?", the voice recognition unit can analyze the voice and respond with, "It's sunny today." The voice recognition unit can also analyze the tone and speed of the user's voice and respond according to the user's emotional state. For example, if a user says, "I'm tired today," the voice recognition unit analyzes the tone and speed of the voice and responds with, "I'll play some relaxing music." The information providing unit provides useful local information based on the voice recognized by the voice recognition unit. For example, the information providing unit can provide voice notification of local event information, garbage collection schedules, information about nearby medical facilities, and the like. The information providing unit can also predict and suggest the next song to play based on the user's past music selection history. For example, when a user says, "Play some music," the information providing unit analyzes the user's past music selection history and responds with, "I'll play some jazz that I've been listening to a lot lately." The health management unit manages the user's health based on the voice recognition unit. For example, the health management unit can collect the user's health data, predict their health status using AI, and provide appropriate advice. If the user says, "I'm not feeling well," the health management unit can predict their health status based on past health data and respond, "I recommend you take a rest today." The health management unit can also record the user's meals and calculate calories via voice, supporting a healthy diet. For example, if the user says, "Record today's meals," the health management unit records the meal contents via voice and responds, "The calories are 300 kcal." The emergency notification unit can notify an emergency based on the voice recognition unit. For example, if the user yells "help," the emergency notification unit can automatically obtain location information and send it to emergency contacts. The emergency notification unit can also save emergency call history, analyze patterns of past emergencies, and suggest preventive measures. For example, if the user yells, "help," the emergency notification unit saves the call history and responds, "Based on your past history, you are at high risk of falling."As a result, the voice recognition IoT device according to the embodiment allows elderly people to live their daily lives with peace of mind. For example, by being able to easily obtain local information, connections with the local community are strengthened. In addition, health management and emergency notification functions help protect the health and safety of elderly people. Furthermore, by promoting communication with family members, feelings of isolation are reduced.

[0051] The voice recognition unit can analyze the tone or speed of the user's voice and respond according to the user's emotional state. For example, if the user says, "I'm tired today," the voice recognition unit analyzes the tone and speed of the voice and suggests relaxing music. For example, the voice recognition unit may respond, "I'll play some relaxing music." If the user says, "I'm happy today," the voice recognition unit analyzes the tone and speed of the voice and suggests uplifting music. For example, the voice recognition unit may respond, "I'll play some uplifting music." If the user says, "I'm sad today," the voice recognition unit analyzes the tone and speed of the voice and offers comforting words. For example, the voice recognition unit may respond, "Is there anything you'd like to talk about?" This enables appropriate responses according to the user's emotional state.

[0052] The information providing unit can predict and suggest the next song to be played based on the user's past music selection history. For example, when the user says, "Play some music," the information providing unit analyzes the user's past music selection history and suggests songs in the user's favorite genre. For example, the information providing unit may respond, "I'll play the jazz you've been listening to a lot lately." When the user says, "I want to listen to a new song," the information providing unit may suggest a new song based on the user's past music selection history. For example, the information providing unit may respond, "Try listening to this new song." When the user says, "Play some relaxing music," the information providing unit may suggest a relaxing song based on the user's past music selection history. For example, the information providing unit may respond, "I'll play this relaxing song." This makes it possible to suggest music that suits the user's preferences.

[0053] The health management unit collects the user's health data, uses AI to predict their health condition, and provides appropriate advice. For example, if the user says, "I'm not feeling well," the health management unit predicts their health condition based on past health data and provides appropriate advice. For example, it may respond, "I recommend you take a rest today." If the user says, "Give me some exercise advice," the health management unit provides exercise advice based on past health data. For example, it may respond, "It would be good to do some light stretching today." If the user says, "Give me some dietary advice," the health management unit provides dietary advice based on past health data. For example, it may respond, "It would be good to eat more vegetables today." This allows the user's health to be managed efficiently.

[0054] The emergency notification unit can automatically acquire location information in an emergency and send it to an emergency contact. For example, when a user yells "help," the emergency notification unit automatically acquires location information and sends it to an emergency contact. For example, the emergency notification unit responds with "Location information has been sent to an emergency contact." Furthermore, when a user says "I have fallen," the emergency notification unit automatically acquires location information and sends it to an emergency contact. For example, the emergency notification unit responds with "Location information has been sent to an emergency contact." Furthermore, when a user says "I am feeling unwell," the emergency notification unit automatically acquires location information and sends it to an emergency contact. For example, the emergency notification unit responds with "Location information has been sent to an emergency contact." This enables a rapid response in an emergency.

[0055] The information providing unit can suggest an optimal medical institution based on the user's health condition and past medical history. For example, when the user says, "Tell me about a nearby hospital," the information providing unit suggests an optimal hospital taking into consideration the user's health condition and past medical history. For example, the information providing unit may respond with, "This is the best hospital for you." Furthermore, when the user says, "I'm looking for a specialist," the information providing unit suggests an optimal specialist taking into consideration the user's health condition and past medical history. For example, the information providing unit may respond with, "This specialist is suitable." Furthermore, when the user says, "Tell me about a medical department," the information providing unit suggests an optimal medical department taking into consideration the user's health condition and past medical history. For example, the information providing unit may respond with, "This medical department is suitable." This makes it possible to suggest an optimal medical institution for the user.

[0056] The health management unit can support a healthy diet by recording the user's meals or calculating calories through voice. For example, when the user says, "Record what I eat today," the health management unit records the meal details through voice and calculates the calories. For example, when the user says, "I had bread and eggs for breakfast," the health management unit responds, "That's 300 kilocalories." When the user says, "Calculate the calories," the health management unit records the meal details through voice and calculates the calories. For example, when the user says, "I had salad and chicken for lunch," the health management unit responds, "That's 400 kilocalories." When the user says, "Give me some dietary advice," the health management unit records the meal details through voice, calculates the calories, and provides appropriate advice. For example, the health management unit responds, "It would be good to eat fish for dinner." This makes it possible to support the user's healthy diet.

[0057] The emergency notification unit stores emergency notification history, analyzes patterns of past emergency situations, and can propose preventive measures. For example, when a user yells "help," the emergency notification unit stores the notification history and analyzes patterns of past emergency situations. For example, the emergency notification unit responds with, "Based on past history, there is a high risk of falling." When a user says, "I fell," the emergency notification unit stores the notification history and analyzes patterns of past emergency situations. For example, the emergency notification unit responds with, "Based on past history, there is a high risk of falling." When a user says, "I feel unwell," the emergency notification unit stores the notification history and analyzes patterns of past emergency situations. For example, the emergency notification unit responds with, "Based on past history, there is a high risk of feeling unwell." In this way, by analyzing patterns of past emergency situations and proposing preventive measures, it is possible to prevent emergencies from occurring.

[0058] The physical condition management unit can estimate the user's stress level using the emotion estimation function and suggest relaxation methods. For example, when the user says, "I'm stressed," the physical condition management unit estimates the user's stress level using the emotion estimation function and suggests a relaxation method. For example, the physical condition management unit responds, "Try taking deep breaths." When the user says, "I want to relax," the physical condition management unit estimates the user's stress level using the emotion estimation function and suggests a relaxation method. For example, the physical condition management unit responds, "Try meditation." When the user says, "Tell me how to relieve stress," the physical condition management unit estimates the user's stress level using the emotion estimation function and suggests a relaxation method. For example, the physical condition management unit responds, "Try listening to relaxing music." In this way, the physical condition management unit estimates the user's stress level and suggests an appropriate relaxation method, thereby supporting the user's mental health.

[0059] The information providing unit can use the emotion estimation function to preferentially provide information about areas that evoke positive emotions in the user. For example, when the user says, "I'm feeling down today," the information providing unit uses the emotion estimation function to provide local event information that elicits positive emotions. For example, the information providing unit responds with, "There are some fun events like this." Furthermore, when the user says, "Tell me about some fun things to do," the information providing unit uses the emotion estimation function to provide local information that elicits positive emotions. For example, the information providing unit responds with, "You can have some fun things to do in this area." Furthermore, when the user says, "Tell me some information that will cheer me up," the information providing unit uses the emotion estimation function to provide local information that elicits positive emotions. For example, the information providing unit responds with, "You can have some fun things to do in this area." In this way, preferentially providing information that evokes positive emotions in the user supports the user's mental health.

[0060] The emergency notification unit can use the emotion estimation function to detect signs of an emergency situation that could lead to a user falling into one, and issue a warning in advance. For example, when a user says, "I feel unwell," the emergency notification unit uses the emotion estimation function to detect signs of an emergency situation and issue a warning in advance. For example, the emergency notification unit responds with, "Please take a rest immediately." Furthermore, when a user says, "I feel anxious," the emergency notification unit uses the emotion estimation function to detect signs of an emergency situation and issue a warning in advance. For example, the emergency notification unit responds with, "Please take a deep breath and calm down." Furthermore, when a user says, "I have chest pain," the emergency notification unit uses the emotion estimation function to detect signs of an emergency situation and issue a warning in advance. For example, the emergency notification unit responds with, "Please contact a medical institution immediately." In this way, by detecting signs of an emergency situation and issuing a warning in advance, it is possible to prevent an emergency situation from occurring.

[0061] The information providing unit can add a function to promote participation in local volunteer activities and community events, thereby strengthening social connections. For example, when a user says, "I'm looking for volunteer activities," the information providing unit suggests local volunteer activities. For example, it responds with, "This volunteer activity is available." Also, when a user says, "I want to participate in a community event," the information providing unit suggests local community events. For example, it responds with, "This community event is available." Also, when a user says, "I want to have social connections," the information providing unit suggests local volunteer activities and community events. For example, it responds with, "Try participating in this volunteer activity or community event." In this way, the user's social connections are strengthened by promoting participation in local volunteer activities and community events.

[0062] The health management unit cooperates with the wearable device to acquire health data in real time and perform health management. For example, when a user says, "Tell me how many steps I took today," the health management unit acquires step count data from the wearable device in real time and provides the result. For example, the health management unit may respond, "I walked 5,000 steps today." When a user says, "Tell me my heart rate," the health management unit acquires heart rate data from the wearable device in real time and provides the result. For example, the health management unit may respond, "My current heart rate is 70." When a user says, "Tell me the quality of my sleep," the health management unit acquires sleep data from the wearable device in real time and provides the result. For example, the health management unit may respond, "The quality of my sleep last night was good." This enables real-time health management by cooperating with the wearable device.

[0063] The information providing unit can suggest conversation topics based on the user's hobbies and interests, and promote dialogue. For example, when a user says, "What shall we talk about today?", the information providing unit suggests conversation topics based on the user's hobbies and interests. For example, the information providing unit responds with, "Shall we talk about recent movies?". Also, when a user says, "I want to talk about my hobbies," the information providing unit suggests conversation topics based on the user's hobbies. For example, the information providing unit responds with, "Shall we talk about recent sports news?". Also, when a user says, "I want to talk about things that interest me," the information providing unit suggests conversation topics based on the user's interests. For example, the information providing unit responds with, "Shall we talk about recent science news?". In this way, by suggesting conversation topics based on the user's hobbies and interests, dialogue is promoted and a sense of isolation is reduced.

[0064] The information providing unit can use the emotion estimation function to automatically generate dialogue content that evokes empathy based on the user's emotions and elicit empathy. For example, when the user says, "I'm feeling down today," the information providing unit uses the emotion estimation function to automatically generate dialogue content that evokes empathy. For example, the information providing unit responds with, "That's tough. Is there anything you'd like to talk about?". Also, when the user says, "I'm happy today," the information providing unit uses the emotion estimation function to automatically generate dialogue content that evokes empathy. For example, the information providing unit responds with, "That's great. Did something good happen?". Also, when the user says, "I'm tired today," the information providing unit uses the emotion estimation function to automatically generate dialogue content that evokes empathy. For example, the information providing unit responds with, "That's tough. Shall we do something to relax?". In this way, dialogue content that evokes empathy based on the user's emotions is automatically generated, thereby reducing the user's sense of isolation.

[0065] The information providing unit can form an online community with other elderly people and promote interaction with people who share common hobbies and interests. For example, when a user says, "I want to talk to other people," the information providing unit suggests an online community and promotes interaction with people who share common hobbies and interests. For example, the information providing unit responds with, "Please try joining this online community." Also, when a user says, "I'm looking for people who share my hobbies," the information providing unit suggests an online community and promotes interaction with people who share common hobbies. For example, the information providing unit responds with, "Please try joining an online community for this hobby." Also, when a user says, "I want to talk about things that interest me," the information providing unit suggests an online community and promotes interaction with people who share common interests. For example, the information providing unit responds with, "Please try joining an online community for this interest." In this way, an online community can be formed with other elderly people, promoting interaction with people who share common hobbies and interests, thereby reducing a sense of isolation.

[0066] The information providing unit can use the emotion estimation function to preferentially provide dialogue content that evokes positive emotions in the user. For example, when the user says, "I'm feeling down today," the information providing unit uses the emotion estimation function to provide dialogue content that elicits positive emotions. For example, the information providing unit responds with, "Has anything fun happened recently?". Also, when the user says, "I'm happy today," the information providing unit uses the emotion estimation function to provide dialogue content that elicits positive emotions. For example, the information providing unit responds with, "That's great. Did something good happen?". Also, when the user says, "I'm tired today," the information providing unit uses the emotion estimation function to provide dialogue content that elicits positive emotions. For example, the information providing unit responds with, "That's tough. Shall we do something relaxing?" In this way, by preferentially providing dialogue content that elicits positive emotions in the user, the user's sense of isolation is reduced.

[0067] The information provision unit allows the AI ​​to analyze the content of conversations during video calls with family members and suggest appropriate topics. For example, when a user says, "What should we talk about?" during a video call with family members, the AI ​​analyzes the content of the conversation and suggests appropriate topics. For example, the information provision unit may respond with, "Shall we talk about our recent trip?". Also, when a user says, "I don't have anything to talk about," during a video call with family members, the AI ​​analyzes the content of the conversation and suggests appropriate topics. For example, the information provision unit may respond with, "Shall we talk about your recent hobbies?". Also, when a user says, "Suggest a topic," during a video call with family members, the AI ​​analyzes the content of the conversation and suggests appropriate topics. For example, the information provision unit may respond with, "Shall we talk about the latest news?". This allows for smoother communication by suggesting appropriate topics during video calls with family members.

[0068] The information providing unit can use the emotion estimation function to analyze the user's emotional state in real time during a conversation with family members and provide an appropriate response. For example, if the user says, "I'm tired today," during a conversation with family members, the information providing unit analyzes the user's emotional state using the emotion estimation function and provides an appropriate response. For example, the information providing unit may respond, "That's tough. Is there anything I can help you with?" If the user says, "I'm happy today," during a conversation with family members, the information providing unit analyzes the user's emotional state using the emotion estimation function and provides an appropriate response. For example, the information providing unit may respond, "That's great. Did something good happen?" If the user says, "I'm sad today," during a conversation with family members, the information providing unit analyzes the user's emotional state using the emotion estimation function and provides an appropriate response. For example, the information providing unit may respond, "That's tough. Is there anything you'd like to talk about?" In this way, the information providing unit can analyze the user's emotional state in real time during a conversation with family members and provide an appropriate response, thereby facilitating communication.

[0069] The information providing unit can use the emotion estimation function to preferentially provide content that will inspire positive emotions while the user is using the digital device. For example, when the user says, "I'm feeling down today," the information providing unit uses the emotion estimation function to provide content that will elicit positive emotions. For example, the information providing unit responds with, "Watch this fun video." Furthermore, when the user says, "Tell me something fun," the information providing unit uses the emotion estimation function to provide content that will elicit positive emotions. For example, the information providing unit responds with, "Read this interesting article." Furthermore, when the user says, "Tell me something that will cheer you up," the information providing unit uses the emotion estimation function to provide content that will elicit positive emotions. For example, the information providing unit responds with, "Listen to this uplifting music." In this way, by preferentially providing content that will inspire positive emotions while the user is using the digital device, the digital divide is reduced.

[0070] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0071] Voice recognition IoT devices can not only analyze the tone and speed of a user's voice, but also recognize the user's facial expressions using a camera and respond according to their emotional state. For example, if a user says, "I'm tired today," the device can use facial recognition technology to detect the fatigue on the user's face and respond, "I'll play some relaxing music." If the user says, "I'm happy today," the device can detect a smile and respond, "I'll play some uplifting music." If the user says, "I'm sad today," the device can detect tears and respond, "Is there anything you'd like to talk about?" This allows for more accurate emotion estimation by analyzing both voice and facial expressions.

[0072] Voice recognition IoT devices can not only analyze the tone and speed of a user's voice, but also measure the user's heart rate and electrodermal activity with sensors and respond according to their emotional state. For example, if a user says, "I'm tired today," the device can detect an increase in heart rate and respond, "I'll play some relaxing music." If the user says, "I'm happy today," the device can detect a stabilization of the heart rate and respond, "I'll play some uplifting music." If the user says, "I'm sad today," the device can detect a change in electrodermal activity and respond, "Is there anything you'd like to talk about?" This allows for more accurate emotion estimation by analyzing both voice and biometric signals.

[0073] Voice recognition IoT devices can not only analyze the tone and speed of a user's voice, but can also respond according to the user's emotional state based on their past emotional history. For example, if a user says, "I'm tired today," the device can refer to their past emotional history and respond, "I'll play some relaxing music." If the user says, "I'm happy today," the device can refer to their past emotional history and respond, "I'll play some uplifting music." If the user says, "I'm sad today," the device can refer to their past emotional history and respond, "Is there anything you'd like to talk about?" This makes it possible to utilize past emotional history to more individually estimate emotions.

[0074] Voice recognition IoT devices can not only analyze the tone and speed of a user's voice, but also analyze the environmental sounds around the user and respond according to their emotional state. For example, if a user says, "I'm tired today," the device can detect quiet ambient sounds and respond, "I'll play some relaxing music." If the user says, "I'm happy today," the device can detect lively ambient sounds and respond, "I'll play some uplifting music." If the user says, "I'm sad today," the device can detect quiet ambient sounds and respond, "Is there anything you'd like to talk about?" By analyzing both voice and environmental sounds, more accurate emotion estimation becomes possible.

[0075] Voice recognition IoT devices can not only analyze the tone and speed of a user's voice, but also analyze the content of the user's social media posts and respond according to their emotional state. For example, if a user says, "I'm tired today," the device can refer to the social media post and respond, "I'll play some relaxing music." If the user says, "I'm happy today," the device can refer to the social media post and respond, "I'll play some uplifting music." If the user says, "I'm sad today," the device can refer to the social media post and respond, "Is there anything you'd like to talk about?" By analyzing both the voice and the content of the social media posts, more accurate emotion estimation becomes possible.

[0076] In addition to the user's voice recognition function, a voice recognition IoT device can be equipped with a motion sensor that detects the user's movements. For example, if the user says, "I'm going to start exercising," the motion sensor detects the user's movements and monitors the progress of the exercise in real time. If the user says, "I'm going to take a break," the motion sensor detects the cessation of movement and records the timing of the break. Furthermore, if the user says, "I fell," the motion sensor detects the fall and notifies the emergency reporting department. This allows for safer and more effective support by monitoring the user's movements in real time.

[0077] In addition to the user's voice recognition function, voice recognition IoT devices can also be equipped with a GPS function that uses the user's location information. For example, if a user says, "Tell me where the nearest park is," the GPS function will identify the user's current location and provide information on the nearest park. If the user says, "I'm going for a walk," the GPS function will record the user's route so that it can be viewed later. Furthermore, if the user says, "I'm lost," the GPS function will identify the user's current location and notify emergency contacts. This makes it possible to provide more convenient and safer support by utilizing the user's location information.

[0078] In addition to the ability to recognize a user's voice, voice recognition IoT devices can also be equipped with the ability to store the user's health data in the cloud and share it with a doctor in a remote location. For example, if a user says, "Send my health data," the health data stored in the cloud can be sent to a doctor, allowing for remote medical treatment. If the user says, "Tell me the diagnosis results," the doctor's diagnosis results will be provided via voice. Furthermore, if the user says, "Give me some medication advice," the doctor's advice will be provided via voice. This makes it possible to collaborate with doctors in remote locations by utilizing the cloud, allowing for faster and more appropriate medical support.

[0079] In addition to the user's voice recognition function, a voice-recognition IoT device can also have a smart home function that controls the user's home appliances. For example, if the user says "Turn on the lights," the smart home function will turn on the lights. If the user says "Turn on the air conditioner," the smart home function will turn on the air conditioner. If the user says "Turn on the TV," the smart home function will turn on the TV. This allows for voice control of home appliances, providing a more convenient and comfortable living environment.

[0080] In addition to the user's voice recognition function, a voice-recognition IoT device can also have a calendar function that manages the user's schedule. For example, if the user says, "Tell me what's on my schedule for tomorrow," the calendar function will provide the next day's schedule via voice. If the user says, "Add an event," the calendar function will add a new event. Furthermore, if the user says, "Set a reminder," the calendar function will set a reminder and notify the user at the specified time. This allows for more efficient time management by managing schedules via voice.

[0081] The processing flow of the second embodiment will be briefly explained below.

[0082] Step 1: The voice recognition unit uses voice recognition technology to recognize the user's voice. For example, if the user asks, "What's the weather like today?", the voice can be analyzed and the answer can be, "The weather is sunny today." The voice recognition unit can also analyze the tone and speed of the user's voice and respond according to their emotional state. For example, if the user says, "I'm tired today," the voice recognition unit can analyze the tone and speed of the voice and respond, "I'll play some relaxing music." Step 2: The information providing unit provides useful local information based on the voice recognized by the voice recognition unit. For example, it can provide information about local events, garbage collection schedules, and information about nearby medical facilities through voice. The information providing unit can also predict and suggest the next song to play based on the user's past music selection history. For example, if the user says, "Play some music," the information providing unit will analyze the user's past music selection history and respond with, "I'll play some jazz, which I've been listening to a lot lately." Step 3: The health management unit manages the user's health based on the voice recognized by the voice recognition unit. For example, it can collect the user's health data, predict their health condition using AI, and provide appropriate advice. If the user says, "I'm not feeling well," the health management unit predicts their health condition based on past health data and responds, "I recommend you take a rest today." The health management unit can also record the user's meals and calculate calories via voice, supporting a healthy diet. For example, if the user says, "Record today's meals," the health management unit will record the meal contents via voice and respond, "The calories are 300 kcal." Step 4: The emergency notification unit makes an emergency call based on the voice recognized by the voice recognition unit. For example, if the user calls out "help," the emergency notification unit can automatically obtain location information and send it to an emergency contact. The emergency notification unit can also save emergency call history and analyze patterns of past emergency situations to suggest preventive measures. For example, if the user calls out "help," the emergency notification unit saves the call history and responds by saying, "Based on your past history, you are at high risk of falling."

[0083] 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.

[0084] 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.

[0085] 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.

[0086] [Second embodiment] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0087] 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.

[0088] 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.

[0089] 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.

[0090] 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.

[0091] 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).

[0092] 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.

[0093] 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.

[0094] 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.

[0095] 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.

[0096] 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.

[0097] 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.

[0098] 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.

[0099] 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.

[0100] 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.

[0101] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0102] 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.

[0103] 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.

[0104] 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.

[0105] 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.

[0106] 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).

[0107] 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.

[0108] 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.

[0109] 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.

[0110] 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.

[0111] 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.

[0112] 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.

[0113] 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.

[0114] 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.

[0115] 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.

[0116] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0117] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0118] 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.

[0119] 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.

[0120] 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.

[0121] 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).

[0122] 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.

[0123] 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.

[0124] 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.

[0125] 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.

[0126] 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.

[0127] 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.

[0128] 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.

[0129] 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.

[0130] 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.

[0131] 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.

[0132] 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.

[0133] 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.

[0134] 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.

[0135] 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).

[0136] 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.

[0137] 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."

[0138] 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.

[0139] 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.

[0140] 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.

[0141] 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.

[0142] 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.

[0143] 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.

[0144] 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.

[0145] 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.

[0146] 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.

[0147] 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.

[0148] 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.

[0149] 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]

[0150] 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 voice recognition unit that recognizes a user's voice using voice recognition technology; an information providing unit that provides useful local information based on the voice recognized by the voice recognition unit; a physical condition management unit that manages physical condition based on the voice recognized by the voice recognition unit; an emergency notification unit that notifies the user in an emergency based on the voice recognized by the voice recognition unit; A system characterized by:

2. The voice recognition unit Analyzing the tone or rate of the user's voice and responding according to their emotional state 2. The system of claim 1.

3. The information providing unit Predict and suggest the next song to play based on the user's past song selection history 2. The system of claim 1.

4. The physical condition management unit Collecting the user's physical condition data, predicting their health status using AI, and providing appropriate advice 2. The system of claim 1.

5. The emergency notification unit In the event of an emergency, location information will be automatically acquired and sent to emergency contacts.

2. The system of claim 1.

6. The physical condition management unit Estimate the user's stress level and suggest relaxation methods 2. The system of claim 1.

7. The information providing unit Preferentially providing information about the area in which the user has a positive feeling 2. The system of claim 1.

8. The emergency notification unit Detects signs that the user is about to fall into an emergency and issues a warning in advance 2. The system of claim 1.

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