system

Abstract

The system according to this embodiment aims to alleviate the anxiety and loneliness that new mothers and fathers feel regarding childcare, and to make childcare a more reassuring and enjoyable experience. [Solution] The system according to the embodiment comprises an answering unit, an emotional support unit, a task management unit, a health management unit, and a community unit. The answering unit provides immediate answers to questions about the baby's daily routine and health. The emotional support unit listens attentively based on the answers provided by the answering unit and offers encouragement and advice. The task management unit manages schedules such as breastfeeding, diaper changes, and vaccinations. The health management unit records the baby's growth data and analyzes its health status. The community unit provides information on nearby childcare facilities and events, and offers a community function to connect parents with other mothers and fathers.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor, and includes steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of the chatbot's 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

Summary of the Invention

Problems to be Solved by the Invention

[0004] In the conventional technology, the support for reducing the anxiety and loneliness related to child-rearing that new mothers and fathers have is not sufficient, and there is room for improvement.

[0005] The system according to the embodiment aims to reduce the anxiety and loneliness related to child-rearing that new mothers and fathers have, and make the child-rearing life more secure and enjoyable.

Means for Solving the Problems

[0006] The system according to this embodiment comprises an answering unit, an emotional support unit, a task management unit, a health management unit, and a community unit. The answering unit provides immediate answers to questions about the baby's daily routine and health. The emotional support unit listens attentively based on the answers provided by the answering unit and offers encouragement and advice. The task management unit manages schedules such as breastfeeding, diaper changes, and vaccinations. The health management unit records the baby's growth data and analyzes its health status. The community unit provides information on nearby childcare facilities and events, and offers a community function to connect parents with other parents. [Effects of the Invention]

[0007] The system according to this embodiment can alleviate the anxiety and loneliness that new mothers and fathers feel regarding childcare, making their parenting experience more reassuring and enjoyable. [Brief explanation of the drawing]

[0008] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Modes for carrying out the invention]

[0009] Hereinafter, an example of an embodiment of the system relating to the technology of this disclosure will be described with reference to the attached drawings.

[0010] First, let's explain the terminology used in the following explanation.

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

[0012] In the following embodiments, signed RAM (Random Access Memory) is a memory that temporarily stores information and is used as work memory by the processor.

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

[0014] In the following embodiments, the labeled communication I / F (Interface) 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 such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0015] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B". That is, "A and / or B" means that it may be only A, only B, or a combination of A and B. Also, in this specification, when expressing three or more matters connected by "and / or", the same concept as "A and / or B" is applied.

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

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

[0018] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. Also, the database 24 and the communication I / F 26 are 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 comprises a computer 36, a receiving device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The receiving device 38, output device 40, and camera 42 are also connected to the bus 52.

[0020] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, and accepts user input. The touch panel 38A accepts user input via touch by detecting contact with an object (e.g., a pen or finger). The microphone 38B accepts user input via voice by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 (see Figure 2) acquires the data indicating the user input.

[0021] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user by outputting the data in a form perceptible to the user (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0022] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

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

[0024] As shown in Figure 2, in the data processing device 12, a specific processing 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" related to the technology of this 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 processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0025] Storage 32 stores the data generation model 58 and the 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 emotions using the emotion identification model 59 and perform identification processing using the user's emotions. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotions, including but not limited to these examples. Furthermore, emotion estimation and prediction also include, for example, emotion analysis.

[0026] In the smart device 14, specific processing is performed by the processor 46. The storage 50 stores a specific processing program 60. The specific processing program 60 is used in conjunction 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 a control unit 46A according to the specific processing program 60 executed on the RAM 48. The smart device 14 also has a data generation model 58 and an emotion identification model 59, similar to the data generation model and emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0027] Furthermore, other devices besides the data processing device 12 may also 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 processing results (such as prediction results) using the data generation model 58 by communicating with the server device having the data generation model 58. The data processing device 12 may also be a server device or a terminal device owned by a user (e.g., a mobile phone, robot, home appliance, etc.). Next, an example of processing by the data processing system 10 according to the first embodiment will be described.

[0028] (Example of form 1) The dedicated AI assistant system according to an embodiment of the present invention is a system that alleviates the anxiety and loneliness felt by new mothers and fathers, making childcare a safer and more enjoyable experience. This dedicated AI assistant system has the function of providing instant 24-hour answers to questions about the baby's daily rhythm and health, based on information supervised by experts. For example, the AI ​​can instantly answer questions about how to deal with nighttime crying or how to handle illness. Next, it has an emotional support function, where the AI ​​listens empathetically and provides encouragement and advice. This reduces feelings of loneliness and stress for mothers and fathers. Furthermore, it has a childcare task management function, where the AI ​​agent proactively grasps schedules for breastfeeding, diaper changes, vaccinations, etc., shares them with the family, and provides reminders to support more efficient childcare. It also has a function to record the baby's growth data and analyze its health status. If there is an abnormality, the AI ​​will suggest visiting a medical institution. In addition, it has a local information and parent community function, providing information on nearby childcare facilities and events, and also includes a community function that connects parents with other parents. In this way, by resolving the worries and alleviating feelings of loneliness experienced during childcare, the system provides an environment where mothers and fathers can confidently face the challenges of raising children. It functions as a "reliable partner" that supports them throughout their childcare journey. As a result, the dedicated AI assistant system can provide an environment where mothers and fathers can confidently face the challenges of raising children by resolving the worries and alleviating feelings of loneliness experienced during childcare.

[0029] The dedicated AI assistant system according to this embodiment comprises an answering unit, an emotional support unit, a task management unit, a health management unit, and a community unit. The answering unit provides immediate answers to questions about the baby's daily rhythm and health. For example, if asked about how to deal with a baby's nighttime crying, the answering unit provides an immediate answer based on information supervised by experts. The answering unit can also provide immediate answers to questions about how to deal with a baby's illness. Furthermore, the answering unit can also provide immediate answers to questions about the baby's daily rhythm. The emotional support unit listens empathetically based on the answers provided by the answering unit and offers encouragement and advice. For example, if a mother or father is feeling anxious about childcare, the emotional support unit listens empathetically and offers words of encouragement. Furthermore, if a mother or father is feeling lonely, the emotional support unit can listen empathetically and offer advice. Furthermore, if a mother or father is feeling stressed, the emotional support unit can listen empathetically and offer encouragement and advice. The task management unit manages schedules such as breastfeeding, diaper changes, and vaccinations. For example, the Task Management Department manages breastfeeding schedules and sends reminders to mothers and fathers. It can also manage and remind them of diaper changing schedules. Furthermore, it can manage and remind them of vaccination schedules. The Health Management Department records the baby's growth data and analyzes their health status. For example, it records the baby's height and weight data to understand their growth process. It also analyzes the baby's health status and can suggest a visit to a medical institution if there are any abnormalities. Furthermore, it records data on the baby's developmental stage and can comprehensively analyze their health status. The Community Department provides information on nearby childcare facilities and events, and offers community features to connect parents. For example, it provides information on nearby childcare facilities and introduces facilities that parents can use. It can also provide information on childcare events held in the neighborhood. Furthermore, it provides community features to connect parents and promote interaction.As a result, the dedicated AI assistant system according to this embodiment can make childcare a safer and more enjoyable experience.

[0030] The Q&A section provides instant answers to questions about a baby's daily routine and health. For example, if asked about how to deal with a baby's nighttime crying, the Q&A section will provide an immediate answer based on expert-supervised information. Specifically, it will provide detailed information on the causes and solutions for nighttime crying, based on past data and expert advice. The Q&A section can also provide instant answers to questions about how to handle a baby's illness. For example, it will provide information on appropriate responses to symptoms such as fever and diarrhea, and when to seek medical attention. Furthermore, the Q&A section can also provide instant answers to questions about a baby's daily routine. For example, it will provide advice on a baby's sleep patterns and feeding timing, supporting parents in establishing a healthy routine for their baby. The Q&A section utilizes AI to provide more personalized answers based on past question history and individual baby data. This allows parents to obtain quick and accurate information, alleviating anxieties and questions about childcare. In addition, the Q&A section can always provide the latest knowledge by incorporating regularly updated expert information and the latest childcare research. This allows the Q&A section to provide strong support for parents to confidently engage in childcare.

[0031] The Emotional Support Department listens attentively to parents based on the answers provided by the Response Department, offering encouragement and advice. For example, if a mother or father is feeling anxious about childcare, the Emotional Support Department will listen attentively and offer words of encouragement. Specifically, the AI ​​analyzes the parent's emotions and sends encouraging messages at the appropriate time. The Emotional Support Department can also listen attentively and offer advice if a mother or father is feeling lonely. For example, it may suggest joining a community to alleviate feelings of loneliness in childcare and offer advice to encourage interaction with other parents. Furthermore, if a mother or father is feeling stressed, the Emotional Support Department can listen attentively and offer encouragement and advice. For example, it may offer relaxation methods to relieve stress and specific advice to reduce the burden of childcare. The Emotional Support Department can use AI to monitor the parent's emotional state in real time and provide appropriate support. This allows parents to reduce anxiety and stress about childcare and approach it more positively. In addition, the Emotional Support Department can continuously improve its support based on parent feedback, providing more effective support. This allows the emotional support department to provide strong support that enables parents to confidently engage in childcare.

[0032] The Task Management Department manages schedules for tasks such as breastfeeding, diaper changes, and vaccinations. For example, it manages breastfeeding schedules and reminds parents. Specifically, AI learns the baby's breastfeeding patterns and suggests the optimal feeding times. The Task Management Department also manages and reminds parents of diaper changes. For example, it analyzes the baby's excretion patterns and suggests diaper changes at the appropriate time. Furthermore, the Task Management Department manages and reminds parents of vaccination schedules. For example, it automatically generates vaccination schedules and sends reminders as vaccination dates approach. The Task Management Department uses AI to optimize schedules based on the baby's individual data, supporting parents in efficiently managing childcare tasks. This allows parents to ensure they don't forget childcare tasks and can thoroughly manage their baby's health. In addition, the Task Management Department can adjust schedules based on parental feedback, providing more flexible and effective task management. As a result, the Task Management Department becomes a powerful tool for parents to efficiently manage childcare tasks and support their baby's health and growth.

[0033] The Health Management Department records the baby's growth data and analyzes their health status. For example, it records the baby's height and weight data to understand their growth process. Specifically, it regularly measures the baby's height and weight and records it in a database. The Health Management Department also analyzes the baby's health status and can suggest a visit to a medical institution if any abnormalities are found. For example, it evaluates whether the baby's growth is normal based on growth curves and recommends a visit to a medical institution if abnormalities are found. Furthermore, the Health Management Department records data on the baby's developmental stage and can comprehensively analyze their health status. For example, it records data on the baby's motor skills and language development to check for any developmental delays. The Health Management Department can use AI to analyze the baby's growth data in real time and provide appropriate advice to parents. This allows parents to constantly monitor their baby's health status and detect and address abnormalities early. Furthermore, the Health Management Department can continuously improve its analysis results based on parental feedback, providing more accurate health management. In this way, the Health Management Department becomes a powerful tool for comprehensively supporting the baby's health and growth.

[0034] The Community Department provides information on nearby childcare facilities and events, and offers community features to connect parents with other parents. For example, the Community Department provides information on nearby childcare facilities, introducing facilities that parents can use. Specifically, it provides details on the location, usage methods, and services offered at childcare facilities. The Community Department can also provide information on childcare events held in the neighborhood. For example, it provides information on the date, time, location, and participation methods for childcare seminars and parent-child interaction events. Furthermore, the Community Department can provide community features to connect parents with other parents and promote interaction. For example, it provides a place to exchange information and consult about childcare through online forums and chat functions. The Community Department uses AI to provide information based on parents' interests and concerns, supporting parents in efficiently obtaining information about childcare. This allows parents to obtain the latest information on childcare, share and solve childcare problems through interaction with other parents. Furthermore, the Community Department can continuously improve the information and functions it provides based on parent feedback, providing more effective community support. In this way, the Community Department can provide strong support to make parenting life safer and more enjoyable for parents.

[0035] The question reception department can receive questions about a baby's daily routine and health. For example, the question reception department can receive questions about how to deal with a baby's nighttime crying. It can also receive questions about how to deal with a baby's illness. Furthermore, the question reception department can receive questions about a baby's daily routine. In this way, the question reception department can respond to user questions. Some or all of the above processing in the question reception department may be performed using AI, for example, or not using AI. For example, the question reception department can receive questions from users via text input or voice input, and AI can analyze the content and provide an appropriate answer.

[0036] The Information Provision Department can provide answers based on information supervised by experts. For example, the Information Provision Department can provide answers to questions about how to deal with a baby's nighttime crying, based on information supervised by experts. The Information Provision Department can also provide answers to questions about how to deal with a baby's illness, based on information supervised by experts. Furthermore, the Information Provision Department can provide answers to questions about a baby's daily rhythm, based on information supervised by experts. In this way, the Information Provision Department can provide users with highly reliable information. Some or all of the above processing in the Information Provision Department may be performed using AI, for example, or not using AI. For example, the Information Provision Department can store expert-supervised information in a database, and AI can generate appropriate answers based on that information.

[0037] The Schedule Management Unit can manage schedules for activities such as breastfeeding, diaper changes, and vaccinations. For example, the Schedule Management Unit can manage breastfeeding schedules and remind mothers and fathers. It can also manage and remind them of diaper change schedules. Furthermore, it can manage and remind them of vaccination schedules. In this way, the Schedule Management Unit can support the efficiency of childcare. Some or all of the above processes in the Schedule Management Unit may be performed using AI, for example, or not using AI. For example, the Schedule Management Unit can display the user's schedule in a calendar format, and AI can use a reminder function to send notifications at appropriate times.

[0038] The reminder function can send reminders based on a schedule. For example, the reminder function can send reminders based on a breastfeeding schedule. It can also send reminders based on a diaper changing schedule. Furthermore, it can send reminders based on a vaccination schedule. This ensures that the user does not forget to perform important tasks. Some or all of the above processing in the reminder function may be performed using AI, for example, or not. For example, the reminder function can analyze the user's schedule, and the AI ​​can send reminders at the appropriate time.

[0039] The data recording unit can record the baby's growth data. For example, the data recording unit can record the baby's height and weight. It can also record data on the baby's developmental stage. Furthermore, the data recording unit can record data on the baby's health status. This allows the data recording unit to understand the baby's growth process. Some or all of the above processing in the data recording unit may be performed using AI, for example, or without AI. For example, the data recording unit can automatically collect the baby's growth data, and AI can analyze that data to understand the growth process.

[0040] The anomaly detection unit can analyze the health status and detect abnormalities. For example, the anomaly detection unit can analyze the baby's health data and detect abnormalities. It can also analyze the baby's growth data and detect abnormalities. Furthermore, it can analyze data on the baby's developmental stage and detect abnormalities. This allows the anomaly detection unit to detect abnormalities early and take appropriate action. Some or all of the above processing in the anomaly detection unit may be performed using AI, for example, or without AI. For example, the anomaly detection unit can monitor the baby's health data in real time, and AI can detect abnormalities and issue appropriate alerts.

[0041] The Community Department can provide information on nearby childcare facilities and events, and offer community features to connect parents. For example, the Community Department can provide information on nearby childcare facilities and introduce facilities that parents can use. It can also provide information on childcare events held in the neighborhood. Furthermore, the Community Department can provide community features to connect parents and promote interaction. In this way, the Community Department allows users to obtain local childcare information and interact with other parents. Some or all of the above processes in the Community Department may be performed using AI, for example, or not. For example, the Community Department can store information on local childcare facilities and events in a database, and AI can provide appropriate information based on that information.

[0042] The answering unit can adjust the level of detail in its answers depending on the content of the question. For example, it can provide a concise answer to a simple question, and a detailed explanation to a complex question. Furthermore, it can provide additional relevant information depending on the content of the question. In this way, the answering unit can provide information that meets the user's needs by providing answers with a level of detail appropriate to the question. Some or all of the above processing in the answering unit may be performed using AI, for example, or without AI. For example, the answering unit can input the content of the question into a generating AI, which can then analyze the content and generate an answer with an appropriate level of detail.

[0043] The answering unit can provide additional advice and information to the user based on the frequency and content of the questions. For example, if the same question is frequently repeated, the answering unit will provide relevant additional information. The answering unit can also provide relevant advice based on the content of the questions. Furthermore, the answering unit can follow up with the user depending on the frequency of the questions. In this way, the answering unit deepens the user's understanding by providing additional advice and information based on the frequency and content of the questions. Some or all of the above processing in the answering unit may be performed using AI, for example, or not using AI. For example, the answering unit can input the frequency and content of the questions into a generating AI, and the generating AI can analyze that data to generate appropriate advice and information.

[0044] The answering unit can provide answers by referring to relevant past questions and answers, depending on the content of the question. For example, if the answering unit has received answers to similar questions in the past, it can refer to those answers and provide them. The answering unit can also refer to past questions related to the content of the question and provide additional information. Furthermore, the answering unit can provide answers by referring to past answers based on the content of the question. In this way, the answering unit can provide quick and appropriate answers by referring to past questions and answers. Some or all of the above processing in the answering unit may be performed using AI, for example, or not using AI. For example, the answering unit can store past questions and answers in a database, and AI can search that data to provide appropriate answers.

[0045] The answering unit can provide answers based on the content of the question, incorporating relevant external resources and expert opinions. For example, the answering unit can provide answers by referring to external resources related to the content of the question. Furthermore, the answering unit can provide answers based on the content of the question, incorporating expert opinions. In addition, the answering unit can provide relevant external resources depending on the content of the question. This allows the answering unit to provide highly reliable answers by incorporating relevant external resources and expert opinions. Some or all of the above processing in the answering unit may be performed using AI, for example, or not. For example, the answering unit can store external resources and expert opinions in a database, and AI can search that data to provide appropriate answers.

[0046] The emotional support unit can analyze the user's past emotional history and select the optimal support method. For example, the emotional support unit can select the most appropriate method of encouragement based on the user's past emotional history. Furthermore, the emotional support unit can analyze the user's past emotional history and provide optimal advice. In addition, the emotional support unit can adjust the content of support based on the user's past emotional history. Thus, by analyzing the user's past emotional history, the emotional support unit can provide the user with the most suitable support method. Some or all of the above processes in the emotional support unit may be performed using AI, for example, or without AI. For example, the emotional support unit can input the user's past emotional data into a generating AI, which can then analyze the data to select the optimal support method.

[0047] The task management unit can analyze a user's past task history and select the optimal task management method. For example, the task management unit can select the optimal task management method based on the user's past task history. Furthermore, the task management unit can analyze the user's past task history and provide the optimal reminder method. In addition, the task management unit can adjust task priorities based on the user's past task history. Thus, by analyzing past task history, the task management unit can provide the user with the optimal task management method. Some or all of the above processes in the task management unit may be performed using AI, for example, or without AI. For example, the task management unit can input the user's past task data into a generating AI, which can then analyze that data to select the optimal task management method.

[0048] The task management unit can provide real-time task reminders based on the task's progress. For example, the task management unit can provide real-time reminders based on the task's progress. Furthermore, the task management unit can monitor the task's progress and provide reminders as needed. In addition, the task management unit can provide reminders at the optimal time based on the task's progress. This allows the task management unit to provide real-time reminders based on the task's progress, ensuring users remember to complete tasks. Some or all of the above processes in the task management unit may be performed using AI, or not. For example, the task management unit can input task progress data into a generating AI, which can then analyze the data and provide appropriate reminders.

[0049] The task management unit can suggest relevant resources and tools based on the user's task management. For example, the task management unit can suggest the optimal resources based on the user's task management. Furthermore, the task management unit can suggest relevant tools based on the user's task management. In addition, the task management unit can suggest efficient resources based on the user's task management. Thus, the task management unit improves task efficiency by suggesting relevant resources and tools based on the user's task management. Some or all of the above processing in the task management unit may be performed using AI, for example, or without AI. For example, the task management unit can input the user's task data into a generating AI, which can then analyze the data and suggest appropriate resources and tools.

[0050] The task management unit can provide a task sharing function with other family members based on the user's task management. For example, the task management unit can provide a function to share tasks with other family members based on the user's task management. Furthermore, the task management unit can facilitate task sharing with family members based on the user's task management. In addition, the task management unit can support task sharing with family members based on the user's task management. This streamlines task management for the entire family by providing a task sharing function with other family members based on the user's task management. Some or all of the above processing in the task management unit may be performed using AI, for example, or without AI. For example, the task management unit can input the user's task data into a generating AI, which can then analyze the data and propose an appropriate task sharing method.

[0051] The Health Management Department can analyze a baby's past health data and select the optimal health management method. For example, the Health Management Department can select the optimal health management method based on the baby's past health data. Furthermore, the Health Management Department can analyze the baby's past health data and provide optimal advice. In addition, the Health Management Department can adjust the content of health management based on the baby's past health data. Thus, by analyzing the baby's past health data, the Health Management Department can provide the optimal health management method. Some or all of the above processes in the Health Management Department may be performed using AI, for example, or without AI. For example, the Health Management Department can input the baby's past health data into a generating AI, which can then analyze the data and select the optimal health management method.

[0052] The Health Management Department can update health management advice in real time in response to changes in health data. For example, the Health Management Department updates advice in real time in response to changes in health data. Furthermore, the Health Management Department can monitor changes in health data and update advice as needed. In addition, the Health Management Department can update advice at the optimal time based on changes in health data. This allows the Health Management Department to provide appropriate health management by updating advice in real time in response to changes in health data. Some or all of the above processes in the Health Management Department may be performed using AI, for example, or without AI. For example, the Health Management Department can input changes in health data into a generating AI, which can then analyze the data and provide appropriate advice.

[0053] The Health Management Department can provide advice based on the baby's health data, incorporating the opinions of relevant medical institutions and specialists. For example, the Health Management Department can provide information on relevant medical institutions based on the baby's health data. Furthermore, the Health Management Department can provide advice based on the baby's health data, incorporating the opinions of specialists. In addition, the Health Management Department can suggest the most suitable medical institution based on the baby's health data. This allows the Health Management Department to provide highly reliable health management advice by incorporating the opinions of relevant medical institutions and specialists based on the baby's health data. Some or all of the above processes in the Health Management Department may be performed using AI, for example, or not. For example, the Health Management Department can input the baby's health data into a generating AI, which can then analyze the data and provide opinions on appropriate medical institutions and specialists.

[0054] The Health Management Department can provide a function for sharing health information with other family members based on the baby's health data. For example, the Health Management Department can provide a function for sharing health information with other family members based on the baby's health data. Furthermore, the Health Management Department can facilitate the sharing of health information with family members based on the baby's health data. In addition, the Health Management Department can support the sharing of health information with family members based on the baby's health data. This improves overall family health management by providing a function for sharing health information with other family members based on the baby's health data. Some or all of the above processing in the Health Management Department may be performed using AI, for example, or without AI. For example, the Health Management Department can input the baby's health data into a generating AI, which can then analyze the data and propose an appropriate method for sharing health information.

[0055] The Community Department can analyze a user's past community participation history and select the optimal way to participate in a community. For example, the Community Department can select the optimal participation method based on a user's past community participation history. Furthermore, the Community Department can analyze a user's past community participation history and propose the optimal participation method. In addition, the Community Department can adjust the content of community participation based on a user's past community participation history. In this way, the Community Department can provide users with the optimal way to participate in a community by analyzing their past community participation history. Some or all of the above-described processes in the Community Department may be performed using AI, for example, or without AI. For example, the Community Department can input a user's past community participation data into a generating AI, which can then analyze that data to select the optimal way to participate in a community.

[0056] The Community Department can provide real-time participation reminders based on the community's activity status. For example, the Community Department can provide real-time participation reminders based on the community's activity status. Furthermore, the Community Department can monitor the community's activity status and provide reminders as needed. In addition, the Community Department can provide reminders at the optimal time based on the community's activity status. This allows the Community Department to provide real-time reminders based on the community's activity status, enabling users to actively participate in community activities. Some or all of the above processing in the Community Department may be performed using AI, or not. For example, the Community Department can input community activity data into a generating AI, which can then analyze the data and provide appropriate reminders.

[0057] The community department can suggest relevant events and activities based on users' community participation. For example, the community department can suggest relevant events based on users' community participation. Furthermore, the community department can suggest relevant activities based on users' community participation. In addition, the community department can suggest optimal events and activities based on users' community participation. This allows the community department to promote user community participation by suggesting relevant events and activities based on users' community participation. Some or all of the above processing in the community department may be performed using AI, for example, or without AI. For example, the community department can input user community participation data into a generating AI, which can then analyze the data and suggest appropriate events and activities.

[0058] The community department can provide functions to promote interaction between users based on their community participation. For example, the community department can provide functions to promote interaction between users based on their community participation. Furthermore, the community department can propose events to promote interaction based on users' community participation. In addition, the community department can propose optimal methods of interaction based on users' community participation. In this way, the community department reduces feelings of isolation among users by promoting interaction between users based on their community participation. Some or all of the above-described processes in the community department may be performed using AI, for example, or without AI. For example, the community department can input user community participation data into a generating AI, which can then analyze the data and propose appropriate methods of interaction.

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

[0060] The dedicated AI assistant system can also include an education section to enhance users' knowledge of childcare. This education section provides specialized knowledge and skills related to childcare, supporting users in deepening their understanding of the subject. For example, it can provide appropriate care methods according to the baby's developmental stage. It can also provide the latest research findings and expert opinions on childcare. Furthermore, it can offer online courses and workshops on childcare, providing users with opportunities to practically learn about childcare. This allows the education section to boost users' confidence in childcare and enrich their parenting experience.

[0061] The dedicated AI assistant system can also include a consultation service to help users resolve their parenting concerns. This consultation service provides a space where users can easily discuss their parenting worries and questions. For example, it could offer online consultations with parenting experts. It could also provide group consultations, allowing parents to exchange information and opinions with other parents. Furthermore, it could offer anonymous consultations, providing a safe space for users to confide their worries. In this way, the consultation service can help users resolve their parenting concerns and make their parenting life more secure and enjoyable.

[0062] A dedicated AI assistant system can also include a data management unit to organize the user's childcare-related information. This data management unit supports the user in efficiently managing childcare information. For example, it centrally manages the baby's growth records and health data. It can also organize childcare schedules and tasks, supporting the user in raising their child efficiently. Furthermore, it can analyze childcare-related information and provide the user with appropriate advice and suggestions. In this way, the data management unit can organize the user's childcare-related information and support them in raising their child more efficiently.

[0063] The dedicated AI assistant system can also include a motivation section to enhance the user's motivation for childcare. This section provides support to increase the user's enthusiasm for childcare. For example, it can help users set childcare goals, allowing them to feel a sense of accomplishment. It can also share successful childcare experiences, helping users approach childcare with confidence. Furthermore, it can provide encouraging messages and advice to help users maintain their motivation. In this way, the motivation section can increase the user's enthusiasm for childcare and enrich their childcare life.

[0064] The dedicated AI assistant system can also include a relaxation section to alleviate the user's stress related to childcare. This relaxation section supports the user in relieving stress related to childcare. For example, it suggests relaxation methods and stress-relieving techniques. It can also provide relaxation music and meditation guides to create a relaxing environment for the user. Furthermore, it can offer advice on stress management related to childcare, enabling the user to effectively control stress. In this way, the relaxation section reduces the user's stress related to childcare, making their childcare life more comfortable.

[0065] The following briefly describes the processing flow for example form 1.

[0066] Step 1: The answer section provides immediate answers to questions about the baby's daily routine and health. For example, it provides immediate answers to questions about how to deal with a baby's nighttime crying, how to handle illness, and questions about daily routines, based on information supervised by experts. Step 2: The Emotional Support Department listens attentively to the responses provided by the Response Department and offers encouragement and advice. For example, they listen attentively to mothers and fathers who are feeling anxious, lonely, or stressed about childcare and offer encouragement and advice. Step 3: The task management department manages schedules for things like breastfeeding, diaper changes, and vaccinations. For example, it manages the schedules for breastfeeding, diaper changes, and vaccinations and sends reminders to moms and dads. Step 4: The health management department records the baby's growth data and analyzes their health status. For example, they record the baby's height and weight data to understand their growth process. They also analyze the baby's health status and suggest a visit to a medical institution if any abnormalities are found. Furthermore, they record developmental stage data and conduct a comprehensive analysis of the baby's health status. Step 5: The Community Department provides information on nearby childcare facilities and events, and offers community features to connect parents. For example, it provides information on nearby childcare facilities and events, and offers community features to connect parents.

[0067] (Example of form 2) The dedicated AI assistant system according to an embodiment of the present invention is a system that alleviates the anxiety and loneliness felt by new mothers and fathers, making childcare a safer and more enjoyable experience. This dedicated AI assistant system has the function of providing instant 24-hour answers to questions about the baby's daily rhythm and health, based on information supervised by experts. For example, the AI ​​can instantly answer questions about how to deal with nighttime crying or how to handle illness. Next, it has an emotional support function, where the AI ​​listens empathetically and provides encouragement and advice. This reduces feelings of loneliness and stress for mothers and fathers. Furthermore, it has a childcare task management function, where the AI ​​agent proactively grasps schedules for breastfeeding, diaper changes, vaccinations, etc., shares them with the family, and provides reminders to support more efficient childcare. It also has a function to record the baby's growth data and analyze its health status. If there is an abnormality, the AI ​​will suggest visiting a medical institution. In addition, it has a local information and parent community function, providing information on nearby childcare facilities and events, and also includes a community function that connects parents with other parents. In this way, by resolving the worries and alleviating feelings of loneliness experienced during childcare, the system provides an environment where mothers and fathers can confidently face the challenges of raising children. It functions as a "reliable partner" that supports them throughout their childcare journey. As a result, the dedicated AI assistant system can provide an environment where mothers and fathers can confidently face the challenges of raising children by resolving the worries and alleviating feelings of loneliness experienced during childcare.

[0068] The dedicated AI assistant system according to this embodiment comprises an answering unit, an emotional support unit, a task management unit, a health management unit, and a community unit. The answering unit provides immediate answers to questions about the baby's daily rhythm and health. For example, if asked about how to deal with a baby's nighttime crying, the answering unit provides an immediate answer based on information supervised by experts. The answering unit can also provide immediate answers to questions about how to deal with a baby's illness. Furthermore, the answering unit can also provide immediate answers to questions about the baby's daily rhythm. The emotional support unit listens empathetically based on the answers provided by the answering unit and offers encouragement and advice. For example, if a mother or father is feeling anxious about childcare, the emotional support unit listens empathetically and offers words of encouragement. Furthermore, if a mother or father is feeling lonely, the emotional support unit can listen empathetically and offer advice. Furthermore, if a mother or father is feeling stressed, the emotional support unit can listen empathetically and offer encouragement and advice. The task management unit manages schedules such as breastfeeding, diaper changes, and vaccinations. For example, the Task Management Department manages breastfeeding schedules and sends reminders to mothers and fathers. It can also manage and remind them of diaper changing schedules. Furthermore, it can manage and remind them of vaccination schedules. The Health Management Department records the baby's growth data and analyzes their health status. For example, it records the baby's height and weight data to understand their growth process. It also analyzes the baby's health status and can suggest a visit to a medical institution if there are any abnormalities. Furthermore, it records data on the baby's developmental stage and can comprehensively analyze their health status. The Community Department provides information on nearby childcare facilities and events, and offers community features to connect parents. For example, it provides information on nearby childcare facilities and introduces facilities that parents can use. It can also provide information on childcare events held in the neighborhood. Furthermore, it provides community features to connect parents and promote interaction.As a result, the dedicated AI assistant system according to this embodiment can make childcare a safer and more enjoyable experience.

[0069] The Q&A section provides instant answers to questions about a baby's daily routine and health. For example, if asked about how to deal with a baby's nighttime crying, the Q&A section will provide an immediate answer based on expert-supervised information. Specifically, it will provide detailed information on the causes and solutions for nighttime crying, based on past data and expert advice. The Q&A section can also provide instant answers to questions about how to handle a baby's illness. For example, it will provide information on appropriate responses to symptoms such as fever and diarrhea, and when to seek medical attention. Furthermore, the Q&A section can also provide instant answers to questions about a baby's daily routine. For example, it will provide advice on a baby's sleep patterns and feeding timing, supporting parents in establishing a healthy routine for their baby. The Q&A section utilizes AI to provide more personalized answers based on past question history and individual baby data. This allows parents to obtain quick and accurate information, alleviating anxieties and questions about childcare. In addition, the Q&A section can always provide the latest knowledge by incorporating regularly updated expert information and the latest childcare research. This allows the Q&A section to provide strong support for parents to confidently engage in childcare.

[0070] The Emotional Support Department listens attentively to parents based on the answers provided by the Response Department, offering encouragement and advice. For example, if a mother or father is feeling anxious about childcare, the Emotional Support Department will listen attentively and offer words of encouragement. Specifically, the AI ​​analyzes the parent's emotions and sends encouraging messages at the appropriate time. The Emotional Support Department can also listen attentively and offer advice if a mother or father is feeling lonely. For example, it may suggest joining a community to alleviate feelings of loneliness in childcare and offer advice to encourage interaction with other parents. Furthermore, if a mother or father is feeling stressed, the Emotional Support Department can listen attentively and offer encouragement and advice. For example, it may offer relaxation methods to relieve stress and specific advice to reduce the burden of childcare. The Emotional Support Department can use AI to monitor the parent's emotional state in real time and provide appropriate support. This allows parents to reduce anxiety and stress about childcare and approach it more positively. In addition, the Emotional Support Department can continuously improve its support based on parent feedback, providing more effective support. This allows the emotional support department to provide strong support that enables parents to confidently engage in childcare.

[0071] The Task Management Department manages schedules for tasks such as breastfeeding, diaper changes, and vaccinations. For example, it manages breastfeeding schedules and reminds parents. Specifically, AI learns the baby's breastfeeding patterns and suggests the optimal feeding times. The Task Management Department also manages and reminds parents of diaper changes. For example, it analyzes the baby's excretion patterns and suggests diaper changes at the appropriate time. Furthermore, the Task Management Department manages and reminds parents of vaccination schedules. For example, it automatically generates vaccination schedules and sends reminders as vaccination dates approach. The Task Management Department uses AI to optimize schedules based on the baby's individual data, supporting parents in efficiently managing childcare tasks. This allows parents to ensure they don't forget childcare tasks and can thoroughly manage their baby's health. In addition, the Task Management Department can adjust schedules based on parental feedback, providing more flexible and effective task management. As a result, the Task Management Department becomes a powerful tool for parents to efficiently manage childcare tasks and support their baby's health and growth.

[0072] The Health Management Department records the baby's growth data and analyzes their health status. For example, it records the baby's height and weight data to understand their growth process. Specifically, it regularly measures the baby's height and weight and records it in a database. The Health Management Department also analyzes the baby's health status and can suggest a visit to a medical institution if any abnormalities are found. For example, it evaluates whether the baby's growth is normal based on growth curves and recommends a visit to a medical institution if abnormalities are found. Furthermore, the Health Management Department records data on the baby's developmental stage and can comprehensively analyze their health status. For example, it records data on the baby's motor skills and language development to check for any developmental delays. The Health Management Department can use AI to analyze the baby's growth data in real time and provide appropriate advice to parents. This allows parents to constantly monitor their baby's health status and detect and address abnormalities early. Furthermore, the Health Management Department can continuously improve its analysis results based on parental feedback, providing more accurate health management. In this way, the Health Management Department becomes a powerful tool for comprehensively supporting the baby's health and growth.

[0073] The Community Department provides information on nearby childcare facilities and events, and offers community features to connect parents with other parents. For example, the Community Department provides information on nearby childcare facilities, introducing facilities that parents can use. Specifically, it provides details on the location, usage methods, and services offered at childcare facilities. The Community Department can also provide information on childcare events held in the neighborhood. For example, it provides information on the date, time, location, and participation methods for childcare seminars and parent-child interaction events. Furthermore, the Community Department can provide community features to connect parents with other parents and promote interaction. For example, it provides a place to exchange information and consult about childcare through online forums and chat functions. The Community Department uses AI to provide information based on parents' interests and concerns, supporting parents in efficiently obtaining information about childcare. This allows parents to obtain the latest information on childcare, share and solve childcare problems through interaction with other parents. Furthermore, the Community Department can continuously improve the information and functions it provides based on parent feedback, providing more effective community support. In this way, the Community Department can provide strong support to make parenting life safer and more enjoyable for parents.

[0074] The question reception department can receive questions about a baby's daily routine and health. For example, the question reception department can receive questions about how to deal with a baby's nighttime crying. It can also receive questions about how to deal with a baby's illness. Furthermore, the question reception department can receive questions about a baby's daily routine. In this way, the question reception department can respond to user questions. Some or all of the above processing in the question reception department may be performed using AI, for example, or not using AI. For example, the question reception department can receive questions from users via text input or voice input, and AI can analyze the content and provide an appropriate answer.

[0075] The Information Provision Department can provide answers based on information supervised by experts. For example, the Information Provision Department can provide answers to questions about how to deal with a baby's nighttime crying, based on information supervised by experts. The Information Provision Department can also provide answers to questions about how to deal with a baby's illness, based on information supervised by experts. Furthermore, the Information Provision Department can provide answers to questions about a baby's daily rhythm, based on information supervised by experts. In this way, the Information Provision Department can provide users with highly reliable information. Some or all of the above processing in the Information Provision Department may be performed using AI, for example, or not using AI. For example, the Information Provision Department can store expert-supervised information in a database, and AI can generate appropriate answers based on that information.

[0076] The Schedule Management Unit can manage schedules for activities such as breastfeeding, diaper changes, and vaccinations. For example, the Schedule Management Unit can manage breastfeeding schedules and remind mothers and fathers. It can also manage and remind them of diaper change schedules. Furthermore, it can manage and remind them of vaccination schedules. In this way, the Schedule Management Unit can support the efficiency of childcare. Some or all of the above processes in the Schedule Management Unit may be performed using AI, for example, or not using AI. For example, the Schedule Management Unit can display the user's schedule in a calendar format, and AI can use a reminder function to send notifications at appropriate times.

[0077] The reminder function can send reminders based on a schedule. For example, the reminder function can send reminders based on a breastfeeding schedule. It can also send reminders based on a diaper changing schedule. Furthermore, it can send reminders based on a vaccination schedule. This ensures that the user does not forget to perform important tasks. Some or all of the above processing in the reminder function may be performed using AI, for example, or not. For example, the reminder function can analyze the user's schedule, and the AI ​​can send reminders at the appropriate time.

[0078] The data recording unit can record the baby's growth data. For example, the data recording unit can record the baby's height and weight. It can also record data on the baby's developmental stage. Furthermore, the data recording unit can record data on the baby's health status. This allows the data recording unit to understand the baby's growth process. Some or all of the above processing in the data recording unit may be performed using AI, for example, or without AI. For example, the data recording unit can automatically collect the baby's growth data, and AI can analyze that data to understand the growth process.

[0079] The anomaly detection unit can analyze the health status and detect abnormalities. For example, the anomaly detection unit can analyze the baby's health data and detect abnormalities. It can also analyze the baby's growth data and detect abnormalities. Furthermore, it can analyze data on the baby's developmental stage and detect abnormalities. This allows the anomaly detection unit to detect abnormalities early and take appropriate action. Some or all of the above processing in the anomaly detection unit may be performed using AI, for example, or without AI. For example, the anomaly detection unit can monitor the baby's health data in real time, and AI can detect abnormalities and issue appropriate alerts.

[0080] The Community Department can provide information on nearby childcare facilities and events, and offer community features to connect parents. For example, the Community Department can provide information on nearby childcare facilities and introduce facilities that parents can use. It can also provide information on childcare events held in the neighborhood. Furthermore, the Community Department can provide community features to connect parents and promote interaction. In this way, the Community Department allows users to obtain local childcare information and interact with other parents. Some or all of the above processes in the Community Department may be performed using AI, for example, or not. For example, the Community Department can store information on local childcare facilities and events in a database, and AI can provide appropriate information based on that information.

[0081] The response unit can estimate the user's emotions and adjust the way it expresses its response based on those emotions. For example, if the user is stressed, the response unit can provide a gentle response. If the user is relaxed, the response unit can provide a more detailed response. Furthermore, if the user is in a hurry, the response unit can provide a concise and quick response. This improves user satisfaction by providing responses in a way that matches the user's emotions. Emotion estimation is achieved using an emotion estimation function, such as an emotion engine or generative AI. Generative AI may be, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the response unit may be performed using AI or not. For example, the response unit can input user emotion data into a generative AI, which can then analyze the data and select an appropriate expression.

[0082] The answering unit can adjust the level of detail in its answers depending on the content of the question. For example, it can provide a concise answer to a simple question, and a detailed explanation to a complex question. Furthermore, it can provide additional relevant information depending on the content of the question. In this way, the answering unit can provide information that meets the user's needs by providing answers with a level of detail appropriate to the question. Some or all of the above processing in the answering unit may be performed using AI, for example, or without AI. For example, the answering unit can input the content of the question into a generating AI, which can then analyze the content and generate an answer with an appropriate level of detail.

[0083] The answering unit can provide additional advice and information to the user based on the frequency and content of the questions. For example, if the same question is frequently repeated, the answering unit will provide relevant additional information. The answering unit can also provide relevant advice based on the content of the questions. Furthermore, the answering unit can follow up with the user depending on the frequency of the questions. In this way, the answering unit deepens the user's understanding by providing additional advice and information based on the frequency and content of the questions. Some or all of the above processing in the answering unit may be performed using AI, for example, or not using AI. For example, the answering unit can input the frequency and content of the questions into a generating AI, and the generating AI can analyze that data to generate appropriate advice and information.

[0084] The response unit can estimate the user's emotions and determine the priority of responses based on the estimated emotions. For example, if the user is feeling anxious, the response unit will provide a priority response. If the user is relaxed, the response unit can provide a normal priority response. Furthermore, if the user is in a hurry, the response unit can provide a quick response. In this way, the response unit reduces the user's anxiety and stress by providing responses with priorities according to the user's emotions. Emotion estimation is achieved using an emotion estimation function, for example, using an emotion engine or generative AI. Generative AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the response unit may be performed using AI, or not using AI. For example, the response unit can input user emotion data into a generative AI, which can analyze the data to determine an appropriate priority.

[0085] The answering unit can provide answers by referring to relevant past questions and answers, depending on the content of the question. For example, if the answering unit has received answers to similar questions in the past, it can refer to those answers and provide them. The answering unit can also refer to past questions related to the content of the question and provide additional information. Furthermore, the answering unit can provide answers by referring to past answers based on the content of the question. In this way, the answering unit can provide quick and appropriate answers by referring to past questions and answers. Some or all of the above processing in the answering unit may be performed using AI, for example, or not using AI. For example, the answering unit can store past questions and answers in a database, and AI can search that data to provide appropriate answers.

[0086] The answering unit can provide answers based on the content of the question, incorporating relevant external resources and expert opinions. For example, the answering unit can provide answers by referring to external resources related to the content of the question. Furthermore, the answering unit can provide answers based on the content of the question, incorporating expert opinions. In addition, the answering unit can provide relevant external resources depending on the content of the question. This allows the answering unit to provide highly reliable answers by incorporating relevant external resources and expert opinions. Some or all of the above processing in the answering unit may be performed using AI, for example, or not. For example, the answering unit can store external resources and expert opinions in a database, and AI can search that data to provide appropriate answers.

[0087] The emotional support unit can estimate the user's emotions and adjust the content of encouragement and advice based on the estimated emotions. For example, if the user is feeling stressed, the emotional support unit can offer gentle words of encouragement. If the user is relaxed, the emotional support unit can offer detailed advice. Furthermore, if the user is feeling anxious, the emotional support unit can offer reassuring advice. In this way, the emotional support unit reduces the user's feelings of loneliness and stress by providing encouragement and advice that are appropriate to the user's emotions. Emotion estimation is achieved using an emotion estimation function, for example, using an emotion engine or a generative AI. The generative AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the emotional support unit may be performed using AI, or not using AI. For example, the emotional support unit can input the user's emotional data into a generative AI, which can then analyze the data to generate appropriate encouragement and advice.

[0088] The emotional support unit can analyze the user's past emotional history and select the optimal support method. For example, the emotional support unit can select the most appropriate method of encouragement based on the user's past emotional history. Furthermore, the emotional support unit can analyze the user's past emotional history and provide optimal advice. In addition, the emotional support unit can adjust the content of support based on the user's past emotional history. Thus, by analyzing the user's past emotional history, the emotional support unit can provide the user with the most suitable support method. Some or all of the above processes in the emotional support unit may be performed using AI, for example, or without AI. For example, the emotional support unit can input the user's past emotional data into a generating AI, which can then analyze the data to select the optimal support method.

[0089] The emotional support unit can update support content in real time in response to changes in the user's emotions. For example, if the user's emotions change, the emotional support unit will update the content of encouragement in real time. Furthermore, the emotional support unit can update the content of advice in real time in response to changes in the user's emotions. In addition, the emotional support unit can detect changes in the user's emotions and adjust the support content in real time. This allows the emotional support unit to provide appropriate support by updating the support content in real time in response to changes in the user's emotions. Emotion estimation is achieved using an emotion estimation function, for example, an emotion engine or a generative AI. The generative AI may be, but is not limited to, a text generation AI (e.g., LLM) or a multimodal generation AI. Some or all of the above-described processes in the emotional support unit may be performed using AI, or not. For example, the emotional support unit can input user emotion data into a generative AI, which can then analyze the data and update the support content in real time.

[0090] The emotional support unit can estimate the user's emotions and adjust the frequency of support based on the estimated emotions. For example, if the user is feeling stressed, the emotional support unit can provide encouragement frequently. If the user is relaxed, the emotional support unit can provide support at a normal frequency. Furthermore, if the user is feeling anxious, the emotional support unit can provide advice frequently. In this way, the emotional support unit reduces the user's feelings of loneliness and stress by providing support at a frequency appropriate to the user's emotions. Emotion estimation is achieved using an emotion estimation function, for example, using an emotion engine or generative AI. The generative AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the emotional support unit may be performed using AI, or not using AI. For example, the emotional support unit can input the user's emotion data into the generative AI, which can analyze the data to determine an appropriate support frequency.

[0091] The emotional support unit can suggest relevant relaxation and stress relief methods based on the user's emotions. For example, if the user is feeling stressed, the emotional support unit can suggest relaxation methods. Similarly, if the user is relaxed, the emotional support unit can suggest stress relief methods. Furthermore, the emotional support unit can suggest the most suitable relaxation method based on the user's emotions. In this way, the emotional support unit reduces the user's stress by suggesting relaxation and stress relief methods based on the user's emotions. Emotion estimation is achieved using an emotion estimation function, for example, with an emotion engine or generative AI. Generative AI may be, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above-described processes in the emotional support unit may be performed using AI, or not. For example, the emotional support unit can input user emotion data into a generative AI, which can then analyze the data to suggest appropriate relaxation and stress relief methods.

[0092] The emotional support unit can provide community features to facilitate interaction with other users based on the user's emotions. For example, if the emotional support unit is feeling lonely, it can provide features to facilitate interaction with other users. It can also provide community features if the user is relaxed. Furthermore, the emotional support unit can provide optimal community features based on the user's emotions. In this way, the emotional support unit reduces the user's feelings of loneliness by facilitating interaction with other users based on their emotions. Emotion estimation is achieved using an emotion estimation function, for example, an emotion engine or a generative AI. The generative AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above-described processing in the emotional support unit may be performed using AI, or not. For example, the emotional support unit can input user emotion data into a generative AI, which can then analyze the data to provide appropriate community features.

[0093] The task management unit can estimate the user's emotions and adjust task priorities based on those emotions. For example, if the user is stressed, the task management unit will prioritize and remind them of important tasks. If the user is relaxed, the task management unit can remind them of tasks with normal priority. Furthermore, if the user is in a hurry, the task management unit can prioritize and remind them of tasks that require immediate attention. In this way, the task management unit reduces user stress by managing tasks with priorities that match the user's emotions. Emotion estimation is achieved using an emotion estimation function, for example, using an emotion engine or generative AI. Generative AI may be, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the task management unit may be performed using AI or not using AI. For example, the task management unit can input user emotion data into a generative AI, which can analyze that data to determine appropriate task priorities.

[0094] The task management unit can analyze a user's past task history and select the optimal task management method. For example, the task management unit can select the optimal task management method based on the user's past task history. Furthermore, the task management unit can analyze the user's past task history and provide the optimal reminder method. In addition, the task management unit can adjust task priorities based on the user's past task history. Thus, by analyzing past task history, the task management unit can provide the user with the optimal task management method. Some or all of the above processes in the task management unit may be performed using AI, for example, or without AI. For example, the task management unit can input the user's past task data into a generating AI, which can then analyze that data to select the optimal task management method.

[0095] The task management unit can provide real-time task reminders based on the task's progress. For example, the task management unit can provide real-time reminders based on the task's progress. Furthermore, the task management unit can monitor the task's progress and provide reminders as needed. In addition, the task management unit can provide reminders at the optimal time based on the task's progress. This allows the task management unit to provide real-time reminders based on the task's progress, ensuring users remember to complete tasks. Some or all of the above processes in the task management unit may be performed using AI, or not. For example, the task management unit can input task progress data into a generating AI, which can then analyze the data and provide appropriate reminders.

[0096] The task management unit can estimate the user's emotions and adjust the frequency of task reminders based on the estimated emotions. For example, if the user is stressed, the task management unit will send frequent reminders. If the user is relaxed, the task management unit can send reminders at a normal frequency. Furthermore, if the user is in a hurry, the task management unit can send reminders quickly. In this way, the task management unit reduces user stress by reminding users of tasks at a frequency appropriate to their emotions. Emotion estimation is achieved using an emotion estimation function, for example, using an emotion engine or generative AI. Generative AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the task management unit may be performed using AI, or not using AI. For example, the task management unit can input user emotion data into a generative AI, which can analyze the data to determine an appropriate reminder frequency.

[0097] The task management unit can suggest relevant resources and tools based on the user's task management. For example, the task management unit can suggest the optimal resources based on the user's task management. Furthermore, the task management unit can suggest relevant tools based on the user's task management. In addition, the task management unit can suggest efficient resources based on the user's task management. Thus, the task management unit improves task efficiency by suggesting relevant resources and tools based on the user's task management. Some or all of the above processing in the task management unit may be performed using AI, for example, or without AI. For example, the task management unit can input the user's task data into a generating AI, which can then analyze the data and suggest appropriate resources and tools.

[0098] The task management unit can provide a task sharing function with other family members based on the user's task management. For example, the task management unit can provide a function to share tasks with other family members based on the user's task management. Furthermore, the task management unit can facilitate task sharing with family members based on the user's task management. In addition, the task management unit can support task sharing with family members based on the user's task management. This streamlines task management for the entire family by providing a task sharing function with other family members based on the user's task management. Some or all of the above processing in the task management unit may be performed using AI, for example, or without AI. For example, the task management unit can input the user's task data into a generating AI, which can then analyze the data and propose an appropriate task sharing method.

[0099] The health management department can estimate the user's emotions and adjust health management advice based on those emotions. For example, if the user is feeling stressed, the health management department can provide health management advice to help them relax. If the user is relaxed, the health management department can provide standard health management advice. Furthermore, if the user is feeling anxious, the health management department can provide reassuring health management advice. In this way, the health management department improves the user's health management by providing health management advice tailored to the user's emotions. Emotion estimation is achieved using an emotion estimation function, for example, using an emotion engine or generative AI. Generative AI may be, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the health management department may be performed using AI, or not using AI. For example, the health management department can input user emotion data into a generative AI, which can then analyze the data to provide appropriate health management advice.

[0100] The Health Management Department can analyze a baby's past health data and select the optimal health management method. For example, the Health Management Department can select the optimal health management method based on the baby's past health data. Furthermore, the Health Management Department can analyze the baby's past health data and provide optimal advice. In addition, the Health Management Department can adjust the content of health management based on the baby's past health data. Thus, by analyzing the baby's past health data, the Health Management Department can provide the optimal health management method. Some or all of the above processes in the Health Management Department may be performed using AI, for example, or without AI. For example, the Health Management Department can input the baby's past health data into a generating AI, which can then analyze the data and select the optimal health management method.

[0101] The Health Management Department can update health management advice in real time in response to changes in health data. For example, the Health Management Department updates advice in real time in response to changes in health data. Furthermore, the Health Management Department can monitor changes in health data and update advice as needed. In addition, the Health Management Department can update advice at the optimal time based on changes in health data. This allows the Health Management Department to provide appropriate health management by updating advice in real time in response to changes in health data. Some or all of the above processes in the Health Management Department may be performed using AI, for example, or without AI. For example, the Health Management Department can input changes in health data into a generating AI, which can then analyze the data and provide appropriate advice.

[0102] The health management unit can estimate the user's emotions and adjust the frequency of health management based on the estimated emotions. For example, if the user is stressed, the health management unit can provide health management advice more frequently. If the user is relaxed, the health management unit can provide health management advice at a normal frequency. Furthermore, if the user is anxious, the health management unit can provide health management advice more frequently. In this way, the health management unit improves the user's health management by providing health management advice at a frequency appropriate to the user's emotions. Emotion estimation is achieved using an emotion estimation function, for example, using an emotion engine or generative AI. Generative AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the health management unit may be performed using AI, for example, or not using AI. For example, the health management unit can input user emotion data into a generative AI, which can analyze the data to determine an appropriate frequency of health management.

[0103] The Health Management Department can provide advice based on the baby's health data, incorporating the opinions of relevant medical institutions and specialists. For example, the Health Management Department can provide information on relevant medical institutions based on the baby's health data. Furthermore, the Health Management Department can provide advice based on the baby's health data, incorporating the opinions of specialists. In addition, the Health Management Department can suggest the most suitable medical institution based on the baby's health data. This allows the Health Management Department to provide highly reliable health management advice by incorporating the opinions of relevant medical institutions and specialists based on the baby's health data. Some or all of the above processes in the Health Management Department may be performed using AI, for example, or not. For example, the Health Management Department can input the baby's health data into a generating AI, which can then analyze the data and provide opinions on appropriate medical institutions and specialists.

[0104] The Health Management Department can provide a function for sharing health information with other family members based on the baby's health data. For example, the Health Management Department can provide a function for sharing health information with other family members based on the baby's health data. Furthermore, the Health Management Department can facilitate the sharing of health information with family members based on the baby's health data. In addition, the Health Management Department can support the sharing of health information with family members based on the baby's health data. This improves overall family health management by providing a function for sharing health information with other family members based on the baby's health data. Some or all of the above processing in the Health Management Department may be performed using AI, for example, or without AI. For example, the Health Management Department can input the baby's health data into a generating AI, which can then analyze the data and propose an appropriate method for sharing health information.

[0105] The community unit can estimate a user's emotions and promote community participation based on those emotions. For example, if a user is feeling lonely, the community unit can encourage community participation. It can also suggest community participation if a user is relaxed. Furthermore, based on the user's emotions, the community unit can suggest the most appropriate way to participate in the community. In this way, the community unit reduces the user's feelings of loneliness by promoting community participation based on their emotions. Emotion estimation is achieved using an emotion estimation function, such as an emotion engine or generative AI. Generative AI may be, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above-described processes in the community unit may be performed using AI, or not. For example, the community unit can input user emotion data into a generative AI, which can then analyze the data and suggest an appropriate way to participate in the community.

[0106] The Community Department can analyze a user's past community participation history and select the optimal way to participate in a community. For example, the Community Department can select the optimal participation method based on a user's past community participation history. Furthermore, the Community Department can analyze a user's past community participation history and propose the optimal participation method. In addition, the Community Department can adjust the content of community participation based on a user's past community participation history. In this way, the Community Department can provide users with the optimal way to participate in a community by analyzing their past community participation history. Some or all of the above-described processes in the Community Department may be performed using AI, for example, or without AI. For example, the Community Department can input a user's past community participation data into a generating AI, which can then analyze that data to select the optimal way to participate in a community.

[0107] The Community Department can provide real-time participation reminders based on the community's activity status. For example, the Community Department can provide real-time participation reminders based on the community's activity status. Furthermore, the Community Department can monitor the community's activity status and provide reminders as needed. In addition, the Community Department can provide reminders at the optimal time based on the community's activity status. This allows the Community Department to provide real-time reminders based on the community's activity status, enabling users to actively participate in community activities. Some or all of the above processing in the Community Department may be performed using AI, or not. For example, the Community Department can input community activity data into a generating AI, which can then analyze the data and provide appropriate reminders.

[0108] The community unit can estimate the user's emotions and adjust community activities based on those emotions. For example, if the community unit is feeling lonely, it can suggest activities that promote interaction. If the user is relaxed, it can suggest normal activities. Furthermore, the community unit can suggest the most suitable activities based on the user's emotions. In this way, the community unit reduces the user's feelings of loneliness and stress by adjusting community activities based on their emotions. Emotion estimation is achieved using an emotion estimation function, for example, using an emotion engine or generative AI. Generative AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the community unit may be performed using AI, or not using AI. For example, the community unit can input user emotion data into a generative AI, which can analyze that data and suggest appropriate activities.

[0109] The community department can suggest relevant events and activities based on users' community participation. For example, the community department can suggest relevant events based on users' community participation. Furthermore, the community department can suggest relevant activities based on users' community participation. In addition, the community department can suggest optimal events and activities based on users' community participation. This allows the community department to promote user community participation by suggesting relevant events and activities based on users' community participation. Some or all of the above processing in the community department may be performed using AI, for example, or without AI. For example, the community department can input user community participation data into a generating AI, which can then analyze the data and suggest appropriate events and activities.

[0110] The community department can provide functions to promote interaction between users based on their community participation. For example, the community department can provide functions to promote interaction between users based on their community participation. Furthermore, the community department can propose events to promote interaction based on users' community participation. In addition, the community department can propose optimal methods of interaction based on users' community participation. In this way, the community department reduces feelings of isolation among users by promoting interaction between users based on their community participation. Some or all of the above-described processes in the community department may be performed using AI, for example, or without AI. For example, the community department can input user community participation data into a generating AI, which can then analyze the data and propose appropriate methods of interaction.

[0111] The system according to the embodiment is not limited to the example described above, and various modifications are possible, for example, as follows.

[0112] The dedicated AI assistant system can also include an education section to enhance users' knowledge of childcare. This education section provides specialized knowledge and skills related to childcare, supporting users in deepening their understanding of the subject. For example, it can provide appropriate care methods according to the baby's developmental stage. It can also provide the latest research findings and expert opinions on childcare. Furthermore, it can offer online courses and workshops on childcare, providing users with opportunities to practically learn about childcare. This allows the education section to boost users' confidence in childcare and enrich their parenting experience.

[0113] The dedicated AI assistant system can also include a consultation service to help users resolve their parenting concerns. This consultation service provides a space where users can easily discuss their parenting worries and questions. For example, it could offer online consultations with parenting experts. It could also provide group consultations, allowing parents to exchange information and opinions with other parents. Furthermore, it could offer anonymous consultations, providing a safe space for users to confide their worries. In this way, the consultation service can help users resolve their parenting concerns and make their parenting life more secure and enjoyable.

[0114] A dedicated AI assistant system can also include a data management unit to organize the user's childcare-related information. This data management unit supports the user in efficiently managing childcare information. For example, it centrally manages the baby's growth records and health data. It can also organize childcare schedules and tasks, supporting the user in raising their child efficiently. Furthermore, it can analyze childcare-related information and provide the user with appropriate advice and suggestions. In this way, the data management unit can organize the user's childcare-related information and support them in raising their child more efficiently.

[0115] The dedicated AI assistant system can also include a motivation section to enhance the user's motivation for childcare. This section provides support to increase the user's enthusiasm for childcare. For example, it can help users set childcare goals, allowing them to feel a sense of accomplishment. It can also share successful childcare experiences, helping users approach childcare with confidence. Furthermore, it can provide encouraging messages and advice to help users maintain their motivation. In this way, the motivation section can increase the user's enthusiasm for childcare and enrich their childcare life.

[0116] The dedicated AI assistant system can also include a relaxation section to alleviate the user's stress related to childcare. This relaxation section supports the user in relieving stress related to childcare. For example, it suggests relaxation methods and stress-relieving techniques. It can also provide relaxation music and meditation guides to create a relaxing environment for the user. Furthermore, it can offer advice on stress management related to childcare, enabling the user to effectively control stress. In this way, the relaxation section reduces the user's stress related to childcare, making their childcare life more comfortable.

[0117] The dedicated AI assistant system can estimate the user's emotions and provide parenting advice based on those emotions. For example, if the user is feeling anxious, the emotion estimation unit can provide reassuring advice. If the user is feeling stressed, the emotion estimation unit can provide advice to help them relax. Furthermore, if the user is feeling lonely, the emotion estimation unit can provide advice to encourage interaction with other parents. In this way, the emotion estimation unit can reduce the user's anxiety and stress related to parenting by providing advice tailored to their emotions.

[0118] The dedicated AI assistant system can estimate the user's emotions and adjust the frequency of childcare support based on those emotions. For example, the emotion estimation unit can provide support more frequently if the user is feeling stressed. Conversely, if the user is relaxed, the emotion estimation unit can provide support at a normal frequency. Furthermore, if the user is feeling anxious, the emotion estimation unit can provide advice more frequently. In this way, the emotion estimation unit can reduce the user's anxiety and stress related to childcare by providing support at a frequency that matches the user's emotions.

[0119] The dedicated AI assistant system can estimate the user's emotions and adjust the content of childcare support based on those emotions. For example, if the user is feeling stressed, the emotion estimation unit can provide support to help them relax. If the user is relaxed, the emotion estimation unit can provide detailed advice. Furthermore, if the user is feeling anxious, the emotion estimation unit can provide support to reassure them. In this way, the emotion estimation unit can reduce the user's anxiety and stress related to childcare by providing support that is tailored to the user's emotions.

[0120] The dedicated AI assistant system can estimate the user's emotions and adjust the priority of childcare support based on those emotions. For example, the emotion estimation unit will prioritize support if the user is feeling anxious. Conversely, if the user is relaxed, the emotion estimation unit can provide support at the normal priority level. Furthermore, if the user is in a hurry, the emotion estimation unit can provide support quickly. In this way, the emotion estimation unit can reduce the user's anxiety and stress related to childcare by providing support with priorities tailored to the user's emotions.

[0121] The dedicated AI assistant system can estimate the user's emotions and update the content of childcare support in real time based on the estimated emotions. For example, the emotion estimation unit updates the support content in real time if the user's emotions change. Furthermore, the emotion estimation unit can update the advice content in real time in response to changes in the user's emotions. In addition, the emotion estimation unit can detect changes in the user's emotions and adjust the support content in real time. As a result, the emotion estimation unit can provide appropriate support by updating the support content in real time in response to changes in the user's emotions.

[0122] The following briefly describes the processing flow for example form 2.

[0123] Step 1: The answer section provides immediate answers to questions about the baby's daily routine and health. For example, it provides immediate answers to questions about how to deal with a baby's nighttime crying, how to handle illness, and questions about daily routines, based on information supervised by experts. Step 2: The Emotional Support Department listens attentively to the responses provided by the Response Department and offers encouragement and advice. For example, they listen attentively to mothers and fathers who are feeling anxious, lonely, or stressed about childcare and offer encouragement and advice. Step 3: The task management department manages schedules for things like breastfeeding, diaper changes, and vaccinations. For example, it manages the schedules for breastfeeding, diaper changes, and vaccinations and sends reminders to moms and dads. Step 4: The health management department records the baby's growth data and analyzes their health status. For example, they record the baby's height and weight data to understand their growth process. They also analyze the baby's health status and suggest a visit to a medical institution if any abnormalities are found. Furthermore, they record developmental stage data and conduct a comprehensive analysis of the baby's health status. Step 5: The Community Department provides information on nearby childcare facilities and events, and offers community features to connect parents. For example, it provides information on nearby childcare facilities and events, and offers community features to connect parents.

[0124] 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 user input for the result of the specific processing. The control unit 46A transmits the audio data indicating 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.

[0125] Data generation model 58 is a form of so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> Examples of generative AI include text generation AI, image generation AI, and multimodal generation AI. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images (e.g., still image data or video data). The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference result in one or more data formats from audio data, text data, and image data. The data generation model 58 includes, for example, text generation AI, image generation AI, and multimodal generation AI. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specific processing unit 290 performs the specific processing described above using the data generation model 58. The data generation model 58 may be a fine-tuned model that outputs inference results from prompts that do not contain instructions, in which case the data generation model 58 can output inference results from prompts that do not contain instructions. In the data processing device 12, etc., there are multiple types of data generation models 58, and the data generation model 58 includes AI other than generative AI. AI other than generative AI includes, for example, linear regression, logistic regression, decision trees, random forests, support vector machines (SVMs), k-means clustering, convolutional neural networks (CNNs), recurrent neural networks (RNNs), generative adversarial networks (GANs), or naive Bayes, and can perform various processes, but is not limited to these examples. Also, the AI ​​may be an AI agent. Furthermore, when the processing of each of the above parts is performed by the AI, the processing may be performed by the AI ​​in part or in whole, but is not limited to this example.Furthermore, processing performed by AI, including generative AI, may be replaced with rule-based processing, and rule-based processing may be replaced with processing performed by AI, including generative AI.

[0126] Furthermore, the processing performed by the data processing system 10 described above is carried out by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart device 14, but it may also be carried out by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart device 14. In addition, 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.

[0127] Each of the multiple elements mentioned above, including the answering unit, emotional support unit, task management unit, health management unit, community unit, question reception unit, information provision unit, schedule management unit, reminder unit, data recording unit, anomaly detection unit, and community unit, is implemented by at least one of the smart device 14 and the data processing unit 12. For example, the answering unit is implemented by the control unit 46A of the smart device 14 and provides immediate answers to questions about the baby's daily rhythm and health. The emotional support unit is implemented by the specific processing unit 290 of the data processing unit 12 and listens empathetically and provides encouragement and advice. The task management unit is implemented by the control unit 46A of the smart device 14 and manages schedules such as breastfeeding, diaper changes, and vaccinations. The health management unit is implemented by the specific processing unit 290 of the data processing unit 12 and records the baby's growth data and analyzes its health status. The community unit is implemented by the control unit 46A of the smart device 14 and provides information on nearby childcare facilities and events, and provides community functions to connect with other parents. The question reception unit is implemented by the control unit 46A of the smart device 14 and receives questions about the baby's daily routine and health. The information provision unit is implemented by the specific processing unit 290 of the data processing device 12 and provides answers based on information supervised by experts. The schedule management unit is implemented by the control unit 46A of the smart device 14 and manages schedules such as breastfeeding, diaper changes, and vaccinations. The reminder unit is implemented by the control unit 46A of the smart device 14 and provides reminders based on the schedule. The data recording unit is implemented by the specific processing unit 290 of the data processing device 12 and records the baby's growth data. The abnormality detection unit is implemented by the specific processing unit 290 of the data processing device 12 and analyzes the health status and detects abnormalities. The correspondence between each unit and the device or control unit is not limited to the example described above and can be changed in various ways.

[0128] [Second Embodiment] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0129] As shown in Figure 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.

[0130] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN and / or LAN.

[0131] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0132] The microphone 238 receives voice signals from the user and accepts instructions from the user. The microphone 238 captures the voice signals from the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0133] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, which captures images of the area around the user (for example, an imaging range defined by a field of view equivalent to the field of vision of a typical healthy person).

[0134] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0135] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing by the processor 28. The storage 32 stores the specific processing program 56.

[0136] The processor 28 reads a 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 acting as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0137] Storage 32 stores the data generation model 58 and the 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 emotions using the emotion identification model 59 and perform identification processing using the user's emotions. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotions, including but not limited to these examples. Furthermore, emotion estimation and prediction also include, for example, emotion analysis.

[0138] In the smart glasses 214, specific processing is performed by the processor 46. The storage 50 stores a specific processing program 60. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 acting as a control unit 46A according to the specific processing program 60 executed on the RAM 48. The smart glasses 214 also have a data generation model 58 and an emotion identification model 59, similar to the data generation model and emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0139] Furthermore, other devices besides the data processing device 12 may also have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 obtains processing results (such as prediction results) using the data generation model 58 by communicating with the server device that has the data generation model 58. Also, the data processing device 12 may be a server device or a terminal device owned by the user (for example, a mobile phone, robot, home appliance, etc.).

[0140] 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 user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0141] The data generation model 58 is a so-called generative AI. An example of a 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 is input with prompts containing instructions, and inference data such as audio data representing speech, text data representing text, and image data representing images (e.g., still image data or video data). The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference result in one or more data formats such as audio data, text data, and image data. The data generation model 58 includes, for example, text generation AI, image generation AI, and multimodal generation AI. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specific processing unit 290 performs the specific processing described above using the data generation model 58. The data generation model 58 may be a fine-tuned model that outputs inference results from prompts that do not contain instructions, in which case the data generation model 58 can output inference results from prompts that do not contain instructions. In the data processing device 12, etc., there are multiple types of data generation models 58, and the data generation model 58 includes AI other than generative AI. AI other than generative AI includes, for example, linear regression, logistic regression, decision trees, random forests, support vector machines (SVM), k-means clustering, convolutional neural networks (CNN), recurrent neural networks (RNN), generative adversarial networks (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. Also, the AI ​​may be an AI agent. Furthermore, when the processing of each part described above is performed by the AI, the processing may be performed by the AI ​​in part or in whole, but is not limited to this example. Also, processing performed by an AI including a generative AI may be replaced by rule-based processing, and rule-based processing may be replaced by processing performed by an AI including a generative AI.

[0142] 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 performed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart glasses 214, but it may also be performed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart glasses 214. In addition, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the smart glasses 214 or an external device, and the smart glasses 214 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0143] Each of the multiple elements mentioned above, including the answering unit, emotional support unit, task management unit, health management unit, community unit, question reception unit, information provision unit, schedule management unit, reminder unit, data recording unit, anomaly detection unit, and community unit, is implemented in at least one of the smart glasses 214 and the data processing unit 12. For example, the answering unit is implemented by the control unit 46A of the smart glasses 214 and provides immediate answers to questions about the baby's daily rhythm and health. The emotional support unit is implemented by the specific processing unit 290 of the data processing unit 12 and listens empathetically, providing encouragement and advice. The task management unit is implemented by the control unit 46A of the smart glasses 214 and manages schedules such as breastfeeding, diaper changes, and vaccinations. The health management unit is implemented by the specific processing unit 290 of the data processing unit 12 and records the baby's growth data and analyzes its health status. The community unit is implemented by the control unit 46A of the smart glasses 214 and provides information on nearby childcare facilities and events, and offers community functions to connect parents. The question reception unit is implemented by the control unit 46A of the smart glasses 214 and accepts questions about the baby's daily routine and health. The information provision unit is implemented by the specific processing unit 290 of the data processing device 12 and provides answers based on information supervised by experts. The schedule management unit is implemented by the control unit 46A of the smart glasses 214 and manages schedules such as breastfeeding, diaper changes, and vaccinations. The reminder unit is implemented by the control unit 46A of the smart glasses 214 and provides reminders based on the schedule. The data recording unit is implemented by the specific processing unit 290 of the data processing device 12 and records the baby's growth data. The abnormality detection unit is implemented by the specific processing unit 290 of the data processing device 12 and analyzes the health status and detects abnormalities. The correspondence between each unit and the device and control unit is not limited to the example described above and can be changed in various ways.

[0144] [Third Embodiment] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0145] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0146] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN and / or LAN.

[0147] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0148] The microphone 238 receives voice signals from the user and accepts instructions from the user. The microphone 238 captures the voice signals from the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0149] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, which captures images of the area around the user (for example, an imaging range defined by a field of view equivalent to the field of vision of a typical healthy person).

[0150] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0151] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0152] The processor 28 reads a 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 acting as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0153] Storage 32 stores the data generation model 58 and the 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 emotions using the emotion identification model 59 and perform identification processing using the user's emotions. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotions, including but not limited to these examples. Furthermore, emotion estimation and prediction also include, for example, emotion analysis.

[0154] In the headset terminal 314, specific processing is performed by the processor 46. The storage 50 stores a specific program 60. The processor 46 reads the specific program 60 from the storage 50 and executes the read specific program 60 on the RAM 48. The specific processing is realized by the processor 46 acting as a control unit 46A according to the specific program 60 executed on the RAM 48. The headset terminal 314 also has a data generation model 58 and an emotion identification model 59, similar to the data generation model and emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0155] Furthermore, other devices besides the data processing device 12 may also have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 obtains processing results (such as prediction results) using the data generation model 58 by communicating with the server device that has the data generation model 58. Also, the data processing device 12 may be a server device or a terminal device owned by the user (for example, a mobile phone, robot, home appliance, etc.).

[0156] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0157] The data generation model 58 is a so-called generative AI. An example of a 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 is input with prompts containing instructions, and inference data such as audio data representing speech, text data representing text, and image data representing images (e.g., still image data or video data). The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference result in one or more data formats such as audio data, text data, and image data. The data generation model 58 includes, for example, text generation AI, image generation AI, and multimodal generation AI. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specific processing unit 290 performs the specific processing described above using the data generation model 58. The data generation model 58 may be a fine-tuned model that outputs inference results from prompts that do not contain instructions, in which case the data generation model 58 can output inference results from prompts that do not contain instructions. In the data processing device 12, etc., there are multiple types of data generation models 58, and the data generation model 58 includes AI other than generative AI. AI other than generative AI includes, for example, linear regression, logistic regression, decision trees, random forests, support vector machines (SVM), k-means clustering, convolutional neural networks (CNN), recurrent neural networks (RNN), generative adversarial networks (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. Also, the AI ​​may be an AI agent. Furthermore, when the processing of each part described above is performed by the AI, the processing may be performed by the AI ​​in part or in whole, but is not limited to this example. Also, processing performed by an AI including a generative AI may be replaced by rule-based processing, and rule-based processing may be replaced by processing performed by an AI including a generative AI.

[0158] 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 performed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the headset terminal 314, but may also be performed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the headset terminal 314. In addition, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the headset terminal 314 or an external device, and the headset terminal 314 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0159] Each of the multiple elements mentioned above, including the answering unit, emotional support unit, task management unit, health management unit, community unit, question reception unit, information provision unit, schedule management unit, reminder unit, data recording unit, anomaly detection unit, and community unit, is implemented by at least one of the headset terminal 314 and the data processing unit 12. For example, the answering unit is implemented by the control unit 46A of the headset terminal 314 and provides immediate answers to questions about the baby's daily rhythm and health. The emotional support unit is implemented by the specific processing unit 290 of the data processing unit 12 and listens empathetically and provides encouragement and advice. The task management unit is implemented by the control unit 46A of the headset terminal 314 and manages schedules such as breastfeeding, diaper changes, and vaccinations. The health management unit is implemented by the specific processing unit 290 of the data processing unit 12 and records the baby's growth data and analyzes its health status. The community unit is implemented by the control unit 46A of the headset terminal 314 and provides information on nearby childcare facilities and events, and provides a community function to connect with other parents. The question reception unit is implemented by the control unit 46A of the headset terminal 314 and receives questions about the baby's daily routine and health. The information provision unit is implemented by the specific processing unit 290 of the data processing device 12 and provides answers based on information supervised by experts. The schedule management unit is implemented by the control unit 46A of the headset terminal 314 and manages schedules such as breastfeeding, diaper changes, and vaccinations. The reminder unit is implemented by the control unit 46A of the headset terminal 314 and provides reminders based on the schedule. The data recording unit is implemented by the specific processing unit 290 of the data processing device 12 and records the baby's growth data. The abnormality detection unit is implemented by the specific processing unit 290 of the data processing device 12 and analyzes the health status and detects abnormalities. The correspondence between each unit and the device and control unit is not limited to the example described above and can be changed in various ways.

[0160] [Fourth Embodiment] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0161] As shown in Figure 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.

[0162] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN and / or LAN.

[0163] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0164] The microphone 238 receives voice signals from the user and accepts instructions from the user. The microphone 238 captures the voice signals from the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0165] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS image sensor or CCD image sensor, which captures images of the area around the user (for example, an imaging range defined by a field of view equivalent to the field of vision of a typical healthy person).

[0166] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0167] The controlled 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 robot 414's emotions can be expressed by controlling these motors. The robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0168] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0169] The processor 28 reads a 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 acting as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0170] Storage 32 stores the data generation model 58 and the 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 emotions using the emotion identification model 59 and perform identification processing using the user's emotions. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotions, including but not limited to these examples. Furthermore, emotion estimation and prediction also include, for example, emotion analysis.

[0171] In robot 414, specific processing is performed by processor 46. A specific program 60 is stored in storage 50. Processor 46 reads the specific program 60 from storage 50 and executes it on RAM 48. The specific processing is achieved by processor 46 acting as a control unit 46A according to the specific program 60 executed on RAM 48. Robot 414 also has data generation model 58 and emotion identification model 59, similar to those of the robot, and can perform processing similar to that of the specific processing unit 290 using these models.

[0172] Furthermore, other devices besides the data processing device 12 may also have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 obtains processing results (such as prediction results) using the data generation model 58 by communicating with the server device that has the data generation model 58. Also, the data processing device 12 may be a server device or a terminal device owned by the user (for example, a mobile phone, robot, home appliance, etc.).

[0173] 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 controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0174] The data generation model 58 is a so-called generative AI. An example of a 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 is input with prompts containing instructions, and inference data such as audio data representing speech, text data representing text, and image data representing images (e.g., still image data or video data). The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference result in one or more data formats such as audio data, text data, and image data. The data generation model 58 includes, for example, text generation AI, image generation AI, and multimodal generation AI. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specific processing unit 290 performs the specific processing described above using the data generation model 58. The data generation model 58 may be a fine-tuned model that outputs inference results from prompts that do not contain instructions, in which case the data generation model 58 can output inference results from prompts that do not contain instructions. In the data processing device 12, etc., there are multiple types of data generation models 58, and the data generation model 58 includes AI other than generative AI. AI other than generative AI includes, for example, linear regression, logistic regression, decision trees, random forests, support vector machines (SVM), k-means clustering, convolutional neural networks (CNN), recurrent neural networks (RNN), generative adversarial networks (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. Also, the AI ​​may be an AI agent. Furthermore, when the processing of each part described above is performed by the AI, the processing may be performed by the AI ​​in part or in whole, but is not limited to this example. Also, processing performed by an AI including a generative AI may be replaced by rule-based processing, and rule-based processing may be replaced by processing performed by an AI including a generative AI.

[0175] 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 performed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the robot 414, but it may also be performed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the robot 414. In addition, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the robot 414 or an external device, and the robot 414 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0176] Each of the multiple elements mentioned above, including the answering unit, emotional support unit, task management unit, health management unit, community unit, question reception unit, information provision unit, schedule management unit, reminder unit, data recording unit, anomaly detection unit, and community unit, is implemented by at least one of the robot 414 and the data processing unit 12. For example, the answering unit is implemented by the control unit 46A of the robot 414 and provides immediate answers to questions about the baby's daily routine and health. The emotional support unit is implemented by the specific processing unit 290 of the data processing unit 12 and listens empathetically and provides encouragement and advice. The task management unit is implemented by the control unit 46A of the robot 414 and manages schedules such as breastfeeding, diaper changes, and vaccinations. The health management unit is implemented by the specific processing unit 290 of the data processing unit 12 and records the baby's growth data and analyzes its health status. The community unit is implemented by the control unit 46A of the robot 414 and provides information on nearby childcare facilities and events, and offers community functions to connect parents. The question reception unit is implemented by the control unit 46A of the robot 414 and receives questions about the baby's daily routine and health. The information provision unit is implemented by the specific processing unit 290 of the data processing device 12 and provides answers based on information supervised by experts. The schedule management unit is implemented by the control unit 46A of the robot 414 and manages schedules such as breastfeeding, diaper changes, and vaccinations. The reminder unit is implemented by the control unit 46A of the robot 414 and provides reminders based on the schedule. The data recording unit is implemented by the specific processing unit 290 of the data processing device 12 and records the baby's growth data. The abnormality detection unit is implemented by the specific processing unit 290 of the data processing device 12 and analyzes the health status and detects abnormalities. The correspondence between each unit and the device and control unit is not limited to the example described above and can be changed in various ways.

[0177] Furthermore, the emotion identification model 59, acting 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 a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0178] Figure 9 shows the emotion map 400, in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0179] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0180] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0181] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, and motorcycles, emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated based, for example, on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0182] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0183] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0184] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing method for the specific process may be used, which includes computer 22 and multiple other computers.

[0185] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0186] 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.

[0187] Furthermore, it is not necessary to store the entirety 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 the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0188] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0189] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of 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). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0190] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0191] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0192] Furthermore, although the above-described examples were divided into four embodiments, some or all of these embodiments may be combined. Also, the smart device 14, smart glasses 214, headset terminal 314, and robot 414 are just examples, and they may be combined, or other devices may be used. Also, although the above-described examples were divided into two embodiments, Embodiment 1 and Embodiment 2, these may be combined.

[0193] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and other things that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0194] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0195] (Note 1) A section that provides immediate answers to questions about the baby's daily routine and health, Based on the answers provided by the aforementioned response department, the emotional support department listens attentively, offers encouragement and advice, The task management department manages schedules for things like breastfeeding, diaper changes, and vaccinations, The health management department records the baby's growth data and analyzes their health status, It includes a community department that provides information on nearby childcare facilities and events, and offers a community function that connects parents with other parents. A system characterized by the following features. (Note 2) The facility includes a question desk to answer questions about babies' daily routines and health. The system described in Appendix 1, characterized by the features described herein. (Note 3) We have an information provision department that provides answers based on information supervised by experts. The system described in Appendix 1, characterized by the features described herein. (Note 4) It has a scheduling department to manage schedules for breastfeeding, diaper changes, vaccinations, and other activities. The system described in Appendix 1, characterized by the features described herein. (Note 5) It includes a reminder function that sends reminders based on a schedule. The system described in Appendix 4, characterized by the features described herein. (Note 6) It is equipped with a data recording unit that records the baby's growth data. The system described in Appendix 1, characterized by the features described herein. (Note 7) It is equipped with an anomaly detection unit that analyzes health conditions and detects abnormalities. The system described in Appendix 1, characterized by the features described herein. (Note 8) It features a community department that provides information on nearby childcare facilities and events, and offers a community function to connect parents with other parents. The system described in Appendix 1, characterized by the features described herein. (Note 9) The aforementioned response section is, It estimates the user's emotions and adjusts the way responses are expressed based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 10) The aforementioned response section is, Adjust the level of detail in your answer depending on the question. The system described in Appendix 1, characterized by the features described herein. (Note 11) The aforementioned response section is, Based on the frequency and content of questions, provide additional advice and information to the user. The system described in Appendix 1, characterized by the features described herein. (Note 12) The aforementioned response section is, The system estimates the user's emotions and prioritizes responses based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 13) The aforementioned response section is, Depending on the content of the question, we will provide an answer by referring to related past questions and answers. The system described in Appendix 1, characterized by the features described herein. (Note 14) The aforementioned response section is, Based on the content of the question, we will provide an answer incorporating the opinions of relevant external resources and experts. The system described in Appendix 1, characterized by the features described herein. (Note 15) The aforementioned emotional support unit is It estimates the user's emotions and adjusts the content of encouragement and advice based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 16) The aforementioned emotional support unit is Analyze the user's past emotional history to select the most appropriate support method. The system described in Appendix 1, characterized by the features described herein. (Note 17) The aforementioned emotional support unit is Support content is updated in real time in response to changes in the user's emotions. The system described in Appendix 1, characterized by the features described herein. (Note 18) The aforementioned emotional support unit is It estimates the user's emotions and adjusts the frequency of support based on those emotions. The system described in Appendix 1, characterized by the features described herein. (Note 19) The aforementioned emotional support unit is Based on the user's emotions, it suggests relevant relaxation and stress relief methods. The system described in Appendix 1, characterized by the features described herein. (Note 20) The aforementioned emotional support unit is Based on user sentiment, we provide community features to facilitate interaction with other users. The system described in Appendix 1, characterized by the features described herein. (Note 21) The aforementioned task management unit, It estimates the user's emotions and adjusts task priorities based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 22) The aforementioned task management unit, Analyze the user's past task history and select the optimal task management method. The system described in Appendix 1, characterized by the features described herein. (Note 23) The aforementioned task management unit, The system provides real-time task reminders based on the task's progress. The system described in Appendix 1, characterized by the features described herein. (Note 24) The aforementioned task management unit, It estimates the user's emotions and adjusts the task reminder frequency based on those emotions. The system described in Appendix 1, characterized by the features described herein. (Note 25) The aforementioned task management unit, Based on the user's task management, we suggest relevant resources and tools. The system described in Appendix 1, characterized by the features described herein. (Note 26) The aforementioned task management unit, Based on the user's task management, it provides a task sharing function with other family members. The system described in Appendix 1, characterized by the features described herein. (Note 27) The aforementioned health management department, It estimates the user's emotions and adjusts health management advice based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 28) The aforementioned health management department, Analyze the baby's past health data to select the optimal health management method. The system described in Appendix 1, characterized by the features described herein. (Note 29) The aforementioned health management department, Health management advice is updated in real time based on changes in health data. The system described in Appendix 1, characterized by the features described herein. (Note 30) The aforementioned health management department, It estimates the user's emotions and adjusts the frequency of health checks based on those emotions. The system described in Appendix 1, characterized by the features described herein. (Note 31) The aforementioned health management department, Based on your baby's health data, we provide advice incorporating the opinions of relevant medical institutions and specialists. The system described in Appendix 1, characterized by the features described herein. (Note 32) The aforementioned health management department, Based on the baby's health data, it provides a function to share health information with other family members. The system described in Appendix 1, characterized by the features described herein. (Note 33) The aforementioned community department, It estimates user sentiment and promotes community participation based on the estimated user sentiment. The system described in Appendix 1, characterized by the features described herein. (Note 34) The aforementioned community department, Analyze the user's past community participation history to select the most suitable method for community participation. The system described in Appendix 1, characterized by the features described herein. (Note 35) The aforementioned community department, Depending on the community's activity status, participation reminders will be sent in real time. The system described in Appendix 1, characterized by the features described herein. (Note 36) The aforementioned community department, It estimates user sentiment and adjusts community activities based on that estimated sentiment. The system described in Appendix 1, characterized by the features described herein. (Note 37) The aforementioned community department, Based on user community participation, we propose relevant events and activities. The system described in Appendix 1, characterized by the features described herein. (Note 38) The aforementioned community department, Based on user community participation, we provide features to facilitate interaction with other users. The system described in Appendix 1, characterized by the features described herein. [Explanation of Symbols]

[0196] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots

Claims

1. A section that provides immediate answers to questions about the baby's daily routine and health, Based on the answers provided by the aforementioned response department, the emotional support department listens attentively, offers encouragement and advice, The task management department manages schedules for things like breastfeeding, diaper changes, and vaccinations, The health management department records the baby's growth data and analyzes their health status, It includes a community department that provides information on nearby childcare facilities and events, and offers a community function that connects parents with other parents. A system characterized by the following features.

2. The facility includes a question desk to answer questions about babies' daily routines and health. The system according to feature 1.

3. We have an information provision department that provides answers based on information supervised by experts. The system according to feature 1.

4. It has a scheduling department to manage schedules for breastfeeding, diaper changes, vaccinations, and other activities. The system according to feature 1.

5. It includes a reminder function that sends reminders based on a schedule. The system according to feature 4.

6. It is equipped with a data recording unit that records the baby's growth data. The system according to feature 1.

7. It is equipped with an anomaly detection unit that analyzes the health status and detects abnormalities. The system according to feature 1.

8. It features a community department that provides information on nearby childcare facilities and events, and offers a community function to connect parents with other parents. The system according to feature 1.

9. The aforementioned response section is, It estimates the user's emotions and adjusts the way responses are expressed based on those estimated emotions. The system according to feature 1.

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