System

Abstract

To provide a system which acquires health information of a user, conducts health management, and reproduces a user according to generative AI through interactions with the user.SOLUTION: A system includes an acquisition part, a management part, an interactive part, and a reproduction part. The acquisition part acquires health information of a user. The management part manages the health of a user, based on the health information acquired by the acquisition part. The interactive part conducts interaction with a user. The reproduction part reproduces a user according to generative AI, based on interactions with the user.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 a description and related instruction sentence regarding 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] JP 2022-180282 A Summary of the Invention [Problem to be solved by the invention]

[0004] Conventional technology includes systems that acquire a user's health information and manage their health, but there is a problem in that the system has not adequately reproduced the user through dialogue with the user using generative AI.

[0005] The system of the embodiment aims to acquire the user's health information, manage the user's health, and recreate the user using generative AI through dialogue with the user. [Means for solving the problem]

[0006] The system according to the embodiment includes an acquisition unit, a management unit, a dialogue unit, and a reproduction unit. The acquisition unit acquires health information of a user. The management unit manages the health of the user based on the health information acquired by the acquisition unit. The dialogue unit engages in a dialogue with the user. The reproduction unit reproduces the user using a generative AI based on the dialogue with the user. Effect of the Invention

[0007] The system according to the embodiment can acquire a user's health information, manage their health, and recreate the user through dialogue with the user using a generative AI. [Brief description 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. [Diagram 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. FIG. [Diagram 3] FIG. 11 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Diagram 5] FIG. 13 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. 13 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 13 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 PREFERRED EMBODIMENTS

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

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

[0011] In the following embodiments, a signed processor (hereinafter simply referred to as a "processor") may be one arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be one 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 signed RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by the processor.

[0013] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs and 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 code is an interface including a communication processor and an antenna. The communication I / F controls communication between multiple computers. An example of a communication standard applied to the communication I / F is a wireless communication standard including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0015] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. In addition, in this specification, the same idea as "A and / or B" is also applied when three or more things are expressed by connecting them with "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, the RAM 30, and the 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 (e.g., 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., voice and / or text). Display 40A displays visible information such as text and images according to instructions from processor 46. Speaker 40B outputs voice according to 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 Complementary Metal-Oxide-Semiconductor (CMOS) image sensor or a Charge Coupled Device (CCD) image sensor.

[0022] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for transmitting and receiving various types of information between the processor 46 and the processor 28 via the network 54.

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

[0024] As shown in Fig. 2, 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. The specific process program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific process program 56 from the storage 32, and executes the read specific process 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 process 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 emotion of the user using the emotion identification model 59 and perform identification processing using the user's emotion. In the emotion estimation function (emotion identification function) using the emotion identification model 59, various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, are performed, but are not limited to such examples. In addition, the estimation and prediction of the emotion also include, for example, analysis of the 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 specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. Note that the smart device 14 has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can also perform processing similar to that of the specific processing unit 290 using these models.

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

[0028] (Example 1) The system according to the embodiment of the present invention is a system that provides an approach to recreating a deceased person using a generative AI. This system uses a "cat-type robot" that takes care of the user's body and mind before the user's death. For physical care, the cat-type care robot acquires the user's health information (e.g., blood pressure, heart rate, calorie information, etc.) and manages the user's health based on this information. For mental care, the robot relieves the user's loneliness through daily conversations. The contents of the conversations are recorded, and the user's thoughts, catchphrases, values, messages, etc. are acquired. After the user dies, an AI capable of talking in a manner reminiscent of the deceased is born based on this information. This AI uses a generative AI to recreate the user and provide a conversation to remember the deceased. For example, the cat-type care robot is a system that includes an acquisition unit (which may include AI processing) that acquires the user's health information, a management unit (which may include AI processing) that manages the user's health based on the acquired health information, a dialogue unit (which may include AI processing or generative AI processing) that dialogues with the user, and a reproduction unit (which includes generative AI processing) that reproduces the user by generative AI based on the dialogue with the user. The system also features a care robot that includes an acquisition unit, a management unit, and a dialogue unit. This allows the system using the generative AI to acquire, manage, and dialogue with the user's health information, and reproduce it using the generative AI.

[0029] The system according to the embodiment includes an acquisition unit, a management unit, a dialogue unit, and a reproduction unit. The acquisition unit acquires health information of the user. The health information of the user includes, for example, blood pressure, heart rate, calorie information, and the like, but is not limited to such examples. The acquisition unit measures the blood pressure of the user using, for example, a blood pressure monitor. The acquisition unit can also measure the heart rate of the user using a heart rate monitor. Furthermore, the acquisition unit can acquire the calorie information of the user using a calorie meter. For example, the acquisition unit measures the systolic blood pressure and the diastolic blood pressure using the blood pressure monitor and stores them as data. The heart rate monitor measures the resting heart rate and the exercise heart rate and stores them as data. The calorie meter measures the calories consumed and the calories ingested and stores them as data. The management unit manages the health of the user based on the health information acquired by the acquisition unit. The management unit, for example, monitors the health state. The management unit can also notify the user of abnormal values. Furthermore, the management unit can provide health advice based on the health information. For example, if the management unit detects an abnormal blood pressure value, it notifies the user. If an abnormal heart rate value is detected, it also notifies the user. Based on the calorie information, it can provide appropriate diet and exercise advice. The dialogue unit has daily conversations with the user and records the contents. The dialogue unit, for example, performs voice dialogue. The dialogue unit can also perform text dialogue. Furthermore, the dialogue unit can acquire the user's thoughts, catchphrases, values, messages, and the like. For example, the dialogue unit uses voice recognition technology to save the contents of the user's conversation as text data. In the case of text dialogue, the text entered by the user is saved as is. The reproduction unit reproduces the user using a generation AI based on the information recorded by the dialogue unit. The reproduction unit, for example, reproduces the user's voice. The reproduction unit can also reproduce the user's actions. Furthermore, the reproduction unit can reproduce the user's facial expressions. For example, the reproduction unit reproduces the user's tone of voice and speaking style using a generation AI. The reproduction of the actions can include the user's unique gestures and movements. The reproduction of facial expressions can include the user's smile, surprised expression, etc.As a result, the system according to the embodiment can acquire, manage, and interact with the user's health information, and reproduce it using a generative AI.

[0030] The acquisition unit acquires the health information of the user. The health information of the user includes, for example, blood pressure, heart rate, calorie information, and the like, but is not limited to such examples. The acquisition unit measures the blood pressure of the user using, for example, a blood pressure monitor. Specifically, the blood pressure monitor measures systolic blood pressure and diastolic blood pressure, and stores the measured values ​​as data. The systolic blood pressure indicates the pressure when the heart contracts to pump blood, and the diastolic blood pressure indicates the pressure when the heart expands to receive blood. This allows the user's blood pressure fluctuations to be grasped in detail. The acquisition unit can also measure the user's heart rate using a heart rate monitor. The heart rate monitor measures the resting heart rate and the exercise heart rate, and stores the measured values ​​as data. The resting heart rate indicates the heart rate when the user is at rest, and the exercise heart rate indicates the heart rate when the user is exercising. This allows the user's heart health to be monitored in detail. The acquisition unit can also acquire the user's calorie information using a calorie meter. The calorie meter measures the calories consumed and the calories ingested, and stores the measured values ​​as data. The calorie consumption indicates the amount of energy consumed by the user through daily life and exercise, and the calorie intake indicates the amount of energy taken in by the user through food. This allows the user's energy balance to be understood in detail. The acquisition unit manages these data in an integrated manner and provides basic information for comprehensively evaluating the user's health condition.

[0031] The management unit manages the health of the user based on the health information acquired by the acquisition unit. The management unit, for example, monitors the health condition. Specifically, the management unit monitors the collected blood pressure, heart rate, and calorie information in real time, and immediately notifies the user when an abnormal value is detected. For example, when blood pressure exceeds the normal range, the management unit can issue a warning to the user and urge the user to see a doctor. In addition, a similar notification is given when the heart rate is abnormally high or low. Furthermore, the management unit can provide health advice based on the health information. For example, based on the calorie information, the management unit provides the user with appropriate diet and exercise advice. Specifically, when the calorie intake exceeds the calorie consumption, the management unit can suggest to the user to review their diet and increase their exercise. In addition, the management unit can analyze the user's health data over the long term and grasp the trend of the health condition. This makes it possible to detect changes in the user's health condition early and take appropriate measures. The management unit plays an important role in comprehensively managing the user's health and supporting health maintenance and improvement.

[0032] The dialogue unit has daily conversations with the user and records the contents of the conversations. The dialogue unit, for example, performs voice dialogue. Specifically, the dialogue unit uses voice recognition technology to save the contents of the user's conversation as text data. Voice recognition technology can analyze the user's speech in real time and convert it into text. This allows the contents of the user's conversation to be accurately recorded. The dialogue unit can also perform text dialogue. In the case of text dialogue, the text entered by the user is saved as is. This allows the user's intentions and emotions to be accurately understood. Furthermore, the dialogue unit can also obtain the user's thoughts, catchphrases, values, messages, and the like. For example, the dialogue unit can record words and phrases that the user uses daily and grasp the user's personality and characteristics. This allows the dialogue unit to make communication with the user more natural and familiar. Through dialogue with the user, the dialogue unit grasps changes in the user's psychological state and emotions and provides important information for appropriate response.

[0033] The reproduction unit reproduces the user using the generation AI based on the information recorded by the dialogue unit. The reproduction unit reproduces, for example, the user's voice. Specifically, the generation AI can learn the user's tone of voice and speaking style, and generate the user's voice based on this. This allows the user's voice to be faithfully reproduced. The reproduction unit can also reproduce the user's actions. The generation AI can learn the user's unique gestures and movements, and reproduce the user's actions based on this. For example, it can reproduce the hand movements and postures that the user often performs. Furthermore, the reproduction unit can also reproduce the user's facial expressions. The generation AI can learn the changes in the user's facial expressions, and reproduce the user's facial expressions based on this. For example, it can reproduce the user's smile and surprised expression. This allows the reproduction unit to comprehensively reproduce the user's voice, actions, and facial expressions, and enhance the user's presence. The reproduction unit plays an important role in faithfully reproducing the user's personality and characteristics using the generation AI, making communication with the user more natural and familiar.

[0034] The system includes a care robot including an acquisition unit, a management unit, and a dialogue unit. The care robot can acquire, manage, and interact with the user's health information. The care robot, for example, has a moving function. The moving function allows the care robot to move freely around the user. The care robot also has a dialogue function. The dialogue function allows the care robot to have voice dialogue and text dialogue with the user. Furthermore, the care robot has a monitoring function. The monitoring function allows the care robot to constantly monitor the user's health condition. For example, the care robot periodically measures the user's blood pressure and notifies the user when an abnormal value is detected. The heart rate can also be monitored in a similar manner. By monitoring calorie information, the user's diet and exercise status can be grasped and appropriate advice can be provided. This allows the care robot to acquire, manage, and interact with the user's health information. A part or all of the above-mentioned processing in the care robot may be performed, for example, using AI, or may be performed without using AI. For example, the care robot can analyze data using AI to acquire the user's health information and evaluate the health condition. In addition, the care robot can use AI in the dialogue function to analyze the user's emotions and generate appropriate responses, and in the monitoring function, the care robot can use AI to detect abnormal values ​​and respond quickly.

[0035] The acquisition unit can acquire health information including the user's blood pressure, heart rate, and calorie information. The acquisition unit, for example, measures the user's blood pressure using a blood pressure monitor. The blood pressure monitor measures systolic blood pressure and diastolic blood pressure and stores the data. The acquisition unit can also measure the user's heart rate using a heart rate monitor. The heart rate monitor measures the resting heart rate and the exercise heart rate and stores the data as data. The acquisition unit can also acquire the user's calorie information using a calorie meter. The calorie meter measures the calories consumed and the calories ingested and stores the data as data. This allows the acquisition unit to acquire detailed health information of the user. A part or all of the above-mentioned processing in the acquisition unit may be performed using, for example, AI, or may be performed without using AI. For example, the acquisition unit can input data acquired by the blood pressure monitor to AI, and the AI ​​can analyze the data to detect abnormal values. The acquisition unit can also input data acquired by the heart rate monitor to AI, and the AI ​​can analyze the data to evaluate the health condition. Furthermore, the acquisition unit can input the data acquired by the calorie meter into the AI, which can then analyze the data and provide appropriate advice.

[0036] The management unit can manage the health of the user based on the acquired health information. The management unit, for example, monitors the health state. The management unit can constantly monitor the health state of the user based on the acquired health information. The management unit can also notify the user of abnormal values. For example, when an abnormal value of blood pressure is detected, the management unit notifies the user. When an abnormal value of heart rate is detected, the management unit also notifies the user. Furthermore, the management unit can provide health advice based on the health information. For example, based on calorie information, the management unit provides advice on appropriate meals and exercise. This allows the management unit to manage the health of the user based on the acquired health information. A part or all of the above-mentioned processing in the management unit may be performed using, for example, AI, or may be performed without using AI. For example, the management unit can input the acquired health information into AI, and the AI ​​can analyze the data to evaluate the health state. Furthermore, the management unit can use AI to detect abnormal values. Furthermore, the management unit can use AI to provide health advice.

[0037] The dialogue unit can have daily conversations with the user and record the contents of the conversations. The dialogue unit, for example, performs voice dialogue. The dialogue unit uses voice recognition technology to save the contents of the user's conversation as text data. The dialogue unit can also perform text dialogue. In the case of text dialogue, the text input by the user is saved as is. Furthermore, the dialogue unit can also acquire the user's thoughts, catchphrases, values, messages, and the like. For example, the dialogue unit analyzes the contents of the user's conversation, extracts and saves specific keywords and phrases. This allows the dialogue unit to record daily conversations with the user. A part or all of the above-mentioned processing in the dialogue unit may be performed, for example, using AI, or may be performed without using AI. For example, the dialogue unit can input data acquired using voice recognition technology to AI, and the AI ​​can analyze the data to extract specific keywords and phrases. Furthermore, the dialogue unit can input data of the text dialogue to AI, and the AI ​​can analyze the data to extract the user's values ​​and messages.

[0038] The reproduction unit can reproduce the user using the generation AI based on the information recorded in the dialogue unit. The reproduction unit reproduces, for example, the user's voice. The reproduction unit reproduces the user's tone of voice and speaking style using the generation AI. The reproduction unit can also reproduce the user's actions. The reproduction unit reproduces the user's unique gestures and movements using the generation AI. Furthermore, the reproduction unit can also reproduce the user's facial expressions. The reproduction unit reproduces the user's smile, surprised facial expression, and the like using the generation AI. This allows the reproduction unit to reproduce the user using the generation AI. A part or all of the above-mentioned processing in the reproduction unit may be performed using, for example, the generation AI, or may be performed without using the generation AI. For example, the reproduction unit can input the voice data recorded in the dialogue unit to the generation AI, and the generation AI can reproduce the voice. Also, the reproduction unit can input the action data recorded in the dialogue unit to the generation AI, and the generation AI can reproduce the action. Furthermore, the reproduction unit can input the facial expression data recorded in the dialogue unit to the generation AI, and the generation AI can reproduce the facial expression.

[0039] The acquisition unit can analyze the user's past health data and select the optimal acquisition method. The acquisition unit can, for example, analyze the user's past blood pressure data and acquire health information during the most stable time period. The acquisition unit can also be set to avoid acquiring data after exercise based on the user's past heart rate data. Furthermore, the acquisition unit can prioritize acquiring data after meals by referring to the user's past calorie data. This allows the acquisition unit to analyze the user's past health data and select the optimal acquisition method. A part or all of the above-mentioned processing in the acquisition unit may be performed using AI, for example, or may be performed without using AI. For example, the acquisition unit can input past health data into AI, and the AI ​​can analyze the data and select the optimal acquisition method. Furthermore, the acquisition unit can adjust the acquisition timing based on the past data. Furthermore, the acquisition unit can customize the acquisition method based on the past data.

[0040] The acquisition unit can filter the health information based on the user's current living situation and activity level when acquiring the health information. For example, when the user is exercising, the acquisition unit adjusts the acquisition so that the health information is acquired after the exercise. Also, when the user is resting, the acquisition unit can acquire the health information in a relaxed state. Furthermore, when the user is working, the acquisition unit can be set to acquire the health information in between work. This allows the acquisition unit to filter the health information based on the user's living situation and activity level. A part or all of the above-mentioned processing in the acquisition unit may be performed using, for example, AI, or may be performed without using AI. For example, the acquisition unit can input the user's activity data to the AI, and the AI ​​can analyze the data and adjust the acquisition timing. Also, the acquisition unit can input the user's living situation data to the AI, and the AI ​​can analyze the data and customize the acquisition method. Furthermore, the acquisition unit can input the user's activity level data to the AI, and the AI ​​can analyze the data and optimize the acquisition method.

[0041] When acquiring health information, the acquisition unit can prioritize acquiring highly relevant information in consideration of the geographical location information of the user. For example, when the user is at high altitude, the acquisition unit prioritizes acquisition of oxygen concentration. In addition, when the user is in an urban area, the acquisition unit can also acquire information on air quality. Furthermore, when the user is outdoors, the acquisition unit can also acquire information on the amount of ultraviolet rays. This allows the acquisition unit to acquire health information in consideration of the geographical location information of the user. A part or all of the above-mentioned processing in the acquisition unit may be performed using AI, for example, or may be performed without using AI. For example, the acquisition unit can input the user's location data to AI, and the AI ​​can analyze the data and select highly relevant information. In addition, the acquisition unit can customize the acquisition method by AI based on the location information. Furthermore, the acquisition unit can adjust the acquisition timing by AI based on the location information.

[0042] The acquisition unit can analyze the user's social media activity and acquire related health information when acquiring health information. For example, when the user posts on social media that he / she feels stressed, the acquisition unit prioritizes acquisition of the heart rate. In addition, when the user posts on exercise, the acquisition unit can also acquire health information after exercise. Furthermore, when the user posts on meals, the acquisition unit can also acquire calorie information after meals. This allows the acquisition unit to analyze the user's social media activity and acquire health information. A part or all of the above-mentioned processing in the acquisition unit may be performed using AI, for example, or may be performed without using AI. For example, the acquisition unit can input social media data into AI, and the AI ​​can analyze the data and select related health information. In addition, the acquisition unit can customize the acquisition method by AI based on social media activity data. Furthermore, the acquisition unit can adjust the acquisition timing by AI based on social media data.

[0043] The management unit can select an appropriate management method by referring to the user's past health data during health management. The management unit, for example, proposes an optimal exercise plan based on the user's past blood pressure data. The management unit can also propose a method for relaxing by referring to the user's past heart rate data. The management unit can also propose a method of diet management based on the user's past calorie data. This allows the management unit to select an optimal management method by referring to the user's past health data. Some or all of the above-mentioned processing in the management unit may be performed using AI, for example, or may be performed without using AI. For example, the management unit can input past health data into AI, and the AI ​​can analyze the data and select an optimal management method. The management unit can also customize the management method by AI based on past data. Furthermore, the management unit can adjust the management timing by AI based on past data.

[0044] The management unit can customize the management means based on the user's current living situation during health management. For example, when the user is at work, the management unit suggests a stretch that can be done in a short time. In addition, when the user is resting, the management unit can also suggest a breathing technique for relaxation. Furthermore, when the user is exercising, the management unit can also suggest an appropriate method of hydration. This allows the management unit to customize the health management means based on the user's current living situation. A part or all of the above-mentioned processing in the management unit may be performed using AI, for example, or may be performed without using AI. For example, the management unit can input the user's living situation data into AI, and the AI ​​can analyze the data to customize the management means. In addition, the management unit can adjust the management method by AI based on the user's activity data. Furthermore, the management unit can adjust the management timing by AI based on the user's living situation data.

[0045] The management unit can select an appropriate management method in consideration of the geographical location information of the user during health management. For example, when the user is at high altitude, the management unit prioritizes management of oxygen concentration. In addition, when the user is in an urban area, the management unit can also prioritize management of air quality. Furthermore, when the user is outdoors, the management unit can also prioritize ultraviolet ray protection. This allows the management unit to select a health management method in consideration of the geographical location information of the user. A part or all of the above-mentioned processing in the management unit may be performed using AI, for example, or may be performed without using AI. For example, the management unit can input the user's location data into AI, and the AI ​​can analyze the data and select highly relevant information. In addition, the management unit can customize the management method by AI based on the location information. Furthermore, the management unit can adjust the management timing by AI based on the location information.

[0046] The management unit can analyze the user's social media activity and suggest management measures during health management. For example, if the user posts on social media that he or she is feeling stressed, the management unit can suggest a way to relax. In addition, if the user posts on exercise, the management unit can also suggest an appropriate exercise plan. Furthermore, if the user posts on diet, the management unit can also suggest a balanced diet plan. This allows the management unit to analyze the user's social media activity and suggest health management measures. Some or all of the above-mentioned processing in the management unit may be performed using AI, for example, or may be performed without using AI. For example, the management unit can input social media data into AI, and the AI ​​can analyze the data and select related health information. In addition, the management unit can customize the management method by AI based on social media activity data. Furthermore, the management unit can adjust the management timing by AI based on social media data.

[0047] The dialogue unit can select an appropriate dialogue method by referring to the user's past dialogue history during dialogue. The dialogue unit selects the optimal dialogue method based on, for example, a dialogue style that the user has preferred in the past. The dialogue unit can also prioritize a specific topic from the user's past dialogue history. The dialogue unit can also analyze the user's past dialogue history and select the most effective dialogue method. This allows the dialogue unit to select the optimal dialogue method by referring to the user's past dialogue history. A part or all of the above-mentioned processing in the dialogue unit may be performed using, for example, an AI, or may be performed without using an AI. For example, the dialogue unit can input the past dialogue history into an AI, and the AI ​​can analyze the data and select the optimal dialogue method. The dialogue unit can also customize the dialogue method by the AI ​​based on past data. Furthermore, the dialogue unit can adjust the dialogue timing by the AI ​​based on past data.

[0048] The dialogue unit can customize the dialogue content based on the user's current mood and situation during the dialogue. For example, when the user is sad, the dialogue unit can conduct a dialogue with comforting content. Furthermore, when the user is happy, the dialogue unit can conduct a dialogue with empathy content. Furthermore, when the user is tired, the dialogue unit can conduct a dialogue with relaxing content. This allows the dialogue unit to customize the dialogue content based on the user's current mood and situation. A part or all of the above-mentioned processing in the dialogue unit may be performed using, for example, AI, or may be performed without using AI. For example, the dialogue unit can input the user's mood data into the AI, and the AI ​​can analyze the data to customize the dialogue content. Furthermore, the dialogue unit can adjust the dialogue method based on the user's situation data. Furthermore, the dialogue unit can adjust the dialogue timing based on the user's mood data.

[0049] The dialogue unit can select appropriate dialogue content in consideration of the geographical location information of the user during dialogue. For example, when the user is traveling, the dialogue unit performs dialogue to provide information about the travel destination. Furthermore, when the user is at home, the dialogue unit can also perform dialogue for relaxation. Furthermore, when the user is at work, the dialogue unit can also perform work-related dialogue. This allows the dialogue unit to select dialogue content in consideration of the geographical location information of the user. A part or all of the above-mentioned processing in the dialogue unit may be performed using, for example, an AI, or may be performed without using an AI. For example, the dialogue unit can input the user's location data into the AI, and the AI ​​can analyze the data and select highly relevant dialogue content. Furthermore, the dialogue unit can customize the dialogue method by the AI ​​based on the location information. Furthermore, the dialogue unit can adjust the dialogue timing by the AI ​​based on the location information.

[0050] The dialogue unit can analyze the user's social media activity and suggest dialogue content at the time of dialogue. For example, if the user posts on social media that he or she is feeling stressed, the dialogue unit can suggest a dialogue for relaxing. In addition, if the user posts on exercise, the dialogue unit can also suggest a dialogue related to exercise. In addition, if the user posts on food, the dialogue unit can also suggest a dialogue related to food. This allows the dialogue unit to analyze the user's social media activity and suggest dialogue content. A part or all of the above-mentioned processing in the dialogue unit may be performed, for example, using AI, or may be performed without using AI. For example, the dialogue unit can input social media data into the AI, and the AI ​​can analyze the data and select related dialogue content. In addition, the dialogue unit can customize the dialogue method based on the social media activity data. In addition, the dialogue unit can adjust the dialogue timing based on the social media data.

[0051] The reproduction unit can select an appropriate reproduction method by referring to the user's past dialogue history at the time of reproduction. The reproduction unit selects the optimal reproduction method based on, for example, a dialogue style that the user has preferred in the past. The reproduction unit can also prioritize reproduction of a specific topic from the user's past dialogue history. Furthermore, the reproduction unit can analyze the user's past dialogue history and select the most effective reproduction method. This allows the reproduction unit to select the optimal reproduction method by referring to the user's past dialogue history. A part or all of the above-mentioned processing in the reproduction unit may be performed, for example, using the generation AI, or may be performed without using the generation AI. For example, the reproduction unit can input the past dialogue history into the generation AI, and the generation AI can analyze the data and select the optimal reproduction method. Furthermore, the reproduction unit can customize the reproduction method by the generation AI based on the past data. Furthermore, the reproduction unit can adjust the reproduction timing by the generation AI based on the past data.

[0052] The reproduction unit can customize the reproduction content based on the user's current feelings and situation at the time of reproduction. For example, if the user is sad, the reproduction unit reproduces comforting content. Also, if the user is happy, the reproduction unit can reproduce empathetic content. Furthermore, if the user is tired, the reproduction unit can reproduce relaxing content. This allows the reproduction unit to customize the reproduction content based on the user's current feelings and situation. A part or all of the above-mentioned processing in the reproduction unit may be performed using, for example, a generation AI, or may be performed without using a generation AI. For example, the reproduction unit can input the user's feelings data into the generation AI, and the generation AI can analyze the data to customize the reproduction content. Also, the reproduction unit can adjust the reproduction method based on the user's situation data. Furthermore, the reproduction unit can adjust the reproduction timing based on the user's feelings data.

[0053] The reproduction unit can select an appropriate reproduction method in consideration of the geographical location information of the user at the time of reproduction. For example, when the user is traveling, the reproduction unit performs reproduction that provides information about the travel destination. Furthermore, when the user is at home, the reproduction unit can also perform reproduction for relaxation. Furthermore, when the user is at work, the reproduction unit can also perform work-related reproduction. This allows the reproduction unit to select a reproduction method in consideration of the geographical location information of the user. A part or all of the above-mentioned processing in the reproduction unit may be performed using, for example, the generation AI, or may be performed without using the generation AI. For example, the reproduction unit can input the user's location data to the generation AI, and the generation AI can analyze the data and select a highly relevant reproduction method. Furthermore, the reproduction unit can customize the reproduction method by the generation AI based on the location information. Furthermore, the reproduction unit can adjust the reproduction timing by the generation AI based on the location information.

[0054] The reproducing unit can analyze the user's social media activity and suggest the reproduction content at the time of reproduction. For example, if the user posts on social media that he / she feels stressed, the reproducing unit can suggest a reproducing for relaxing. In addition, if the user posts on exercise, the reproducing unit can also suggest a reproducing related to exercise. Furthermore, if the user posts on food, the reproducing unit can also suggest a reproducing related to food. In this way, the reproducing unit can analyze the user's social media activity and suggest the reproduction content. A part or all of the above-mentioned processing in the reproducing unit may be performed, for example, using the generating AI, or may be performed without using the generating AI. For example, the reproducing unit can input social media data to the generating AI, and the generating AI can analyze the data and select the relevant reproduction content. In addition, the reproducing unit can customize the reproduction method by the generating AI based on the social media activity data. Furthermore, the reproducing unit can adjust the timing of reproduction by the generating AI based on the social media data.

[0055] The care robot can select an appropriate operation method by referring to the user's past health data when operating. The care robot can suggest an operation for relaxing based on the user's past blood pressure data, for example. The care robot can also suggest an appropriate exercise by referring to the user's past heart rate data. Furthermore, the care robot can also suggest a balanced meal based on the user's past calorie data. This allows the care robot to select an optimal operation method by referring to the user's past health data. A part or all of the above-mentioned processing in the care robot may be performed using, for example, an AI, or may be performed without using an AI. For example, the care robot can input past health data into an AI, and the AI ​​can analyze the data and select an optimal operation method. Furthermore, the care robot can customize the operation method by the AI ​​based on the past data. Furthermore, the care robot can adjust the operation timing by the AI ​​based on the past data.

[0056] The care robot can customize the operating means based on the user's current living situation when operating. For example, when the user is at work, the care robot can suggest a stretching exercise that can be performed in a short time. Furthermore, when the user is resting, the care robot can also suggest a breathing technique for relaxation. Furthermore, when the user is exercising, the care robot can also suggest an appropriate method of hydration. This allows the care robot to customize the operating means based on the user's current living situation. A part or all of the above-mentioned processing in the care robot may be performed using, for example, an AI, or may be performed without using an AI. For example, the care robot can input the user's living situation data into the AI, and the AI ​​can analyze the data to customize the operating means. Furthermore, the care robot can adjust the operating method based on the user's activity data. Furthermore, the care robot can adjust the operating timing based on the user's living situation data.

[0057] The care robot can select an appropriate operation method in consideration of the geographical location information of the user when operating. For example, when the user is at high altitude, the care robot prioritizes management of oxygen concentration. In addition, when the user is in an urban area, the care robot can also prioritize management of air quality. Furthermore, when the user is outdoors, the care robot can also prioritize ultraviolet protection. This allows the care robot to select an operation method in consideration of the geographical location information of the user. A part or all of the above-mentioned processing in the care robot may be performed, for example, using AI, or may be performed without using AI. For example, the care robot can input the user's location data into the AI, and the AI ​​can analyze the data and select a highly relevant operation method. In addition, the care robot can customize the operation method by the AI ​​based on the location information. Furthermore, the care robot can adjust the operation timing by the AI ​​based on the location information.

[0058] The care robot can analyze the social media activity of the user and suggest a motion means when operating. For example, when the user posts on social media that he / she feels stressed, the care robot can suggest a way to relax. In addition, when the user posts on exercise, the care robot can also suggest an appropriate exercise plan. Furthermore, when the user posts on diet, the care robot can also suggest a balanced diet plan. This allows the care robot to analyze the social media activity of the user and suggest a motion means. A part or all of the above-mentioned processing in the care robot may be performed using, for example, an AI, or may be performed without using an AI. For example, the care robot can input social media data into an AI, and the AI ​​can analyze the data and select a related motion means. In addition, the care robot can customize the motion method based on the social media activity data. Furthermore, the care robot can adjust the motion timing based on the social media data.

[0059] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0060] The system includes an acquisition unit, a management unit, a dialogue unit, and a reproduction unit. The system may further include a data analysis unit that analyzes the user's past health data and selects the optimal acquisition method. For example, the data analysis unit analyzes the user's past blood pressure data and acquires health information during the most stable time period. Also, based on the user's past heart rate data, it may be set to avoid acquiring data after exercise. Furthermore, based on the user's past calorie data, it may be possible to prioritize acquiring data after meals. This allows the system to analyze the user's past health data and select the optimal acquisition method.

[0061] The system includes an acquisition unit, a management unit, a dialogue unit, and a reproduction unit. The system may further include a life situation analysis unit that adjusts the timing of acquiring health information based on the user's current life situation and activity level. For example, the life situation analysis unit adjusts the timing of acquiring health information to be acquired after exercise when the user is exercising. Also, when the user is resting, the health information can be acquired in a relaxed state. Furthermore, when the user is at work, the health information can be set to be acquired during breaks from work. This allows the system to filter health information based on the user's life situation and activity level.

[0062] The system includes an acquisition unit, a management unit, a dialogue unit, and a reproduction unit. The system may further include a location information analysis unit that prioritizes acquisition of highly relevant information in consideration of the geographical location information of the user. For example, the location information analysis unit prioritizes acquisition of oxygen concentration when the user is at high altitude. Also, when the user is in an urban area, it may acquire information on air quality. Furthermore, when the user is outdoors, it may acquire information on the amount of ultraviolet light. This allows the system to acquire health information in consideration of the geographical location information of the user.

[0063] The system includes an acquisition unit, a management unit, a dialogue unit, and a reproduction unit. The system may further include a social media analysis unit that analyzes the user's social media activity and acquires related health information. For example, the social media analysis unit prioritizes acquisition of the heart rate when the user posts on social media that he or she is feeling stressed. Also, when the user posts about exercise, the social media analysis unit may acquire health information after exercise. Furthermore, when the user posts about meals, calorie information after meals may be acquired. This allows the system to acquire health information by analyzing the user's social media activity.

[0064] The system includes an acquisition unit, a management unit, a dialogue unit, and a reproduction unit. The system may further include a dialogue history analysis unit that refers to the user's past dialogue history to select an appropriate dialogue method. For example, the dialogue history analysis unit selects the optimal dialogue method based on the dialogue style that the user has preferred in the past. The system may also prioritize a specific topic from the user's past dialogue history. The system may further analyze the user's past dialogue history to select the most effective dialogue method. This allows the system to select the optimal dialogue method by referring to the user's past dialogue history.

[0065] The system includes an acquisition unit, a management unit, a dialogue unit, and a reproduction unit. The system may further include a location information reproduction unit that selects an appropriate reproduction method in consideration of the geographical location information of the user. For example, when the user is traveling, the location information reproduction unit performs reproduction that provides information about the travel destination. When the user is at home, the location information reproduction unit may perform reproduction for relaxation. When the user is at work, the location information reproduction unit may perform work-related reproduction. This allows the system to select a reproduction method in consideration of the geographical location information of the user.

[0066] The process flow of the first embodiment will be briefly described below.

[0067] Step 1: The acquisition unit acquires health information of the user. The health information of the user includes, for example, blood pressure, heart rate, calorie information, etc. The acquisition unit measures the user's blood pressure using a blood pressure meter, measures the user's heart rate using a heart rate meter, and acquires the user's calorie information using a calorie meter. These data are stored. Step 2: The management unit manages the user's health based on the health information acquired by the acquisition unit. The management unit monitors the health status, notifies the user of abnormal values, and provides health advice based on the health information. For example, if an abnormal value is detected in blood pressure or heart rate, the management unit notifies the user and provides appropriate diet and exercise advice based on calorie information. Step 3: The dialogue unit conducts daily conversations with the user and records the contents of those conversations. The dialogue unit conducts voice dialogues and text dialogues to obtain the user's thoughts, catchphrases, values, messages, etc. The content of the user's conversations is saved as text data using voice recognition technology, and in the case of text dialogues, the text entered by the user is saved as is. Step 4: The reproduction unit uses the generation AI to reproduce the user based on the information recorded by the dialogue unit. The reproduction unit reproduces the user's voice, actions, and facial expressions. For example, the generation AI can be used to reproduce the user's tone of voice and speaking style, reproduce actions including unique gestures and movements, and reproduce smiles, surprised expressions, etc.

[0068] (Example 2) The system according to the embodiment of the present invention is a system that provides an approach to recreating a deceased person using a generative AI. This system uses a "cat-type robot" that takes care of the user's body and mind before the user's death. For physical care, the cat-type care robot acquires the user's health information (e.g., blood pressure, heart rate, calorie information, etc.) and manages the user's health based on this information. For mental care, the robot relieves the user's loneliness through daily conversations. The contents of the conversations are recorded, and the user's thoughts, catchphrases, values, messages, etc. are acquired. After the user dies, an AI capable of talking in a manner reminiscent of the deceased is born based on this information. This AI uses a generative AI to recreate the user and provide a conversation to remember the deceased. For example, the cat-type care robot is a system that includes an acquisition unit (which may include AI processing) that acquires the user's health information, a management unit (which may include AI processing) that manages the user's health based on the acquired health information, a dialogue unit (which may include AI processing or generative AI processing) that dialogues with the user, and a reproduction unit (which includes generative AI processing) that reproduces the user by generative AI based on the dialogue with the user. The system also features a care robot that includes an acquisition unit, a management unit, and a dialogue unit. This allows the system using the generative AI to acquire, manage, and dialogue with the user's health information, and reproduce it using the generative AI.

[0069] The system according to the embodiment includes an acquisition unit, a management unit, a dialogue unit, and a reproduction unit. The acquisition unit acquires health information of the user. The health information of the user includes, for example, blood pressure, heart rate, calorie information, and the like, but is not limited to such examples. The acquisition unit measures the blood pressure of the user using, for example, a blood pressure monitor. The acquisition unit can also measure the heart rate of the user using a heart rate monitor. Furthermore, the acquisition unit can acquire the calorie information of the user using a calorie meter. For example, the acquisition unit measures the systolic blood pressure and the diastolic blood pressure using the blood pressure monitor and stores them as data. The heart rate monitor measures the resting heart rate and the exercise heart rate and stores them as data. The calorie meter measures the calories consumed and the calories ingested and stores them as data. The management unit manages the health of the user based on the health information acquired by the acquisition unit. The management unit, for example, monitors the health state. The management unit can also notify the user of abnormal values. Furthermore, the management unit can provide health advice based on the health information. For example, if the management unit detects an abnormal blood pressure value, it notifies the user. If an abnormal heart rate value is detected, it also notifies the user. Based on the calorie information, it can provide appropriate diet and exercise advice. The dialogue unit has daily conversations with the user and records the contents. The dialogue unit, for example, performs voice dialogue. The dialogue unit can also perform text dialogue. Furthermore, the dialogue unit can acquire the user's thoughts, catchphrases, values, messages, and the like. For example, the dialogue unit uses voice recognition technology to save the contents of the user's conversation as text data. In the case of text dialogue, the text entered by the user is saved as is. The reproduction unit reproduces the user using a generation AI based on the information recorded by the dialogue unit. The reproduction unit, for example, reproduces the user's voice. The reproduction unit can also reproduce the user's actions. Furthermore, the reproduction unit can reproduce the user's facial expressions. For example, the reproduction unit reproduces the user's tone of voice and speaking style using a generation AI. The reproduction of the actions can include the user's unique gestures and movements. The reproduction of facial expressions can include the user's smile, surprised expression, etc.As a result, the system according to the embodiment can acquire, manage, and interact with the user's health information, and reproduce it using a generative AI.

[0070] The acquisition unit acquires the health information of the user. The health information of the user includes, for example, blood pressure, heart rate, calorie information, and the like, but is not limited to such examples. The acquisition unit measures the blood pressure of the user using, for example, a blood pressure monitor. Specifically, the blood pressure monitor measures systolic blood pressure and diastolic blood pressure, and stores the measured values ​​as data. The systolic blood pressure indicates the pressure when the heart contracts to pump blood, and the diastolic blood pressure indicates the pressure when the heart expands to receive blood. This allows the user's blood pressure fluctuations to be grasped in detail. The acquisition unit can also measure the user's heart rate using a heart rate monitor. The heart rate monitor measures the resting heart rate and the exercise heart rate, and stores the measured values ​​as data. The resting heart rate indicates the heart rate when the user is at rest, and the exercise heart rate indicates the heart rate when the user is exercising. This allows the user's heart health to be monitored in detail. The acquisition unit can also acquire the user's calorie information using a calorie meter. The calorie meter measures the calories consumed and the calories ingested, and stores the measured values ​​as data. The calorie consumption indicates the amount of energy consumed by the user through daily life and exercise, and the calorie intake indicates the amount of energy taken in by the user through food. This allows the user's energy balance to be understood in detail. The acquisition unit manages these data in an integrated manner and provides basic information for comprehensively evaluating the user's health condition.

[0071] The management unit manages the health of the user based on the health information acquired by the acquisition unit. The management unit, for example, monitors the health condition. Specifically, the management unit monitors the collected blood pressure, heart rate, and calorie information in real time, and immediately notifies the user when an abnormal value is detected. For example, when blood pressure exceeds the normal range, the management unit can issue a warning to the user and urge the user to see a doctor. In addition, a similar notification is given when the heart rate is abnormally high or low. Furthermore, the management unit can provide health advice based on the health information. For example, based on the calorie information, the management unit provides the user with appropriate diet and exercise advice. Specifically, when the calorie intake exceeds the calorie consumption, the management unit can suggest to the user to review their diet and increase their exercise. In addition, the management unit can analyze the user's health data over the long term and grasp the trend of the health condition. This makes it possible to detect changes in the user's health condition early and take appropriate measures. The management unit plays an important role in comprehensively managing the user's health and supporting health maintenance and improvement.

[0072] The dialogue unit has daily conversations with the user and records the contents of the conversations. The dialogue unit, for example, performs voice dialogue. Specifically, the dialogue unit uses voice recognition technology to save the contents of the user's conversation as text data. Voice recognition technology can analyze the user's speech in real time and convert it into text. This allows the contents of the user's conversation to be accurately recorded. The dialogue unit can also perform text dialogue. In the case of text dialogue, the text entered by the user is saved as is. This allows the user's intentions and emotions to be accurately understood. Furthermore, the dialogue unit can also obtain the user's thoughts, catchphrases, values, messages, and the like. For example, the dialogue unit can record words and phrases that the user uses daily and grasp the user's personality and characteristics. This allows the dialogue unit to make communication with the user more natural and familiar. Through dialogue with the user, the dialogue unit grasps changes in the user's psychological state and emotions and provides important information for appropriate response.

[0073] The reproduction unit reproduces the user using the generation AI based on the information recorded by the dialogue unit. The reproduction unit reproduces, for example, the user's voice. Specifically, the generation AI can learn the user's tone of voice and speaking style, and generate the user's voice based on this. This allows the user's voice to be faithfully reproduced. The reproduction unit can also reproduce the user's actions. The generation AI can learn the user's unique gestures and movements, and reproduce the user's actions based on this. For example, it can reproduce the hand movements and postures that the user often performs. Furthermore, the reproduction unit can also reproduce the user's facial expressions. The generation AI can learn the changes in the user's facial expressions, and reproduce the user's facial expressions based on this. For example, it can reproduce the user's smile and surprised expression. This allows the reproduction unit to comprehensively reproduce the user's voice, actions, and facial expressions, and enhance the user's presence. The reproduction unit plays an important role in faithfully reproducing the user's personality and characteristics using the generation AI, making communication with the user more natural and familiar.

[0074] The system includes a care robot including an acquisition unit, a management unit, and a dialogue unit. The care robot can acquire, manage, and interact with the user's health information. The care robot, for example, has a moving function. The moving function allows the care robot to move freely around the user. The care robot also has a dialogue function. The dialogue function allows the care robot to have voice dialogue and text dialogue with the user. Furthermore, the care robot has a monitoring function. The monitoring function allows the care robot to constantly monitor the user's health condition. For example, the care robot periodically measures the user's blood pressure and notifies the user when an abnormal value is detected. The heart rate can also be monitored in a similar manner. By monitoring calorie information, the user's diet and exercise status can be grasped and appropriate advice can be provided. This allows the care robot to acquire, manage, and interact with the user's health information. A part or all of the above-mentioned processing in the care robot may be performed, for example, using AI, or may be performed without using AI. For example, the care robot can analyze data using AI to acquire the user's health information and evaluate the health condition. In addition, the care robot can use AI in the dialogue function to analyze the user's emotions and generate appropriate responses, and in the monitoring function, the care robot can use AI to detect abnormal values ​​and respond quickly.

[0075] The acquisition unit can acquire health information including the user's blood pressure, heart rate, and calorie information. The acquisition unit, for example, measures the user's blood pressure using a blood pressure monitor. The blood pressure monitor measures systolic blood pressure and diastolic blood pressure and stores the data. The acquisition unit can also measure the user's heart rate using a heart rate monitor. The heart rate monitor measures the resting heart rate and the exercise heart rate and stores the data as data. The acquisition unit can also acquire the user's calorie information using a calorie meter. The calorie meter measures the calories consumed and the calories ingested and stores the data as data. This allows the acquisition unit to acquire detailed health information of the user. A part or all of the above-mentioned processing in the acquisition unit may be performed using, for example, AI, or may be performed without using AI. For example, the acquisition unit can input data acquired by the blood pressure monitor to AI, and the AI ​​can analyze the data to detect abnormal values. The acquisition unit can also input data acquired by the heart rate monitor to AI, and the AI ​​can analyze the data to evaluate the health condition. Furthermore, the acquisition unit can input the data acquired by the calorie meter into the AI, which can then analyze the data and provide appropriate advice.

[0076] The management unit can manage the health of the user based on the acquired health information. The management unit, for example, monitors the health state. The management unit can constantly monitor the health state of the user based on the acquired health information. The management unit can also notify the user of abnormal values. For example, when an abnormal value of blood pressure is detected, the management unit notifies the user. When an abnormal value of heart rate is detected, the management unit also notifies the user. Furthermore, the management unit can provide health advice based on the health information. For example, based on calorie information, the management unit provides advice on appropriate meals and exercise. This allows the management unit to manage the health of the user based on the acquired health information. A part or all of the above-mentioned processing in the management unit may be performed using, for example, AI, or may be performed without using AI. For example, the management unit can input the acquired health information into AI, and the AI ​​can analyze the data to evaluate the health state. Furthermore, the management unit can use AI to detect abnormal values. Furthermore, the management unit can use AI to provide health advice.

[0077] The dialogue unit can have daily conversations with the user and record the contents of the conversations. The dialogue unit, for example, performs voice dialogue. The dialogue unit uses voice recognition technology to save the contents of the user's conversation as text data. The dialogue unit can also perform text dialogue. In the case of text dialogue, the text input by the user is saved as is. Furthermore, the dialogue unit can also acquire the user's thoughts, catchphrases, values, messages, and the like. For example, the dialogue unit analyzes the contents of the user's conversation, extracts and saves specific keywords and phrases. This allows the dialogue unit to record daily conversations with the user. A part or all of the above-mentioned processing in the dialogue unit may be performed, for example, using AI, or may be performed without using AI. For example, the dialogue unit can input data acquired using voice recognition technology to AI, and the AI ​​can analyze the data to extract specific keywords and phrases. Furthermore, the dialogue unit can input data of the text dialogue to AI, and the AI ​​can analyze the data to extract the user's values ​​and messages.

[0078] The reproduction unit can reproduce the user using the generation AI based on the information recorded in the dialogue unit. The reproduction unit reproduces, for example, the user's voice. The reproduction unit reproduces the user's tone of voice and speaking style using the generation AI. The reproduction unit can also reproduce the user's actions. The reproduction unit reproduces the user's unique gestures and movements using the generation AI. Furthermore, the reproduction unit can also reproduce the user's facial expressions. The reproduction unit reproduces the user's smile, surprised facial expression, and the like using the generation AI. This allows the reproduction unit to reproduce the user using the generation AI. A part or all of the above-mentioned processing in the reproduction unit may be performed using, for example, the generation AI, or may be performed without using the generation AI. For example, the reproduction unit can input the voice data recorded in the dialogue unit to the generation AI, and the generation AI can reproduce the voice. Also, the reproduction unit can input the action data recorded in the dialogue unit to the generation AI, and the generation AI can reproduce the action. Furthermore, the reproduction unit can input the facial expression data recorded in the dialogue unit to the generation AI, and the generation AI can reproduce the facial expression.

[0079] The acquisition unit can estimate the user's emotion and adjust the timing of acquiring the health information based on the estimated emotion of the user. For example, when the user is feeling stressed, the acquisition unit adjusts the timing of acquiring the health information so that the health information is acquired during a time period when the user is relaxed. Furthermore, the acquisition unit can also set the timing of acquiring the health information so that the health information is acquired during a regular time period when the user is relaxed. Furthermore, when the user is in a hurry, the acquisition unit can also adjust the timing of acquiring the health information so that the health information is acquired in a short time. This allows the acquisition unit to adjust the timing of acquiring the health information based on the user's emotion. The estimation of the emotion is realized using an emotion estimation function using, for example, an emotion engine or a generation AI. The generation AI is, for example, a text generation AI (for example, LLM) or a multimodal generation AI, but is not limited to such examples. A part or all of the above-mentioned processing in the acquisition unit may be performed using, for example, an AI, or may be performed without using an AI. For example, the acquisition unit can input the user's facial expression data to the generation AI, and the generation AI can estimate the emotion. Furthermore, the acquisition unit can input the user's voice data to the generation AI, and the generation AI can estimate the emotion. Furthermore, the acquisition unit inputs the user's biometric data into the generation AI, allowing the generation AI to estimate emotions.

[0080] The acquisition unit can analyze the user's past health data and select the optimal acquisition method. The acquisition unit can, for example, analyze the user's past blood pressure data and acquire health information during the most stable time period. The acquisition unit can also be set to avoid acquiring data after exercise based on the user's past heart rate data. Furthermore, the acquisition unit can prioritize acquiring data after meals by referring to the user's past calorie data. This allows the acquisition unit to analyze the user's past health data and select the optimal acquisition method. A part or all of the above-mentioned processing in the acquisition unit may be performed using AI, for example, or may be performed without using AI. For example, the acquisition unit can input past health data into AI, and the AI ​​can analyze the data and select the optimal acquisition method. Furthermore, the acquisition unit can adjust the acquisition timing based on the past data. Furthermore, the acquisition unit can customize the acquisition method based on the past data.

[0081] The acquisition unit can filter the health information based on the user's current living situation and activity level when acquiring the health information. For example, when the user is exercising, the acquisition unit adjusts the acquisition so that the health information is acquired after the exercise. Also, when the user is resting, the acquisition unit can acquire the health information in a relaxed state. Furthermore, when the user is working, the acquisition unit can be set to acquire the health information in between work. This allows the acquisition unit to filter the health information based on the user's living situation and activity level. A part or all of the above-mentioned processing in the acquisition unit may be performed using, for example, AI, or may be performed without using AI. For example, the acquisition unit can input the user's activity data to the AI, and the AI ​​can analyze the data and adjust the acquisition timing. Also, the acquisition unit can input the user's living situation data to the AI, and the AI ​​can analyze the data and customize the acquisition method. Furthermore, the acquisition unit can input the user's activity level data to the AI, and the AI ​​can analyze the data and optimize the acquisition method.

[0082] The acquisition unit can estimate the user's emotion and determine the priority of the health information to be acquired based on the estimated user's emotion. For example, when the user is feeling stressed, the acquisition unit prioritizes the acquisition of the heart rate. Furthermore, when the user is relaxed, the acquisition unit can also prioritize the acquisition of blood pressure. Furthermore, when the user is tired, the acquisition unit can also prioritize the acquisition of calorie information. This allows the acquisition unit to determine the priority of the health information based on the user's emotion. The estimation of the emotion is realized using an emotion estimation function using, for example, an emotion engine or a generation AI. The generation AI is a text generation AI (for example, LLM) or a multimodal generation AI, but is not limited to such examples. A part or all of the above-mentioned processing in the acquisition unit may be performed using, for example, an AI, or may be performed without using an AI. For example, the acquisition unit inputs the user's facial expression data to the generation AI, and the generation AI can estimate the emotion. Furthermore, the acquisition unit inputs the user's voice data to the generation AI, and the generation AI can estimate the emotion. Furthermore, the acquisition unit inputs the user's biometric data to the generation AI, and the generation AI can estimate the emotion.

[0083] When acquiring health information, the acquisition unit can prioritize acquiring highly relevant information in consideration of the geographical location information of the user. For example, when the user is at high altitude, the acquisition unit prioritizes acquisition of oxygen concentration. In addition, when the user is in an urban area, the acquisition unit can also acquire information on air quality. Furthermore, when the user is outdoors, the acquisition unit can also acquire information on the amount of ultraviolet rays. This allows the acquisition unit to acquire health information in consideration of the geographical location information of the user. A part or all of the above-mentioned processing in the acquisition unit may be performed using AI, for example, or may be performed without using AI. For example, the acquisition unit can input the user's location data to AI, and the AI ​​can analyze the data and select highly relevant information. In addition, the acquisition unit can customize the acquisition method by AI based on the location information. Furthermore, the acquisition unit can adjust the acquisition timing by AI based on the location information.

[0084] The acquisition unit can analyze the user's social media activity and acquire related health information when acquiring health information. For example, when the user posts on social media that he / she feels stressed, the acquisition unit prioritizes acquisition of the heart rate. In addition, when the user posts on exercise, the acquisition unit can also acquire health information after exercise. Furthermore, when the user posts on meals, the acquisition unit can also acquire calorie information after meals. This allows the acquisition unit to analyze the user's social media activity and acquire health information. A part or all of the above-mentioned processing in the acquisition unit may be performed using AI, for example, or may be performed without using AI. For example, the acquisition unit can input social media data into AI, and the AI ​​can analyze the data and select related health information. In addition, the acquisition unit can customize the acquisition method by AI based on social media activity data. Furthermore, the acquisition unit can adjust the acquisition timing by AI based on social media data.

[0085] The management unit can estimate the user's emotions and adjust the health management method based on the estimated user's emotions. For example, if the user is feeling stressed, the management unit can suggest an exercise to relax. Also, if the user is relaxed, the management unit can also suggest a regular health check. Furthermore, if the user is in a hurry, the management unit can also suggest a health management method that can be performed in a short time. This allows the management unit to adjust the health management method based on the user's emotions. Estimation of emotions is realized using an emotion estimation function using, for example, an emotion engine or a generation AI. The generation AI is a text generation AI (for example, LLM) or a multimodal generation AI, but is not limited to such examples. A part or all of the above-mentioned processing in the management unit may be performed using, for example, an AI, or may be performed without using an AI. For example, the management unit can input the user's facial expression data to the generation AI, and the generation AI can estimate the emotions. Also, the management unit can input the user's voice data to the generation AI, and the generation AI can estimate the emotions. Furthermore, the management unit can input the user's biometric data to the generation AI, and the generation AI can estimate the emotions.

[0086] The management unit can select an appropriate management method by referring to the user's past health data during health management. The management unit, for example, proposes an optimal exercise plan based on the user's past blood pressure data. The management unit can also propose a method for relaxing by referring to the user's past heart rate data. The management unit can also propose a method of diet management based on the user's past calorie data. This allows the management unit to select an optimal management method by referring to the user's past health data. Some or all of the above-mentioned processing in the management unit may be performed using AI, for example, or may be performed without using AI. For example, the management unit can input past health data into AI, and the AI ​​can analyze the data and select an optimal management method. The management unit can also customize the management method by AI based on past data. Furthermore, the management unit can adjust the management timing by AI based on past data.

[0087] The management unit can customize the management means based on the user's current living situation during health management. For example, when the user is at work, the management unit suggests a stretch that can be done in a short time. In addition, when the user is resting, the management unit can also suggest a breathing technique for relaxation. Furthermore, when the user is exercising, the management unit can also suggest an appropriate method of hydration. This allows the management unit to customize the health management means based on the user's current living situation. A part or all of the above-mentioned processing in the management unit may be performed using AI, for example, or may be performed without using AI. For example, the management unit can input the user's living situation data into AI, and the AI ​​can analyze the data to customize the management means. In addition, the management unit can adjust the management method by AI based on the user's activity data. Furthermore, the management unit can adjust the management timing by AI based on the user's living situation data.

[0088] The management unit can estimate the user's emotions and determine the priority of health management based on the estimated user's emotions. For example, when the user is feeling stressed, the management unit prioritizes a method for relaxing. Furthermore, when the user is relaxed, the management unit can also prioritize regular health checks. Furthermore, when the user is in a hurry, the management unit can also prioritize a health management method that can be performed in a short time. This allows the management unit to determine the priority of health management based on the user's emotions. The estimation of emotions is realized using an emotion estimation function using, for example, an emotion engine or a generation AI. The generation AI is a text generation AI (for example, LLM) or a multimodal generation AI, but is not limited to such examples. A part or all of the above-mentioned processing in the management unit may be performed using, for example, an AI, or may be performed without using an AI. For example, the management unit can input the user's facial expression data to the generation AI, and the generation AI can estimate the emotions. Furthermore, the management unit can input the user's voice data to the generation AI, and the generation AI can estimate the emotions. Furthermore, the management unit can input the user's biometric data to the generation AI, and the generation AI can estimate the emotions.

[0089] The management unit can select an appropriate management method in consideration of the geographical location information of the user during health management. For example, when the user is at high altitude, the management unit prioritizes management of oxygen concentration. In addition, when the user is in an urban area, the management unit can also prioritize management of air quality. Furthermore, when the user is outdoors, the management unit can also prioritize ultraviolet ray protection. This allows the management unit to select a health management method in consideration of the geographical location information of the user. A part or all of the above-mentioned processing in the management unit may be performed using AI, for example, or may be performed without using AI. For example, the management unit can input the user's location data into AI, and the AI ​​can analyze the data and select highly relevant information. In addition, the management unit can customize the management method by AI based on the location information. Furthermore, the management unit can adjust the management timing by AI based on the location information.

[0090] The management unit can analyze the user's social media activity and suggest management measures during health management. For example, if the user posts on social media that he or she is feeling stressed, the management unit can suggest a way to relax. In addition, if the user posts on exercise, the management unit can also suggest an appropriate exercise plan. Furthermore, if the user posts on diet, the management unit can also suggest a balanced diet plan. This allows the management unit to analyze the user's social media activity and suggest health management measures. Some or all of the above-mentioned processing in the management unit may be performed using AI, for example, or may be performed without using AI. For example, the management unit can input social media data into AI, and the AI ​​can analyze the data and select related health information. In addition, the management unit can customize the management method by AI based on social media activity data. Furthermore, the management unit can adjust the management timing by AI based on social media data.

[0091] The dialogue unit can estimate the user's emotion and adjust the way of expressing the dialogue based on the estimated emotion of the user. For example, when the user is stressed, the dialogue unit can conduct the dialogue in a calm tone. Furthermore, when the user is relaxed, the dialogue unit can also conduct the dialogue in a bright tone. Furthermore, when the user is in a hurry, the dialogue unit can conduct a concise and quick dialogue. This allows the dialogue unit to adjust the way of expressing the dialogue based on the user's emotion. The estimation of the emotion is realized using an emotion estimation function using, for example, an emotion engine or a generation AI. The generation AI is a text generation AI (for example, LLM) or a multimodal generation AI, but is not limited to such examples. A part or all of the above-mentioned processing in the dialogue unit may be performed using, for example, an AI, or may be performed without using an AI. For example, the dialogue unit can input the user's facial expression data to the generation AI, and the generation AI can estimate the emotion. Furthermore, the dialogue unit can input the user's voice data to the generation AI, and the generation AI can estimate the emotion. Furthermore, the dialogue unit can input the user's biometric data to the generation AI, and the generation AI can estimate the emotion.

[0092] The dialogue unit can select an appropriate dialogue method by referring to the user's past dialogue history during dialogue. The dialogue unit selects the optimal dialogue method based on, for example, a dialogue style that the user has preferred in the past. The dialogue unit can also prioritize a specific topic from the user's past dialogue history. The dialogue unit can also analyze the user's past dialogue history and select the most effective dialogue method. This allows the dialogue unit to select the optimal dialogue method by referring to the user's past dialogue history. A part or all of the above-mentioned processing in the dialogue unit may be performed using, for example, an AI, or may be performed without using an AI. For example, the dialogue unit can input the past dialogue history into an AI, and the AI ​​can analyze the data and select the optimal dialogue method. The dialogue unit can also customize the dialogue method by the AI ​​based on past data. Furthermore, the dialogue unit can adjust the dialogue timing by the AI ​​based on past data.

[0093] The dialogue unit can customize the dialogue content based on the user's current mood and situation during the dialogue. For example, when the user is sad, the dialogue unit can conduct a dialogue with comforting content. Furthermore, when the user is happy, the dialogue unit can conduct a dialogue with empathy content. Furthermore, when the user is tired, the dialogue unit can conduct a dialogue with relaxing content. This allows the dialogue unit to customize the dialogue content based on the user's current mood and situation. A part or all of the above-mentioned processing in the dialogue unit may be performed using, for example, AI, or may be performed without using AI. For example, the dialogue unit can input the user's mood data into the AI, and the AI ​​can analyze the data to customize the dialogue content. Furthermore, the dialogue unit can adjust the dialogue method based on the user's situation data. Furthermore, the dialogue unit can adjust the dialogue timing based on the user's mood data.

[0094] The dialogue unit can estimate the user's emotions and determine the priority of the dialogue based on the estimated user's emotions. For example, when the user is feeling stressed, the dialogue unit prioritizes a dialogue for relaxing. Furthermore, when the user is relaxed, the dialogue unit can also prioritize a daily dialogue. Furthermore, when the user is in a hurry, the dialogue unit can also prioritize a quick dialogue. This allows the dialogue unit to determine the priority of the dialogue based on the user's emotions. The estimation of emotions is realized using an emotion estimation function using, for example, an emotion engine or a generation AI. The generation AI is a text generation AI (for example, LLM) or a multimodal generation AI, but is not limited to such examples. A part or all of the above-mentioned processing in the dialogue unit may be performed using, for example, an AI, or may be performed without using an AI. For example, the dialogue unit can input the user's facial expression data to the generation AI, and the generation AI can estimate the emotions. Furthermore, the dialogue unit can input the user's voice data to the generation AI, and the generation AI can estimate the emotions. Furthermore, the dialogue unit can input the user's biometric data to the generation AI, and the generation AI can estimate the emotions.

[0095] The dialogue unit can select appropriate dialogue content in consideration of the geographical location information of the user during dialogue. For example, when the user is traveling, the dialogue unit performs dialogue to provide information about the travel destination. Furthermore, when the user is at home, the dialogue unit can also perform dialogue for relaxation. Furthermore, when the user is at work, the dialogue unit can also perform work-related dialogue. This allows the dialogue unit to select dialogue content in consideration of the geographical location information of the user. A part or all of the above-mentioned processing in the dialogue unit may be performed using, for example, an AI, or may be performed without using an AI. For example, the dialogue unit can input the user's location data into the AI, and the AI ​​can analyze the data and select highly relevant dialogue content. Furthermore, the dialogue unit can customize the dialogue method by the AI ​​based on the location information. Furthermore, the dialogue unit can adjust the dialogue timing by the AI ​​based on the location information.

[0096] The dialogue unit can analyze the user's social media activity and suggest dialogue content at the time of dialogue. For example, if the user posts on social media that he or she is feeling stressed, the dialogue unit can suggest a dialogue for relaxing. In addition, if the user posts on exercise, the dialogue unit can also suggest a dialogue related to exercise. In addition, if the user posts on food, the dialogue unit can also suggest a dialogue related to food. This allows the dialogue unit to analyze the user's social media activity and suggest dialogue content. A part or all of the above-mentioned processing in the dialogue unit may be performed, for example, using AI, or may be performed without using AI. For example, the dialogue unit can input social media data into the AI, and the AI ​​can analyze the data and select related dialogue content. In addition, the dialogue unit can customize the dialogue method based on the social media activity data. In addition, the dialogue unit can adjust the dialogue timing based on the social media data.

[0097] The reproduction unit can estimate the user's emotion and adjust the method of reproduction based on the estimated user's emotion. For example, when the user is relaxed, the reproduction unit performs reproduction in a calm tone. Also, when the user is excited, the reproduction unit can perform reproduction in a lively tone. Furthermore, when the user is sad, the reproduction unit can perform reproduction in a comforting tone. This allows the reproduction unit to adjust the method of reproduction based on the user's emotion. The estimation of emotion is realized using an emotion estimation function using, for example, an emotion engine or a generation AI. The generation AI is a text generation AI (for example, LLM) or a multimodal generation AI, but is not limited to such examples. A part or all of the above-mentioned processing in the reproduction unit may be performed using, for example, the generation AI, or may be performed without using the generation AI. For example, the reproduction unit inputs the user's facial expression data to the generation AI, and the generation AI can estimate the emotion. Also, the reproduction unit inputs the user's voice data to the generation AI, and the generation AI can estimate the emotion. Furthermore, the reproduction unit inputs the user's biometric data to the generation AI, and the generation AI can estimate the emotion.

[0098] The reproduction unit can select an appropriate reproduction method by referring to the user's past dialogue history at the time of reproduction. The reproduction unit selects the optimal reproduction method based on, for example, a dialogue style that the user has preferred in the past. The reproduction unit can also prioritize reproduction of a specific topic from the user's past dialogue history. Furthermore, the reproduction unit can analyze the user's past dialogue history and select the most effective reproduction method. This allows the reproduction unit to select the optimal reproduction method by referring to the user's past dialogue history. A part or all of the above-mentioned processing in the reproduction unit may be performed, for example, using the generation AI, or may be performed without using the generation AI. For example, the reproduction unit can input the past dialogue history into the generation AI, and the generation AI can analyze the data and select the optimal reproduction method. Furthermore, the reproduction unit can customize the reproduction method by the generation AI based on the past data. Furthermore, the reproduction unit can adjust the reproduction timing by the generation AI based on the past data.

[0099] The reproduction unit can customize the reproduction content based on the user's current feelings and situation at the time of reproduction. For example, if the user is sad, the reproduction unit reproduces comforting content. Also, if the user is happy, the reproduction unit can reproduce empathetic content. Furthermore, if the user is tired, the reproduction unit can reproduce relaxing content. This allows the reproduction unit to customize the reproduction content based on the user's current feelings and situation. A part or all of the above-mentioned processing in the reproduction unit may be performed using, for example, a generation AI, or may be performed without using a generation AI. For example, the reproduction unit can input the user's feelings data into the generation AI, and the generation AI can analyze the data to customize the reproduction content. Also, the reproduction unit can adjust the reproduction method based on the user's situation data. Furthermore, the reproduction unit can adjust the reproduction timing based on the user's feelings data.

[0100] The reproduction unit can estimate the user's emotion and determine the priority of reproduction based on the estimated user's emotion. For example, when the user is stressed, the reproduction unit prioritizes reproduction for relaxation. Also, when the user is relaxed, the reproduction unit can also prioritize daily reproduction. Furthermore, when the user is in a hurry, the reproduction unit can also prioritize quick reproduction. This allows the reproduction unit to determine the priority of reproduction based on the user's emotion. The estimation of emotion is realized using an emotion estimation function using, for example, an emotion engine or a generation AI. The generation AI is a text generation AI (for example, LLM) or a multimodal generation AI, but is not limited to such examples. A part or all of the above-mentioned processing in the reproduction unit may be performed using, for example, the generation AI, or may be performed without using the generation AI. For example, the reproduction unit inputs the user's facial expression data to the generation AI, and the generation AI can estimate the emotion. Also, the reproduction unit inputs the user's voice data to the generation AI, and the generation AI can estimate the emotion. Furthermore, the reproduction unit inputs the user's biometric data to the generation AI, and the generation AI can estimate the emotion.

[0101] The reproduction unit can select an appropriate reproduction method in consideration of the geographical location information of the user at the time of reproduction. For example, when the user is traveling, the reproduction unit performs reproduction that provides information about the travel destination. Furthermore, when the user is at home, the reproduction unit can also perform reproduction for relaxation. Furthermore, when the user is at work, the reproduction unit can also perform work-related reproduction. This allows the reproduction unit to select a reproduction method in consideration of the geographical location information of the user. A part or all of the above-mentioned processing in the reproduction unit may be performed using, for example, the generation AI, or may be performed without using the generation AI. For example, the reproduction unit can input the user's location data to the generation AI, and the generation AI can analyze the data and select a highly relevant reproduction method. Furthermore, the reproduction unit can customize the reproduction method by the generation AI based on the location information. Furthermore, the reproduction unit can adjust the reproduction timing by the generation AI based on the location information.

[0102] The reproducing unit can analyze the user's social media activity and suggest the reproduction content at the time of reproduction. For example, if the user posts on social media that he / she feels stressed, the reproducing unit can suggest a reproducing for relaxing. In addition, if the user posts on exercise, the reproducing unit can also suggest a reproducing related to exercise. Furthermore, if the user posts on food, the reproducing unit can also suggest a reproducing related to food. In this way, the reproducing unit can analyze the user's social media activity and suggest the reproduction content. A part or all of the above-mentioned processing in the reproducing unit may be performed, for example, using the generating AI, or may be performed without using the generating AI. For example, the reproducing unit can input social media data to the generating AI, and the generating AI can analyze the data and select the relevant reproduction content. In addition, the reproducing unit can customize the reproduction method by the generating AI based on the social media activity data. Furthermore, the reproducing unit can adjust the timing of reproduction by the generating AI based on the social media data.

[0103] The care robot can estimate the user's emotion and adjust the action of the care robot based on the estimated emotion of the user. For example, when the user is stressed, the care robot performs an action to relax. Also, when the user is relaxed, the care robot can perform a playful action. Furthermore, when the user is in a hurry, the care robot can perform a quick action. This allows the care robot to adjust the action based on the user's emotion. The emotion estimation is realized using an emotion estimation function, for example, using an emotion engine or a generation AI. The generation AI is a text generation AI (for example, LLM) or a multimodal generation AI, but is not limited to such examples. A part or all of the above-mentioned processing in the care robot may be performed using, for example, an AI, or may be performed without using an AI. For example, the care robot can input the user's facial expression data to the generation AI, and the generation AI can estimate the emotion. Also, the care robot can input the user's voice data to the generation AI, and the generation AI can estimate the emotion. Furthermore, the care robot can input the user's biometric data to the generation AI, and the generation AI can estimate the emotion.

[0104] The care robot can select an appropriate operation method by referring to the user's past health data when operating. The care robot can suggest an operation for relaxing based on the user's past blood pressure data, for example. The care robot can also suggest an appropriate exercise by referring to the user's past heart rate data. Furthermore, the care robot can also suggest a balanced meal based on the user's past calorie data. This allows the care robot to select an optimal operation method by referring to the user's past health data. A part or all of the above-mentioned processing in the care robot may be performed using, for example, an AI, or may be performed without using an AI. For example, the care robot can input past health data into an AI, and the AI ​​can analyze the data and select an optimal operation method. Furthermore, the care robot can customize the operation method by the AI ​​based on the past data. Furthermore, the care robot can adjust the operation timing by the AI ​​based on the past data.

[0105] The care robot can customize the operating means based on the user's current living situation when operating. For example, when the user is at work, the care robot can suggest a stretching exercise that can be performed in a short time. Furthermore, when the user is resting, the care robot can also suggest a breathing technique for relaxation. Furthermore, when the user is exercising, the care robot can also suggest an appropriate method of hydration. This allows the care robot to customize the operating means based on the user's current living situation. A part or all of the above-mentioned processing in the care robot may be performed using, for example, an AI, or may be performed without using an AI. For example, the care robot can input the user's living situation data into the AI, and the AI ​​can analyze the data to customize the operating means. Furthermore, the care robot can adjust the operating method based on the user's activity data. Furthermore, the care robot can adjust the operating timing based on the user's living situation data.

[0106] The care robot can estimate the user's emotion and determine the priority order of the care robot's actions based on the estimated emotion of the user. For example, if the user is feeling stressed, the care robot prioritizes actions for relaxing. Also, if the user is relaxed, the care robot can prioritize playful actions. Furthermore, if the user is in a hurry, the care robot can prioritize quick actions. This allows the care robot to determine the priority order of actions based on the user's emotion. The emotion estimation is realized using an emotion estimation function using, for example, an emotion engine or a generation AI. The generation AI is a text generation AI (for example, LLM) or a multimodal generation AI, but is not limited to such examples. A part or all of the above-mentioned processing in the care robot may be performed using, for example, an AI, or may be performed without using an AI. For example, the care robot can input the user's facial expression data to the generation AI, and the generation AI can estimate the emotion. Also, the care robot can input the user's voice data to the generation AI, and the generation AI can estimate the emotion. Furthermore, the care robot can input the user's biometric data to the generation AI, and the generation AI can estimate the emotion.

[0107] The care robot can select an appropriate operation method in consideration of the geographical location information of the user when operating. For example, when the user is at high altitude, the care robot prioritizes management of oxygen concentration. In addition, when the user is in an urban area, the care robot can also prioritize management of air quality. Furthermore, when the user is outdoors, the care robot can also prioritize ultraviolet protection. This allows the care robot to select an operation method in consideration of the geographical location information of the user. A part or all of the above-mentioned processing in the care robot may be performed, for example, using AI, or may be performed without using AI. For example, the care robot can input the user's location data into the AI, and the AI ​​can analyze the data and select a highly relevant operation method. In addition, the care robot can customize the operation method by the AI ​​based on the location information. Furthermore, the care robot can adjust the operation timing by the AI ​​based on the location information.

[0108] The care robot can analyze the social media activity of the user and suggest a motion means when operating. For example, when the user posts on social media that he / she feels stressed, the care robot can suggest a way to relax. In addition, when the user posts on exercise, the care robot can also suggest an appropriate exercise plan. Furthermore, when the user posts on diet, the care robot can also suggest a balanced diet plan. This allows the care robot to analyze the social media activity of the user and suggest a motion means. A part or all of the above-mentioned processing in the care robot may be performed using, for example, an AI, or may be performed without using an AI. For example, the care robot can input social media data into an AI, and the AI ​​can analyze the data and select a related motion means. In addition, the care robot can customize the motion method based on the social media activity data. Furthermore, the care robot can adjust the motion timing based on the social media data.

[0109] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0110] The system includes an acquisition unit that acquires the user's health information, a management unit that manages health based on the health information, a dialogue unit that dialogues with the user, and a reproduction unit that reproduces the user using a generative AI. Furthermore, the system can also include an emotion management unit that estimates the user's emotions and adjusts the health management method based on the estimated emotions. For example, the emotion management unit can suggest exercises to relax the user when the user is feeling stressed. Also, when the user is relaxed, it can suggest regular health checks. Furthermore, when the user is in a hurry, it can suggest a health management method that can be done in a short time. This allows the system to adjust the health management method based on the user's emotions.

[0111] The system includes an acquisition unit, a management unit, a dialogue unit, and a reproduction unit. The system may further include a data analysis unit that analyzes the user's past health data and selects the optimal acquisition method. For example, the data analysis unit analyzes the user's past blood pressure data and acquires health information during the most stable time period. Also, based on the user's past heart rate data, it may be set to avoid acquiring data after exercise. Furthermore, based on the user's past calorie data, it may be possible to prioritize acquiring data after meals. This allows the system to analyze the user's past health data and select the optimal acquisition method.

[0112] The system includes an acquisition unit, a management unit, a dialogue unit, and a reproduction unit. The system may further include a life situation analysis unit that adjusts the timing of acquiring health information based on the user's current life situation and activity level. For example, the life situation analysis unit adjusts the timing of acquiring health information to be acquired after exercise when the user is exercising. Also, when the user is resting, the health information can be acquired in a relaxed state. Furthermore, when the user is at work, the health information can be set to be acquired during breaks from work. This allows the system to filter health information based on the user's life situation and activity level.

[0113] The system includes an acquisition unit, a management unit, a dialogue unit, and a reproduction unit. The system may further include an emotion prioritization unit that estimates the user's emotion and determines the priority of health information to be acquired based on the estimated emotion. For example, the emotion prioritization unit may prioritize acquisition of heart rate when the user is stressed. Also, the emotion prioritization unit may prioritize acquisition of blood pressure when the user is relaxed. Furthermore, the emotion prioritization unit may prioritize acquisition of calorie information when the user is tired. This allows the system to determine the priority of health information based on the user's emotion.

[0114] The system includes an acquisition unit, a management unit, a dialogue unit, and a reproduction unit. The system may further include a location information analysis unit that prioritizes acquisition of highly relevant information in consideration of the geographical location information of the user. For example, the location information analysis unit prioritizes acquisition of oxygen concentration when the user is at high altitude. Also, when the user is in an urban area, it may acquire information on air quality. Furthermore, when the user is outdoors, it may acquire information on the amount of ultraviolet light. This allows the system to acquire health information in consideration of the geographical location information of the user.

[0115] The system includes an acquisition unit, a management unit, a dialogue unit, and a reproduction unit. The system may further include a social media analysis unit that analyzes the user's social media activity and acquires related health information. For example, the social media analysis unit prioritizes acquisition of the heart rate when the user posts on social media that he or she is feeling stressed. Also, when the user posts about exercise, the social media analysis unit may acquire health information after exercise. Furthermore, when the user posts about meals, calorie information after meals may be acquired. This allows the system to acquire health information by analyzing the user's social media activity.

[0116] The system includes an acquisition unit, a management unit, a dialogue unit, and a reproduction unit. The system may further include an emotion dialogue unit that estimates the user's emotion and adjusts the manner of expression of the dialogue based on the estimated emotion. For example, the emotion dialogue unit may perform the dialogue in a calm tone when the user is stressed, or in a bright tone when the user is relaxed. Furthermore, the emotion dialogue unit may perform a concise and quick dialogue when the user is in a hurry. This allows the system to adjust the manner of expression of the dialogue based on the user's emotion.

[0117] The system includes an acquisition unit, a management unit, a dialogue unit, and a reproduction unit. The system may further include a dialogue history analysis unit that refers to the user's past dialogue history to select an appropriate dialogue method. For example, the dialogue history analysis unit selects the optimal dialogue method based on the dialogue style that the user has preferred in the past. The system may also prioritize a specific topic from the user's past dialogue history. The system may further analyze the user's past dialogue history to select the most effective dialogue method. This allows the system to select the optimal dialogue method by referring to the user's past dialogue history.

[0118] The system includes an acquisition unit, a management unit, a dialogue unit, and a reproduction unit. The system may further include an emotion reproduction unit that estimates the emotion of the user and adjusts the reproduction method based on the estimated emotion. For example, the emotion reproduction unit may perform reproduction in a calm tone when the user is relaxed. Also, when the user is excited, the emotion reproduction unit may perform reproduction in a lively tone. Furthermore, when the user is sad, the emotion reproduction unit may perform reproduction in a comforting tone. This allows the system to adjust the reproduction method based on the emotion of the user.

[0119] The system includes an acquisition unit, a management unit, a dialogue unit, and a reproduction unit. The system may further include a location information reproduction unit that selects an appropriate reproduction method in consideration of the geographical location information of the user. For example, when the user is traveling, the location information reproduction unit performs reproduction that provides information about the travel destination. When the user is at home, the location information reproduction unit may perform reproduction for relaxation. When the user is at work, the location information reproduction unit may perform work-related reproduction. This allows the system to select a reproduction method in consideration of the geographical location information of the user.

[0120] The process flow of the second embodiment will be briefly described below.

[0121] Step 1: The acquisition unit acquires health information of the user. The health information of the user includes, for example, blood pressure, heart rate, calorie information, etc. The acquisition unit measures the user's blood pressure using a blood pressure meter, measures the user's heart rate using a heart rate meter, and acquires the user's calorie information using a calorie meter. These data are stored. Step 2: The management unit manages the user's health based on the health information acquired by the acquisition unit. The management unit monitors the health status, notifies the user of abnormal values, and provides health advice based on the health information. For example, if an abnormal value is detected in blood pressure or heart rate, the management unit notifies the user and provides appropriate diet and exercise advice based on calorie information. Step 3: The dialogue unit conducts daily conversations with the user and records the contents of those conversations. The dialogue unit conducts voice dialogues and text dialogues to obtain the user's thoughts, catchphrases, values, messages, etc. The content of the user's conversations is saved as text data using voice recognition technology, and in the case of text dialogues, the text entered by the user is saved as is. Step 4: The reproduction unit uses the generation AI to reproduce the user based on the information recorded by the dialogue unit. The reproduction unit reproduces the user's voice, actions, and facial expressions. For example, the generation AI can be used to reproduce the user's tone of voice and speaking style, reproduce actions including unique gestures and movements, and reproduce smiles, surprised expressions, etc.

[0122] 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 a voice indicating a user input for the result of the specific processing. The control unit 46A transmits the voice 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 voice data.

[0123] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search<URL: https: / / openai.com / blog / chatgpt> ) and other generation AIs. 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 a voice, text data indicating a text, and image data indicating an image (e.g., still image data or video data) are input. The data generation model 58 infers the input inference data according to the instruction indicated by the prompt, and outputs the inference result in one or more data formats of voice data, text data, and image data. The data generation model 58 includes, for example, a text generation AI, an image generation AI, and a multimodal generation AI. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specification processing unit 290 performs the above-mentioned specification processing while 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, and in this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. In the data processing device 12 and the like, the data generation model 58 includes a plurality of types, and the data generation model 58 includes an AI other than the generation AI. The AI ​​other than the generation AI is, for example, a linear regression, a logistic regression, a decision tree, a random forest, a support vector machine (SVM), a k-means clustering, a convolutional neural network (CNN), a recurrent neural network (RNN), a generative adversarial network (GAN), or a naive Bayes, and can perform various processes, but is not limited to such examples. The AI ​​may also be an AI agent. In addition, when the processes of each of the above-mentioned parts are performed by an AI, the processes are performed in part or in whole by the AI, but are not limited to such examples.In addition, processing performed by AI including the generation AI may be replaced with rule-based processing, and rule-based processing may be replaced with processing performed by AI including the generation AI.

[0124] Furthermore, the above-described processing by the data processing system 10 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 required for processing from the smart device 14 or an external device, and the smart device 14 acquires or collects information required for processing from the data processing device 12 or an external device.

[0125] For example, the acquisition unit can acquire health information of the user using the camera 42 or a sensor of the smart device 14. The management unit can perform health management based on the health information acquired by the specific processing unit 290 of the data processing device 12. The dialogue unit can use the control unit 46A of the smart device 14 to have daily conversations with the user and record the contents of the conversations. The reproduction unit can reproduce the user using a generation AI by the specific processing unit 290 of the data processing device 12. The correspondence between each unit and the device or control unit is not limited to the above-mentioned example, and various changes are possible.

[0126] [Second embodiment] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0127] 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.

[0128] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0129] The 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.

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

[0131] Camera 42 is a small digital camera equipped with an optical system including a lens, an aperture, and a 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 (e.g., an imaging range defined by an angle of view equivalent to the width of the field of vision of an average healthy person).

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

[0133] Fig. 4 shows an example of 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.

[0134] 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.

[0135] 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 emotion of the user using the emotion identification model 59 and perform identification processing using the user's emotion. In the emotion estimation function (emotion identification function) using the emotion identification model 59, various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, are performed, but are not limited to such examples. In addition, the estimation and prediction of the emotion also include, for example, analysis of the emotion.

[0136] In the smart glasses 214, the specific processing is performed by the processor 46. The storage 50 stores a specific processing program 60. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 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 have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can also perform processing similar to that of the specific processing unit 290 using these models.

[0137] 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 obtains a processing result (such as a prediction result) using the data generation model 58 by communicating with the server device having the data generation model 58. In addition, the data processing device 12 may be a server device, or may be a terminal device (such as a mobile phone, a robot, or a home appliance) owned by a user.

[0138] 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 a voice indicating a user input for the result of the specific processing. The control unit 46A transmits the 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.

[0139] 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. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating a voice, text data indicating a text, and image data indicating an image (e.g., still image data or video data) is input. The data generation model 58 infers the input inference data according to the instruction indicated by the prompt, and outputs the inference result in one or more data formats of voice data, text data, and image data. The data generation model 58 includes, for example, a text generation AI, an image generation AI, and a multimodal generation AI. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specification processing unit 290 performs the above-mentioned specification processing while 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, and in this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. In the data processing device 12 and the like, the data generation model 58 includes a plurality of types, and the data generation model 58 includes an AI other than the generation AI. The AI ​​other than the generation AI is, for example, a linear regression, a logistic regression, a decision tree, a random forest, a support vector machine (SVM), a k-means clustering, a convolutional neural network (CNN), a recurrent neural network (RNN), a generative adversarial network (GAN), or a naive Bayes, and can perform various processes, but is not limited to such examples. The AI ​​may be an AI agent. In addition, when the processes of each part described above are performed by an AI, the processes are performed in part or in whole by the AI, but are not limited to such examples. In addition, the processes performed by the AI ​​including the generation AI may be replaced with rule-based processes, and the rule-based processes may be replaced with processes performed by the AI ​​including the generation AI.

[0140] 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 be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart glasses 214. In addition, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the smart glasses 214 or an external device, and the smart glasses 214 acquires or collects information required for processing from the data processing device 12 or an external device.

[0141] For example, the acquisition unit can acquire health information of the user using the camera 42 or a sensor of the smart glasses 214. The management unit can perform health management based on the health information acquired by the specific processing unit 290 of the data processing device 12. The dialogue unit can use the control unit 46A of the smart glasses 214 to have daily conversations with the user and record the contents of the conversations. The reproduction unit can reproduce the user using a generation AI by the specific processing unit 290 of the data processing device 12. The correspondence between each unit and the device or control unit is not limited to the above-mentioned example, and various changes are possible.

[0142] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0143] 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.

[0144] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. 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.

[0145] 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.

[0146] 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 the voice according to instructions from the processor 46.

[0147] Camera 42 is a small digital camera equipped with an optical system including a lens, an aperture, and a 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 (e.g., an imaging range defined by an angle of view equivalent to the width of the field of vision of an average healthy person).

[0148] 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 performed in a secure state.

[0149] 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.

[0150] 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.

[0151] 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 emotion of the user using the emotion identification model 59 and perform identification processing using the user's emotion. In the emotion estimation function (emotion identification function) using the emotion identification model 59, various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, are performed, but are not limited to such examples. In addition, the estimation and prediction of the emotion also include, for example, analysis of the emotion.

[0152] In the headset type terminal 314, the specific processing is performed by the processor 46. The storage 50 stores a specific program 60. The processor 46 reads the specific program 60 from the storage 50, and executes the read specific program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific program 60 executed on the RAM 48. Note that the headset type terminal 314 has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can also perform processing similar to that of the identification processing unit 290 using these models.

[0153] 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 obtains a processing result (such as a prediction result) using the data generation model 58 by communicating with the server device having the data generation model 58. In addition, the data processing device 12 may be a server device, or may be a terminal device (such as a mobile phone, a robot, or a home appliance) owned by a user.

[0154] 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 voice indicating a user input for 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.

[0155] 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. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating a voice, text data indicating a text, and image data indicating an image (e.g., still image data or video data) is input. The data generation model 58 infers the input inference data according to the instruction indicated by the prompt, and outputs the inference result in one or more data formats of voice data, text data, and image data. The data generation model 58 includes, for example, a text generation AI, an image generation AI, and a multimodal generation AI. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specification processing unit 290 performs the above-mentioned specification processing while 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, and in this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. In the data processing device 12 and the like, the data generation model 58 includes a plurality of types, and the data generation model 58 includes an AI other than the generation AI. The AI ​​other than the generation AI is, for example, a linear regression, a logistic regression, a decision tree, a random forest, a support vector machine (SVM), a k-means clustering, a convolutional neural network (CNN), a recurrent neural network (RNN), a generative adversarial network (GAN), or a naive Bayes, and can perform various processes, but is not limited to such examples. The AI ​​may be an AI agent. In addition, when the processes of each part described above are performed by an AI, the processes are performed in part or in whole by the AI, but are not limited to such examples. In addition, the processes performed by the AI ​​including the generation AI may be replaced with rule-based processes, and the rule-based processes may be replaced with processes performed by the AI ​​including the generation AI.

[0156] 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 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. In addition, 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, and the headset type terminal 314 acquires or collects information required for processing from the data processing device 12 or an external device.

[0157] For example, the acquisition unit can acquire health information of the user using the camera 42 or a sensor of the headset type terminal 314. The management unit can perform health management based on the health information acquired by the specific processing unit 290 of the data processing device 12. The dialogue unit can have daily conversations with the user using the control unit 46A of the headset type terminal 314 and record the contents of those conversations. The reproduction unit can reproduce the user using a generation AI by the specific processing unit 290 of the data processing device 12. The correspondence between each unit and the device or control unit is not limited to the above-mentioned example, and various changes are possible.

[0158] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0159] 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.

[0160] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. 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.

[0161] 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.

[0162] 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 the voice according to instructions from the processor 46.

[0163] Camera 42 is a small digital camera equipped with an optical system including a lens, an aperture, and a shutter, and an imaging element such as a CMOS image sensor or a CCD image sensor, and captures images of the user's surroundings (e.g., an imaging range defined by an angle of view equivalent to the width of the field of vision of a typical healthy person).

[0164] 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 performed in a secure state.

[0165] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and legs. The posture and behavior of the robot 414 are controlled by controlling the motors of the arms, hands, and legs. 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.

[0166] 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.

[0167] 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.

[0168] 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 emotion of the user using the emotion identification model 59 and perform identification processing using the user's emotion. In the emotion estimation function (emotion identification function) using the emotion identification model 59, various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, are performed, but are not limited to such examples. In addition, the estimation and prediction of the emotion also include, for example, analysis of the emotion.

[0169] In the robot 414, the specific processing is performed by the processor 46. The storage 50 stores a specific program 60. The processor 46 reads out the specific program 60 from the storage 50, and executes the specific 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 program 60 executed on the RAM 48. The robot 414 has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can also perform processing similar to that of the specific processing unit 290 using these models.

[0170] 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 obtains a processing result (such as a prediction result) using the data generation model 58 by communicating with the server device having the data generation model 58. In addition, the data processing device 12 may be a server device, or may be a terminal device (such as a mobile phone, a robot, or a home appliance) owned by a user.

[0171] 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 a voice indicating a user input for 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.

[0172] 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. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating a voice, text data indicating a text, and image data indicating an image (e.g., still image data or video data) is input. The data generation model 58 infers the input inference data according to the instruction indicated by the prompt, and outputs the inference result in one or more data formats of voice data, text data, and image data. The data generation model 58 includes, for example, a text generation AI, an image generation AI, and a multimodal generation AI. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specification processing unit 290 performs the above-mentioned specification processing while 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, and in this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. In the data processing device 12 and the like, the data generation model 58 includes a plurality of types, and the data generation model 58 includes an AI other than the generation AI. The AI ​​other than the generation AI is, for example, a linear regression, a logistic regression, a decision tree, a random forest, a support vector machine (SVM), a k-means clustering, a convolutional neural network (CNN), a recurrent neural network (RNN), a generative adversarial network (GAN), or a naive Bayes, and can perform various processes, but is not limited to such examples. The AI ​​may be an AI agent. In addition, when the processes of each part described above are performed by an AI, the processes are performed in part or in whole by the AI, but are not limited to such examples. In addition, the processes performed by the AI ​​including the generation AI may be replaced with rule-based processes, and the rule-based processes may be replaced with processes performed by the AI ​​including the generation AI.

[0173] 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 be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the robot 414. In addition, the specific processing unit 290 of the data processing device 12 acquires or collects information 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.

[0174] For example, the acquisition unit can acquire health information of the user using the camera 42 or a sensor of the robot 414. The management unit can perform health management based on the health information acquired by the specific processing unit 290 of the data processing device 12. The dialogue unit can use the control unit 46A of the robot 414 to have daily conversations with the user and record the contents of those conversations. The reproduction unit can reproduce the user using a generation AI by the specific processing unit 290 of the data processing device 12. The correspondence between each unit and the device or control unit is not limited to the above-mentioned example, and various changes are possible.

[0175] The emotion identification model 59 as an emotion engine may determine the emotion of the user according to a specific mapping. Specifically, the emotion identification model 59 may determine the emotion of the user according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the emotion of the robot, and the identification processing unit 290 may perform identification processing using the emotion of the robot.

[0176] FIG. 9 is a diagram showing 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. The closer to the center of the concentric circles, the more primitive emotions are arranged. The more outside the concentric circles, the more emotions that represent states and actions that arise from a state of mind are arranged. Emotions are a concept that includes emotions and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions that occur in the brain are arranged. On the right side of the concentric circles, emotions that are generally induced by situational judgment are arranged. On the upper and lower sides of the concentric circles, emotions that are generally generated from reactions that occur in the brain and are induced by situational judgment are arranged. In addition, on the upper side of the concentric circles, emotions of "pleasure" are arranged, and on the lower side, emotions of "discomfort" are arranged. In this way, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[0177] These emotions are distributed in the 3 o'clock direction of emotion map 400 and usually 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.

[0178] The inside of emotion map 400 represents what is going on inside one's mind, and the outside of emotion map 400 represents behavior, so the further out you go on emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[0179] Here, human emotions are based on various balances such as posture and blood sugar level, and when these balances are far from the ideal, it indicates an unpleasant state, and when they are close to the ideal, it indicates a pleasant state. Emotions can also be created for robots, cars, motorcycles, etc., based on various balances such as posture and battery level, so that when these balances are far from the ideal, it indicates an unpleasant state, and when they are close to the ideal, it indicates a pleasant state. The emotion map may be generated, for example, based on the emotion map of Dr. Mitsuyoshi (Research on speech emotion recognition and emotion brain physiological signal analysis system, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). On the left half of the emotion map, emotions belonging to an area called "reaction" where sensation is dominant are lined up. On the right half of the emotion map, emotions belonging to an area called "situation" where situation recognition is dominant are lined up.

[0180] The emotion map defines two emotions that promote learning. The first is the negative emotion around the middle of "repentance" or "remorse" on the situation side. In other words, this is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the positive emotion around "desire" on the response side. In other words, this is when the robot has positive feelings such as "I want more" or "I want to know more."

[0181] The emotion identification model 59 inputs the user input to a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the emotion of the user. This neural network is pre-trained based on multiple learning data that are combinations of the 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, "relief," "calm," and "encouraging," have similar emotion values.

[0182] 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.

[0183] 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 Universal Serial Bus (USB) 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.

[0184] In addition, 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 upon request from the data processing device 12.

[0185] 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.

[0186] As the hardware resource for executing the specific process, various processors as shown below can be used. An example of the processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing the specific process by executing software, i.e., a program. Another example of the processor is a dedicated electric circuit, which is a processor having a circuit configuration designed exclusively for executing a specific process, such as a Field-Programmable Gate Array (FPGA), a Programmable Logic Device (PLD), or an Application Specific Integrated Circuit (ASIC). Each processor has a built-in or connected memory, and each processor executes the specific process by using the memory.

[0187] The hardware resource that executes the specific process may be one of these various processors, or may be 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.

[0188] As an example of a configuration using one 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 configuration using a processor that realizes the functions of the 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.

[0189] Furthermore, more specifically, the hardware structure of these various processors can be an electric circuit that combines circuit elements such as semiconductor elements. The specific processes described above are merely examples. It goes without saying that unnecessary steps may be deleted, new steps may be added, or the order of processes may be changed without departing from the spirit of the invention.

[0190] In the above example, the first to fourth embodiments are described separately, but some or all of these embodiments may be combined. The smart device 14, the smart glasses 214, the headset terminal 314, and the robot 414 are only examples, and they may be combined with each other, or may be other devices. In the above example, the first and second embodiments are described separately, but they may be combined.

[0191] The above description and illustrations are detailed descriptions 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, function, action, and effect is an example of the configuration, function, action, and effect 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 replaced with respect to the description and illustrations shown above, within the scope of the gist of the technology of the present disclosure. In addition, in order to avoid confusion and to facilitate understanding of the parts related to the technology of the present disclosure, the description and illustrations shown above omit explanations of technical common sense that do not require particular explanation in enabling the implementation of the technology of the present disclosure.

[0192] All publications, patent applications, and standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, and standard was specifically and individually indicated to be incorporated by reference.

[0193] (Appendix 1) An acquisition unit for acquiring health information of a user; a management unit that manages the health of the user based on the health information acquired by the acquisition unit; A dialogue unit that dialogues with the user; A reproduction unit that reproduces the user by a generation AI based on a dialogue with the user. A system characterized by: (Appendix 2) A care robot including the acquisition unit, the management unit, and the dialogue unit. 2. The system of claim 1, (Appendix 3) The acquisition unit is Obtaining health information including the user's blood pressure, heart rate, and calorie information 2. The system of claim 1, (Appendix 4) The management unit Manage user's health based on acquired health information 2. The system of claim 1, (Appendix 5) The dialogue unit includes: Conduct daily conversations with users and record those conversations 2. The system of claim 1, (Appendix 6) The reproducing portion comprises: Based on the information recorded by the dialogue section, the user is recreated using generative AI. 2. The system of claim 1, (Appendix 7) The acquisition unit is To estimate a user's emotion and adjust the timing of acquiring health information based on the estimated user's emotion. 2. The system of claim 1, (Appendix 8) The acquisition unit is Analyze the user's past health data and select the appropriate acquisition method 2. The system of claim 1, (Appendix 9) The acquisition unit is When acquiring health information, it will be filtered based on the user's current lifestyle and activity level. 2. The system of claim 1, (Appendix 10) The acquisition unit is A user's emotion is estimated, and a priority order of health information to be acquired is determined based on the estimated user's emotion. 2. The system of claim 1, (Appendix 11) The acquisition unit is When retrieving health information, the system prioritizes retrieving information that is more relevant to the user based on the user's geographic location. 2. The system of claim 1, (Appendix 12) The acquisition unit is When acquiring health information, the user's social media activity is analyzed to acquire relevant health information. 2. The system of claim 1, (Appendix 13) The management unit To estimate a user's emotion and adjust a health management method based on the estimated user's emotion. 2. The system of claim 1, (Appendix 14) The management unit When managing health, the system selects an appropriate management method by referring to the user's past health data. 2. The system of claim 1, (Appendix 15) The management unit Customize health management based on the user's current living situation 2. The system of claim 1, (Appendix 16) The management unit To estimate a user's emotion and determine a priority of health management based on the estimated user's emotion. 2. The system of claim 1, (Appendix 17) The management unit When managing health, select an appropriate management method taking into account the user's geographic location information. 2. The system of claim 1, (Appendix 18) The management unit Analyzing users' social media activity and suggesting management measures when managing their health 2. The system of claim 1, (Appendix 19) The dialogue unit includes: Estimate the user's emotions and adjust the way the dialogue is expressed based on the estimated user's emotions. 2. The system of claim 1, (Appendix 20) The dialogue unit includes: When interacting with a user, the system selects the appropriate interaction method by referring to the user's past interaction history. 2. The system of claim 1, (Appendix 21) The dialogue unit includes: During a conversation, customize the conversation based on the user's current mood or situation 2. The system of claim 1, (Appendix 22) The dialogue unit includes: Estimate user emotions and prioritize interactions based on the estimated user emotions 2. The system of claim 1, (Appendix 23) The dialogue unit includes: During dialogue, appropriate dialogue content is selected taking into account the user's geographic location information. 2. The system of claim 1, (Appendix 24) The dialogue unit includes: During a conversation, the system analyzes the user's social media activity to suggest conversation content. 2. The system of claim 1, (Appendix 25) The reproducing portion comprises: Estimate the user's emotions and adjust the reproduction method based on the estimated user's emotions. 2. The system of claim 1, (Appendix 26) The reproducing portion comprises: When reproducing, the appropriate reproduction method is selected by referring to the user's past interaction history. 2. The system of claim 1, (Appendix 27) The reproducing portion comprises: During replay, customize the replay based on the user's current mood or situation 2. The system of claim 1, (Appendix 28) The reproducing portion comprises: Estimate the user's emotions and determine the priority of reproduction based on the estimated user's emotions. 2. The system of claim 1, (Appendix 29) The reproducing portion comprises: When reproducing, the appropriate reproduction method is selected taking into account the user's geographic location information. 2. The system of claim 1, (Appendix 30) The reproducing portion comprises: When reenacting, the system analyzes users' social media activity to suggest reenactment content. 2. The system of claim 1, (Appendix 31) The care robot includes: Estimating the user's emotions and adjusting the behavior of the care robot based on the estimated user's emotions 3. The system of claim 2, (Appendix 32) The care robot includes: When operating, the system refers to the user's past health data to select the appropriate operating method. 3. The system of claim 2, (Appendix 33) The care robot includes: Customize the means of operation based on the user's current life situation at the time of operation 3. The system of claim 2, (Appendix 34) The care robot includes: Estimating the user's emotions and determining the priority of the care robot's actions based on the estimated user's emotions 3. The system of claim 2, (Appendix 35) The care robot includes: When operating, the appropriate operation method is selected taking into account the user's geographic location information. 3. The system of claim 2, (Appendix 36) The care robot includes: At the time of action, the app analyzes the user's social media activity to suggest action options. 3. The system of claim 2, [Explanation of symbols]

[0194] 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. An acquisition unit for acquiring health information of a user; a management unit that manages the health of the user based on the health information acquired by the acquisition unit; A dialogue unit that dialogues with the user; A reproduction unit that reproduces the user by a generation AI based on a dialogue with the user. A system characterized by:

2. A care robot including the acquisition unit, the management unit, and the dialogue unit.

2. The system of claim 1 .

3. The acquisition unit is Obtain health information of the user, including blood pressure, heart rate, and calorie information. The system of claim 1 .

4. The dialogue unit includes: Conducting daily conversations with said users and recording the contents of those conversations 2. The system of claim 1 .

5. The reproducing portion comprises: Based on the information recorded by the dialogue unit, the user is reproduced using a generation AI.

2. The system of claim 1 .

6. The acquisition unit is The feeling of the user is estimated, and a timing of acquiring health information is adjusted based on the estimated feeling of the user.

2. The system of claim 1 .

7. The acquisition unit is Analyzing the user's past health data and selecting an appropriate acquisition method 2. The system of claim 1 .

8. The acquisition unit is When acquiring health information, filtering is performed based on the user's current living situation and activity level.

2. The system of claim 1 .

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