System

Abstract

An object of a system according to an embodiment is to provide quick and accurate information with respect to questions and worries about childcare.SOLUTION: A system includes an input unit, an answer generation unit, and a notification unit. The input unit receives questions and worries of a user. The answer generation unit generates an answer to the question or concern received by the input unit from the latest research or a reliable information source. The notification unit notifies the user of the answer generated by the answer generation unit.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] Conventional technology has made it difficult to quickly obtain accurate information about childcare, and users have had to spend a lot of time trying to resolve their questions and concerns about childcare.

[0005] The system according to the embodiment aims to provide prompt and accurate information in response to questions and concerns about child-rearing. [Means for solving the problem]

[0006] The system according to the embodiment includes an input unit, an answer generation unit, and a notification unit. The input unit accepts questions and concerns from users. The answer generation unit generates answers to the questions and concerns accepted by the input unit based on the latest research and reliable information sources. The notification unit notifies the user of the answers generated by the answer generation unit. [Effects of the Invention]

[0007] The system according to the embodiment can provide prompt and accurate information in response to questions and concerns about child-rearing. [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 nonvolatile storage devices that store various programs, various parameters, etc. Examples of nonvolatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

[0028] (Example 1) The childcare consultation system according to an embodiment of the present invention automatically accepts questions and concerns about childcare, uses a generation AI to provide answers based on the latest research and reliable sources, and is equipped with task invitation and notification functions. As a result, the childcare consultation system can quickly and accurately resolve questions and concerns about childcare and support childcare-related task management.

[0029] A childcare consultation system according to an embodiment includes an input unit, an answer generation unit, and a notification unit. The input unit accepts questions and concerns from users. For example, users can input their questions and concerns by text input or voice input into the app. The input unit also allows users to upload images and videos, and can accept visual information. For example, a user can upload a photo of a rash on their baby and ask a question about the rash. The answer generation unit uses a generation AI to generate answers based on the latest research and reliable sources for the questions and concerns accepted by the input unit. For example, the generation AI uses a text generation AI (e.g., LLM) to generate answers to the user's questions. The generation AI can also analyze visual information and generate answers using a multimodal generation AI. For example, the generation AI analyzes a photo of a rash on a baby and provides the type of rash and how to deal with it. The notification unit notifies the user of the answer generated by the answer generation unit. For example, the notification unit displays the answer to the user using a notification function within the app. The notification unit is also compatible with devices such as smartwatches and smart speakers, and can send notifications to the devices used by the user. For example, the notification unit may notify the smartwatch that "Answer regarding your baby's rash has arrived." This allows the childcare consultation system according to the embodiment to provide quick and accurate answers to the user's questions and concerns. For example, a user can input a question about childcare, the generation AI can provide an answer to that question, and the notification unit can notify the user of the answer, allowing the user to quickly resolve their question.

[0030] The input unit can generate related follow-up questions based on the user's input and collect detailed information. For example, if the user inputs, "What should I do if my baby cries at night?", the AI ​​generates follow-up questions such as, "How often does the baby cry at night?" and "How old is the baby?" to collect detailed information. If the user inputs, "When should I start solid food?", the AI ​​generates follow-up questions such as, "What is the baby's current diet?" and "Does the baby have any allergies?" to collect detailed information. If the user inputs, "What is the vaccination schedule?", the AI ​​generates follow-up questions such as, "What is the baby's date of birth?" and "Does the baby have a history of past vaccinations?" to collect detailed information. This allows the AI ​​to collect more detailed information about the user's questions and concerns and provide highly accurate answers.

[0031] The input unit can analyze the user's past input history and provide personalized advice. For example, if the user previously asked about "your baby's night crying," the AI ​​will ask personalized questions based on that history, such as "Have you tried the previous advice?" or "How is it going since then?" If the user previously asked about "baby food," the AI ​​will ask personalized questions based on that history, such as "Have you put into practice the previous baby food advice?" or "Has there been any change in your baby's diet?" If the user previously asked about "vaccinations," the AI ​​will ask personalized questions based on that history, such as "Have you checked the schedule for the last vaccination?" or "Is the next vaccination scheduled?" This makes it possible to provide more personalized advice based on the user's past input history.

[0032] The input unit allows input using images and videos in addition to text and voice input, and can also analyze visual information. For example, if a user uploads a photo of a rash on their baby and asks, "What is this rash?", the AI ​​will analyze the image and provide the type of rash and how to deal with it. If a user uploads a video of their baby and asks, "Is this movement normal?", the AI ​​will analyze the video and evaluate the normality of the movement. If a user uploads a photo of their baby's meal and asks, "Is this diet appropriate?", the AI ​​will analyze the image and evaluate the appropriateness of the diet. This allows for more detailed advice to be provided by analyzing visual information as well.

[0033] The input unit can link with other childcare apps and devices, integrating data to provide comprehensive advice. For example, the input unit can link with a childcare app used by the user, integrating sleep data and dietary data, and the AI ​​can provide comprehensive advice. For example, the input unit can provide advice such as, "Your sleep time is short, so try taking more naps." The input unit can also link with a childcare device used by the user, integrating body temperature data and heart rate data, and the AI ​​can provide comprehensive advice. For example, the input unit can provide advice such as, "Your temperature is high, so please consult a doctor." The input unit can also link with a calendar app used by the user, integrating vaccination schedules, and the AI ​​can provide comprehensive advice. For example, the input unit can provide advice such as, "The next vaccination is next week." By linking with other childcare apps and devices, more comprehensive advice can be provided.

[0034] The answer generation unit evaluates and provides feedback on answers provided by the user, and can improve the accuracy of the answers based on the evaluation. For example, the answer generation unit evaluates an answer provided by a user such as "Creating a regular rhythm is effective for preventing a baby from crying at night," and the AI ​​improves the accuracy of the answers based on the evaluation. For example, answers with higher ratings are provided preferentially. The answer generation unit also evaluates an answer provided by a user such as "It is common to start solid food at 6 months of age," and the AI ​​improves the accuracy of the answers based on the evaluation. For example, answers with higher ratings are provided preferentially. The answer generation unit also evaluates an answer provided by a user such as "Consult your doctor about vaccination schedules," and the AI ​​improves the accuracy of the answers based on the evaluation. For example, answers with higher ratings are provided preferentially. In this way, the accuracy of the answers can be improved based on user evaluations and feedback.

[0035] The answer generation unit periodically updates the latest research database, enabling it to always provide the latest information. The answer generation unit, for example, uses AI to periodically update the latest childcare-related research database, ensuring that answers provided to users are always based on the latest information. For example, the database is updated when new research results are published. The answer generation unit also uses AI to update the latest research database in real time, enabling answers provided to users to always be based on the latest information. For example, the database is updated immediately after the latest research results are published. The answer generation unit also uses AI to update the latest research database weekly, enabling answers provided to users to always be based on the latest information. For example, the database is updated every Monday. This constantly provides the latest information, enabling it to provide users with highly reliable answers.

[0036] The answer generation unit enables the provision of information in different languages, making it possible to provide advice from an international perspective. The answer generation unit, for example, enables the AI ​​to provide information in different languages, providing child-rearing advice in a language selected by the user. For example, multiple languages ​​such as English, French, and Chinese are supported. The answer generation unit also enables the AI ​​to provide information in different languages, providing child-rearing advice in a language selected by the user. For example, multiple languages ​​such as Spanish, German, and Italian are supported. The answer generation unit also enables the AI ​​to provide information in different languages, providing child-rearing advice in a language selected by the user. For example, multiple languages ​​such as Korean, Russian, and Arabic are supported. This makes it possible to provide information in different languages, making it possible to provide advice from an international perspective.

[0037] The answer generation unit can automatically generate links to related videos and articles, allowing the user to learn more in-depth. For example, when a user asks a question about "baby crying at night," the answer generation unit uses AI to automatically generate links to related videos and articles, allowing the user to learn more in-depth. For example, it provides a link such as "Click here for a video on how to deal with night crying." When a user asks a question about "baby food," the answer generation unit automatically generates links to related videos and articles, allowing the user to learn more in-depth. For example, it provides a link such as "Click here for an article on how to start baby food." When a user asks a question about "vaccinations," the answer generation unit automatically generates links to related videos and articles, allowing the user to learn more in-depth. For example, it provides a link such as "Click here for a video on vaccination schedules." This allows the user to learn more in-depth by providing links to related videos and articles.

[0038] The notification unit can provide notifications at optimal times based on the user's schedule and lifestyle. For example, the notification unit analyzes the user's schedule and provides vaccination notifications at optimal times. For example, the notification unit may provide a notification that "Tomorrow is vaccination day" to coincide with the time the user returns home from work. The notification unit may also analyze the user's lifestyle and provide notifications about regular checkups at optimal times. For example, the notification unit may provide a notification that "You have a regular checkup this week" to coincide with the time the user wakes up in the morning. The notification unit may also analyze the user's schedule and lifestyle and provide notifications about childcare-related tasks at optimal times. For example, the notification unit may provide a notification that "Have you completed this month's vaccinations?" to coincide with the time the user is relaxing. This allows for improved user convenience by providing notifications at optimal times based on the user's schedule and lifestyle.

[0039] The notification unit can customize the notification content and provide reminders that match the user's preferences. For example, the notification unit customizes the notification content for vaccinations based on the user's preferences. For example, it provides a friendly reminder such as, "Tomorrow is vaccination day. Don't forget!" The notification unit also customizes the notification content for regular checkups based on the user's preferences. For example, it provides a friendly reminder such as, "Your regular checkup is this week. Are you ready?" The notification unit also customizes the notification content for childcare-related tasks based on the user's preferences. For example, it provides a friendly reminder such as, "Have you completed this month's vaccinations? Don't forget!" In this way, by customizing the notification content, it is possible to provide reminders that match the user's preferences.

[0040] The notification unit can add a function that allows a user to share tasks with other family members and jointly manage childcare tasks. For example, the notification unit adds a function that allows a user to share childcare tasks with other family members and jointly manage them. For example, notifying all family members of vaccination schedules. The notification unit also adds a function that allows a user to share childcare tasks with other family members and jointly manage them. For example, notifying all family members of regular checkup schedules. The notification unit also adds a function that allows a user to share childcare tasks with other family members and jointly manage them. For example, sharing the progress of childcare-related tasks with all family members. This makes it possible to jointly manage childcare tasks by sharing tasks with other family members.

[0041] The notification unit can expand the notification function to support devices such as smartwatches and smart speakers. For example, if the user is using a smartwatch, the notification unit sends a vaccination notification to the smartwatch. For example, a notification such as "Tomorrow is vaccination day" is displayed on the smartwatch. If the user is using a smart speaker, the notification unit sends a notification of a regular checkup to the smart speaker. For example, a notification such as "You have a regular checkup this week" is sent to the smart speaker by voice. If the user is using a smartphone, the notification unit sends a notification of a childcare-related task to the smartphone. For example, a notification such as "Have you completed your vaccinations this month?" is displayed on the smartphone. In this way, the notification function can be expanded to support devices such as smartwatches and smart speakers.

[0042] The notification unit can automatically set the priority of tasks and give priority to reminders of important tasks. For example, the notification unit uses AI to automatically set the priority of childcare-related tasks and give priority to reminders of important tasks. For example, it gives priority to notifying users of vaccination appointments. The notification unit can also automatically set the priority of childcare-related tasks and give priority to reminders of important tasks. For example, it gives priority to notifying users of regular checkup appointments. The notification unit can also automatically set the priority of childcare-related tasks and give priority to reminders of important tasks. For example, it gives priority to notifying users of the progress of childcare-related tasks. In this way, by automatically setting the priority of tasks, it is possible to give priority to reminders of important tasks.

[0043] The notification unit can work in conjunction with other childcare apps and calendar apps to centralize task management. The notification unit, for example, works in conjunction with a childcare app used by the user to centralize task management. For example, vaccination schedules are shared with other childcare apps. The notification unit also works in conjunction with a calendar app used by the user to centralize task management. For example, regular checkup schedules are shared with the calendar app. The notification unit also works in conjunction with the childcare app and calendar app used by the user to centralize task management. For example, the progress of childcare-related tasks is shared with other apps. In this way, by working in conjunction with other childcare apps and calendar apps, task management can be centralized.

[0044] The notification unit can expand the task management function to enable management of household tasks other than childcare. For example, the notification unit can enable the AI ​​to expand the childcare-related task management function to enable management of other household tasks. For example, by adding cleaning or laundry tasks. The notification unit can also expand the childcare-related task management function to enable management of other household tasks. For example, by adding shopping or cooking tasks. The notification unit can also expand the childcare-related task management function to enable management of other household tasks. For example, by centrally managing housework and childcare tasks. In this way, the task management function can be expanded to enable management of household tasks other than childcare.

[0045] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0046] The child-rearing consultation system may further include a parenting style analysis unit that provides customized advice based on the user's parenting style. For example, when a user inputs a question about child-rearing, the parenting style analysis unit analyzes the user's parenting style and provides customized advice. The parenting style analysis unit may also provide information and resources related to child-rearing based on the user's parenting style. For example, if the user practices natural parenting, advice and resources suited to that style may be provided. The parenting style analysis unit may also introduce parenting communities and support groups based on the user's parenting style. This allows for more personalized advice by providing support suited to the user's parenting style.

[0047] The childcare consultation system may further include a childcare experience analysis unit that provides advice based on the user's childcare experience. For example, when a user inputs a question about childcare, the childcare experience analysis unit analyzes the user's past childcare experience and provides appropriate advice. The childcare experience analysis unit may also provide information and resources related to childcare based on the user's childcare experience. For example, if the user is raising a child for the first time, advice and resources based on that experience may be provided. The childcare experience analysis unit may also introduce childcare communities and support groups based on the user's childcare experience. This allows for more personalized advice by providing support tailored to the user's childcare experience.

[0048] The childcare consultation system may further include a goal setting unit that supports the user in setting childcare goals. For example, when the user sets a childcare goal, the goal setting unit supports specific goal setting and suggests steps toward achieving the goal. The goal setting unit may also monitor progress based on the user's childcare goal and provide feedback toward achieving the goal. For example, if the user sets the goal of "reducing the baby's crying at night," the goal setting unit may provide specific steps and advice toward achieving the goal. The goal setting unit may also provide reminders and motivation toward achieving the goal based on the user's childcare goal. This allows the system to support the user in setting childcare goals and provide specific advice toward achieving the goal.

[0049] The childcare consultation system may further include a progress visualization unit that visualizes the user's progress in childcare. For example, when the user completes a childcare task, the progress visualization unit visualizes the progress in a graph or chart and provides it to the user. The progress visualization unit may also periodically monitor the user's progress in childcare and visualize the progress of the goal. For example, if the user sets a goal of "reducing the baby's nighttime crying," the progress may be visualized in a graph or chart and provided to the user. The progress visualization unit may also share the user's progress in childcare with other family members and jointly manage the progress. In this way, visualizing the user's progress in childcare can enhance a sense of accomplishment and improve motivation.

[0050] The childcare consultation system may further include an education unit for improving the user's knowledge about childcare. For example, when a user inputs a question about childcare, the education unit provides relevant educational content to improve the user's knowledge. The education unit may also provide appropriate educational content based on the user's level of knowledge about childcare. For example, if the user is experiencing childcare for the first time, educational content based on that experience may be provided. The education unit may also provide quizzes and tests about childcare based on the user's level of knowledge about childcare to check the user's knowledge. This allows for more comprehensive support by providing educational content to improve the user's knowledge about childcare.

[0051] The childcare consultation system may further include a success experience sharing unit that shares users' success experiences in childcare. For example, when a user inputs a success experience in childcare, the success experience sharing unit shares the experience with other users, thereby increasing motivation. The success experience sharing unit may also provide messages of encouragement and support to other users based on the user's success experience in childcare. For example, if a user shares a success experience such as "I was able to reduce my baby's night crying," the experience may be shared with other users, and messages of encouragement and support may be provided. The success experience sharing unit may also provide specific advice and resources to other users based on the user's success experience in childcare. In this way, sharing the user's success experience in childcare may increase the motivation of other users.

[0052] The processing flow of the first embodiment will be briefly explained below.

[0053] Step 1: The input unit accepts the user's questions and concerns. For example, the user can enter questions and concerns into the app by text input or voice input. The input unit also allows the user to upload images and videos, so visual information can be accepted. For example, the user can upload a photo of a rash on their baby and ask a question about the rash. Step 2: In the answer generation section, the generation AI generates answers to the questions and concerns received by the input section using the latest research and reliable sources. For example, the generation AI uses text generation AI (e.g., LLM) to generate answers to the user's questions. The generation AI can also use multimodal generation AI to analyze visual information and generate answers. For example, the generation AI analyzes a photo of a baby's rash and provides the type of rash and how to deal with it. Step 3: The notification unit notifies the user of the answer generated by the answer generation unit. For example, the notification unit displays the answer to the user using a notification function within the app. The notification unit also supports devices such as smart watches and smart speakers, and can send notifications to the devices used by the user. For example, the notification unit notifies the smart watch that "An answer about your baby's rash has been received."

[0054] (Example 2) The childcare consultation system according to an embodiment of the present invention automatically accepts questions and concerns about childcare, uses a generation AI to provide answers based on the latest research and reliable sources, and is equipped with task invitation and notification functions. As a result, the childcare consultation system can quickly and accurately resolve questions and concerns about childcare and support childcare-related task management.

[0055] A childcare consultation system according to an embodiment includes an input unit, an answer generation unit, and a notification unit. The input unit accepts questions and concerns from users. For example, users can input their questions and concerns by text input or voice input into the app. The input unit also allows users to upload images and videos, and can accept visual information. For example, a user can upload a photo of a rash on their baby and ask a question about the rash. The answer generation unit uses a generation AI to generate answers based on the latest research and reliable sources for the questions and concerns accepted by the input unit. For example, the generation AI uses a text generation AI (e.g., LLM) to generate answers to the user's questions. The generation AI can also analyze visual information and generate answers using a multimodal generation AI. For example, the generation AI analyzes a photo of a rash on a baby and provides the type of rash and how to deal with it. The notification unit notifies the user of the answer generated by the answer generation unit. For example, the notification unit displays the answer to the user using a notification function within the app. The notification unit is also compatible with devices such as smartwatches and smart speakers, and can send notifications to the devices used by the user. For example, the notification unit may notify the smartwatch that "Answer regarding your baby's rash has arrived." This allows the childcare consultation system according to the embodiment to provide quick and accurate answers to the user's questions and concerns. For example, a user can input a question about childcare, the generation AI can provide an answer to that question, and the notification unit can notify the user of the answer, allowing the user to quickly resolve their question.

[0056] The input unit can generate related follow-up questions based on the user's input and collect detailed information. For example, if the user inputs, "What should I do if my baby cries at night?", the AI ​​generates follow-up questions such as, "How often does the baby cry at night?" and "How old is the baby?" to collect detailed information. If the user inputs, "When should I start solid food?", the AI ​​generates follow-up questions such as, "What is the baby's current diet?" and "Does the baby have any allergies?" to collect detailed information. If the user inputs, "What is the vaccination schedule?", the AI ​​generates follow-up questions such as, "What is the baby's date of birth?" and "Does the baby have a history of past vaccinations?" to collect detailed information. This allows the AI ​​to collect more detailed information about the user's questions and concerns and provide highly accurate answers.

[0057] The input unit can analyze the user's past input history and provide personalized advice. For example, if the user previously asked about "your baby's night crying," the AI ​​will ask personalized questions based on that history, such as "Have you tried the previous advice?" or "How is it going since then?" If the user previously asked about "baby food," the AI ​​will ask personalized questions based on that history, such as "Have you put into practice the previous baby food advice?" or "Has there been any change in your baby's diet?" If the user previously asked about "vaccinations," the AI ​​will ask personalized questions based on that history, such as "Have you checked the schedule for the last vaccination?" or "Is the next vaccination scheduled?" This makes it possible to provide more personalized advice based on the user's past input history.

[0058] The input unit can use the emotion estimation function to analyze the user's emotional state and suggest relaxation methods to reduce stress and anxiety. For example, if the user inputs, "I'm tired because my baby keeps crying at night," the AI ​​uses the emotion estimation function to analyze the user's stress level and suggests methods such as "taking deep breaths to relax" or "taking a short rest." Alternatively, if the user inputs, "I'm tired of raising my child," the AI ​​can use the emotion estimation function to analyze the user's emotional state and suggest methods such as "listening to relaxation music" or "meditating." Alternatively, if the user inputs, "I'm feeling stressed from raising my child," the AI ​​can use the emotion estimation function to analyze the user's emotional state and suggest methods such as "performing relaxation exercises" or "creating a relaxing environment." This allows the system to suggest appropriate relaxation methods based on the user's emotional state.

[0059] The input unit allows input using images and videos in addition to text and voice input, and can also analyze visual information. For example, if a user uploads a photo of a rash on their baby and asks, "What is this rash?", the AI ​​will analyze the image and provide the type of rash and how to deal with it. If a user uploads a video of their baby and asks, "Is this movement normal?", the AI ​​will analyze the video and evaluate the normality of the movement. If a user uploads a photo of their baby's meal and asks, "Is this diet appropriate?", the AI ​​will analyze the image and evaluate the appropriateness of the diet. This allows for more detailed advice to be provided by analyzing visual information as well.

[0060] The input unit can link with other childcare apps and devices, integrating data to provide comprehensive advice. For example, the input unit can link with a childcare app used by the user, integrating sleep data and dietary data, and the AI ​​can provide comprehensive advice. For example, the input unit can provide advice such as, "Your sleep time is short, so try taking more naps." The input unit can also link with a childcare device used by the user, integrating body temperature data and heart rate data, and the AI ​​can provide comprehensive advice. For example, the input unit can provide advice such as, "Your temperature is high, so please consult a doctor." The input unit can also link with a calendar app used by the user, integrating vaccination schedules, and the AI ​​can provide comprehensive advice. For example, the input unit can provide advice such as, "The next vaccination is next week." By linking with other childcare apps and devices, more comprehensive advice can be provided.

[0061] The input unit uses the emotion estimation function to analyze the user's emotions in real time as they input information and provide positive feedback. For example, when a user inputs, "I'm tired because my baby keeps crying at night," the AI ​​uses the emotion estimation function to analyze the user's stress level and provides positive feedback such as, "You're doing a great job. Take a short break." Similarly, when a user inputs, "I'm exhausted from raising my child," the AI ​​uses the emotion estimation function to analyze the user's emotional state and provides positive feedback such as, "You're a great parent. Take a short break." Similarly, when a user inputs, "I'm stressed from raising my child," the AI ​​uses the emotion estimation function to analyze the user's emotional state and provides positive feedback such as, "You're doing great. Take a short break." This allows the system to provide positive feedback based on the user's emotions, thereby reducing stress.

[0062] The answer generation unit evaluates and provides feedback on answers provided by the user, and can improve the accuracy of the answers based on the evaluation. For example, the answer generation unit evaluates an answer provided by a user such as "Creating a regular rhythm is effective for preventing a baby from crying at night," and the AI ​​improves the accuracy of the answers based on the evaluation. For example, answers with higher ratings are provided preferentially. The answer generation unit also evaluates an answer provided by a user such as "It is common to start solid food at 6 months of age," and the AI ​​improves the accuracy of the answers based on the evaluation. For example, answers with higher ratings are provided preferentially. The answer generation unit also evaluates an answer provided by a user such as "Consult your doctor about vaccination schedules," and the AI ​​improves the accuracy of the answers based on the evaluation. For example, answers with higher ratings are provided preferentially. In this way, the accuracy of the answers can be improved based on user evaluations and feedback.

[0063] The answer generation unit periodically updates the latest research database, enabling it to always provide the latest information. The answer generation unit, for example, uses AI to periodically update the latest childcare-related research database, ensuring that answers provided to users are always based on the latest information. For example, the database is updated when new research results are published. The answer generation unit also uses AI to update the latest research database in real time, enabling answers provided to users to always be based on the latest information. For example, the database is updated immediately after the latest research results are published. The answer generation unit also uses AI to update the latest research database weekly, enabling answers provided to users to always be based on the latest information. For example, the database is updated every Monday. This constantly provides the latest information, enabling it to provide users with highly reliable answers.

[0064] The answer generation unit enables the provision of information in different languages, making it possible to provide advice from an international perspective. The answer generation unit, for example, enables the AI ​​to provide information in different languages, providing child-rearing advice in a language selected by the user. For example, multiple languages ​​such as English, French, and Chinese are supported. The answer generation unit also enables the AI ​​to provide information in different languages, providing child-rearing advice in a language selected by the user. For example, multiple languages ​​such as Spanish, German, and Italian are supported. The answer generation unit also enables the AI ​​to provide information in different languages, providing child-rearing advice in a language selected by the user. For example, multiple languages ​​such as Korean, Russian, and Arabic are supported. This makes it possible to provide information in different languages, making it possible to provide advice from an international perspective.

[0065] The answer generation unit can automatically generate links to related videos and articles, allowing the user to learn more in-depth. For example, when a user asks a question about "baby crying at night," the answer generation unit uses AI to automatically generate links to related videos and articles, allowing the user to learn more in-depth. For example, it provides a link such as "Click here for a video on how to deal with night crying." When a user asks a question about "baby food," the answer generation unit automatically generates links to related videos and articles, allowing the user to learn more in-depth. For example, it provides a link such as "Click here for an article on how to start baby food." When a user asks a question about "vaccinations," the answer generation unit automatically generates links to related videos and articles, allowing the user to learn more in-depth. For example, it provides a link such as "Click here for a video on vaccination schedules." This allows the user to learn more in-depth by providing links to related videos and articles.

[0066] The answer generation unit can use the emotion estimation function to identify topics that the user is most interested in and provide information about those topics preferentially. For example, when a user asks a question about "baby crying at night," the AI ​​uses the emotion estimation function to analyze the user's level of interest and prioritize providing information about night crying. For example, detailed information about causes of night crying and countermeasures can be provided here. When a user asks a question about "baby food," the AI ​​uses the emotion estimation function to analyze the user's level of interest and prioritize providing information about baby food. For example, detailed information about how to start baby food and precautions can be provided here. When a user asks a question about "vaccinations," the AI ​​uses the emotion estimation function to analyze the user's level of interest and prioritize providing information about vaccinations. For example, detailed information about vaccination schedules and precautions can be provided here. This prioritizes providing information about topics that the user is most interested in, thereby improving user satisfaction.

[0067] The notification unit can provide notifications at optimal times based on the user's schedule and lifestyle. For example, the notification unit analyzes the user's schedule and provides vaccination notifications at optimal times. For example, the notification unit may provide a notification that "Tomorrow is vaccination day" to coincide with the time the user returns home from work. The notification unit may also analyze the user's lifestyle and provide notifications about regular checkups at optimal times. For example, the notification unit may provide a notification that "You have a regular checkup this week" to coincide with the time the user wakes up in the morning. The notification unit may also analyze the user's schedule and lifestyle and provide notifications about childcare-related tasks at optimal times. For example, the notification unit may provide a notification that "Have you completed this month's vaccinations?" to coincide with the time the user is relaxing. This allows for improved user convenience by providing notifications at optimal times based on the user's schedule and lifestyle.

[0068] The notification unit can customize the notification content and provide reminders that match the user's preferences. For example, the notification unit customizes the notification content for vaccinations based on the user's preferences. For example, it provides a friendly reminder such as, "Tomorrow is vaccination day. Don't forget!" The notification unit also customizes the notification content for regular checkups based on the user's preferences. For example, it provides a friendly reminder such as, "Your regular checkup is this week. Are you ready?" The notification unit also customizes the notification content for childcare-related tasks based on the user's preferences. For example, it provides a friendly reminder such as, "Have you completed this month's vaccinations? Don't forget!" In this way, by customizing the notification content, it is possible to provide reminders that match the user's preferences.

[0069] The notification unit can use the emotion estimation function to notify the user of encouraging or supportive messages based on their emotional state. For example, when a user inputs, "I'm tired because my baby keeps crying at night," the AI ​​uses the emotion estimation function to analyze the user's stress level and notify them of an encouraging message such as, "You're doing a great job. Take a short break." Similarly, when a user inputs, "I'm exhausted from raising my child," the AI ​​uses the emotion estimation function to analyze the user's emotional state and notify them of an encouraging message such as, "You're a great parent. Take a short break." Similarly, when a user inputs, "I'm stressed from raising my child," the AI ​​uses the emotion estimation function to analyze the user's emotional state and notify them of an encouraging message such as, "You're doing great. Take a short break." This allows the user to reduce stress by notifying them of encouraging or supportive messages based on their emotional state.

[0070] The notification unit can add a function that allows a user to share tasks with other family members and jointly manage childcare tasks. For example, the notification unit adds a function that allows a user to share childcare tasks with other family members and jointly manage them. For example, notifying all family members of vaccination schedules. The notification unit also adds a function that allows a user to share childcare tasks with other family members and jointly manage them. For example, notifying all family members of regular checkup schedules. The notification unit also adds a function that allows a user to share childcare tasks with other family members and jointly manage them. For example, sharing the progress of childcare-related tasks with all family members. This makes it possible to jointly manage childcare tasks by sharing tasks with other family members.

[0071] The notification unit can expand the notification function to support devices such as smartwatches and smart speakers. For example, if the user is using a smartwatch, the notification unit sends a vaccination notification to the smartwatch. For example, a notification such as "Tomorrow is vaccination day" is displayed on the smartwatch. If the user is using a smart speaker, the notification unit sends a notification of a regular checkup to the smart speaker. For example, a notification such as "You have a regular checkup this week" is sent to the smart speaker by voice. If the user is using a smartphone, the notification unit sends a notification of a childcare-related task to the smartphone. For example, a notification such as "Have you completed your vaccinations this month?" is displayed on the smartphone. In this way, the notification function can be expanded to support devices such as smartwatches and smart speakers.

[0072] The notification unit uses the emotion estimation function to analyze the user's emotions when receiving notifications and can provide notifications at the optimal timing. For example, when a user inputs, "I'm tired because my baby keeps crying at night," the AI ​​uses the emotion estimation function to analyze the user's stress level and provide a vaccination notification at the optimal timing. For example, the notification can be provided when the user is relaxing. Also, when a user inputs, "I'm tired of childcare," the AI ​​uses the emotion estimation function to analyze the user's emotional state and provide a notification for a regular checkup at the optimal timing. For example, the notification can be provided when the user wakes up in the morning. Also, when a user inputs, "I'm stressed out from childcare," the AI ​​uses the emotion estimation function to analyze the user's emotional state and provide a notification for childcare-related tasks at the optimal timing. For example, the notification can be provided when the user gets home from work. This improves user convenience by providing notifications at the optimal timing based on the user's emotional state.

[0073] The notification unit can automatically set the priority of tasks and give priority to reminders of important tasks. For example, the notification unit uses AI to automatically set the priority of childcare-related tasks and give priority to reminders of important tasks. For example, it gives priority to notifying users of vaccination appointments. The notification unit can also automatically set the priority of childcare-related tasks and give priority to reminders of important tasks. For example, it gives priority to notifying users of regular checkup appointments. The notification unit can also automatically set the priority of childcare-related tasks and give priority to reminders of important tasks. For example, it gives priority to notifying users of the progress of childcare-related tasks. In this way, by automatically setting the priority of tasks, it is possible to give priority to reminders of important tasks.

[0074] The notification unit can use the emotion estimation function to suggest task management methods according to the user's emotional state. For example, when a user inputs, "I'm tired because my baby keeps crying at night," the AI ​​uses the emotion estimation function to analyze the user's stress level and suggest task management methods to reduce stress. For example, the AI ​​suggests, "Take a short break before proceeding with your task." Furthermore, when a user inputs, "I'm tired from childcare," the AI ​​uses the emotion estimation function to analyze the user's emotional state and suggest task management methods to reduce stress. For example, the AI ​​suggests, "Create a relaxing environment before proceeding with your task." Furthermore, when a user inputs, "I'm feeling stressed from childcare," the AI ​​uses the emotion estimation function to analyze the user's emotional state and suggest task management methods to reduce stress. For example, the AI ​​suggests, "Take a deep breath before proceeding with your task." In this way, the AI ​​can reduce the user's stress by suggesting task management methods according to the user's emotional state.

[0075] The notification unit can work in conjunction with other childcare apps and calendar apps to centralize task management. The notification unit, for example, works in conjunction with a childcare app used by the user to centralize task management. For example, vaccination schedules are shared with other childcare apps. The notification unit also works in conjunction with a calendar app used by the user to centralize task management. For example, regular checkup schedules are shared with the calendar app. The notification unit also works in conjunction with the childcare app and calendar app used by the user to centralize task management. For example, the progress of childcare-related tasks is shared with other apps. In this way, by working in conjunction with other childcare apps and calendar apps, task management can be centralized.

[0076] The notification unit can expand the task management function to enable management of household tasks other than childcare. For example, the notification unit can enable the AI ​​to expand the childcare-related task management function to enable management of other household tasks. For example, by adding cleaning or laundry tasks. The notification unit can also expand the childcare-related task management function to enable management of other household tasks. For example, by adding shopping or cooking tasks. The notification unit can also expand the childcare-related task management function to enable management of other household tasks. For example, by centrally managing housework and childcare tasks. In this way, the task management function can be expanded to enable management of household tasks other than childcare.

[0077] The notification unit can use the emotion estimation function to analyze the user's emotions when they complete a task and provide feedback that enhances their sense of accomplishment. For example, when a user completes a vaccination task, the AI ​​uses the emotion estimation function to analyze the user's emotions and provides feedback that enhances their sense of accomplishment, such as, "Your vaccination went well! Thank you for your hard work!" When a user completes a regular checkup task, the AI ​​uses the emotion estimation function to analyze the user's emotions and provides feedback that enhances their sense of accomplishment, such as, "Your regular checkup went well! Thank you for your hard work!" When a user completes a childcare-related task, the AI ​​uses the emotion estimation function to analyze the user's emotions and provides feedback that enhances their sense of accomplishment, such as, "Your childcare task went well! Thank you for your hard work!" In this way, by analyzing the user's emotions when they complete a task and providing feedback that enhances their sense of accomplishment, it is possible to improve the user's motivation.

[0078] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0079] The childcare consultation system may further include a health management unit that monitors the user's health condition. For example, when a user inputs a question about childcare, the health management unit measures the user's heart rate and stress level and monitors the user's health condition. The health management unit may also provide appropriate advice based on the user's health condition when the user inputs a question about childcare. For example, if the user's stress level is high, the health management unit may provide advice on relaxation methods and stress reduction. The health management unit may also periodically monitor the user's health condition and provide childcare advice based on the health condition. This allows for more comprehensive support by providing advice that takes the user's health condition into consideration.

[0080] The child-rearing consultation system may further include a parenting style analysis unit that provides customized advice based on the user's parenting style. For example, when a user inputs a question about child-rearing, the parenting style analysis unit analyzes the user's parenting style and provides customized advice. The parenting style analysis unit may also provide information and resources related to child-rearing based on the user's parenting style. For example, if the user practices natural parenting, advice and resources suited to that style may be provided. The parenting style analysis unit may also introduce parenting communities and support groups based on the user's parenting style. This allows for more personalized advice by providing support suited to the user's parenting style.

[0081] The childcare consultation system may further include a childcare experience analysis unit that provides advice based on the user's childcare experience. For example, when a user inputs a question about childcare, the childcare experience analysis unit analyzes the user's past childcare experience and provides appropriate advice. The childcare experience analysis unit may also provide information and resources related to childcare based on the user's childcare experience. For example, if the user is raising a child for the first time, advice and resources based on that experience may be provided. The childcare experience analysis unit may also introduce childcare communities and support groups based on the user's childcare experience. This allows for more personalized advice by providing support tailored to the user's childcare experience.

[0082] The childcare consultation system may further include an activity suggestion unit that suggests childcare-related activities based on the user's emotional state. For example, when a user inputs, "I'm tired because my baby keeps crying at night," the activity suggestion unit uses the emotion estimation function to analyze the user's stress level and suggests relaxation activities or activities for stress reduction. Also, when a user inputs, "I'm tired from childcare," the activity suggestion unit uses the emotion estimation function to analyze the user's emotional state and suggests refreshing activities or relaxation activities. Also, when a user inputs, "I'm stressed from childcare," the activity suggestion unit uses the emotion estimation function to analyze the user's emotional state and suggests relaxation exercises or refreshing activities. This allows the user's stress to be reduced by suggesting activities that match the user's emotional state.

[0083] The childcare consultation system may further include a goal setting unit that supports the user in setting childcare goals. For example, when the user sets a childcare goal, the goal setting unit supports specific goal setting and suggests steps toward achieving the goal. The goal setting unit may also monitor progress based on the user's childcare goal and provide feedback toward achieving the goal. For example, if the user sets the goal of "reducing the baby's crying at night," the goal setting unit may provide specific steps and advice toward achieving the goal. The goal setting unit may also provide reminders and motivation toward achieving the goal based on the user's childcare goal. This allows the system to support the user in setting childcare goals and provide specific advice toward achieving the goal.

[0084] The childcare consultation system may further include a progress visualization unit that visualizes the user's progress in childcare. For example, when the user completes a childcare task, the progress visualization unit visualizes the progress in a graph or chart and provides it to the user. The progress visualization unit may also periodically monitor the user's progress in childcare and visualize the progress of the goal. For example, if the user sets a goal of "reducing the baby's nighttime crying," the progress may be visualized in a graph or chart and provided to the user. The progress visualization unit may also share the user's progress in childcare with other family members and jointly manage the progress. In this way, visualizing the user's progress in childcare can enhance a sense of accomplishment and improve motivation.

[0085] The childcare consultation system may further include a resource providing unit that provides childcare resources based on the user's emotional state. For example, when a user inputs, "I'm tired because my baby keeps crying at night," the resource providing unit uses the emotion estimation function to analyze the user's stress level and provides relaxation resources and stress reduction resources. When a user inputs, "I'm tired of childcare," the resource providing unit uses the emotion estimation function to analyze the user's emotional state and provides refreshing resources and relaxation resources. When a user inputs, "I'm stressed out from childcare," the resource providing unit uses the emotion estimation function to analyze the user's emotional state and provides relaxation exercises and refreshing resources. This allows the user's stress to be reduced by providing resources according to the user's emotional state.

[0086] The childcare consultation system may further include an education unit for improving the user's knowledge about childcare. For example, when a user inputs a question about childcare, the education unit provides relevant educational content to improve the user's knowledge. The education unit may also provide appropriate educational content based on the user's level of knowledge about childcare. For example, if the user is experiencing childcare for the first time, educational content based on that experience may be provided. The education unit may also provide quizzes and tests about childcare based on the user's level of knowledge about childcare to check the user's knowledge. This allows for more comprehensive support by providing educational content to improve the user's knowledge about childcare.

[0087] The childcare consultation system may further include a community introduction unit that introduces childcare-related communities based on the user's emotional state. For example, when a user inputs, "I'm tired because my baby keeps crying at night," the community introduction unit uses the emotion estimation function to analyze the user's stress level and introduces communities where parents with similar concerns gather. Also, when a user inputs, "I'm tired of childcare," the community introduction unit uses the emotion estimation function to analyze the user's emotional state and introduces communities and support groups where they can refresh themselves. Also, when a user inputs, "I'm stressed out from childcare," the community introduction unit uses the emotion estimation function to analyze the user's emotional state and introduces communities that offer relaxation exercises and refreshment. This allows the user's stress to be reduced by introducing communities that correspond to the user's emotional state.

[0088] The childcare consultation system may further include a success experience sharing unit that shares users' success experiences in childcare. For example, when a user inputs a success experience in childcare, the success experience sharing unit shares the experience with other users, thereby increasing motivation. The success experience sharing unit may also provide messages of encouragement and support to other users based on the user's success experience in childcare. For example, if a user shares a success experience such as "I was able to reduce my baby's night crying," the experience may be shared with other users, and messages of encouragement and support may be provided. The success experience sharing unit may also provide specific advice and resources to other users based on the user's success experience in childcare. In this way, sharing the user's success experience in childcare may increase the motivation of other users.

[0089] The processing flow of the second embodiment will be briefly explained below.

[0090] Step 1: The input unit accepts the user's questions and concerns. For example, the user can enter questions and concerns into the app by text input or voice input. The input unit also allows the user to upload images and videos, so visual information can be accepted. For example, the user can upload a photo of a rash on their baby and ask a question about the rash. Step 2: In the answer generation section, the generation AI generates answers to the questions and concerns received by the input section using the latest research and reliable sources. For example, the generation AI uses text generation AI (e.g., LLM) to generate answers to the user's questions. The generation AI can also use multimodal generation AI to analyze visual information and generate answers. For example, the generation AI analyzes a photo of a baby's rash and provides the type of rash and how to deal with it. Step 3: The notification unit notifies the user of the answer generated by the answer generation unit. For example, the notification unit displays the answer to the user using a notification function within the app. The notification unit also supports devices such as smart watches and smart speakers, and can send notifications to the devices used by the user. For example, the notification unit notifies the smart watch that "An answer about your baby's rash has been received."

[0091] 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.

[0092] 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.

[0093] 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.

[0094] [Second embodiment] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0095] 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.

[0096] 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.

[0097] 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.

[0098] 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.

[0099] 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).

[0100] 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.

[0101] 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.

[0102] 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.

[0103] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0104] In the smart glasses 214, the specific processing is performed by the processor 46. A specific processing program 60 is stored in the storage 50. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. Note that the smart glasses 214 may have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59.

[0105] 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.

[0106] 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.

[0107] 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.

[0108] 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.

[0109] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0110] 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.

[0111] 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.

[0112] 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.

[0113] 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.

[0114] 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).

[0115] 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.

[0116] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset 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.

[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 the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0119] In the headset type terminal 314, the identification process is performed by the processor 46. A identification program 60 is stored in the storage 50. The processor 46 reads the identification program 60 from the storage 50 and executes the read identification program 60 on the RAM 48. The identification process is realized by the processor 46 operating as a control unit 46A in accordance with the identification program 60 executed on the RAM 48. Note that the headset type terminal 314 may also have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59.

[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 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.

[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 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.

[0124] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0125] 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.

[0126] 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.

[0127] 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.

[0128] 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.

[0129] 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).

[0130] 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.

[0131] 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.

[0132] 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.

[0133] 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.

[0134] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0135] In the robot 414, the processor 46 performs the identification process. A identification program 60 is stored in the storage 50. The processor 46 reads the identification program 60 from the storage 50 and executes the read identification program 60 on the RAM 48. The identification process is realized by the processor 46 operating as a control unit 46A in accordance with the identification program 60 executed on the RAM 48. The robot 414 may have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59.

[0136] 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.

[0137] 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.

[0138] 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.

[0139] 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.

[0140] 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.

[0141] 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.

[0142] 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.

[0143] 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).

[0144] 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.

[0145] 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."

[0146] 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.

[0147] 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.

[0148] 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.

[0149] 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.

[0150] 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.

[0151] The hardware resource for executing a specific process can be any of the following processors: A CPU is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. A dedicated electrical circuit, such as a field-programmable gate array (FPGA), a programmable logic device (PLD), or an application-specific integrated circuit (ASIC), is a processor with a circuit configuration specifically designed to execute a specific process. Each processor has built-in or connected memory, and uses the memory to execute the specific process.

[0152] 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.

[0153] 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.

[0154] 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.

[0155] 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.

[0156] 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.

[0157] 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]

[0158] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot

Claims

1. an input unit for receiving questions and concerns from users; an answer generation unit that generates answers to the questions and concerns received by the input unit from the latest research and reliable information sources; a notification unit that notifies the user of the answer generated by the answer generation unit. A system characterized by:

2. The input unit In addition to text and voice input, it also allows input using images and videos, and analyzes visual information. The system of claim 1 .

3. The answer generation unit Evaluate and provide feedback on answers provided by users, and improve the accuracy of answers based on the evaluations The system of claim 1 .

4. The notification unit Send notifications at optimal times based on the user's schedule and lifestyle The system of claim 1 .

5. The input unit Analyzes the user's emotional state using emotion estimation functionality and suggests relaxation methods to reduce stress and anxiety The system of claim 1 .

6. The answer generation unit Using emotion estimation functionality, the system provides answers that correspond to the user's emotional state, providing a sense of security. The system of claim 1 .

7. The notification unit Using emotion estimation function to send encouraging and supportive messages according to the user's emotional state The system of claim 1 .

8. The notification unit Emotion estimation function is used to analyze the emotions felt when a user completes a task, and provides feedback that enhances the sense of accomplishment. The system of claim 1 .

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