System

Abstract

An object of the system according to the embodiment is to comprehensively support the daily life of elderly people and disabled people.SOLUTION: A system according to an embodiment includes a daily life assisting unit, a medicine managing unit, a social connection promoting unit, and a customizing unit. The daily life assisting unit assists daily life. The medicine management unit manages medicines. The social connection promoting unit promotes a social connection. The customization unit performs customization according to individual needs.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 support the daily lives of elderly and disabled people, and there is room for improvement.

[0005] The system according to the embodiment aims to provide comprehensive support for the daily lives of elderly people and people with disabilities. [Means for solving the problem]

[0006] The system according to the embodiment includes a daily life assistance unit, a medication management unit, a social connection promotion unit, and a customization unit. The daily life assistance unit provides assistance with daily life. The medication management unit manages medications. The social connection promotion unit promotes social connections. The customization unit customizes the system to meet individual needs. [Effects of the Invention]

[0007] The system according to the embodiment can comprehensively support the daily lives of elderly people and people with disabilities. [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) The 360-degree AI nursing care robot system according to an embodiment of the present invention is a revolutionary system for supporting the independence of elderly people and people with disabilities. This system provides assistance with daily activities, medication management, promotion of social connections, and customization to meet individual needs. As a result, the 360-degree AI nursing care robot system can comprehensively support the independence of elderly people and people with disabilities.

[0029] A 360-degree nursing care AI robot system according to an embodiment includes a daily life assistance unit, a medication management unit, a social connection promotion unit, and a customization unit. The daily life assistance unit supports the user's daily life. For example, it helps with housework such as meal preparation, cleaning, and laundry. It also assists with mobility and bathing. The daily life assistance unit, for example, prepares meals based on the user's preferred breakfast time. The medication management unit manages the user's medication. For example, it keeps track of the user's medication schedule and provides medication at the appropriate time. It also monitors the remaining medication and suggests refilling as needed. For example, if the user needs to take medication at a specific time every day, the medication management unit provides the medication at that time to prevent forgetting. The social connection promotion unit promotes the user's social connections. For example, it supports communication with friends and family to reduce feelings of loneliness. For example, the social connection promotion unit helps set up video calls and send messages. It also provides information about local events and activities and encourages participation. The customization unit customizes the system to meet the user's individual needs. For example, the system learns the user's health condition, lifestyle habits, and preferences and provides optimal services based on that information. For example, if the user has specific dietary restrictions, the customization unit prepares meals that meet those restrictions. It also suggests appropriate exercise programs tailored to the user's exercise habits. This allows the 360-degree nursing care AI robot system according to the embodiment to comprehensively support the independence of elderly people and people with disabilities. For example, it can reduce the burden on users by assisting them with daily activities and maintain their health by managing their medications. It can also support the user's mental health by promoting social connections. Furthermore, customization to meet individual needs can provide optimal services to users.

[0030] The daily life assistance unit detects physical movements using sensors, and the generation AI can provide optimal movement assistance in real time. For example, the daily life assistance unit monitors the user's walking movements and automatically provides assistance if the user loses balance. For example, if it is determined that there is a high risk of falling, the robot will step in to support the user. The daily life assistance unit can also detect when the user lifts an object and provide assistance when carrying a heavy object. For example, the robot will support part of the weight when lifting a heavy load. The daily life assistance unit can also analyze the user's sitting-to-standing movements and provide support when standing up. For example, the robot will lend a hand when standing up from a chair. This makes it possible to assist the user's physical movements.

[0031] The daily life assistance unit can learn the user's food preferences and allergy information and automatically generate individually customized meal menus. For example, the daily life assistance unit analyzes the user's past meal history and proposes customized menus based on the user's preferences and allergy information. For example, it automatically generates menus that avoid specific ingredients. The daily life assistance unit also considers the user's health condition and proposes nutritionally balanced meal menus. For example, it provides low-carbohydrate menus to a diabetic user. The daily life assistance unit also learns the user's meal times and frequency and provides meals at the optimal timing. For example, it prepares meals to match the user's preferred breakfast time. This makes it possible to individually customize the user's meals.

[0032] The medication management unit can analyze health data in real time and optimize the timing of medication to maximize its effectiveness. For example, the medication management unit analyzes the user's health data and suggests the optimal timing of medication to maximize its effectiveness. For example, it adjusts medication times based on blood pressure and heart rate. The medication management unit also learns the user's lifestyle and optimizes medication timing to maximize its effectiveness. For example, it adjusts medication times to match meal and exercise timings. The medication management unit also monitors the user's health condition in real time and dynamically adjusts medication timing to maximize its effectiveness. For example, it changes medication times according to changes in physical condition. This makes it possible to optimize medication timing to maximize its effectiveness.

[0033] The medication management unit can monitor medication side effects and send alerts to medical professionals as necessary. For example, the medication management unit monitors the user's health data and sends alerts to medical professionals if medication side effects are suspected. For example, it detects abnormal heart rate or blood pressure fluctuations. The medication management unit also monitors the user's symptoms in real time and notifies medical professionals if side effects occur. For example, it detects symptoms of nausea and dizziness. The medication management unit also analyzes the user's medication history and sends alerts to medical professionals if there is a high risk of side effects. For example, it evaluates the risk of side effects from a specific medication combination. This makes it possible to monitor medication side effects and send alerts to medical professionals.

[0034] The social connection promotion unit can automatically recommend online communities and group activities based on interests and hobbies. For example, the social connection promotion unit analyzes a user's interests and hobbies and recommends related online communities and group activities. For example, it introduces hobby forums and social networking groups. The social connection promotion unit also recommends online events and webinars that match the user's interests and hobbies based on the user's past activity history. For example, it suggests online seminars on specific topics. The social connection promotion unit also monitors the user's interests and hobbies in real time and recommends online communities and group activities based on newly discovered interests. For example, it suggests online classes related to a new hobby. In this way, online communities and group activities can be recommended based on the user's interests and hobbies.

[0035] The customization unit can learn the user's health data and lifestyle habits and automatically generate an individually optimized health management program. The customization unit, for example, analyzes the user's health data and automatically generates an individually optimized health management program. For example, it suggests an exercise program based on blood pressure and heart rate. The customization unit also learns the user's lifestyle habits and automatically generates an individually optimized meal plan. For example, it suggests a nutritionally balanced menu based on meal times and contents. The customization unit also monitors the user's health condition in real time and dynamically generates an individually optimized health management program. For example, it adjusts exercise and meal plans according to changes in physical condition. This allows the health management program to be optimized based on the user's health data and lifestyle habits.

[0036] The customization unit can propose customized travel plans and leisure activities according to the user's needs. The customization unit proposes customized travel plans based on the user's interests and preferences, for example. For example, it proposes natural parks and hiking trails for a user who loves nature. The customization unit also proposes customized leisure activities taking into account the user's health condition and physical strength. For example, it proposes walking tours and relaxation resorts according to the user's physical strength. The customization unit also learns the user's past travel history and preferences and automatically generates customized travel plans. For example, it proposes new travel plans based on places visited in the past and favorite activities. This makes it possible to propose travel plans and leisure activities according to the user's needs.

[0037] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0038] The 360-degree care AI robot system can further include an entertainment provider. The entertainment provider can provide various entertainment based on the user's hobbies and interests. For example, if the user likes movies, the entertainment provider can stream the latest movies and classic movies. If the user enjoys music, the entertainment provider can play music of the user's preferred genre. Furthermore, the entertainment provider can suggest online events and live streaming that the user can participate in. This can bring enjoyment to the user's life and support their mental health.

[0039] The daily living assistance unit may further include a health monitoring unit. The health monitoring unit can monitor the user's health condition in real time and send an alert if an abnormality is detected. For example, the health monitoring unit can constantly monitor the user's heart rate and blood pressure and notify a medical professional if an abnormal value is detected. The health monitoring unit can also measure the user's body temperature and oxygen saturation and send an alert if an abnormality is detected. Furthermore, the health monitoring unit can analyze the user's sleep patterns and provide advice to improve the quality of sleep. This allows for comprehensive support of the user's health.

[0040] The medication management unit may further include a medication assistant unit. The medication assistant unit can support the user in taking medication correctly. For example, the medication assistant unit can set a reminder so that the user does not forget to take the medication. The medication assistant unit can also check whether the user is taking the medication correctly and send an alert if the user takes the medication incorrectly. Furthermore, the medication assistant unit can also prompt the user to consult a medical professional if the user experiences side effects from the medication. This allows the user to take the medication correctly and maintain their health.

[0041] The medication management unit can further include a medication interaction check unit. The medication interaction check unit can check the interactions of medications the user is taking to ensure there are no dangerous combinations. For example, if the user is prescribed a new medication, it can check whether that medication interacts with existing medications. The medication interaction check unit can also check for interactions when the user takes over-the-counter medications or supplements. Furthermore, the medication interaction check unit can check the interactions of all medications even if the user has been prescribed medications by multiple medical institutions. This can support the user in taking medications safely.

[0042] The social connection promotion unit may further include a hobby discovery unit. The hobby discovery unit can suggest new hobbies and activities based on the user's interests and preferences. For example, if the user is interested in art, the hobby discovery unit can suggest online art classes and workshops. If the user is interested in sports, the hobby discovery unit can introduce local sports clubs and online fitness classes. Furthermore, the hobby discovery unit can suggest new hobbies and activities based on the user's past activity history. This allows the user to find new hobbies and add fun to their life.

[0043] The processing flow of the first embodiment will be briefly explained below.

[0044] Step 1: The daily life assistance unit supports the user in their daily life. For example, it helps with household chores such as preparing meals, cleaning, and laundry. It also assists with mobility and bathing. For example, the daily life assistance unit prepares meals according to the user's preferred breakfast time. Step 2: The medication management unit manages the user's medication. For example, it keeps track of medication schedules and provides medication at the appropriate times. It also monitors remaining medication and suggests refilling as needed. For example, if the user needs to take medication at a specific time every day, the medication management unit provides the medication at that time, preventing the user from forgetting to take it. Step 3: The social connection promoter promotes the user's social connections. For example, it supports communication with friends and family and reduces feelings of loneliness. For example, the social connection promoter helps set up video calls and send messages. It also provides information about local events and activities and encourages participation. Step 4: The customization unit customizes the service to meet the user's individual needs. For example, it learns the user's health condition, lifestyle habits, and preferences and provides optimal services based on that information. For example, if the user has specific dietary restrictions, the customization unit prepares meals that meet those restrictions. It also suggests appropriate exercise programs tailored to the user's exercise habits.

[0045] (Example 2) The 360-degree AI nursing care robot system according to an embodiment of the present invention is a revolutionary system for supporting the independence of elderly people and people with disabilities. This system provides assistance with daily activities, medication management, promotion of social connections, and customization to meet individual needs. As a result, the 360-degree AI nursing care robot system can comprehensively support the independence of elderly people and people with disabilities.

[0046] A 360-degree nursing care AI robot system according to an embodiment includes a daily life assistance unit, a medication management unit, a social connection promotion unit, and a customization unit. The daily life assistance unit supports the user's daily life. For example, it helps with housework such as meal preparation, cleaning, and laundry. It also assists with mobility and bathing. The daily life assistance unit, for example, prepares meals based on the user's preferred breakfast time. The medication management unit manages the user's medication. For example, it keeps track of the user's medication schedule and provides medication at the appropriate time. It also monitors the remaining medication and suggests refilling as needed. For example, if the user needs to take medication at a specific time every day, the medication management unit provides the medication at that time to prevent forgetting. The social connection promotion unit promotes the user's social connections. For example, it supports communication with friends and family to reduce feelings of loneliness. For example, the social connection promotion unit helps set up video calls and send messages. It also provides information about local events and activities and encourages participation. The customization unit customizes the system to meet the user's individual needs. For example, the system learns the user's health condition, lifestyle habits, and preferences and provides optimal services based on that information. For example, if the user has specific dietary restrictions, the customization unit prepares meals that meet those restrictions. It also suggests appropriate exercise programs tailored to the user's exercise habits. This allows the 360-degree nursing care AI robot system according to the embodiment to comprehensively support the independence of elderly people and people with disabilities. For example, it can reduce the burden on users by assisting them with daily activities and maintain their health by managing their medications. It can also support the user's mental health by promoting social connections. Furthermore, customization to meet individual needs can provide optimal services to users.

[0047] The daily life assistance unit can monitor the user's emotional state in real time and suggest relaxation activities to reduce stress and anxiety. For example, the daily life assistance unit analyzes the user's facial expressions and vocal tone to monitor the user's emotional state in real time. For example, if it determines that stress is increasing, it provides relaxation music or a meditation guide. The daily life assistance unit also detects the user's heart rate and galvanic skin response using sensors to estimate the user's emotional state. For example, it suggests deep breathing exercises when anxiety is increasing. The daily life assistance unit also learns the user's behavioral patterns and predicts changes in the user's emotional state. For example, if stress tends to increase during a certain time of day, it suggests relaxation activities for that time of day. This can reduce the user's stress and anxiety.

[0048] The daily life assistance unit detects physical movements using sensors, and the generation AI can provide optimal movement assistance in real time. For example, the daily life assistance unit monitors the user's walking movements and automatically provides assistance if the user loses balance. For example, if it is determined that there is a high risk of falling, the robot will step in to support the user. The daily life assistance unit can also detect when the user lifts an object and provide assistance when carrying a heavy object. For example, the robot will support part of the weight when lifting a heavy load. The daily life assistance unit can also analyze the user's sitting-to-standing movements and provide support when standing up. For example, the robot will lend a hand when standing up from a chair. This makes it possible to assist the user's physical movements.

[0049] The daily life assistance unit can learn the user's food preferences and allergy information and automatically generate individually customized meal menus. For example, the daily life assistance unit analyzes the user's past meal history and proposes customized menus based on the user's preferences and allergy information. For example, it automatically generates menus that avoid specific ingredients. The daily life assistance unit also considers the user's health condition and proposes nutritionally balanced meal menus. For example, it provides low-carbohydrate menus to a diabetic user. The daily life assistance unit also learns the user's meal times and frequency and provides meals at the optimal timing. For example, it prepares meals to match the user's preferred breakfast time. This makes it possible to individually customize the user's meals.

[0050] The medicine management unit can monitor the user's emotional state and provide a relaxing environment when taking medicine. For example, the medicine management unit analyzes the user's emotional state and provides music that helps the user relax when taking medicine. For example, it plays music that has a relaxing effect. The medicine management unit also monitors the user's emotional state and creates a relaxing environment when taking medicine. For example, it adjusts the lighting to create a relaxing atmosphere. The medicine management unit also monitors the user's emotional state in real time and provides a relaxing aroma when taking medicine. For example, it uses aromatic oils that have a relaxing effect. This allows the user to take medicine in a relaxed state.

[0051] The medication management unit can analyze health data in real time and optimize the timing of medication to maximize its effectiveness. For example, the medication management unit analyzes the user's health data and suggests the optimal timing of medication to maximize its effectiveness. For example, it adjusts medication times based on blood pressure and heart rate. The medication management unit also learns the user's lifestyle and optimizes medication timing to maximize its effectiveness. For example, it adjusts medication times to match meal and exercise timings. The medication management unit also monitors the user's health condition in real time and dynamically adjusts medication timing to maximize its effectiveness. For example, it changes medication times according to changes in physical condition. This makes it possible to optimize medication timing to maximize its effectiveness.

[0052] The medication management unit can monitor medication side effects and send alerts to medical professionals as necessary. For example, the medication management unit monitors the user's health data and sends alerts to medical professionals if medication side effects are suspected. For example, it detects abnormal heart rate or blood pressure fluctuations. The medication management unit also monitors the user's symptoms in real time and notifies medical professionals if side effects occur. For example, it detects symptoms of nausea and dizziness. The medication management unit also analyzes the user's medication history and sends alerts to medical professionals if there is a high risk of side effects. For example, it evaluates the risk of side effects from a specific medication combination. This makes it possible to monitor medication side effects and send alerts to medical professionals.

[0053] The social connection promotion unit can monitor the user's emotional state and suggest communication activities to reduce the sense of loneliness. For example, the social connection promotion unit analyzes the user's emotional state and suggests communication activities to reduce the sense of loneliness. For example, it suggests video calls with friends and family. The social connection promotion unit also monitors the user's emotional state and suggests online communities and group activities to reduce the sense of loneliness. For example, it introduces online circles based on hobbies and interests. The social connection promotion unit also monitors the user's emotional state in real time and provides interactive activities to reduce the sense of loneliness. For example, it suggests online games and virtual events. This can reduce the user's sense of loneliness.

[0054] The social connection promotion unit can automatically recommend online communities and group activities based on interests and hobbies. For example, the social connection promotion unit analyzes a user's interests and hobbies and recommends related online communities and group activities. For example, it introduces hobby forums and social networking groups. The social connection promotion unit also recommends online events and webinars that match the user's interests and hobbies based on the user's past activity history. For example, it suggests online seminars on specific topics. The social connection promotion unit also monitors the user's interests and hobbies in real time and recommends online communities and group activities based on newly discovered interests. For example, it suggests online classes related to a new hobby. In this way, online communities and group activities can be recommended based on the user's interests and hobbies.

[0055] The social connection promotion unit can use the emotion estimation function to generate a dialogue scenario for eliciting positive emotions. The social connection promotion unit, for example, analyzes the user's emotional state and generates a dialogue scenario for eliciting positive emotions. For example, the dialogue proceeds based on topics that interest the user. The social connection promotion unit also provides an interactive dialogue scenario for eliciting positive emotions based on the user's emotion estimation data. For example, it poses questions about the user's favorite topics or hobbies. The social connection promotion unit also monitors the user's emotional state in real time and dynamically generates a dialogue scenario for eliciting positive emotions. For example, it adjusts the content of the dialogue depending on the user's reaction. In this way, a dialogue scenario for eliciting positive emotions from the user can be generated.

[0056] The customization unit can monitor the emotional state and provide a customized service according to the emotion. For example, the customization unit analyzes the user's emotional state and provides a customized service according to the emotion. For example, it provides a relaxation service when stress is high. The customization unit also monitors the user's emotional state and provides customized entertainment according to the emotion. For example, it suggests movies or music when the emotion is calm. The customization unit also monitors the user's emotional state in real time and provides a customized exercise program according to the emotion. For example, it suggests yoga or meditation when the emotion is high. In this way, it is possible to provide a customized service according to the user's emotion.

[0057] The customization unit can learn the user's health data and lifestyle habits and automatically generate an individually optimized health management program. The customization unit, for example, analyzes the user's health data and automatically generates an individually optimized health management program. For example, it suggests an exercise program based on blood pressure and heart rate. The customization unit also learns the user's lifestyle habits and automatically generates an individually optimized meal plan. For example, it suggests a nutritionally balanced menu based on meal times and contents. The customization unit also monitors the user's health condition in real time and dynamically generates an individually optimized health management program. For example, it adjusts exercise and meal plans according to changes in physical condition. This allows the health management program to be optimized based on the user's health data and lifestyle habits.

[0058] The customization unit can use the emotion estimation function to provide customized entertainment for eliciting positive emotions. For example, the customization unit analyzes the user's emotional state and provides customized entertainment for eliciting positive emotions. For example, it suggests movies or music that will elicit emotions. The customization unit also provides interactive entertainment for eliciting positive emotions based on the user's emotion estimation data. For example, it suggests games or apps that will elicit emotions. The customization unit also monitors the user's emotional state in real time and dynamically provides customized entertainment for eliciting positive emotions. For example, it suggests entertainment at moments when emotions are heightened. In this way, entertainment for eliciting positive emotions can be provided to the user.

[0059] The customization unit can use the emotion estimation function to suggest a customized exercise program according to the emotion. For example, the customization unit analyzes the user's emotional state and suggests a customized exercise program according to the emotion. For example, it suggests relaxation yoga when stress is high. The customization unit also monitors the user's emotional state and suggests customized exercises according to the emotion. For example, it suggests light jogging when the emotion is calm. The customization unit also monitors the user's emotional state in real time and dynamically suggests a customized fitness program according to the emotion. For example, it suggests energetic exercises when the emotion is high. In this way, it is possible to suggest an exercise program according to the user's emotion.

[0060] The customization unit can propose customized travel plans and leisure activities according to the user's needs. The customization unit proposes customized travel plans based on the user's interests and preferences, for example. For example, it proposes natural parks and hiking trails for a user who loves nature. The customization unit also proposes customized leisure activities taking into account the user's health condition and physical strength. For example, it proposes walking tours and relaxation resorts according to the user's physical strength. The customization unit also learns the user's past travel history and preferences and automatically generates customized travel plans. For example, it proposes new travel plans based on places visited in the past and favorite activities. This makes it possible to propose travel plans and leisure activities according to the user's needs.

[0061] The customization unit can use the emotion estimation function to identify the most relaxing environment for the user and provide that environment. The customization unit, for example, analyzes the user's emotional state and identifies the most relaxing environment. For example, it provides music and lighting that soothes the emotions. The customization unit can also identify the most relaxing environment based on the user's emotion estimation data and provide that environment. For example, it can suggest aromas and temperature settings that have a relaxing effect. The customization unit can also monitor the user's emotional state in real time and dynamically provide the most relaxing environment. For example, it can create a relaxing environment at the moment when emotions are heightened. This allows the user to be provided with the most relaxing environment.

[0062] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0063] The 360-degree care AI robot system can further include an entertainment provider. The entertainment provider can provide various entertainment based on the user's hobbies and interests. For example, if the user likes movies, the entertainment provider can stream the latest movies and classic movies. If the user enjoys music, the entertainment provider can play music of the user's preferred genre. Furthermore, the entertainment provider can suggest online events and live streaming that the user can participate in. This can bring enjoyment to the user's life and support their mental health.

[0064] The daily life assistance unit can use its emotion estimation function to suggest relaxation activities based on the user's emotional state. For example, if the user is feeling stressed, it can provide relaxation music or a meditation guide. If the user is feeling anxious, it can suggest deep breathing exercises or relaxation yoga. Furthermore, it can monitor the user's emotional state in real time and dynamically adjust relaxation activities according to changes in emotion. This can reduce the user's stress and anxiety and support their mental health.

[0065] The daily living assistance unit may further include a health monitoring unit. The health monitoring unit can monitor the user's health condition in real time and send an alert if an abnormality is detected. For example, the health monitoring unit can constantly monitor the user's heart rate and blood pressure and notify a medical professional if an abnormal value is detected. The health monitoring unit can also measure the user's body temperature and oxygen saturation and send an alert if an abnormality is detected. Furthermore, the health monitoring unit can analyze the user's sleep patterns and provide advice to improve the quality of sleep. This allows for comprehensive support of the user's health.

[0066] The daily life assistance unit can use the emotion estimation function to suggest a meal menu that corresponds to the user's emotional state. For example, if the user is feeling stressed, it can suggest a menu that uses ingredients that have a relaxing effect. If the user is feeling depressed, it can suggest a menu that uses ingredients that have a mood-boosting effect. Furthermore, it can monitor the user's emotional state in real time and dynamically adjust the meal menu according to changes in emotion. This makes it possible to provide meals that correspond to the user's emotional state and support their mental health.

[0067] The medication management unit may further include a medication assistant unit. The medication assistant unit can support the user in taking medication correctly. For example, the medication assistant unit can set a reminder so that the user does not forget to take the medication. The medication assistant unit can also check whether the user is taking the medication correctly and send an alert if the user takes the medication incorrectly. Furthermore, the medication assistant unit can also prompt the user to consult a medical professional if the user experiences side effects from the medication. This allows the user to take the medication correctly and maintain their health.

[0068] The medication management unit can use the emotion estimation function to provide medication support according to the user's emotional state. For example, if the user is feeling stressed, medication can be provided while playing relaxing music. Alternatively, if the user is feeling anxious, medication can be provided in a relaxing environment. Furthermore, the system can monitor the user's emotional state in real time and dynamically adjust medication support according to changes in emotion. This provides an environment where the user can take medication in a relaxed state, reducing the stress of taking medication.

[0069] The medication management unit can further include a medication interaction check unit. The medication interaction check unit can check the interactions of medications the user is taking to ensure there are no dangerous combinations. For example, if the user is prescribed a new medication, it can check whether that medication interacts with existing medications. The medication interaction check unit can also check for interactions when the user takes over-the-counter medications or supplements. Furthermore, the medication interaction check unit can check the interactions of all medications even if the user has been prescribed medications by multiple medical institutions. This can support the user in taking medications safely.

[0070] The social connection promotion unit can use the emotion estimation function to suggest communication activities according to the user's emotional state. For example, if the user feels lonely, it can suggest a video call with friends or family. If the user feels stressed, it can suggest online communities or group activities that will help them relax. Furthermore, it can monitor the user's emotional state in real time and dynamically adjust communication activities according to changes in emotion. This allows the system to provide communication activities according to the user's emotional state and reduce feelings of loneliness and stress.

[0071] The social connection promotion unit may further include a hobby discovery unit. The hobby discovery unit can suggest new hobbies and activities based on the user's interests and preferences. For example, if the user is interested in art, the hobby discovery unit can suggest online art classes and workshops. If the user is interested in sports, the hobby discovery unit can introduce local sports clubs and online fitness classes. Furthermore, the hobby discovery unit can suggest new hobbies and activities based on the user's past activity history. This allows the user to find new hobbies and add fun to their life.

[0072] The customization unit can use the emotion estimation function to provide entertainment customized according to the user's emotional state. For example, if the user is feeling stressed, it can suggest relaxing movies or music. If the user is feeling depressed, it can provide entertainment that will lift their spirits. Furthermore, it can monitor the user's emotional state in real time and dynamically adjust the entertainment according to changes in emotion. This makes it possible to provide entertainment according to the user's emotional state and support their mental health.

[0073] The processing flow of the second embodiment will be briefly explained below.

[0074] Step 1: The daily life assistance unit supports the user in their daily life. For example, it helps with household chores such as preparing meals, cleaning, and laundry. It also assists with mobility and bathing. For example, the daily life assistance unit prepares meals according to the user's preferred breakfast time. Step 2: The medication management unit manages the user's medication. For example, it keeps track of medication schedules and provides medication at the appropriate times. It also monitors remaining medication and suggests refilling as needed. For example, if the user needs to take medication at a specific time every day, the medication management unit provides the medication at that time, preventing the user from forgetting to take it. Step 3: The social connection promoter promotes the user's social connections. For example, it supports communication with friends and family and reduces feelings of loneliness. For example, the social connection promoter helps set up video calls and send messages. It also provides information about local events and activities and encourages participation. Step 4: The customization unit customizes the service to meet the user's individual needs. For example, it learns the user's health condition, lifestyle habits, and preferences and provides optimal services based on that information. For example, if the user has specific dietary restrictions, the customization unit prepares meals that meet those restrictions. It also suggests appropriate exercise programs tailored to the user's exercise habits.

[0075] 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.

[0076] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> Examples of generative AIs include the data generation model 58, such as a neural network model (e.g., a neural network model), and a neural network model (e.g., a neural network model). The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating speech, text data indicating text, and image data indicating an image is also input to the data generation model 58. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specification processing unit 290 performs the above-mentioned specification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0077] 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.

[0078] [Second embodiment] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0079] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0080] 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.

[0081] 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.

[0082] 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.

[0083] 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).

[0084] 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.

[0085] 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.

[0086] 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.

[0087] 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.

[0088] 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.

[0089] 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.

[0090] 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.

[0091] 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.

[0092] 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.

[0093] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0094] 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.

[0095] 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.

[0096] 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.

[0097] 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.

[0098] 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).

[0099] 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.

[0100] 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.

[0101] 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.

[0102] 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.

[0103] In the headset type terminal 314, the specific processing is performed by the processor 46. A specific processing program 60 is stored in the storage 50. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. Note that the 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 specific processing unit 290 using these models.

[0104] 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.

[0105] 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.

[0106] 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.

[0107] 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.

[0108] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0109] 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.

[0110] 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.

[0111] 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.

[0112] 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.

[0113] 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).

[0114] 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.

[0115] 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.

[0116] 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.

[0117] 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.

[0118] 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.

[0119] In the robot 414, 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 robot 414 has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can also perform processing similar to that of the specific processing unit 290 using these models.

[0120] 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.

[0121] 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.

[0122] 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.

[0123] 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.

[0124] 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.

[0125] 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.

[0126] 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.

[0127] 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).

[0128] 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.

[0129] 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."

[0130] 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.

[0131] 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.

[0132] 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.

[0133] 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.

[0134] 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.

[0135] 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.

[0136] 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.

[0137] 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.

[0138] 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.

[0139] 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.

[0140] 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.

[0141] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference. [Explanation of symbols]

[0142] 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 daily living assistance department that provides assistance with daily living; a drug management department that manages medications; A social connection promotion department that promotes social connections; A customization unit that customizes the system to meet individual needs. A system characterized by:

2. The daily life assistance unit includes: Monitor your emotional state in real time and suggest relaxation activities to reduce stress and anxiety 2. The system of claim 1.

3. The daily life assistance unit includes: Sensors detect physical movements, and generative AI provides optimal movement assistance in real time.

2. The system of claim 1.

4. The daily life assistance unit includes: Learns dietary preferences and allergy information and automatically generates individually customized meal menus 2. The system of claim 1.

5. The medicine management unit Monitor emotional state and provide a relaxing environment when taking medication 2. The system of claim 1.

6. The medicine management unit Analyzing health data in real time to optimize medication timing to maximize effectiveness 2. The system of claim 1.

7. The medicine management unit Monitor side effects of said medication and send alerts to healthcare professionals as needed 2. The system of claim 1.

8. The social connection promotion unit Monitor emotional states and suggest communication activities to reduce feelings of loneliness 2. The system of claim 1.

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