System

Abstract

An object of a system according to an embodiment is to reduce a sense of loneliness of an elderly person and monitor a living situation.SOLUTION: A system includes an interaction unit, a monitoring unit, and a communication unit. The interaction unit performs a conversation with a target person. The monitoring unit monitors a living situation of the target person based on the conversation performed by the dialogue unit. The communication unit performs emergency communication on the basis of the living situation monitored by the monitoring unit.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] Conventional technologies do not adequately provide means to reduce loneliness among the elderly and monitor their living conditions, and there is room for improvement.

[0005] The system according to the embodiment aims to reduce the sense of loneliness felt by the elderly and to monitor their living conditions. [Means for solving the problem]

[0006] The system according to the embodiment includes a dialogue unit, a monitoring unit, and a communication unit. The dialogue unit engages in a conversation with a target person. The monitoring unit monitors the living situation of the target person based on the conversation held by the dialogue unit. The communication unit makes an emergency contact based on the living situation monitored by the monitoring unit. [Effects of the Invention]

[0007] The system according to the embodiment can reduce the sense of loneliness of the elderly and monitor their living conditions. [Brief explanation of the drawings]

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

[0028] (Example 1) An interactive AI system according to an embodiment of the present invention monitors the living conditions of a subject through conversations with the subject and responds promptly in emergencies. The system engages in conversations with the subject, and the AI ​​monitors the subject's living conditions and makes emergency contact as needed. This mechanism reduces the subject's sense of loneliness, prevents dementia, and provides support for daily living. For example, the interactive AI system periodically converses with the subject. The AI ​​listens to the subject and responds appropriately. For example, if the subject says, "The weather is nice today," the AI ​​responds, "Yes, it's sunny today." Next, the AI ​​monitors the subject's living conditions. For example, the AI ​​can determine the subject's health condition and mood from the subject's tone of voice and content of speech. This allows the AI ​​to detect if the subject is feeling unwell or lonely and take appropriate action. Furthermore, it makes emergency contact as needed. For example, if the subject complains of feeling unwell, the AI ​​can automatically contact family or medical institutions. This allows for prompt response in emergencies. This allows the interactive AI system to reduce the subject's sense of loneliness, prevent dementia, and provide support for daily living. For example, regular conversations can help maintain the mental health of the recipient. AI can also monitor their daily life to ensure their safety. Furthermore, an emergency contact function can provide a quick response when the recipient is in trouble.

[0029] An interactive AI system according to an embodiment includes a dialogue unit, a monitoring unit, and a communication unit. The dialogue unit engages in a conversation with a subject. For example, the dialogue unit listens to the subject and provides an appropriate response. The dialogue unit uses AI to analyze the subject's speech and generate an appropriate response. For example, if the subject says, "The weather is nice today," the dialogue unit responds with, "Yes, it's sunny today." The dialogue unit can also engage in regular conversations with the subject. For example, the dialogue unit engages in conversation with the subject at a fixed time every day. The monitoring unit monitors the subject's living situation based on the conversation conducted by the dialogue unit. For example, the monitoring unit analyzes the subject's tone of voice and content of speech to determine the subject's health condition and mood. The monitoring unit uses AI to analyze the subject's tone of voice and content of speech to determine the subject's health condition and mood. For example, the monitoring unit may suspect poor health if the subject's voice tone is low. The monitoring unit can also determine whether the subject is feeling lonely based on the content of the subject's speech. The communication unit makes emergency contact based on the living conditions monitored by the monitoring unit. For example, if the subject complains of feeling unwell, the communication unit automatically contacts family members or medical institutions. The communication unit uses AI to analyze the living conditions of the subject and determine the need for emergency contact. For example, if the subject says, "I'm feeling unwell," the communication unit contacts family members. The communication unit can also contact medical institutions if the subject's health condition worsens. This allows the interactive AI system according to the embodiment to reduce the subject's sense of loneliness, prevent dementia, and provide support for daily life. For example, the subject's mental health can be maintained through regular conversations. Furthermore, by having AI monitor the living conditions, the subject's safety can be ensured. Furthermore, the emergency contact function allows for quick response when the subject is in trouble.

[0030] The dialogue unit can listen to the subject's speech and provide an appropriate response. For example, the dialogue unit listens to the subject's speech and provides an appropriate response. The dialogue unit uses AI to analyze the subject's speech and generate an appropriate response. For example, if the subject says, "The weather is nice today," the dialogue unit responds with, "Yes, it's sunny today." The dialogue unit can also provide an appropriate response based on the content of the subject's speech. For example, if the subject says, "I'm tired today," the dialogue unit responds with, "Thank you for your hard work. Please get plenty of rest." The dialogue unit can also adjust the tone of the response based on the tone of the subject's speech. For example, if the subject speaks in a sad voice, the dialogue unit responds with a gentler tone. This enables a natural conversation with the subject. Some or all of the above-described processing in the dialogue unit may be performed using, for example, a generation AI (text generation AI or multimodal generation AI) or without a generation AI. For example, the dialogue unit can input the subject's speech into the generation AI, which can then generate an appropriate response.

[0031] The monitoring unit can analyze the subject's tone of voice and the content of their speech to determine their health condition and mood. For example, the monitoring unit analyzes the subject's tone of voice to determine their health condition and mood. The monitoring unit uses AI to analyze the subject's tone of voice to determine their health condition and mood. For example, if the subject's tone of voice is low, the monitoring unit may suspect poor health. The monitoring unit can also analyze the content of the subject's speech to determine their health condition and mood. For example, if the subject says, "I'm tired today," the monitoring unit may suspect poor health. The monitoring unit can also determine whether the subject is feeling lonely from the content of the subject's speech. For example, if the subject says, "I haven't talked to anyone," the monitoring unit may determine that the subject is feeling lonely. This allows the subject's health condition and mood to be accurately understood. Some or all of the above-described processing in the monitoring unit may be performed using, for example, a generative AI (text generation AI or multimodal generation AI) or without a generative AI. For example, the monitoring unit can input the subject's tone of voice and the content of their speech into the generation AI, which can then determine their health condition and mood.

[0032] The communication unit can automatically contact family members or medical institutions when the subject complains of feeling unwell. For example, when the subject complains of feeling unwell, the communication unit automatically contacts family members or medical institutions. The communication unit uses AI to analyze the subject's living situation and determine the need for emergency contact. For example, when the subject says, "I'm feeling unwell," the communication unit contacts family members. The communication unit can also contact medical institutions when the subject's health condition worsens. For example, the communication unit can determine whether the subject is feeling unwell based on the subject's tone of voice and the content of their speech and contact a medical institution. This enables rapid response in emergencies. Some or all of the above-mentioned processing in the communication unit may be performed using, for example, a generation AI (text generation AI or multimodal generation AI), or may be performed without using a generation AI. For example, the communication unit can input the subject's living situation into a generation AI, which can determine the need for emergency contact.

[0033] The dialogue unit can have regular conversations with the subject. For example, the dialogue unit has regular conversations with the subject. The dialogue unit uses AI to have regular conversations with the subject. For example, the dialogue unit has conversations with the subject at a fixed time every day. The dialogue unit can also listen to what the subject says and provide an appropriate response. For example, if the subject says, "The weather is nice today," the dialogue unit replies, "Yes, it's sunny today." This can reduce the subject's sense of loneliness through regular conversations. Some or all of the above-mentioned processing in the dialogue unit may be performed using, for example, a generation AI (text generation AI or multimodal generation AI), or may be performed without using a generation AI. For example, the dialogue unit can input regular conversations with the subject into a generation AI, which can generate an appropriate response.

[0034] The monitoring unit can periodically monitor the living situation of the subject. For example, the monitoring unit periodically monitors the living situation of the subject. The monitoring unit periodically monitors the living situation of the subject using AI. For example, the monitoring unit monitors the living situation of the subject at a fixed time every day. The monitoring unit can also analyze the subject's tone of voice and content of speech to determine the subject's health condition and mood. For example, the monitoring unit may suspect poor health if the subject's voice tone is low. The monitoring unit can also determine whether the subject feels lonely from the content of the subject's speech. This allows the subject's living situation to be continuously monitored. Some or all of the above-mentioned processing in the monitoring unit may be performed using, for example, a generation AI (text generation AI or multimodal generation AI), or may be performed without using a generation AI. For example, the monitoring unit can input the living situation of the subject into a generation AI, which can then determine the subject's health condition and mood.

[0035] The dialogue unit can provide a more personalized response by referring to the subject's past conversation history during a dialogue. For example, the dialogue unit can provide a more personalized response by referring to the subject's past conversation history during a dialogue. The dialogue unit uses AI to reference the subject's past conversation history and generate a personalized response. For example, the dialogue unit may revisit a hobby that the subject previously talked about. The dialogue unit may also continue the conversation by referring to a family story that the subject previously talked about. The dialogue unit may also follow up on a health condition that the subject previously mentioned. This enables a personalized response to the subject. Some or all of the above-mentioned processing in the dialogue unit may be performed using, for example, a generation AI (text generation AI or multimodal generation AI), or may be performed without using a generation AI. For example, the dialogue unit may input the subject's past conversation history into a generation AI, which then generates a personalized response.

[0036] The dialogue unit can select an appropriate topic based on the subject's current activity and environment during dialogue. For example, the dialogue unit selects an appropriate topic based on the subject's current activity and environment during dialogue. The dialogue unit uses AI to analyze the subject's current activity and environment and select an appropriate topic. For example, if the subject is out, the dialogue unit can talk about the weather outside and the surrounding scenery. If the subject is eating, the dialogue unit can also talk about food and cooking. If the subject is watching TV, the dialogue unit can also talk about the program the subject is watching. This makes it possible to provide an appropriate topic according to the subject's situation. Some or all of the above-mentioned processing in the dialogue unit may be performed using, for example, a generation AI (text generation AI or multimodal generation AI), or may be performed without using a generation AI. For example, the dialogue unit can input the subject's current activity and environment into a generation AI, which can select an appropriate topic.

[0037] The dialogue unit can adjust the language style of the response depending on the language or dialect of the target person during the dialogue. For example, the dialogue unit adjusts the language style of the response depending on the language or dialect of the target person during the dialogue. The dialogue unit uses AI to analyze the language or dialect of the target person and adjust the language style of the response. For example, if the target person speaks Kansai dialect, the dialogue unit can also have the AI ​​reply in Kansai dialect. Furthermore, if the target person speaks English, the dialogue unit can also have the AI ​​reply in English. Furthermore, if the target person uses honorific language, the dialogue unit can also have the AI ​​reply in honorific language. This enables natural conversation depending on the language or dialect of the target person. Some or all of the above-mentioned processing in the dialogue unit may be performed using, for example, a generation AI (text generation AI or multimodal generation AI), or may be performed without using a generation AI. For example, the dialogue unit can input the language or dialect of the target person into a generation AI, which can generate an appropriate response.

[0038] The dialogue unit can select a topic based on the hobbies and interests of the subject during dialogue. For example, the dialogue unit selects a topic based on the hobbies and interests of the subject during dialogue. The dialogue unit uses AI to analyze the subject's hobbies and interests and select an appropriate topic. For example, if the subject likes music, the dialogue unit can talk about recent music. If the subject enjoys gardening, the dialogue unit can also talk about how to grow plants. If the subject likes reading, the dialogue unit can also talk about books that the subject has recently read. This makes it possible to provide an appropriate topic according to the subject's hobbies and interests. Some or all of the above-mentioned processing in the dialogue unit may be performed using, for example, a generation AI (text generation AI or multimodal generation AI), or may be performed without using a generation AI. For example, the dialogue unit can input the subject's hobbies and interests into a generation AI, which can select an appropriate topic.

[0039] The dialogue unit can provide related topics by referring to information about the subject's family and friends during dialogue. For example, the dialogue unit can provide related topics by referring to information about the subject's family and friends during dialogue. The dialogue unit uses AI to analyze information about the subject's family and friends and provide appropriate topics. For example, the dialogue unit can talk about the subject's family's recent activities. The dialogue unit can also talk about memories the subject has with their friends. The dialogue unit can also talk about recent trips the subject's family and friends have taken. This makes it possible to provide topics related to the subject's family and friends. Some or all of the above-mentioned processing in the dialogue unit may be performed using, for example, a generation AI (text generation AI or multimodal generation AI), or may be performed without using a generation AI. For example, the dialogue unit can input information about the subject's family and friends into a generation AI, which can generate appropriate topics.

[0040] The dialogue unit can provide appropriate advice based on the subject's health condition during dialogue. For example, the dialogue unit provides appropriate advice based on the subject's health condition during dialogue. The dialogue unit uses AI to analyze the subject's health condition and provide appropriate advice. For example, if the subject complains of feeling unwell, the dialogue unit can advise the subject to take a rest. Furthermore, if the subject feels that they are not getting enough exercise, the dialogue unit can also suggest light exercise. Furthermore, if the subject is worried about their diet, the dialogue unit can also suggest a balanced diet. This makes it possible to provide appropriate advice based on the subject's health condition. Some or all of the above-mentioned processing in the dialogue unit may be performed using, for example, a generation AI (text generation AI or multimodal generation AI), or may be performed without using a generation AI. For example, the dialogue unit can input the subject's health condition into a generation AI, which then generates appropriate advice.

[0041] The monitoring unit can detect abnormalities early by referring to the subject's past health data during monitoring. For example, the monitoring unit can detect abnormalities early by referring to the subject's past health data during monitoring. The monitoring unit uses AI to analyze the subject's past health data and detect abnormalities early. For example, the monitoring unit can refer to the subject's past blood pressure data and detect abnormal fluctuations. The monitoring unit can also refer to the subject's past body temperature data to detect fever early. The monitoring unit can also refer to the subject's past heart rate data to detect abnormal heart rates. In this way, abnormalities can be detected early by referring to past health data. Some or all of the above-mentioned processing in the monitoring unit may be performed using, for example, a generation AI (text generation AI or multimodal generation AI), or may be performed without using a generation AI. For example, the monitoring unit can input the subject's past health data into a generation AI, which can detect abnormalities early.

[0042] The monitoring unit can adjust the timing of monitoring based on the subject's lifestyle rhythm during monitoring. For example, the monitoring unit adjusts the timing of monitoring based on the subject's lifestyle rhythm during monitoring. The monitoring unit uses AI to analyze the subject's lifestyle rhythm and adjust the timing of monitoring. For example, the monitoring unit starts monitoring in accordance with the time the subject wakes up in the morning. The monitoring unit can also end monitoring in accordance with the time the subject goes to bed at night. The monitoring unit can also perform monitoring in accordance with the subject's meal times. This enables appropriate monitoring in accordance with the subject's lifestyle rhythm. Some or all of the above-mentioned processing in the monitoring unit may be performed using, for example, a generation AI (text generation AI or multimodal generation AI), or may be performed without using a generation AI. For example, the monitoring unit can input the subject's lifestyle rhythm into a generation AI, which can generate appropriate monitoring timing.

[0043] The monitoring unit can analyze the environmental sounds and movements of the subject during monitoring to grasp the living situation in more detail. For example, the monitoring unit can analyze the environmental sounds and movements of the subject during monitoring to grasp the living situation in more detail. The monitoring unit uses AI to analyze the environmental sounds and movements of the subject to grasp the living situation. For example, the monitoring unit analyzes the environmental sounds in the subject's room to detect abnormal sounds. The monitoring unit can also analyze the subject's movements to detect abnormalities such as falls. The monitoring unit can also analyze the living sounds of the subject to detect changes in their daily rhythms. This allows the living situation of the subject to be grasped in detail. Some or all of the above-mentioned processing in the monitoring unit may be performed using, for example, a generation AI (text generation AI or multimodal generation AI), or may be performed without using a generation AI. For example, the monitoring unit inputs the environmental sounds and movements of the subject into a generation AI, which can grasp the living situation.

[0044] The monitoring unit can monitor the subject's diet and exercise status during monitoring to support health management. For example, the monitoring unit can monitor the subject's diet and exercise status during monitoring to support health management. The monitoring unit can use AI to analyze the subject's diet and exercise status to support health management. For example, the monitoring unit can monitor the subject's diet and check nutritional balance. The monitoring unit can also monitor the subject's exercise status and detect lack of exercise. The monitoring unit can also monitor the subject's balance between diet and exercise to support health management. This can support the subject's health management. Some or all of the above-mentioned processing in the monitoring unit can be performed using, for example, a generation AI (text generation AI or multimodal generation AI), or can be performed without using a generation AI. For example, the monitoring unit can input the subject's diet and exercise status into a generation AI, which can support health management.

[0045] The monitoring unit can analyze the subject's sleep patterns during monitoring and provide advice to improve sleep quality. For example, the monitoring unit can analyze the subject's sleep patterns during monitoring and provide advice to improve sleep quality. The monitoring unit uses AI to analyze the subject's sleep patterns and provide appropriate advice. For example, the monitoring unit can monitor the subject's sleep duration and suggest an appropriate sleep duration. The monitoring unit can also analyze the subject's sleep quality and suggest improvements. The monitoring unit can also monitor the subject's sleep environment and suggest improvements. This makes it possible to provide advice to improve the subject's sleep quality. Some or all of the above-mentioned processing in the monitoring unit can be performed using, for example, a generation AI (text generation AI or multimodal generation AI) or without a generation AI. For example, the monitoring unit can input the subject's sleep patterns into a generation AI, which can generate appropriate advice.

[0046] The monitoring unit can monitor the social activities of the subject during monitoring and suggest measures to reduce loneliness. For example, the monitoring unit can monitor the social activities of the subject during monitoring and suggest measures to reduce loneliness. The monitoring unit can analyze the social activities of the subject using AI and suggest appropriate measures. For example, the monitoring unit can monitor the frequency of the subject's social activities and suggest measures to reduce loneliness. The monitoring unit can also monitor the subject's interactions with friends and family and suggest measures to reduce loneliness. The monitoring unit can also suggest social activities based on the subject's hobbies and interests. This makes it possible to take measures to reduce the subject's loneliness. Some or all of the above-mentioned processing in the monitoring unit can be performed using, for example, a generation AI (text generation AI or multimodal generation AI) or without a generation AI. For example, the monitoring unit can input the social activities of the subject into a generation AI, which can generate appropriate measures.

[0047] The communication unit can select an appropriate contact by referring to the subject's past contact history when making contact. For example, the communication unit can select an appropriate contact by referring to the subject's past contact history when making contact. The communication unit uses AI to analyze the subject's past contact history and select an appropriate contact. For example, the communication unit can prioritize selecting family members who the subject has contacted in the past as contacts. The communication unit can also prioritize selecting medical institutions that the subject has contacted in the past as contacts. The communication unit can also select the optimal contact from the subject's past contact history. In this way, an appropriate contact can be selected by referring to the past contact history. Some or all of the above-mentioned processing in the communication unit may be performed using, for example, a generation AI (text generation AI or multimodal generation AI), or may be performed without using a generation AI. For example, the communication unit can input the subject's past contact history into a generation AI, which can generate an appropriate contact.

[0048] The communication unit can customize the communication content based on the subject's current situation when contacting the subject. For example, the communication unit customizes the communication content based on the subject's current situation when contacting the subject. The communication unit uses AI to analyze the subject's current situation and customize the communication content. For example, if the subject complains of poor health, the communication unit can include information about the subject's health in the communication content. Furthermore, if the subject feels lonely, the communication unit can also include information about psychological support in the communication content. Furthermore, if the subject is in an emergency, the communication unit can also include information about emergency responses in the communication content. This enables appropriate communication content to be provided according to the subject's current situation. Some or all of the above-mentioned processing in the communication unit may be performed using, for example, a generation AI (text generation AI or multimodal generation AI), or may be performed without using a generation AI. For example, the communication unit can input the subject's current situation into a generation AI, which can generate appropriate communication content.

[0049] The communication unit can contact an appropriate medical institution by referring to the medical information of the subject when contacting the subject. For example, the communication unit can contact an appropriate medical institution by referring to the medical information of the subject when contacting the subject. The communication unit uses AI to analyze the medical information of the subject and select an appropriate medical institution. For example, the communication unit can contact an appropriate medical institution by referring to the subject's past medical history. The communication unit can also contact an appropriate medical institution by referring to the subject's current health condition. The communication unit can also contact the most appropriate medical institution based on the subject's medical information. This makes it possible to contact an appropriate medical institution based on the subject's medical information. Some or all of the above-mentioned processing in the communication unit may be performed using, for example, a generation AI (text generation AI or multimodal generation AI), or may be performed without using a generation AI. For example, the communication unit can input the subject's medical information into a generation AI, which can select an appropriate medical institution.

[0050] The contact unit can select appropriate contact information by referring to information about the subject's family and friends when making contact. For example, the contact unit can select appropriate contact information by referring to information about the subject's family and friends when making contact. The contact unit uses AI to analyze information about the subject's family and friends and select appropriate contact information. For example, the contact unit prioritizes selecting contact information for the subject's family. The contact unit can also prioritize selecting contact information for the subject's friends. The contact unit can also select optimal contact information from the subject's past contact history. This makes it possible to select appropriate contact information based on information about the subject's family and friends. Some or all of the above-mentioned processing in the contact unit may be performed using, for example, a generation AI (text generation AI or multimodal generation AI), or may be performed without using a generation AI. For example, the contact unit can input information about the subject's family and friends into a generation AI, which then generates appropriate contact information.

[0051] The communication unit can contact the nearest medical institution by referring to the subject's location information when contacting the subject. For example, the communication unit contacts the nearest medical institution by referring to the subject's location information when contacting the subject. The communication unit uses AI to analyze the subject's location information and select the nearest medical institution. For example, the communication unit contacts the nearest medical institution based on the subject's current location. The communication unit can also contact the most appropriate medical institution based on the subject's location information. The communication unit can also update the subject's location information in real time and contact the nearest medical institution. This makes it possible to contact the nearest medical institution based on the subject's location information. Some or all of the above-mentioned processing in the communication unit may be performed using, for example, a generation AI (text generation AI or multimodal generation AI), or may be performed without using a generation AI. For example, the communication unit can input the subject's location information into a generation AI, which can select the nearest medical institution.

[0052] The communication unit can customize the content of the communication by referring to the subject's past health data when making the communication. For example, the communication unit customizes the content of the communication by referring to the subject's past health data when making the communication. The communication unit uses AI to analyze the subject's past health data and customize the content of the communication. For example, the communication unit customizes the content of the communication based on the subject's past health data. The communication unit can also customize the content of the communication based on the subject's past medical history. The communication unit can also customize the content of the communication based on the subject's past health condition. This enables appropriate content to be communicated based on the subject's past health data. Some or all of the above-mentioned processing in the communication unit may be performed using, for example, a generation AI (text generation AI or multimodal generation AI), or may be performed without using a generation AI. For example, the communication unit can input the subject's past health data into a generation AI, which then generates appropriate content of the communication.

[0053] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0054] A conversational AI system can further include a learning unit. The learning unit can accumulate conversation history and lifestyle data with the subject and use it to improve the accuracy of the AI's responses. For example, the learning unit can record what the subject has previously said and use that information in the next conversation. The learning unit can also learn the subject's lifestyle patterns and respond appropriately based on predicted behavior and status. Furthermore, the learning unit can track changes in the subject's health condition over the long term and provide data for early detection of abnormalities. This enables the conversational AI system to provide more personalized responses and improve the subject's quality of life.

[0055] The monitoring unit can monitor the living environment of the subject and issue appropriate alerts in response to changes in the environment. For example, if the room temperature changes suddenly, the monitoring unit can prompt the subject to take appropriate action. The monitoring unit can also monitor the lighting status and issue an alert if the lights are not turned on at night. Furthermore, the monitoring unit can analyze the subject's movements and issue an alert if it detects abnormal movements. This ensures the safety of the subject's living environment.

[0056] The dialogue unit can select topics based on the subject's hobbies and interests. For example, if the subject likes music, it can talk about the latest music. If the subject likes gardening, it can talk about how to grow plants. Furthermore, if the subject likes reading, it can talk about books that the subject has recently read. In this way, the dialogue unit can provide appropriate topics according to the subject's hobbies and interests.

[0057] During the dialogue, the dialogue unit can refer to the subject's past conversation history to provide a more personalized response. For example, the dialogue unit can revisit a hobby that the subject previously mentioned. It can also continue the conversation by referring to a story about the subject's family that the subject previously mentioned. It can also follow up on a health condition that the subject previously mentioned. This allows the dialogue unit to provide a personalized response to the subject.

[0058] During monitoring, the monitoring unit can detect abnormalities early by referring to the subject's past health data. For example, the monitoring unit can detect abnormal fluctuations by referring to the subject's past blood pressure data. The monitoring unit can also detect fever early by referring to the subject's past body temperature data. Furthermore, the monitoring unit can also detect abnormal heartbeats by referring to the subject's past heart rate data. In this way, the monitoring unit can detect abnormalities early by referring to past health data.

[0059] When contacting the subject, the communication unit can customize the content of the communication based on the subject's current situation. For example, if the subject complains of feeling unwell, information about the subject's health can be included in the content of the communication. Also, if the subject feels lonely, information about psychological support can be included in the content of the communication. Furthermore, if the subject is in an emergency, information about emergency response can be included in the content of the communication. This allows the communication unit to provide appropriate content of the communication based on the subject's current situation.

[0060] The processing flow of the first embodiment will be briefly explained below.

[0061] Step 1: The dialogue unit has a conversation with the subject. For example, the dialogue unit listens to what the subject says and provides an appropriate response. The dialogue unit uses AI to analyze what the subject says and generate an appropriate response. For example, if the subject says, "The weather is nice today," the AI ​​will respond, "Yes, it's sunny today." The dialogue unit can also have regular conversations with the subject. For example, the dialogue unit may have a conversation with the subject at a set time every day. Step 2: The monitoring unit monitors the living conditions of the subject based on the conversation conducted by the dialogue unit. For example, the monitoring unit analyzes the subject's tone of voice and the content of what is said to determine their health condition and mood. The monitoring unit uses AI to analyze the subject's tone of voice and the content of what is said to determine their health condition and mood. For example, if the subject's voice tone is low, the monitoring unit may suspect that they are in poor health. The monitoring unit can also determine whether they are feeling lonely based on the content of what the subject is saying. Step 3: The communication unit makes an emergency contact based on the living conditions monitored by the monitoring unit. For example, if the subject complains of feeling unwell, the communication unit automatically contacts the subject's family or a medical institution. The communication unit uses AI to analyze the subject's living conditions and determine the need for emergency contact. For example, if the subject says they are "feeling unwell," the communication unit will contact their family. The communication unit can also contact a medical institution if the subject's health condition worsens.

[0062] (Example 2) An interactive AI system according to an embodiment of the present invention monitors the living conditions of a subject through conversations with the subject and responds promptly in emergencies. The system engages in conversations with the subject, and the AI ​​monitors the subject's living conditions and makes emergency contact as needed. This mechanism reduces the subject's sense of loneliness, prevents dementia, and provides support for daily living. For example, the interactive AI system periodically converses with the subject. The AI ​​listens to the subject and responds appropriately. For example, if the subject says, "The weather is nice today," the AI ​​responds, "Yes, it's sunny today." Next, the AI ​​monitors the subject's living conditions. For example, the AI ​​can determine the subject's health condition and mood from the subject's tone of voice and content of speech. This allows the AI ​​to detect if the subject is feeling unwell or lonely and take appropriate action. Furthermore, it makes emergency contact as needed. For example, if the subject complains of feeling unwell, the AI ​​can automatically contact family or medical institutions. This allows for prompt response in emergencies. This allows the interactive AI system to reduce the subject's sense of loneliness, prevent dementia, and provide support for daily living. For example, regular conversations can help maintain the mental health of the recipient. AI can also monitor their daily life to ensure their safety. Furthermore, an emergency contact function can provide a quick response when the recipient is in trouble.

[0063] An interactive AI system according to an embodiment includes a dialogue unit, a monitoring unit, and a communication unit. The dialogue unit engages in a conversation with a subject. For example, the dialogue unit listens to the subject and provides an appropriate response. The dialogue unit uses AI to analyze the subject's speech and generate an appropriate response. For example, if the subject says, "The weather is nice today," the dialogue unit responds with, "Yes, it's sunny today." The dialogue unit can also engage in regular conversations with the subject. For example, the dialogue unit engages in conversation with the subject at a fixed time every day. The monitoring unit monitors the subject's living situation based on the conversation conducted by the dialogue unit. For example, the monitoring unit analyzes the subject's tone of voice and content of speech to determine the subject's health condition and mood. The monitoring unit uses AI to analyze the subject's tone of voice and content of speech to determine the subject's health condition and mood. For example, the monitoring unit may suspect poor health if the subject's voice tone is low. The monitoring unit can also determine whether the subject is feeling lonely based on the content of the subject's speech. The communication unit makes emergency contact based on the living conditions monitored by the monitoring unit. For example, if the subject complains of feeling unwell, the communication unit automatically contacts family members or medical institutions. The communication unit uses AI to analyze the living conditions of the subject and determine the need for emergency contact. For example, if the subject says, "I'm feeling unwell," the communication unit contacts family members. The communication unit can also contact medical institutions if the subject's health condition worsens. This allows the interactive AI system according to the embodiment to reduce the subject's sense of loneliness, prevent dementia, and provide support for daily life. For example, the subject's mental health can be maintained through regular conversations. Furthermore, by having AI monitor the living conditions, the subject's safety can be ensured. Furthermore, the emergency contact function allows for quick response when the subject is in trouble.

[0064] The dialogue unit can listen to the subject's speech and provide an appropriate response. For example, the dialogue unit listens to the subject's speech and provides an appropriate response. The dialogue unit uses AI to analyze the subject's speech and generate an appropriate response. For example, if the subject says, "The weather is nice today," the dialogue unit responds with, "Yes, it's sunny today." The dialogue unit can also provide an appropriate response based on the content of the subject's speech. For example, if the subject says, "I'm tired today," the dialogue unit responds with, "Thank you for your hard work. Please get plenty of rest." The dialogue unit can also adjust the tone of the response based on the tone of the subject's speech. For example, if the subject speaks in a sad voice, the dialogue unit responds with a gentler tone. This enables a natural conversation with the subject. Some or all of the above-described processing in the dialogue unit may be performed using, for example, a generation AI (text generation AI or multimodal generation AI) or without a generation AI. For example, the dialogue unit can input the subject's speech into the generation AI, which can then generate an appropriate response.

[0065] The monitoring unit can analyze the subject's tone of voice and the content of their speech to determine their health condition and mood. For example, the monitoring unit analyzes the subject's tone of voice to determine their health condition and mood. The monitoring unit uses AI to analyze the subject's tone of voice to determine their health condition and mood. For example, if the subject's tone of voice is low, the monitoring unit may suspect poor health. The monitoring unit can also analyze the content of the subject's speech to determine their health condition and mood. For example, if the subject says, "I'm tired today," the monitoring unit may suspect poor health. The monitoring unit can also determine whether the subject is feeling lonely from the content of the subject's speech. For example, if the subject says, "I haven't talked to anyone," the monitoring unit may determine that the subject is feeling lonely. This allows the subject's health condition and mood to be accurately understood. Some or all of the above-described processing in the monitoring unit may be performed using, for example, a generative AI (text generation AI or multimodal generation AI) or without a generative AI. For example, the monitoring unit can input the subject's tone of voice and the content of their speech into the generation AI, which can then determine their health condition and mood.

[0066] The communication unit can automatically contact family members or medical institutions when the subject complains of feeling unwell. For example, when the subject complains of feeling unwell, the communication unit automatically contacts family members or medical institutions. The communication unit uses AI to analyze the subject's living situation and determine the need for emergency contact. For example, when the subject says, "I'm feeling unwell," the communication unit contacts family members. The communication unit can also contact medical institutions when the subject's health condition worsens. For example, the communication unit can determine whether the subject is feeling unwell based on the subject's tone of voice and the content of their speech and contact a medical institution. This enables rapid response in emergencies. Some or all of the above-mentioned processing in the communication unit may be performed using, for example, a generation AI (text generation AI or multimodal generation AI), or may be performed without using a generation AI. For example, the communication unit can input the subject's living situation into a generation AI, which can determine the need for emergency contact.

[0067] The dialogue unit can have regular conversations with the subject. For example, the dialogue unit has regular conversations with the subject. The dialogue unit uses AI to have regular conversations with the subject. For example, the dialogue unit has conversations with the subject at a fixed time every day. The dialogue unit can also listen to what the subject says and provide an appropriate response. For example, if the subject says, "The weather is nice today," the dialogue unit replies, "Yes, it's sunny today." This can reduce the subject's sense of loneliness through regular conversations. Some or all of the above-mentioned processing in the dialogue unit may be performed using, for example, a generation AI (text generation AI or multimodal generation AI), or may be performed without using a generation AI. For example, the dialogue unit can input regular conversations with the subject into a generation AI, which can generate an appropriate response.

[0068] The monitoring unit can periodically monitor the living situation of the subject. For example, the monitoring unit periodically monitors the living situation of the subject. The monitoring unit periodically monitors the living situation of the subject using AI. For example, the monitoring unit monitors the living situation of the subject at a fixed time every day. The monitoring unit can also analyze the subject's tone of voice and content of speech to determine the subject's health condition and mood. For example, the monitoring unit may suspect poor health if the subject's voice tone is low. The monitoring unit can also determine whether the subject feels lonely from the content of the subject's speech. This allows the subject's living situation to be continuously monitored. Some or all of the above-mentioned processing in the monitoring unit may be performed using, for example, a generation AI (text generation AI or multimodal generation AI), or may be performed without using a generation AI. For example, the monitoring unit can input the living situation of the subject into a generation AI, which can then determine the subject's health condition and mood.

[0069] The dialogue unit can estimate the emotions of the target person and adjust the tone and content of the response based on the estimated emotions of the target person. For example, the dialogue unit can estimate the emotions of the target person and adjust the tone and content of the response based on the estimated emotions of the target person. The dialogue unit can use AI to estimate the emotions of the target person and adjust the tone and content of the response based on the estimated emotions of the target person. For example, if the dialogue unit is sad, the AI ​​can speak encouraging words in a gentle tone. If the dialogue unit is excited, the AI ​​can listen to the target person in a calm tone and calm them down. If the dialogue unit is tired, the AI ​​can provide a topic that will help the target person relax in a gentle tone. This enables an appropriate response to be given according to the target person's emotions. Some or all of the above-mentioned processing in the dialogue unit may be performed using, for example, a generation AI (text generation AI or multimodal generation AI), or may be performed without using a generation AI. For example, the dialogue unit can input the emotions of the target person into a generation AI, which can generate an appropriate response.

[0070] The dialogue unit can provide a more personalized response by referring to the subject's past conversation history during a dialogue. For example, the dialogue unit can provide a more personalized response by referring to the subject's past conversation history during a dialogue. The dialogue unit uses AI to reference the subject's past conversation history and generate a personalized response. For example, the dialogue unit may revisit a hobby that the subject previously talked about. The dialogue unit may also continue the conversation by referring to a family story that the subject previously talked about. The dialogue unit may also follow up on a health condition that the subject previously mentioned. This enables a personalized response to the subject. Some or all of the above-mentioned processing in the dialogue unit may be performed using, for example, a generation AI (text generation AI or multimodal generation AI), or may be performed without using a generation AI. For example, the dialogue unit may input the subject's past conversation history into a generation AI, which then generates a personalized response.

[0071] The dialogue unit can select an appropriate topic based on the subject's current activity and environment during dialogue. For example, the dialogue unit selects an appropriate topic based on the subject's current activity and environment during dialogue. The dialogue unit uses AI to analyze the subject's current activity and environment and select an appropriate topic. For example, if the subject is out, the dialogue unit can talk about the weather outside and the surrounding scenery. If the subject is eating, the dialogue unit can also talk about food and cooking. If the subject is watching TV, the dialogue unit can also talk about the program the subject is watching. This makes it possible to provide an appropriate topic according to the subject's situation. Some or all of the above-mentioned processing in the dialogue unit may be performed using, for example, a generation AI (text generation AI or multimodal generation AI), or may be performed without using a generation AI. For example, the dialogue unit can input the subject's current activity and environment into a generation AI, which can select an appropriate topic.

[0072] The dialogue unit can adjust the language style of the response depending on the language or dialect of the target person during the dialogue. For example, the dialogue unit adjusts the language style of the response depending on the language or dialect of the target person during the dialogue. The dialogue unit uses AI to analyze the language or dialect of the target person and adjust the language style of the response. For example, if the target person speaks Kansai dialect, the dialogue unit can also have the AI ​​reply in Kansai dialect. Furthermore, if the target person speaks English, the dialogue unit can also have the AI ​​reply in English. Furthermore, if the target person uses honorific language, the dialogue unit can also have the AI ​​reply in honorific language. This enables natural conversation depending on the language or dialect of the target person. Some or all of the above-mentioned processing in the dialogue unit may be performed using, for example, a generation AI (text generation AI or multimodal generation AI), or may be performed without using a generation AI. For example, the dialogue unit can input the language or dialect of the target person into a generation AI, which can generate an appropriate response.

[0073] The dialogue unit can estimate the emotions of the subject and adjust the frequency of conversation based on the estimated emotions of the subject. For example, the dialogue unit can estimate the emotions of the subject and adjust the frequency of conversation based on the estimated emotions of the subject. The dialogue unit can estimate the emotions of the subject using AI and adjust the frequency of conversation based on the estimated emotions of the subject. For example, the dialogue unit can conduct conversations frequently when the subject is feeling lonely. The dialogue unit can also reduce the frequency of conversations when the subject is busy. The dialogue unit can also conduct conversations at an appropriate frequency when the subject is relaxed. This enables an appropriate conversation frequency according to the emotions of the subject. Some or all of the above-mentioned processing in the dialogue unit can be performed using, for example, a generation AI (text generation AI or multimodal generation AI), or can be performed without using a generation AI. For example, the dialogue unit can input the emotions of the subject into a generation AI, which can generate an appropriate conversation frequency.

[0074] The dialogue unit can select a topic based on the hobbies and interests of the subject during dialogue. For example, the dialogue unit selects a topic based on the hobbies and interests of the subject during dialogue. The dialogue unit uses AI to analyze the subject's hobbies and interests and select an appropriate topic. For example, if the subject likes music, the dialogue unit can talk about recent music. If the subject enjoys gardening, the dialogue unit can also talk about how to grow plants. If the subject likes reading, the dialogue unit can also talk about books that the subject has recently read. This makes it possible to provide an appropriate topic according to the subject's hobbies and interests. Some or all of the above-mentioned processing in the dialogue unit may be performed using, for example, a generation AI (text generation AI or multimodal generation AI), or may be performed without using a generation AI. For example, the dialogue unit can input the subject's hobbies and interests into a generation AI, which can select an appropriate topic.

[0075] The dialogue unit can provide related topics by referring to information about the subject's family and friends during dialogue. For example, the dialogue unit can provide related topics by referring to information about the subject's family and friends during dialogue. The dialogue unit uses AI to analyze information about the subject's family and friends and provide appropriate topics. For example, the dialogue unit can talk about the subject's family's recent activities. The dialogue unit can also talk about memories the subject has with their friends. The dialogue unit can also talk about recent trips the subject's family and friends have taken. This makes it possible to provide topics related to the subject's family and friends. Some or all of the above-mentioned processing in the dialogue unit may be performed using, for example, a generation AI (text generation AI or multimodal generation AI), or may be performed without using a generation AI. For example, the dialogue unit can input information about the subject's family and friends into a generation AI, which can generate appropriate topics.

[0076] The dialogue unit can provide appropriate advice based on the subject's health condition during dialogue. For example, the dialogue unit provides appropriate advice based on the subject's health condition during dialogue. The dialogue unit uses AI to analyze the subject's health condition and provide appropriate advice. For example, if the subject complains of feeling unwell, the dialogue unit can advise the subject to take a rest. Furthermore, if the subject feels that they are not getting enough exercise, the dialogue unit can also suggest light exercise. Furthermore, if the subject is worried about their diet, the dialogue unit can also suggest a balanced diet. This makes it possible to provide appropriate advice based on the subject's health condition. Some or all of the above-mentioned processing in the dialogue unit may be performed using, for example, a generation AI (text generation AI or multimodal generation AI), or may be performed without using a generation AI. For example, the dialogue unit can input the subject's health condition into a generation AI, which then generates appropriate advice.

[0077] The monitoring unit can estimate the subject's emotions and adjust the focus of monitoring based on the estimated subject's emotions. For example, the monitoring unit can estimate the subject's emotions and adjust the focus of monitoring based on the estimated subject's emotions. The monitoring unit can use AI to estimate the subject's emotions and adjust the focus of monitoring based on the estimated subject's emotions. For example, the monitoring unit can monitor the subject more frequently if the subject is feeling lonely. The monitoring unit can also reduce the frequency of monitoring if the subject is relaxed. The monitoring unit can also intensify monitoring of the subject's health status if the subject is feeling stressed. This enables appropriate monitoring according to the subject's emotions. Some or all of the above-mentioned processing in the monitoring unit can be performed using, for example, a generation AI (text generation AI or multimodal generation AI), or can be performed without using a generation AI. For example, the monitoring unit can input the subject's emotions into a generation AI, which can generate an appropriate focus of monitoring.

[0078] The monitoring unit can detect abnormalities early by referring to the subject's past health data during monitoring. For example, the monitoring unit can detect abnormalities early by referring to the subject's past health data during monitoring. The monitoring unit uses AI to analyze the subject's past health data and detect abnormalities early. For example, the monitoring unit can refer to the subject's past blood pressure data and detect abnormal fluctuations. The monitoring unit can also refer to the subject's past body temperature data to detect fever early. The monitoring unit can also refer to the subject's past heart rate data to detect abnormal heart rates. In this way, abnormalities can be detected early by referring to past health data. Some or all of the above-mentioned processing in the monitoring unit may be performed using, for example, a generation AI (text generation AI or multimodal generation AI), or may be performed without using a generation AI. For example, the monitoring unit can input the subject's past health data into a generation AI, which can detect abnormalities early.

[0079] The monitoring unit can adjust the timing of monitoring based on the subject's lifestyle rhythm during monitoring. For example, the monitoring unit adjusts the timing of monitoring based on the subject's lifestyle rhythm during monitoring. The monitoring unit uses AI to analyze the subject's lifestyle rhythm and adjust the timing of monitoring. For example, the monitoring unit starts monitoring in accordance with the time the subject wakes up in the morning. The monitoring unit can also end monitoring in accordance with the time the subject goes to bed at night. The monitoring unit can also perform monitoring in accordance with the subject's meal times. This enables appropriate monitoring in accordance with the subject's lifestyle rhythm. Some or all of the above-mentioned processing in the monitoring unit may be performed using, for example, a generation AI (text generation AI or multimodal generation AI), or may be performed without using a generation AI. For example, the monitoring unit can input the subject's lifestyle rhythm into a generation AI, which can generate appropriate monitoring timing.

[0080] The monitoring unit can analyze the environmental sounds and movements of the subject during monitoring to grasp the living situation in more detail. For example, the monitoring unit can analyze the environmental sounds and movements of the subject during monitoring to grasp the living situation in more detail. The monitoring unit uses AI to analyze the environmental sounds and movements of the subject to grasp the living situation. For example, the monitoring unit analyzes the environmental sounds in the subject's room to detect abnormal sounds. The monitoring unit can also analyze the subject's movements to detect abnormalities such as falls. The monitoring unit can also analyze the living sounds of the subject to detect changes in their daily rhythms. This allows the living situation of the subject to be grasped in detail. Some or all of the above-mentioned processing in the monitoring unit may be performed using, for example, a generation AI (text generation AI or multimodal generation AI), or may be performed without using a generation AI. For example, the monitoring unit inputs the environmental sounds and movements of the subject into a generation AI, which can grasp the living situation.

[0081] The monitoring unit can estimate the subject's emotions and adjust the monitoring frequency based on the estimated subject's emotions. For example, the monitoring unit can estimate the subject's emotions and adjust the monitoring frequency based on the estimated subject's emotions. The monitoring unit can estimate the subject's emotions using AI and adjust the monitoring frequency based on the estimated subject's emotions. For example, the monitoring unit can monitor the subject more frequently if the subject is feeling lonely. The monitoring unit can also reduce the monitoring frequency if the subject is relaxed. The monitoring unit can also intensify monitoring of the subject's health status if the subject is feeling stressed. This enables an appropriate monitoring frequency according to the subject's emotions. Some or all of the above-mentioned processing in the monitoring unit can be performed using, for example, a generation AI (text generation AI or multimodal generation AI), or can be performed without using a generation AI. For example, the monitoring unit can input the subject's emotions into a generation AI, which can generate an appropriate monitoring frequency.

[0082] The monitoring unit can monitor the subject's diet and exercise status during monitoring to support health management. For example, the monitoring unit can monitor the subject's diet and exercise status during monitoring to support health management. The monitoring unit can use AI to analyze the subject's diet and exercise status to support health management. For example, the monitoring unit can monitor the subject's diet and check nutritional balance. The monitoring unit can also monitor the subject's exercise status and detect lack of exercise. The monitoring unit can also monitor the subject's balance between diet and exercise to support health management. This can support the subject's health management. Some or all of the above-mentioned processing in the monitoring unit can be performed using, for example, a generation AI (text generation AI or multimodal generation AI), or can be performed without using a generation AI. For example, the monitoring unit can input the subject's diet and exercise status into a generation AI, which can support health management.

[0083] The monitoring unit can analyze the subject's sleep patterns during monitoring and provide advice to improve sleep quality. For example, the monitoring unit can analyze the subject's sleep patterns during monitoring and provide advice to improve sleep quality. The monitoring unit uses AI to analyze the subject's sleep patterns and provide appropriate advice. For example, the monitoring unit can monitor the subject's sleep duration and suggest an appropriate sleep duration. The monitoring unit can also analyze the subject's sleep quality and suggest improvements. The monitoring unit can also monitor the subject's sleep environment and suggest improvements. This makes it possible to provide advice to improve the subject's sleep quality. Some or all of the above-mentioned processing in the monitoring unit can be performed using, for example, a generation AI (text generation AI or multimodal generation AI) or without a generation AI. For example, the monitoring unit can input the subject's sleep patterns into a generation AI, which can generate appropriate advice.

[0084] The monitoring unit can monitor the social activities of the subject during monitoring and suggest measures to reduce loneliness. For example, the monitoring unit can monitor the social activities of the subject during monitoring and suggest measures to reduce loneliness. The monitoring unit can analyze the social activities of the subject using AI and suggest appropriate measures. For example, the monitoring unit can monitor the frequency of the subject's social activities and suggest measures to reduce loneliness. The monitoring unit can also monitor the subject's interactions with friends and family and suggest measures to reduce loneliness. The monitoring unit can also suggest social activities based on the subject's hobbies and interests. This makes it possible to take measures to reduce the subject's loneliness. Some or all of the above-mentioned processing in the monitoring unit can be performed using, for example, a generation AI (text generation AI or multimodal generation AI) or without a generation AI. For example, the monitoring unit can input the social activities of the subject into a generation AI, which can generate appropriate measures.

[0085] The communication unit can estimate the subject's emotions and determine the urgency of the contact based on the estimated subject's emotions. The communication unit, for example, estimates the subject's emotions and determines the urgency of the contact based on the estimated subject's emotions. The communication unit uses AI to estimate the subject's emotions and determine the urgency of the contact based on the estimated subject's emotions. For example, the communication unit sets the urgency high if the subject is feeling a strong sense of loneliness. The communication unit can also set the urgency low if the subject is relaxed. The communication unit can also set the urgency to medium if the subject is feeling stressed. This makes it possible to determine an appropriate urgency based on the subject's emotions. Some or all of the above-mentioned processing in the communication unit may be performed using, for example, a generation AI (text generation AI or multimodal generation AI), or may be performed without using a generation AI. For example, the communication unit can input the subject's emotions into a generation AI, which then generates an appropriate urgency.

[0086] The communication unit can select an appropriate contact by referring to the subject's past contact history when making contact. For example, the communication unit can select an appropriate contact by referring to the subject's past contact history when making contact. The communication unit uses AI to analyze the subject's past contact history and select an appropriate contact. For example, the communication unit can prioritize selecting family members who the subject has contacted in the past as contacts. The communication unit can also prioritize selecting medical institutions that the subject has contacted in the past as contacts. The communication unit can also select the optimal contact from the subject's past contact history. In this way, an appropriate contact can be selected by referring to the past contact history. Some or all of the above-mentioned processing in the communication unit may be performed using, for example, a generation AI (text generation AI or multimodal generation AI), or may be performed without using a generation AI. For example, the communication unit can input the subject's past contact history into a generation AI, which can generate an appropriate contact.

[0087] The communication unit can customize the communication content based on the subject's current situation when contacting the subject. For example, the communication unit customizes the communication content based on the subject's current situation when contacting the subject. The communication unit uses AI to analyze the subject's current situation and customize the communication content. For example, if the subject complains of poor health, the communication unit can include information about the subject's health in the communication content. Furthermore, if the subject feels lonely, the communication unit can also include information about psychological support in the communication content. Furthermore, if the subject is in an emergency, the communication unit can also include information about emergency responses in the communication content. This enables appropriate communication content to be provided according to the subject's current situation. Some or all of the above-mentioned processing in the communication unit may be performed using, for example, a generation AI (text generation AI or multimodal generation AI), or may be performed without using a generation AI. For example, the communication unit can input the subject's current situation into a generation AI, which can generate appropriate communication content.

[0088] The communication unit can contact an appropriate medical institution by referring to the medical information of the subject when contacting the subject. For example, the communication unit can contact an appropriate medical institution by referring to the medical information of the subject when contacting the subject. The communication unit uses AI to analyze the medical information of the subject and select an appropriate medical institution. For example, the communication unit can contact an appropriate medical institution by referring to the subject's past medical history. The communication unit can also contact an appropriate medical institution by referring to the subject's current health condition. The communication unit can also contact the most appropriate medical institution based on the subject's medical information. This makes it possible to contact an appropriate medical institution based on the subject's medical information. Some or all of the above-mentioned processing in the communication unit may be performed using, for example, a generation AI (text generation AI or multimodal generation AI), or may be performed without using a generation AI. For example, the communication unit can input the subject's medical information into a generation AI, which can select an appropriate medical institution.

[0089] The communication unit can estimate the target person's emotions and adjust the timing of contact based on the estimated target person's emotions. The communication unit, for example, estimates the target person's emotions and adjusts the timing of contact based on the estimated target person's emotions. The communication unit uses AI to estimate the target person's emotions and adjusts the timing of contact based on the estimated target person's emotions. For example, the communication unit contacts the target person promptly if the target person is feeling lonely. The communication unit can also delay the timing of contact if the target person is relaxed. The communication unit can also contact the target person at an appropriate time if the target person is feeling stressed. This enables appropriate timing of contact based on the target person's emotions. Some or all of the above-mentioned processing in the communication unit may be performed using, for example, a generation AI (text generation AI or multimodal generation AI), or may be performed without using a generation AI. For example, the communication unit can input the target person's emotions into a generation AI, which can generate an appropriate timing of contact.

[0090] The contact unit can select appropriate contact information by referring to information about the subject's family and friends when making contact. For example, the contact unit can select appropriate contact information by referring to information about the subject's family and friends when making contact. The contact unit uses AI to analyze information about the subject's family and friends and select appropriate contact information. For example, the contact unit prioritizes selecting contact information for the subject's family. The contact unit can also prioritize selecting contact information for the subject's friends. The contact unit can also select optimal contact information from the subject's past contact history. This makes it possible to select appropriate contact information based on information about the subject's family and friends. Some or all of the above-mentioned processing in the contact unit may be performed using, for example, a generation AI (text generation AI or multimodal generation AI), or may be performed without using a generation AI. For example, the contact unit can input information about the subject's family and friends into a generation AI, which then generates appropriate contact information.

[0091] The communication unit can contact the nearest medical institution by referring to the subject's location information when contacting the subject. For example, the communication unit contacts the nearest medical institution by referring to the subject's location information when contacting the subject. The communication unit uses AI to analyze the subject's location information and select the nearest medical institution. For example, the communication unit contacts the nearest medical institution based on the subject's current location. The communication unit can also contact the most appropriate medical institution based on the subject's location information. The communication unit can also update the subject's location information in real time and contact the nearest medical institution. This makes it possible to contact the nearest medical institution based on the subject's location information. Some or all of the above-mentioned processing in the communication unit may be performed using, for example, a generation AI (text generation AI or multimodal generation AI), or may be performed without using a generation AI. For example, the communication unit can input the subject's location information into a generation AI, which can select the nearest medical institution.

[0092] The communication unit can customize the content of the communication by referring to the subject's past health data when making the communication. For example, the communication unit customizes the content of the communication by referring to the subject's past health data when making the communication. The communication unit uses AI to analyze the subject's past health data and customize the content of the communication. For example, the communication unit customizes the content of the communication based on the subject's past health data. The communication unit can also customize the content of the communication based on the subject's past medical history. The communication unit can also customize the content of the communication based on the subject's past health condition. This enables appropriate content to be communicated based on the subject's past health data. Some or all of the above-mentioned processing in the communication unit may be performed using, for example, a generation AI (text generation AI or multimodal generation AI), or may be performed without using a generation AI. For example, the communication unit can input the subject's past health data into a generation AI, which then generates appropriate content of the communication. === Hard Collateral 1-1 === Each of the multiple elements including the dialogue unit, monitoring unit, and communication unit described above is realized, for example, by at least one of the smart device 14 and the data processing device 12. For example, the dialogue unit is realized by the control unit 46A of the smart device 14 or the specific processing unit 290 of the data processing device 12. For example, the monitoring unit analyzes the subject's tone of voice and content of speech using the camera 42 and microphone 38B of the smart device 14, and determines the subject's health condition and mood by the control unit 46A or the specific processing unit 290 of the data processing device 12. For example, the communication unit is realized by the specific processing unit 290 of the data processing device 12, analyzes the subject's living situation, and contacts family members or medical institutions as necessary. === Hard Collateral 1-2 === Each of the multiple elements including the dialogue unit, monitoring unit, and communication unit described above is realized, for example, by at least one of the smart glasses 214 and the data processing device 12. For example, the dialogue unit is realized by the control unit 46A of the smart glasses 214 or the specific processing unit 290 of the data processing device 12. For example, the monitoring unit analyzes the subject's tone of voice and content of speech using the camera 42 and microphone 238 of the smart glasses 214, and determines the subject's health condition and mood by the control unit 46A or the specific processing unit 290 of the data processing device 12. For example, the communication unit is realized by the specific processing unit 290 of the data processing device 12, analyzes the subject's living situation, and contacts family members or medical institutions as necessary. === Hard Collateral 1-3 === Each of the multiple elements including the dialogue unit, monitoring unit, and communication unit described above is realized, for example, by at least one of the headset type terminal 314 and the data processing device 12. For example, the dialogue unit is realized by the control unit 46A of the headset type terminal 314 or the specific processing unit 290 of the data processing device 12. For example, the monitoring unit analyzes the subject's tone of voice and the content of what is being said using the camera 42 and microphone 238 of the headset type terminal 314, and determines the subject's health condition and mood by the control unit 46A or the specific processing unit 290 of the data processing device 12. For example, the communication unit is realized by the specific processing unit 290 of the data processing device 12, analyzes the subject's living situation, and contacts family members or medical institutions as necessary. === Hard Collateral 1-4 === Each of the multiple elements including the dialogue unit, monitoring unit, and communication unit described above is realized, for example, by at least one of the robot 414 and the data processing device 12. For example, the dialogue unit is realized by the control unit 46A of the robot 414 or the specific processing unit 290 of the data processing device 12. For example, the monitoring unit analyzes the tone of voice and content of speech of the subject using the camera 42 and microphone 238 of the robot 414, and determines the health condition and mood of the subject by the control unit 46A or the specific processing unit 290 of the data processing device 12. For example, the communication unit is realized by the specific processing unit 290 of the data processing device 12, analyzes the living situation of the subject, and contacts family members or medical institutions as necessary.

[0093] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0094] A conversational AI system can further include a learning unit. The learning unit can accumulate conversation history and lifestyle data with the subject and use it to improve the accuracy of the AI's responses. For example, the learning unit can record what the subject has previously said and use that information in the next conversation. The learning unit can also learn the subject's lifestyle patterns and respond appropriately based on predicted behavior and status. Furthermore, the learning unit can track changes in the subject's health condition over the long term and provide data for early detection of abnormalities. This enables the conversational AI system to provide more personalized responses and improve the subject's quality of life.

[0095] The dialogue unit can estimate the emotions of the target person and adjust the content of the conversation based on the estimated emotions. For example, if the target person is sad, the dialogue unit can offer words of comfort. If the target person is excited, the dialogue unit can continue the conversation in a calm tone. Furthermore, if the target person is tired, the dialogue unit can suggest topics that will help the target person relax. This allows the dialogue unit to respond appropriately according to the target person's emotions, resulting in more natural conversations.

[0096] The monitoring unit can monitor the living environment of the subject and issue appropriate alerts in response to changes in the environment. For example, if the room temperature changes suddenly, the monitoring unit can prompt the subject to take appropriate action. The monitoring unit can also monitor the lighting status and issue an alert if the lights are not turned on at night. Furthermore, the monitoring unit can analyze the subject's movements and issue an alert if it detects abnormal movements. This ensures the safety of the subject's living environment.

[0097] The communication unit can estimate the emotion of the subject and determine the urgency of contact based on the estimated emotion. For example, if the subject is feeling a strong sense of loneliness, the communication unit can set the urgency to high and quickly contact family and friends. Also, if the subject is relaxed, the communication unit can set the urgency of contact to low. Furthermore, if the subject is feeling stressed, the communication unit can contact the subject with a medium level of urgency. This makes it possible to contact the subject appropriately according to their emotion.

[0098] The dialogue unit can select topics based on the subject's hobbies and interests. For example, if the subject likes music, it can talk about the latest music. If the subject likes gardening, it can talk about how to grow plants. Furthermore, if the subject likes reading, it can talk about books that the subject has recently read. In this way, the dialogue unit can provide appropriate topics according to the subject's hobbies and interests.

[0099] The monitoring unit can estimate the subject's emotions and adjust the frequency of monitoring based on the estimated emotions. For example, if the subject feels lonely, the monitoring unit can monitor more frequently. If the subject feels relaxed, the monitoring unit can also reduce the frequency of monitoring. Furthermore, if the subject feels stressed, the monitoring unit can strengthen monitoring of the subject's health condition. This enables appropriate monitoring according to the subject's emotions.

[0100] During the dialogue, the dialogue unit can refer to the subject's past conversation history to provide a more personalized response. For example, the dialogue unit can revisit a hobby that the subject previously mentioned. It can also continue the conversation by referring to a story about the subject's family that the subject previously mentioned. It can also follow up on a health condition that the subject previously mentioned. This allows the dialogue unit to provide a personalized response to the subject.

[0101] During monitoring, the monitoring unit can detect abnormalities early by referring to the subject's past health data. For example, the monitoring unit can detect abnormal fluctuations by referring to the subject's past blood pressure data. The monitoring unit can also detect fever early by referring to the subject's past body temperature data. Furthermore, the monitoring unit can also detect abnormal heartbeats by referring to the subject's past heart rate data. In this way, the monitoring unit can detect abnormalities early by referring to past health data.

[0102] When contacting the subject, the communication unit can customize the content of the communication based on the subject's current situation. For example, if the subject complains of feeling unwell, information about the subject's health can be included in the content of the communication. Also, if the subject feels lonely, information about psychological support can be included in the content of the communication. Furthermore, if the subject is in an emergency, information about emergency response can be included in the content of the communication. This allows the communication unit to provide appropriate content of the communication based on the subject's current situation.

[0103] The dialogue unit can estimate the emotion of the subject and adjust the frequency of conversation based on the estimated emotion. For example, if the subject feels lonely, the dialogue unit can have frequent conversations. If the subject is busy, the dialogue unit can reduce the frequency of conversations. Furthermore, if the subject is relaxed, the dialogue unit can have conversations at an appropriate frequency. In this way, the dialogue unit can provide an appropriate frequency of conversation according to the subject's emotion.

[0104] The processing flow of the second embodiment will be briefly explained below.

[0105] Step 1: The dialogue unit has a conversation with the subject. For example, the dialogue unit listens to what the subject says and provides an appropriate response. The dialogue unit uses AI to analyze what the subject says and generate an appropriate response. For example, if the subject says, "The weather is nice today," the AI ​​will respond, "Yes, it's sunny today." The dialogue unit can also have regular conversations with the subject. For example, the dialogue unit may have a conversation with the subject at a set time every day. Step 2: The monitoring unit monitors the living conditions of the subject based on the conversation conducted by the dialogue unit. For example, the monitoring unit analyzes the subject's tone of voice and the content of what is said to determine their health condition and mood. The monitoring unit uses AI to analyze the subject's tone of voice and the content of what is said to determine their health condition and mood. For example, if the subject's voice tone is low, the monitoring unit may suspect that they are in poor health. The monitoring unit can also determine whether they are feeling lonely based on the content of what the subject is saying. Step 3: The communication unit makes an emergency contact based on the living conditions monitored by the monitoring unit. For example, if the subject complains of feeling unwell, the communication unit automatically contacts the subject's family or a medical institution. The communication unit uses AI to analyze the subject's living conditions and determine the need for emergency contact. For example, if the subject says they are "feeling unwell," the communication unit will contact their family. The communication unit can also contact a medical institution if the subject's health condition worsens.

[0106] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0107] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> Examples of generative AIs include the data generation model 58, such as a neural network model (e.g., a neural network model), and a neural network model (e.g., a neural network model). The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating speech, text data indicating text, and image data indicating an image is also input to the data generation model 58. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specification processing unit 290 performs the above-mentioned specification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0108] Furthermore, the processing by the data processing system 10 described above is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart device 14, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart device 14. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the smart device 14 or an external device, and the smart device 14 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0109] The correspondence between each part and the device or control part is not limited to the example described above, and various modifications are possible.

[0110] [Second embodiment] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0111] 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0112] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0113] 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.

[0114] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0115] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0116] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0117] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0118] 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.

[0119] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0120] In the smart glasses 214, the specific processing is performed by the processor 46. A specific processing program 60 is stored in the storage 50. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. The smart glasses 214 also have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0121] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0122] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0123] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0124] The data processing system 210 according to the second embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 210 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart glasses 214, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart glasses 214. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the smart glasses 214 or an external device, etc., and the smart glasses 214 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0125] The correspondence between each part and the device or control part is not limited to the example described above, and various modifications are possible.

[0126] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0127] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

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

[0129] The 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.

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

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

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

[0133] 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.

[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 a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0136] In the headset type terminal 314, the identification process is performed by the processor 46. A identification program 60 is stored in the storage 50. The processor 46 reads the identification program 60 from the storage 50 and executes the read identification program 60 on the RAM 48. The identification process is realized by the processor 46 operating as a control unit 46A in accordance with the identification program 60 executed on the RAM 48. Note that the headset type terminal 314 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.

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

[0138] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

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

[0140] The data processing system 310 according to the third embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 310 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the headset type terminal 314, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the headset type terminal 314. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the headset type terminal 314 or an external device, etc., and the headset type terminal 314 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0141] The correspondence between each part and the device or control part is not limited to the example described above, and various modifications are possible.

[0142] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0143] 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

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

[0145] 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.

[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 audio according to instructions from the processor 46.

[0147] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS image sensor or a CCD image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[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 carried out in a secure state.

[0149] The control object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[0150] 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.

[0151] 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.

[0152] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0153] In the robot 414, the processor 46 performs the identification process. The storage 50 stores the identification program 60. The processor 46 reads the identification program 60 from the storage 50 and executes the read identification program 60 on the RAM 48. The identification process is realized by the processor 46 operating as the control unit 46A in accordance with the identification program 60 executed on the RAM 48. The robot 414 also has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can perform the same process as the identification processing unit 290 using these models.

[0154] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0155] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[0156] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0157] The data processing system 410 according to the fourth embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 410 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the robot 414, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the robot 414. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the robot 414 or an external device, etc., and the robot 414 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0158] The correspondence between each part and the device or control part is not limited to the example described above, and various modifications are possible.

[0159] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0160] FIG. 9 illustrates an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and behaviors arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion encompasses both emotions and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[0161] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[0162] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[0163] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is expressed, and when they approach the ideal, a state of pleasure is expressed. Emotions can also be created for robots, cars, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is expressed, and when they approach the ideal, a state of pleasure is expressed. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on speech emotion recognition and brain physiological signal analysis systems for emotions, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the area called "reaction," where sensation is dominant. The right half of the emotion map lists emotions belonging to the area called "situation," where situational awareness is dominant.

[0164] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[0165] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[0166] 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.

[0167] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[0168] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[0169] 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.

[0170] The hardware resource for executing a specific process can be any of the following types of processors: A processor, for example, is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. A processor also includes a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[0171] The hardware resource that executes the specific process may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific process may be a single processor.

[0172] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[0173] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[0174] In the above example, the first to fourth embodiments have been described separately, but some or all of these embodiments may be combined. The smart device 14, smart glasses 214, headset terminal 314, and robot 414 are merely examples, and they may be combined, or other devices may be used. In the above example, the first and second embodiments have been described separately, but they may be combined.

[0175] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[0176] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[0177] [Explanation of symbols]

[0178] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot

Claims

1. A dialogue section that converses with the target person; a monitoring unit that monitors the living conditions of the subject based on the conversation carried out by the dialogue unit; a contact unit that makes an emergency contact based on the living conditions monitored by the monitoring unit; Equipped with A system characterized by:

2. The dialogue unit Listen to the person and respond appropriately 2. The system of claim 1.

3. The monitoring unit Analyze the subject's tone of voice and the content of their speech to determine their health and mood 2. The system of claim 1.

4. The communication unit If the subject complains of feeling unwell, the system will automatically contact their family or a medical institution.

2. The system of claim 1.

5. The dialogue unit Talk to your target audience regularly 2. The system of claim 1.

6. The monitoring unit Regularly monitor the living conditions of the subjects 2. The system of claim 1.

7. The dialogue unit Inferring the target person's emotions and adjusting the tone and content of responses based on the estimated emotions 2. The system of claim 1.

8. The dialogue unit During a conversation, refer to the target person's past conversation history to provide a more personalized response 2. The system of claim 1.

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