system

Abstract

The system according to this embodiment aims to automatically manage a child's vaccination schedule and to provide reminder notifications and make reservations. [Solution] The system according to the embodiment comprises a reception unit, a schedule creation unit, a notification unit, and a reservation unit. The reception unit inputs the child's birthday and health information. The schedule creation unit creates an optimal vaccination schedule based on the information entered by the reception unit. The notification unit sends reminder notifications based on the schedule created by the schedule creation unit. The reservation unit makes reservations for vaccinations based on the schedule created by the schedule creation unit.

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 a chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In the conventional technology, it is laborious to manage the vaccination schedule of children, and there is a risk of missing important schedules.

[0005] The system according to the embodiment aims to automatically manage the vaccination schedule of children and issue reminder notifications and reservations.

Means for Solving the Problems

[0006] The system according to this embodiment comprises a reception unit, a schedule creation unit, a notification unit, and a reservation unit. The reception unit inputs the child's birthday and health information. The schedule creation unit creates an optimal vaccination schedule based on the information entered by the reception unit. The notification unit sends reminder notifications based on the schedule created by the schedule creation unit. The reservation unit makes reservations for vaccinations based on the schedule created by the schedule creation unit. [Effects of the Invention]

[0007] The system according to this embodiment can automatically manage a child's vaccination schedule and provide reminder notifications and make reservations. [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, and the like. The communication I / F controls communication between a plurality of 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 three or more matters are connected and expressed 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.<000W4>

[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 mobile app according to an embodiment of the present invention is a system for easily and effectively supporting children's health management and vaccinations. This system allows parents to simply input their child's birthday and health information, and the AI ​​automatically creates an optimal vaccination schedule, notifying parents of important dates with reminder notifications. Furthermore, the AI ​​considers the child's genetic information, place of residence, family medical history, etc., to provide an individually optimized vaccination plan. It also collaborates with local hospitals and clinics, allowing for automatic booking while checking availability. The app also provides a community space where parents can interact with each other in a safe environment, easily sharing questions and concerns about childcare. Additionally, the built-in chatbot answers childcare questions in real time based on the latest medical information. It truly acts as an AI childcare concierge, providing comprehensive support for parents' childcare. Other features include regular check-up schedules and developmental checklists tailored to the child's growth, allowing for comprehensive management of the child's growth and health. The app also prioritizes data management and privacy protection, providing a safe environment for parents to use with peace of mind. As a partner in protecting children's health, this app supports healthy growth, including vaccinations. This allows mobile apps to easily and effectively support children's health management and vaccinations.

[0029] The mobile application according to this embodiment comprises a reception unit, a schedule creation unit, a notification unit, and a reservation unit. The reception unit inputs the child's birthday and health information. The reception unit provides, for example, an interface for parents to input the child's birthday and health information into the app. The reception unit allows for easy information input using, for example, text input fields or dropdown menus. The reception unit also has a voice input function, allowing parents to input information by voice. The schedule creation unit creates an optimal vaccination schedule based on the information entered by the reception unit. The schedule creation unit calculates the timing of vaccinations based on the child's age and health condition using, for example, AI. The schedule creation unit creates an optimal vaccination schedule based on, for example, medical guidelines. The schedule creation unit can also provide an individually optimized schedule by considering the child's genetic information and family medical history. The notification unit provides reminder notifications based on the schedule created by the schedule creation unit. The notification unit sends a reminder notification, for example, the day before a vaccination. The notification unit sends reminders by, for example, in-app notifications, email, SMS, etc. Furthermore, the notification unit can customize the notification method according to the parent's preferences. The reservation unit makes vaccination reservations based on the schedule created by the schedule creation unit. The reservation unit automatically makes reservations, for example, by checking the availability of local hospitals and clinics. The reservation unit can also link with hospital reservation systems using APIs, for example, to check availability in real time. In addition, the reservation unit provides an easy-to-use interface for parents to make reservations manually. As a result, the mobile app according to the embodiment can create an optimal vaccination schedule based on the child's birthday and health information, and can send reminder notifications and make reservations.

[0030] The reception section is where parents enter their child's birthday and health information. For example, the reception section provides an interface for parents to enter their child's birthday and health information into the app. Specifically, the reception section uses text input fields and dropdown menus to make it easy to enter information. Text input fields are for entering the child's name, birthday, allergy information, etc., while dropdown menus provide options such as gender and medical history. The reception section also has a voice input function, allowing parents to enter information by voice. The voice input function uses speech recognition technology to convert the parent's speech into text and automatically reflect it in the input field. Furthermore, the reception section has a function to centrally manage the entered information and store it in a database. This saves parents the trouble of re-entering information they have already entered. The reception section also has a validation function to check the accuracy of the entered information, and if incorrect information is entered, it displays an error message and prompts correction. In this way, the reception section enables parents to easily and accurately enter their child's information and realizes smooth information management.

[0031] The scheduling unit creates an optimal vaccination schedule based on the information entered by the reception unit. For example, the scheduling unit uses AI to calculate the timing of vaccinations based on the child's age and health condition. Specifically, the AI ​​refers to medical guidelines and historical data to calculate the optimal timing for vaccinations based on the child's age and health. For example, the AI ​​calculates the appropriate timing for each vaccination based on the child's birth date. The scheduling unit can also provide individually optimized schedules by considering the child's genetic information and family medical history. Genetic information and family medical history are used to assess the risk of specific diseases, and the timing and type of vaccinations are adjusted accordingly. Furthermore, the scheduling unit provides the created schedule to parents and offers an easy-to-use interface for review and modification if necessary. This ensures that the scheduling unit provides an optimal vaccination schedule tailored to each child's individual circumstances, allowing parents to confidently ensure their children receive vaccinations.

[0032] The notification unit sends reminder notifications based on the schedule created by the schedule creation unit. For example, the notification unit sends a reminder notification the day before a vaccination. Specifically, the notification unit sends reminders via in-app notifications, email, SMS, etc. In-app notifications appear as pop-up messages when the app is opened, while emails and SMS messages are sent to the parent's registered contacts. The notification unit can also customize the notification method according to the parent's preference. For example, if the parent prefers email notifications, the reminder will be sent via email; if they prefer SMS notifications, the reminder will be sent via SMS. Furthermore, the notification unit has a function to adjust the timing of reminder notifications, allowing parents to receive notifications at their preferred time. For example, reminders can be sent at times specified by the parent, such as one week or three days before a vaccination. In this way, the notification unit helps parents manage their child's vaccination schedule without forgetting, supporting their child's health management.

[0033] The reservation department makes vaccination appointments based on schedules created by the scheduling department. The reservation department automatically makes appointments, for example, by checking the availability of local hospitals and clinics. Specifically, the reservation department uses an API to connect with hospital reservation systems and check availability in real time. This allows parents to make vaccination appointments without any hassle. The reservation department also provides an easy-to-use interface for parents who make appointments manually. For example, they can select their desired date and time using a calendar-style interface and confirm the appointment. Furthermore, the reservation department includes features that allow for easy appointment changes and cancellations, enabling parents to respond flexibly. For example, in case of a sudden change in plans, appointments can be easily changed or canceled within the app. In this way, the reservation department enables parents to smoothly make vaccination appointments and efficiently manage their children's health.

[0034] The schedule creation unit creates an immunization schedule considering the child's genetic information, place of residence, family medical history, etc. For example, the schedule creation unit analyzes the child's genetic information and adjusts the immunization schedule based on specific genetic risks. For example, the schedule creation unit considers environmental factors of the place of residence and prioritizes vaccinations against diseases prevalent in the area. The schedule creation unit can also consider the family medical history and add vaccinations against specific diseases. In this way, the schedule creation unit can create an optimal immunization schedule that takes the child's individual information into account. Some or all of the above processes in the schedule creation unit may be performed using AI, for example, or not. For example, the schedule creation unit can create a schedule using an AI model that takes the child's genetic information and family medical history as input and outputs an optimal immunization schedule.

[0035] The reservation department automatically makes reservations while checking the availability of local hospitals and clinics. The reservation department can, for example, use an API to connect with hospital reservation systems and check availability in real time. The reservation department can, for example, suggest the optimal reservation date and time based on availability. The reservation department also provides an easy-to-use interface for parents who wish to make reservations manually. This allows the reservation department to automatically make reservations while checking the availability of local hospitals and clinics. Some or all of the above processes in the reservation department may be performed using AI, for example, or not. For example, the reservation department can make reservations using an AI model that takes hospital availability data as input and outputs the optimal reservation date and time.

[0036] The service provider will offer a community space where parents can interact with each other. For example, the service provider will provide an online forum where parents can share questions and concerns about childcare. For example, the service provider will provide a chat function so that parents can interact in real time. In addition, the service provider can provide blogs and articles for sharing information about childcare. In this way, the service provider can provide a community space where parents can interact with each other.

[0037] The chatbot section answers questions related to childcare. The chatbot section provides real-time answers to questions from parents, for example, using AI. The chatbot section provides answers to frequently asked questions, for example, by referring to an FAQ database. The chatbot section can also provide expert advice on childcare based on the latest medical information. In this way, the chatbot section can answer questions related to childcare. Some or all of the above processing in the chatbot section may be performed using AI, for example, or without AI. For example, the chatbot section can provide answers using an AI model that takes questions from parents as input and outputs the optimal answer.

[0038] The management department manages regular health checkup schedules and developmental checklists tailored to each child's growth. For example, the management department creates schedules for regular health checkups and sends reminder notifications. For example, the management department provides developmental checklists tailored to each child's growth, allowing parents to record their child's development. The management department can also store children's health information in a database and refer to it as needed. This allows the management department to manage regular health checkup schedules and developmental checklists tailored to each child's growth.

[0039] The protection unit handles data management and privacy protection. For example, the protection unit securely protects parental data using data encryption technology. For example, the protection unit implements access control to prevent unauthorized access to parental data. The protection unit can also allow parents to set the scope of data sharing. This enables the protection unit to perform data management and privacy protection.

[0040] The reception desk reduces the effort required for inputting children's health information by referring to past input history. For example, the reception desk can automatically display previously entered health information of children, so that parents only need to confirm it. For example, the reception desk can reduce the effort required by prioritizing the display of frequently entered information from past input history. In addition, the reception desk can provide a predictive input function based on past input history to minimize the effort required for parents to input information. This allows the reception desk to reduce the effort required for input by referring to past input history. Some or all of the above processing in the reception desk may be performed using AI, for example, or without AI. For example, the reception desk can reduce the effort required for input by using an AI model that takes past input history data as input and outputs predictive input.

[0041] The reception desk verifies the accuracy of the entered information in real time and prompts for correction as needed. For example, if the entered child's birthday or health information is inaccurate, the reception desk will display a warning in real time and prompt for correction. For example, if the entered information is incomplete, the reception desk will suggest ways to complete it in real time. Also, if the entered information is contradictory, the reception desk will point out the inconsistencies in real time and prompt for correction. In this way, the reception desk can verify the accuracy of the entered information in real time and prompt for correction as needed. Some or all of the above processing in the reception desk may be performed using AI, for example, or not using AI. For example, the reception desk can use an AI model that takes the entered information as input and verifies its accuracy to prompt for correction in real time.

[0042] The reception desk automatically completes relevant health information by considering the guardian's geographical location information during input. For example, the reception desk automatically completes local health information based on the guardian's current location. For example, the reception desk automatically displays information on local hospitals and clinics based on the guardian's geographical location information. The reception desk also automatically completes local vaccination schedules based on the guardian's geographical location information. In this way, the reception desk can automatically complete relevant health information by considering the guardian's geographical location information. Some or all of the above processing in the reception desk may be performed using AI, for example, or without AI. For example, the reception desk can complete health information using an AI model that takes the guardian's geographical location information as input and outputs relevant health information.

[0043] The reception desk analyzes the parent's social media activity during input and suggests relevant health information. For example, the reception desk automatically suggests relevant health information based on the parent's social media activity. For example, the reception desk suggests health information shared by other parents based on the parent's social media activity. The reception desk also suggests relevant vaccination information based on the parent's social media activity. This allows the reception desk to analyze the parent's social media activity and suggest relevant health information. Some or all of the above processing in the reception desk may be performed using AI, for example, or without AI. For example, the reception desk can suggest health information using an AI model that takes the parent's social media data as input and outputs relevant health information.

[0044] The schedule creation unit proposes an optimal schedule by referring to past vaccination data when creating a schedule. For example, the schedule creation unit proposes the next vaccination schedule based on past vaccination data. For example, the schedule creation unit proposes the optimal timing of vaccinations based on past vaccination data. The schedule creation unit also optimizes the interval between vaccinations based on past vaccination data. In this way, the schedule creation unit can propose an optimal schedule by referring to past vaccination data. Some or all of the above processes in the schedule creation unit may be performed using AI, for example, or without AI. For example, the schedule creation unit can propose a schedule using an AI model that takes past vaccination data as input and outputs an optimal schedule.

[0045] The schedule creation unit selects the optimal vaccination timing based on the child's daily rhythm when creating the schedule. For example, the schedule creation unit selects the optimal vaccination timing by considering the child's sleep pattern. For example, the schedule creation unit selects the optimal vaccination timing by considering the child's meal times. Furthermore, the schedule creation unit selects the optimal vaccination timing by considering the child's activity time. In this way, the schedule creation unit can select the optimal vaccination timing based on the child's daily rhythm. Some or all of the above processing in the schedule creation unit may be performed using AI, for example, or without AI. For example, the schedule creation unit can select the vaccination timing using an AI model that takes the child's daily rhythm data as input and outputs the optimal vaccination timing.

[0046] The schedule creation unit proposes the optimal vaccination location when creating a schedule, taking into account the child's geographical location. For example, the schedule creation unit proposes the nearest hospital or clinic based on the child's current location. For example, the schedule creation unit proposes the optimal vaccination location based on the child's geographical location. The schedule creation unit also proposes a regional vaccination schedule based on the child's geographical location. In this way, the schedule creation unit can propose the optimal vaccination location while taking the child's geographical location into consideration. Some or all of the above processing in the schedule creation unit may be performed using AI, for example, or without AI. For example, the schedule creation unit can propose vaccination locations using an AI model that takes the child's geographical location as input and outputs the optimal vaccination location.

[0047] The schedule creation unit analyzes the child's social media activity when creating a schedule and suggests relevant vaccination information. For example, the schedule creation unit analyzes the child's social media activity and suggests relevant vaccination information. For example, the schedule creation unit suggests vaccination information shared by other parents based on the child's social media activity. The schedule creation unit also suggests relevant vaccination schedules based on the child's social media activity. In this way, the schedule creation unit can analyze the child's social media activity and suggest relevant vaccination information. Some or all of the above processing in the schedule creation unit may be performed using AI, for example, or without AI. For example, the schedule creation unit can suggest vaccination information using an AI model that takes the child's social media data as input and outputs relevant vaccination information.

[0048] The notification unit selects the optimal notification method by referring to past notification history when issuing a notification. For example, the notification unit selects the optimal notification method based on past notification history. For example, the notification unit prioritizes notification methods preferred by parents based on past notification history. The notification unit also selects the optimal notification timing based on past notification history. In this way, the notification unit can select the optimal notification method by referring to past notification history. Some or all of the above processing in the notification unit may be performed using AI, for example, or without AI. For example, the notification unit can select a notification method using an AI model that takes past notification history data as input and outputs the optimal notification method.

[0049] The notification unit selects the optimal notification timing based on the parent's daily rhythm when sending a notification. For example, the notification unit may select the optimal notification timing by considering the parent's sleep pattern. For example, the notification unit may select the optimal notification timing by considering the parent's meal times. Furthermore, the notification unit may select the optimal notification timing by considering the parent's activity times. In this way, the notification unit can select the optimal notification timing based on the parent's daily rhythm. Some or all of the above processing in the notification unit may be performed using AI, for example, or without AI. For example, the notification unit may select the notification timing using an AI model that takes the parent's daily rhythm data as input and outputs the optimal notification timing.

[0050] The notification unit selects the optimal notification method when sending a notification, taking into account the guardian's geographical location information. For example, the notification unit selects the optimal notification method based on the guardian's current location. For example, the notification unit notifies the guardian of local health information based on the guardian's geographical location information. The notification unit also notifies the guardian of local vaccination schedules based on the guardian's geographical location information. This allows the notification unit to select the optimal notification method while taking the guardian's geographical location information into consideration. Some or all of the above processing in the notification unit may be performed using AI, for example, or without AI. For example, the notification unit can select a notification method using an AI model that takes the guardian's geographical location information as input and outputs the optimal notification method.

[0051] The notification unit analyzes the parent's social media activity at the time of notification and suggests relevant notification information. For example, the notification unit analyzes the parent's social media activity and suggests relevant notification information. For example, the notification unit suggests notification information shared by other parents based on the parent's social media activity. The notification unit also notifies relevant vaccination information based on the parent's social media activity. In this way, the notification unit can analyze the parent's social media activity and suggest relevant notification information. Some or all of the above processing in the notification unit may be performed using AI, for example, or without AI. For example, the notification unit can suggest notification information using an AI model that takes the parent's social media data as input and outputs relevant notification information.

[0052] The reservation department selects the optimal reservation method by referring to past reservation history when a reservation is made. For example, the reservation department proposes the optimal reservation method based on past reservation history. For example, the reservation department prioritizes the reservation method preferred by the parent based on past reservation history. The reservation department also proposes the optimal reservation timing based on past reservation history. In this way, the reservation department can select the optimal reservation method by referring to past reservation history. Some or all of the above processes in the reservation department may be performed using AI, for example, or without AI. For example, the reservation department can select a reservation method using an AI model that takes past reservation history data as input and outputs the optimal reservation method.

[0053] The reservation unit selects the optimal reservation timing based on the child's daily rhythm when a reservation is made. For example, the reservation unit selects the optimal reservation timing by considering the child's sleep patterns. For example, the reservation unit selects the optimal reservation timing by considering the child's meal times. Furthermore, the reservation unit selects the optimal reservation timing by considering the child's activity times. In this way, the reservation unit can select the optimal reservation timing based on the child's daily rhythm. Some or all of the above processing in the reservation unit may be performed using AI, for example, or without AI. For example, the reservation unit can select the reservation timing using an AI model that takes the child's daily rhythm data as input and outputs the optimal reservation timing.

[0054] The reservation department, when making a reservation, proposes the optimal reservation location considering the guardian's geographical location. For example, the reservation department proposes the nearest hospital or clinic based on the guardian's current location. For example, the reservation department proposes the optimal reservation location based on the guardian's geographical location. The reservation department also proposes the local vaccination schedule based on the guardian's geographical location. In this way, the reservation department can propose the optimal reservation location considering the guardian's geographical location. Some or all of the above processing in the reservation department may be performed using AI, for example, or without AI. For example, the reservation department can propose a reservation location using an AI model that takes the guardian's geographical location as input and outputs the optimal reservation location.

[0055] The reservation department analyzes the parent's social media activity at the time of reservation and suggests relevant reservation information. For example, the reservation department analyzes the parent's social media activity and suggests relevant reservation information. For example, the reservation department suggests reservation information shared by other parents based on the parent's social media activity. The reservation department also suggests relevant vaccination information based on the parent's social media activity. In this way, the reservation department can analyze the parent's social media activity and suggest relevant reservation information. Some or all of the above processing in the reservation department may be performed using AI, for example, or without AI. For example, the reservation department can suggest reservation information using an AI model that takes the parent's social media data as input and outputs relevant reservation information.

[0056] The service provider analyzes the interaction history in the community space and proposes the optimal interaction method. For example, the service provider proposes the optimal interaction method based on past interaction history. For example, the service provider prioritizes interaction methods preferred by parents based on past interaction history. The service provider also proposes the optimal timing for interaction based on past interaction history. In this way, the service provider can analyze the interaction history in the community space and propose the optimal interaction method. Some or all of the above processing in the service provider may be performed using AI, for example, or without AI. For example, the service provider can propose interaction methods using an AI model that takes past interaction history data as input and outputs the optimal interaction method.

[0057] The service provider proposes the most suitable interaction method for parents during interactions in community spaces, taking into account their geographical location. For example, the service provider proposes the most suitable interaction method based on the parents' current location. For example, the service provider proposes local interaction events based on the parents' geographical location. The service provider also proposes local childcare information based on the parents' geographical location. In this way, the service provider can propose the most suitable interaction method considering the parents' geographical location. Some or all of the above processing in the service provider may be performed using AI, for example, or without AI. For example, the service provider can propose interaction methods using an AI model that takes the parents' geographical location as input and outputs the most suitable interaction method.

[0058] The chatbot provides the most suitable answer by referring to past question history when responding. For example, the chatbot provides the most suitable answer based on past question history. For example, the chatbot prioritizes the response method preferred by the parent based on past question history. The chatbot also suggests the optimal timing for a response based on past question history. This allows the chatbot to provide the most suitable answer by referring to past question history. Some or all of the above processing in the chatbot may be performed using AI, for example, or without AI. For example, the chatbot can provide an answer using an AI model that takes past question history data as input and outputs the most suitable answer.

[0059] The chatbot section provides the most appropriate response when responding to a question, taking into account the parent's geographical location. For example, the chatbot section provides the most appropriate response based on the parent's current location. For example, the chatbot section provides local childcare information based on the parent's geographical location. The chatbot section also provides local medical institution information based on the parent's geographical location. This allows the chatbot section to provide the most appropriate response by taking the parent's geographical location into account. Some or all of the above processing in the chatbot section may be performed using AI, for example, or without AI. For example, the chatbot section can provide a response using an AI model that takes the parent's geographical location as input and outputs the most appropriate response.

[0060] The management department, during management, proposes the optimal management method by referring to past management history. For example, the management department proposes the optimal management method based on past management history. For example, the management department prioritizes management methods preferred by parents based on past management history. The management department also proposes the optimal timing for management based on past management history. In this way, the management department can propose the optimal management method by referring to past management history. Some or all of the above processes in the management department may be performed using AI, for example, or without AI. For example, the management department can propose a management method using an AI model that takes past management history data as input and outputs the optimal management method.

[0061] The management department proposes the optimal management method while considering the geographical location information of the guardian. For example, the management department proposes the optimal management method based on the guardian's current location. For example, the management department provides local childcare information based on the guardian's geographical location information. The management department also provides local medical institution information based on the guardian's geographical location information. This allows the management department to propose the optimal management method while considering the guardian's geographical location information. Some or all of the above processing in the management department may be performed using AI, for example, or without AI. For example, the management department can propose a management method using an AI model that takes the guardian's geographical location information as input and outputs the optimal management method.

[0062] The protection unit, when protecting data, refers to past protection history to propose the optimal protection method. For example, the protection unit proposes the optimal data protection method based on past protection history. For example, the protection unit prioritizes the data protection method preferred by the guardian based on past protection history. The protection unit also proposes the optimal timing for data protection based on past protection history. In this way, the protection unit can propose the optimal protection method by referring to past protection history. Some or all of the above processing in the protection unit may be performed using AI, for example, or without AI. For example, the protection unit can propose a protection method using an AI model that takes past protection history data as input and outputs the optimal protection method.

[0063] The protection unit proposes the optimal protection method when protecting data, taking into account the guardian's geographical location information. For example, the protection unit proposes the optimal data protection method based on the guardian's current location. For example, the protection unit proposes a method that complies with local data protection regulations based on the guardian's geographical location information. The protection unit also provides data protection information of local medical institutions based on the guardian's geographical location information. This allows the protection unit to propose the optimal protection method considering the guardian's geographical location information. Some or all of the above processing in the protection unit may be performed using AI, for example, or without AI. For example, the protection unit can propose a protection method using an AI model that takes the guardian's geographical location information as input and outputs the optimal protection method.

[0064] The protection unit analyzes the parent's social media activity and suggests relevant protection information when protecting data. For example, the protection unit analyzes the parent's social media activity and suggests relevant data protection information. For example, based on the parent's social media activity, the protection unit suggests data protection information shared by other parents. The protection unit also suggests relevant data protection settings based on the parent's social media activity. This allows the protection unit to analyze the parent's social media activity and suggest relevant protection information. Some or all of the above processing in the protection unit may be performed using AI, for example, or without AI. For example, the protection unit can suggest protection information using an AI model that takes the parent's social media data as input and outputs relevant protection information.

[0065] The system according to the embodiment is not limited to the example described above, and various modifications are possible, for example, as follows.

[0066] The mobile app can also include a health information analysis unit. This unit analyzes the child's health information and detects changes in their health status. For example, it can regularly collect data such as the child's body temperature, weight, and height, and notify parents if there are any abnormal changes. It can also analyze records of the child's diet and exercise and provide advice to maintain healthy lifestyle habits. Furthermore, it can predict health risks associated with the child's growth and suggest preventive measures. As a result, the mobile app can continuously monitor the child's health status, detect abnormalities early, and take appropriate action.

[0067] The mobile app can also include a vaccination history management section. This section provides detailed management of a child's vaccination history and offers necessary information to parents. For example, it can store records of past vaccinations and notify parents of the timing of the next vaccination. It can also allow parents to easily check detailed information such as the type of vaccination, the date of vaccination, and the location of vaccination. Furthermore, it can provide information on the effectiveness and side effects of vaccinations, supporting parents in ensuring their children receive vaccinations with peace of mind. In this way, the mobile app can centrally manage a child's vaccination history and provide parents with the necessary information.

[0068] The mobile app can also include a parenting advice section. This section provides parents with expert advice on childcare. For example, it can provide parenting methods and points to note according to the child's developmental stage, supporting parents in raising their children appropriately. Furthermore, it can provide personalized advice based on the child's health and developmental stage. In addition, it can quickly and accurately answer parents' questions, alleviating anxieties and doubts about childcare. This allows the mobile app to provide comprehensive parenting support to parents and help their children grow up healthy.

[0069] The mobile app can also include a data analysis unit. This unit analyzes children's health data and identifies trends in their health status. For example, it can collect data such as a child's body temperature, weight, and height over a long period and visually display changes in their health status using graphs and charts. Furthermore, based on the child's health data, the data analysis unit can predict future health risks and suggest preventative measures. It can also compare a child's health data with data from other children, detecting abnormalities by comparing it against standard growth patterns. This allows the mobile app to continuously monitor a child's health, detect abnormalities early, and take appropriate action.

[0070] The mobile app can also include a immunization information section. This section provides parents with the latest immunization information. For example, it can provide the latest immunization guidelines and recommended schedules, giving parents information to ensure their children receive appropriate vaccinations. It can also provide the latest research findings on the effectiveness and side effects of vaccinations, allowing parents to obtain accurate information about immunization. Furthermore, it can provide information on local immunization campaigns and events, helping parents not miss immunization opportunities. In this way, the mobile app can provide parents with the latest immunization information and support them in protecting their children's health.

[0071] The following briefly describes the processing flow for example form 1.

[0072] Step 1: The reception desk enters the child's birthday and health information. The reception desk provides an interface for parents to enter their child's birthday and health information into the app. For example, it uses text input fields and dropdown menus to make it easy to enter information. It also has a voice input function, allowing parents to enter information by voice. Step 2: The scheduling unit creates an optimal vaccination schedule based on the information entered by the reception unit. The scheduling unit uses AI to calculate the timing of vaccinations based on the child's age and health condition. Furthermore, it can create an optimal vaccination schedule based on medical guidelines and provide an individually optimized schedule that takes into account the child's genetic information and family medical history. Step 3: The notification unit sends reminder notifications based on the schedule created by the schedule creation unit. The notification unit sends a reminder notification the day before the vaccination. Notification methods include in-app notifications, email, and SMS, and can be customized according to the parent's preferences. Step 4: The reservation department makes vaccination appointments based on the schedule created by the schedule creation department. The reservation department automatically makes reservations while checking the availability of local hospitals and clinics. It uses an API to connect with hospital reservation systems and check availability in real time. It also provides an easy-to-use interface for parents to make reservations manually.

[0073] (Example of form 2) The mobile app according to an embodiment of the present invention is a system for easily and effectively supporting children's health management and vaccinations. This system allows parents to simply input their child's birthday and health information, and the AI ​​automatically creates an optimal vaccination schedule, notifying parents of important dates with reminder notifications. Furthermore, the AI ​​considers the child's genetic information, place of residence, family medical history, etc., to provide an individually optimized vaccination plan. It also collaborates with local hospitals and clinics, allowing for automatic booking while checking availability. The app also provides a community space where parents can interact with each other in a safe environment, easily sharing questions and concerns about childcare. Additionally, the built-in chatbot answers childcare questions in real time based on the latest medical information. It truly acts as an AI childcare concierge, providing comprehensive support for parents' childcare. Other features include regular check-up schedules and developmental checklists tailored to the child's growth, allowing for comprehensive management of the child's growth and health. The app also prioritizes data management and privacy protection, providing a safe environment for parents to use with peace of mind. As a partner in protecting children's health, this app supports healthy growth, including vaccinations. This allows mobile apps to easily and effectively support children's health management and vaccinations.

[0074] The mobile application according to this embodiment comprises a reception unit, a schedule creation unit, a notification unit, and a reservation unit. The reception unit inputs the child's birthday and health information. The reception unit provides, for example, an interface for parents to input the child's birthday and health information into the app. The reception unit allows for easy information input using, for example, text input fields or dropdown menus. The reception unit also has a voice input function, allowing parents to input information by voice. The schedule creation unit creates an optimal vaccination schedule based on the information entered by the reception unit. The schedule creation unit calculates the timing of vaccinations based on the child's age and health condition using, for example, AI. The schedule creation unit creates an optimal vaccination schedule based on, for example, medical guidelines. The schedule creation unit can also provide an individually optimized schedule by considering the child's genetic information and family medical history. The notification unit provides reminder notifications based on the schedule created by the schedule creation unit. The notification unit sends a reminder notification, for example, the day before a vaccination. The notification unit sends reminders by, for example, in-app notifications, email, SMS, etc. Furthermore, the notification unit can customize the notification method according to the parent's preferences. The reservation unit makes vaccination reservations based on the schedule created by the schedule creation unit. The reservation unit automatically makes reservations, for example, by checking the availability of local hospitals and clinics. The reservation unit can also link with hospital reservation systems using APIs, for example, to check availability in real time. In addition, the reservation unit provides an easy-to-use interface for parents to make reservations manually. As a result, the mobile app according to the embodiment can create an optimal vaccination schedule based on the child's birthday and health information, and can send reminder notifications and make reservations.

[0075] The reception section is where parents enter their child's birthday and health information. For example, the reception section provides an interface for parents to enter their child's birthday and health information into the app. Specifically, the reception section uses text input fields and dropdown menus to make it easy to enter information. Text input fields are for entering the child's name, birthday, allergy information, etc., while dropdown menus provide options such as gender and medical history. The reception section also has a voice input function, allowing parents to enter information by voice. The voice input function uses speech recognition technology to convert the parent's speech into text and automatically reflect it in the input field. Furthermore, the reception section has a function to centrally manage the entered information and store it in a database. This saves parents the trouble of re-entering information they have already entered. The reception section also has a validation function to check the accuracy of the entered information, and if incorrect information is entered, it displays an error message and prompts correction. In this way, the reception section enables parents to easily and accurately enter their child's information and realizes smooth information management.

[0076] The scheduling unit creates an optimal vaccination schedule based on the information entered by the reception unit. For example, the scheduling unit uses AI to calculate the timing of vaccinations based on the child's age and health condition. Specifically, the AI ​​refers to medical guidelines and historical data to calculate the optimal timing for vaccinations based on the child's age and health. For example, the AI ​​calculates the appropriate timing for each vaccination based on the child's birth date. The scheduling unit can also provide individually optimized schedules by considering the child's genetic information and family medical history. Genetic information and family medical history are used to assess the risk of specific diseases, and the timing and type of vaccinations are adjusted accordingly. Furthermore, the scheduling unit provides the created schedule to parents and offers an easy-to-use interface for review and modification if necessary. This ensures that the scheduling unit provides an optimal vaccination schedule tailored to each child's individual circumstances, allowing parents to confidently ensure their children receive vaccinations.

[0077] The notification unit sends reminder notifications based on the schedule created by the schedule creation unit. For example, the notification unit sends a reminder notification the day before a vaccination. Specifically, the notification unit sends reminders via in-app notifications, email, SMS, etc. In-app notifications appear as pop-up messages when the app is opened, while emails and SMS messages are sent to the parent's registered contacts. The notification unit can also customize the notification method according to the parent's preference. For example, if the parent prefers email notifications, the reminder will be sent via email; if they prefer SMS notifications, the reminder will be sent via SMS. Furthermore, the notification unit has a function to adjust the timing of reminder notifications, allowing parents to receive notifications at their preferred time. For example, reminders can be sent at times specified by the parent, such as one week or three days before a vaccination. In this way, the notification unit helps parents manage their child's vaccination schedule without forgetting, supporting their child's health management.

[0078] The reservation department makes vaccination appointments based on schedules created by the scheduling department. The reservation department automatically makes appointments, for example, by checking the availability of local hospitals and clinics. Specifically, the reservation department uses an API to connect with hospital reservation systems and check availability in real time. This allows parents to make vaccination appointments without any hassle. The reservation department also provides an easy-to-use interface for parents who make appointments manually. For example, they can select their desired date and time using a calendar-style interface and confirm the appointment. Furthermore, the reservation department includes features that allow for easy appointment changes and cancellations, enabling parents to respond flexibly. For example, in case of a sudden change in plans, appointments can be easily changed or canceled within the app. In this way, the reservation department enables parents to smoothly make vaccination appointments and efficiently manage their children's health.

[0079] The schedule creation unit creates an immunization schedule considering the child's genetic information, place of residence, family medical history, etc. For example, the schedule creation unit analyzes the child's genetic information and adjusts the immunization schedule based on specific genetic risks. For example, the schedule creation unit considers environmental factors of the place of residence and prioritizes vaccinations against diseases prevalent in the area. The schedule creation unit can also consider the family medical history and add vaccinations against specific diseases. In this way, the schedule creation unit can create an optimal immunization schedule that takes the child's individual information into account. Some or all of the above processes in the schedule creation unit may be performed using AI, for example, or not. For example, the schedule creation unit can create a schedule using an AI model that takes the child's genetic information and family medical history as input and outputs an optimal immunization schedule.

[0080] The reservation department automatically makes reservations while checking the availability of local hospitals and clinics. The reservation department can, for example, use an API to connect with hospital reservation systems and check availability in real time. The reservation department can, for example, suggest the optimal reservation date and time based on availability. The reservation department also provides an easy-to-use interface for parents who wish to make reservations manually. This allows the reservation department to automatically make reservations while checking the availability of local hospitals and clinics. Some or all of the above processes in the reservation department may be performed using AI, for example, or not. For example, the reservation department can make reservations using an AI model that takes hospital availability data as input and outputs the optimal reservation date and time.

[0081] The service provider will offer a community space where parents can interact with each other. For example, the service provider will provide an online forum where parents can share questions and concerns about childcare. For example, the service provider will provide a chat function so that parents can interact in real time. In addition, the service provider can provide blogs and articles for sharing information about childcare. In this way, the service provider can provide a community space where parents can interact with each other.

[0082] The chatbot section answers questions related to childcare. The chatbot section provides real-time answers to questions from parents, for example, using AI. The chatbot section provides answers to frequently asked questions, for example, by referring to an FAQ database. The chatbot section can also provide expert advice on childcare based on the latest medical information. In this way, the chatbot section can answer questions related to childcare. Some or all of the above processing in the chatbot section may be performed using AI, for example, or without AI. For example, the chatbot section can provide answers using an AI model that takes questions from parents as input and outputs the optimal answer.

[0083] The management department manages regular health checkup schedules and developmental checklists tailored to each child's growth. For example, the management department creates schedules for regular health checkups and sends reminder notifications. For example, the management department provides developmental checklists tailored to each child's growth, allowing parents to record their child's development. The management department can also store children's health information in a database and refer to it as needed. This allows the management department to manage regular health checkup schedules and developmental checklists tailored to each child's growth.

[0084] The protection unit handles data management and privacy protection. For example, the protection unit securely protects parental data using data encryption technology. For example, the protection unit implements access control to prevent unauthorized access to parental data. The protection unit can also allow parents to set the scope of data sharing. This enables the protection unit to perform data management and privacy protection.

[0085] The reception desk estimates the parent's emotions and adjusts the design of the input interface based on the estimated emotions. For example, if the parent is stressed, the reception desk provides a simple and intuitive interface and minimizes the input steps. If the parent is relaxed, for example, the reception desk provides detailed input options and suggests a customizable input method. Also, if the parent is in a hurry, the reception desk prioritizes voice input to allow for quick input of the child's birthday and health information. This allows the reception desk to adjust the design of the input interface based on the parent'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 reception desk may be performed using AI or not. For example, the reception desk can take the parent's facial expression data as input and estimate emotions using an AI model that estimates emotions.

[0086] The reception desk reduces the effort required for inputting children's health information by referring to past input history. For example, the reception desk can automatically display previously entered health information of children, so that parents only need to confirm it. For example, the reception desk can reduce the effort required by prioritizing the display of frequently entered information from past input history. In addition, the reception desk can provide a predictive input function based on past input history to minimize the effort required for parents to input information. This allows the reception desk to reduce the effort required for input by referring to past input history. Some or all of the above processing in the reception desk may be performed using AI, for example, or without AI. For example, the reception desk can reduce the effort required for input by using an AI model that takes past input history data as input and outputs predictive input.

[0087] The reception desk verifies the accuracy of the entered information in real time and prompts for correction as needed. For example, if the entered child's birthday or health information is inaccurate, the reception desk will display a warning in real time and prompt for correction. For example, if the entered information is incomplete, the reception desk will suggest ways to complete it in real time. Also, if the entered information is contradictory, the reception desk will point out the inconsistencies in real time and prompt for correction. In this way, the reception desk can verify the accuracy of the entered information in real time and prompt for correction as needed. Some or all of the above processing in the reception desk may be performed using AI, for example, or not using AI. For example, the reception desk can use an AI model that takes the entered information as input and verifies its accuracy to prompt for correction in real time.

[0088] The reception desk estimates the parent's emotions and prioritizes input based on the estimated emotions. For example, if the parent is stressed, the reception desk prioritizes input of important information and postpones other information. For example, if the parent is relaxed, the reception desk encourages input of detailed information to collect more accurate data. Also, if the parent is in a hurry, the reception desk asks for only the minimum necessary information and allows for the addition of details later. This allows the reception desk to prioritize input based on the parent's emotions. Emotion estimation is achieved using an emotion estimation function, such as 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 reception desk may be performed using AI or not. For example, the reception desk can take the parent's facial expression data as input and estimate emotions using an AI model that estimates emotions.

[0089] The reception desk automatically completes relevant health information by considering the guardian's geographical location information during input. For example, the reception desk automatically completes local health information based on the guardian's current location. For example, the reception desk automatically displays information on local hospitals and clinics based on the guardian's geographical location information. The reception desk also automatically completes local vaccination schedules based on the guardian's geographical location information. In this way, the reception desk can automatically complete relevant health information by considering the guardian's geographical location information. Some or all of the above processing in the reception desk may be performed using AI, for example, or without AI. For example, the reception desk can complete health information using an AI model that takes the guardian's geographical location information as input and outputs relevant health information.

[0090] The reception desk analyzes the parent's social media activity during input and suggests relevant health information. For example, the reception desk automatically suggests relevant health information based on the parent's social media activity. For example, the reception desk suggests health information shared by other parents based on the parent's social media activity. The reception desk also suggests relevant vaccination information based on the parent's social media activity. This allows the reception desk to analyze the parent's social media activity and suggest relevant health information. Some or all of the above processing in the reception desk may be performed using AI, for example, or without AI. For example, the reception desk can suggest health information using an AI model that takes the parent's social media data as input and outputs relevant health information.

[0091] The scheduling unit estimates the parent's emotions and adjusts the way the schedule is presented based on the estimated emotions. For example, if the parent is stressed, the scheduling unit presents a simple and intuitive schedule. If the parent is relaxed, for example, the scheduling unit presents a detailed schedule and offers customizable options. Also, if the parent is in a hurry, the scheduling unit highlights and presents only the most important dates. This allows the scheduling unit to adjust the way the schedule is presented based on the parent'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 scheduling unit may be performed using AI or not. For example, the scheduling unit can take the parent's facial expression data as input and estimate emotions using an AI model that estimates emotions.

[0092] The schedule creation unit proposes an optimal schedule by referring to past vaccination data when creating a schedule. For example, the schedule creation unit proposes the next vaccination schedule based on past vaccination data. For example, the schedule creation unit proposes the optimal timing of vaccinations based on past vaccination data. The schedule creation unit also optimizes the interval between vaccinations based on past vaccination data. In this way, the schedule creation unit can propose an optimal schedule by referring to past vaccination data. Some or all of the above processes in the schedule creation unit may be performed using AI, for example, or without AI. For example, the schedule creation unit can propose a schedule using an AI model that takes past vaccination data as input and outputs an optimal schedule.

[0093] The schedule creation unit selects the optimal vaccination timing based on the child's daily rhythm when creating the schedule. For example, the schedule creation unit selects the optimal vaccination timing by considering the child's sleep pattern. For example, the schedule creation unit selects the optimal vaccination timing by considering the child's meal times. Furthermore, the schedule creation unit selects the optimal vaccination timing by considering the child's activity time. In this way, the schedule creation unit can select the optimal vaccination timing based on the child's daily rhythm. Some or all of the above processing in the schedule creation unit may be performed using AI, for example, or without AI. For example, the schedule creation unit can select the vaccination timing using an AI model that takes the child's daily rhythm data as input and outputs the optimal vaccination timing.

[0094] The scheduling unit estimates the parent's emotions and determines schedule priorities based on the estimated emotions. For example, if the parent is stressed, the scheduling unit prioritizes important vaccinations in the schedule. For example, if the parent is relaxed, the scheduling unit provides a detailed schedule and suggests customizable options. Also, if the parent is in a hurry, the scheduling unit includes only the minimum necessary vaccinations in the schedule. This allows the scheduling unit to determine schedule priorities based on the parent'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 scheduling unit may be performed using AI or not. For example, the scheduling unit can take the parent's facial expression data as input and estimate emotions using an AI model that estimates emotions.

[0095] The schedule creation unit proposes the optimal vaccination location when creating a schedule, taking into account the child's geographical location. For example, the schedule creation unit proposes the nearest hospital or clinic based on the child's current location. For example, the schedule creation unit proposes the optimal vaccination location based on the child's geographical location. The schedule creation unit also proposes a regional vaccination schedule based on the child's geographical location. In this way, the schedule creation unit can propose the optimal vaccination location while taking the child's geographical location into consideration. Some or all of the above processing in the schedule creation unit may be performed using AI, for example, or without AI. For example, the schedule creation unit can propose vaccination locations using an AI model that takes the child's geographical location as input and outputs the optimal vaccination location.

[0096] The schedule creation unit analyzes the child's social media activity when creating a schedule and suggests relevant vaccination information. For example, the schedule creation unit analyzes the child's social media activity and suggests relevant vaccination information. For example, the schedule creation unit suggests vaccination information shared by other parents based on the child's social media activity. The schedule creation unit also suggests relevant vaccination schedules based on the child's social media activity. In this way, the schedule creation unit can analyze the child's social media activity and suggest relevant vaccination information. Some or all of the above processing in the schedule creation unit may be performed using AI, for example, or without AI. For example, the schedule creation unit can suggest vaccination information using an AI model that takes the child's social media data as input and outputs relevant vaccination information.

[0097] The notification unit estimates the parent's emotions and adjusts the timing of notifications based on the estimated emotions. For example, if the parent is stressed, the notification unit will send a notification during a time when the parent can relax. If the parent is relaxed, the notification unit will provide a detailed notification and offer customizable options. Also, if the parent is in a hurry, the notification unit will quickly send only important notifications. This allows the notification unit to adjust the timing of notifications based on the parent'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 notification unit may be performed using AI or not. For example, the notification unit can take the parent's facial expression data as input and estimate emotions using an AI model that estimates emotions.

[0098] The notification unit selects the optimal notification method by referring to past notification history when issuing a notification. For example, the notification unit selects the optimal notification method based on past notification history. For example, the notification unit prioritizes notification methods preferred by parents based on past notification history. The notification unit also selects the optimal notification timing based on past notification history. In this way, the notification unit can select the optimal notification method by referring to past notification history. Some or all of the above processing in the notification unit may be performed using AI, for example, or without AI. For example, the notification unit can select a notification method using an AI model that takes past notification history data as input and outputs the optimal notification method.

[0099] The notification unit selects the optimal notification timing based on the parent's daily rhythm when sending a notification. For example, the notification unit may select the optimal notification timing by considering the parent's sleep pattern. For example, the notification unit may select the optimal notification timing by considering the parent's meal times. Furthermore, the notification unit may select the optimal notification timing by considering the parent's activity times. In this way, the notification unit can select the optimal notification timing based on the parent's daily rhythm. Some or all of the above processing in the notification unit may be performed using AI, for example, or without AI. For example, the notification unit may select the notification timing using an AI model that takes the parent's daily rhythm data as input and outputs the optimal notification timing.

[0100] The notification unit estimates the parent's emotions and determines notification priorities based on the estimated emotions. For example, if the parent is stressed, the notification unit will prioritize important notifications. If the parent is relaxed, the notification unit will provide detailed notifications and customizable options. If the parent is in a hurry, the notification unit will only provide the minimum necessary notifications. This allows the notification unit to prioritize notifications based on the parent's emotions. Emotion estimation is achieved using an emotion estimation function, such as an emotion engine or generative AI. Generative AI includes, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the notification unit may be performed using AI or not. For example, the notification unit can take the parent's facial expression data as input and estimate emotions using an AI model that estimates emotions.

[0101] The notification unit selects the optimal notification method when sending a notification, taking into account the guardian's geographical location information. For example, the notification unit selects the optimal notification method based on the guardian's current location. For example, the notification unit notifies the guardian of local health information based on the guardian's geographical location information. The notification unit also notifies the guardian of local vaccination schedules based on the guardian's geographical location information. This allows the notification unit to select the optimal notification method while taking the guardian's geographical location information into consideration. Some or all of the above processing in the notification unit may be performed using AI, for example, or without AI. For example, the notification unit can select a notification method using an AI model that takes the guardian's geographical location information as input and outputs the optimal notification method.

[0102] The notification unit analyzes the parent's social media activity at the time of notification and suggests relevant notification information. For example, the notification unit analyzes the parent's social media activity and suggests relevant notification information. For example, the notification unit suggests notification information shared by other parents based on the parent's social media activity. The notification unit also notifies relevant vaccination information based on the parent's social media activity. In this way, the notification unit can analyze the parent's social media activity and suggest relevant notification information. Some or all of the above processing in the notification unit may be performed using AI, for example, or without AI. For example, the notification unit can suggest notification information using an AI model that takes the parent's social media data as input and outputs relevant notification information.

[0103] The reservation system estimates the parent's emotions and adjusts the reservation presentation method based on the estimated emotions. For example, if the parent is stressed, the reservation system provides a simple and intuitive reservation interface. If the parent is relaxed, the reservation system provides detailed reservation options and suggests a customizable reservation method. Also, if the parent is in a hurry, the reservation system prioritizes voice input to allow for quick reservation completion. This allows the reservation system to adjust the reservation presentation method based on the parent'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 reservation system may be performed using AI or not. For example, the reservation system can take the parent's facial expression data as input and estimate emotions using an AI model that estimates emotions.

[0104] The reservation department selects the optimal reservation method by referring to past reservation history when a reservation is made. For example, the reservation department proposes the optimal reservation method based on past reservation history. For example, the reservation department prioritizes the reservation method preferred by the parent based on past reservation history. The reservation department also proposes the optimal reservation timing based on past reservation history. In this way, the reservation department can select the optimal reservation method by referring to past reservation history. Some or all of the above processes in the reservation department may be performed using AI, for example, or without AI. For example, the reservation department can select a reservation method using an AI model that takes past reservation history data as input and outputs the optimal reservation method.

[0105] The reservation unit selects the optimal reservation timing based on the child's daily rhythm when a reservation is made. For example, the reservation unit selects the optimal reservation timing by considering the child's sleep patterns. For example, the reservation unit selects the optimal reservation timing by considering the child's meal times. Furthermore, the reservation unit selects the optimal reservation timing by considering the child's activity times. In this way, the reservation unit can select the optimal reservation timing based on the child's daily rhythm. Some or all of the above processing in the reservation unit may be performed using AI, for example, or without AI. For example, the reservation unit can select the reservation timing using an AI model that takes the child's daily rhythm data as input and outputs the optimal reservation timing.

[0106] The booking system estimates the parent's emotions and prioritizes bookings based on the estimated emotions. For example, if the parent is stressed, the booking system prioritizes important bookings. If the parent is relaxed, the booking system provides detailed booking options and suggests a customizable booking method. If the parent is in a hurry, the booking system quickly makes only the minimum necessary bookings. This allows the booking system to prioritize bookings based on the parent's emotions. Emotion estimation is achieved using an emotion estimation function, such as an emotion engine or generative AI. Generative AI includes, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the booking system may be performed using AI or not. For example, the booking system can take the parent's facial expression data as input and estimate emotions using an AI model that estimates emotions.

[0107] The reservation department, when making a reservation, proposes the optimal reservation location considering the guardian's geographical location. For example, the reservation department proposes the nearest hospital or clinic based on the guardian's current location. For example, the reservation department proposes the optimal reservation location based on the guardian's geographical location. The reservation department also proposes the local vaccination schedule based on the guardian's geographical location. In this way, the reservation department can propose the optimal reservation location considering the guardian's geographical location. Some or all of the above processing in the reservation department may be performed using AI, for example, or without AI. For example, the reservation department can propose a reservation location using an AI model that takes the guardian's geographical location as input and outputs the optimal reservation location.

[0108] The reservation department analyzes the parent's social media activity at the time of reservation and suggests relevant reservation information. For example, the reservation department analyzes the parent's social media activity and suggests relevant reservation information. For example, the reservation department suggests reservation information shared by other parents based on the parent's social media activity. The reservation department also suggests relevant vaccination information based on the parent's social media activity. In this way, the reservation department can analyze the parent's social media activity and suggest relevant reservation information. Some or all of the above processing in the reservation department may be performed using AI, for example, or without AI. For example, the reservation department can suggest reservation information using an AI model that takes the parent's social media data as input and outputs relevant reservation information.

[0109] The service provider estimates the emotions of parents and adjusts the design of the community space based on the estimated emotions. For example, if a parent is stressed, the service provider provides a design with calming colors to reduce visual stress. For example, if a parent is relaxed, the service provider provides a design with bright colors to make interaction more enjoyable. Also, if a parent is tired, the service provider provides a simple and highly visible design to facilitate interaction. In this way, the service provider can adjust the design of the community space based on the emotions of parents. 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 service provider may be performed using AI, for example, or not using AI. For example, the service provider can take parent facial expression data as input and estimate emotions using an AI model that estimates emotions.

[0110] The service provider analyzes the interaction history in the community space and proposes the optimal interaction method. For example, the service provider proposes the optimal interaction method based on past interaction history. For example, the service provider prioritizes interaction methods preferred by parents based on past interaction history. The service provider also proposes the optimal timing for interaction based on past interaction history. In this way, the service provider can analyze the interaction history in the community space and propose the optimal interaction method. Some or all of the above processing in the service provider may be performed using AI, for example, or without AI. For example, the service provider can propose interaction methods using an AI model that takes past interaction history data as input and outputs the optimal interaction method.

[0111] The service provider estimates the parent's emotions and determines the priority of interactions based on the estimated emotions. For example, if the parent is stressed, the service provider will prioritize important interactions. If the parent is relaxed, the service provider will offer detailed interaction options and suggest customizable interaction methods. If the parent is in a hurry, the service provider will quickly provide only the minimum necessary interactions. This allows the service provider to determine the priority of interactions based on the parent'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 service provider may be performed using AI or not. For example, the service provider can take the parent's facial expression data as input and estimate emotions using an AI model that estimates emotions.

[0112] The service provider proposes the most suitable interaction method for parents during interactions in community spaces, taking into account their geographical location. For example, the service provider proposes the most suitable interaction method based on the parents' current location. For example, the service provider proposes local interaction events based on the parents' geographical location. The service provider also proposes local childcare information based on the parents' geographical location. In this way, the service provider can propose the most suitable interaction method considering the parents' geographical location. Some or all of the above processing in the service provider may be performed using AI, for example, or without AI. For example, the service provider can propose interaction methods using an AI model that takes the parents' geographical location as input and outputs the most suitable interaction method.

[0113] The chatbot section estimates the parent's emotions and adjusts the way it expresses its responses based on the estimated emotions. For example, if the parent is stressed, the chatbot section provides simple and intuitive responses. If the parent is relaxed, for example, the chatbot section provides detailed responses and suggests customizable options. Also, if the parent is in a hurry, the chatbot section quickly provides only the essential information. This allows the chatbot section to adjust the way it expresses its responses based on the parent'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 chatbot section may be performed using AI or not. For example, the chatbot section can take the parent's facial expression data as input and estimate emotions using an AI model that estimates emotions.

[0114] The chatbot provides the most suitable answer by referring to past question history when responding. For example, the chatbot provides the most suitable answer based on past question history. For example, the chatbot prioritizes the response method preferred by the parent based on past question history. The chatbot also suggests the optimal timing for a response based on past question history. This allows the chatbot to provide the most suitable answer by referring to past question history. Some or all of the above processing in the chatbot may be performed using AI, for example, or without AI. For example, the chatbot can provide an answer using an AI model that takes past question history data as input and outputs the most suitable answer.

[0115] The chatbot unit estimates the parent's emotions and prioritizes responses based on the estimated emotions. For example, if the parent is stressed, the chatbot unit will prioritize answering important questions. If the parent is relaxed, the chatbot unit will provide detailed answers and suggest customizable options. If the parent is in a hurry, the chatbot unit will quickly provide only the minimum necessary answers. This allows the chatbot unit to prioritize responses based on the parent's emotions. Emotion estimation is achieved using an emotion estimation function, such as an emotion engine or generative AI. Generative AI includes, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the chatbot unit may be performed using AI or not. For example, the chatbot unit can take the parent's facial expression data as input and estimate emotions using an AI model that estimates emotions.

[0116] The chatbot section provides the most appropriate response when responding to a question, taking into account the parent's geographical location. For example, the chatbot section provides the most appropriate response based on the parent's current location. For example, the chatbot section provides local childcare information based on the parent's geographical location. The chatbot section also provides local medical institution information based on the parent's geographical location. This allows the chatbot section to provide the most appropriate response by taking the parent's geographical location into account. Some or all of the above processing in the chatbot section may be performed using AI, for example, or without AI. For example, the chatbot section can provide a response using an AI model that takes the parent's geographical location as input and outputs the most appropriate response.

[0117] The management unit estimates the parent's emotions and adjusts the design of the management screen based on the estimated emotions. For example, if the parent is stressed, the management unit provides a simple and intuitive management screen. If the parent is relaxed, the management unit provides detailed management options and suggests a customizable management method. Also, if the parent is in a hurry, the management unit quickly displays only the most important management items. This allows the management unit to adjust the design of the management screen based on the parent'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 management unit may be performed using AI or not. For example, the management unit can take the parent's facial expression data as input and estimate emotions using an AI model that estimates emotions.

[0118] The management department, during management, proposes the optimal management method by referring to past management history. For example, the management department proposes the optimal management method based on past management history. For example, the management department prioritizes management methods preferred by parents based on past management history. The management department also proposes the optimal timing for management based on past management history. In this way, the management department can propose the optimal management method by referring to past management history. Some or all of the above processes in the management department may be performed using AI, for example, or without AI. For example, the management department can propose a management method using an AI model that takes past management history data as input and outputs the optimal management method.

[0119] The management department estimates the parent's emotions and determines management priorities based on the estimated emotions. For example, if the parent is stressed, the management department will prioritize important management items. For example, if the parent is relaxed, the management department will provide detailed management options and suggest customizable management methods. Also, if the parent is in a hurry, the management department will quickly perform only the minimum necessary management items. This allows the management department to determine management priorities based on the parent's emotions. Emotion estimation is achieved using emotion estimation functions, such as emotion engines or generative AI. Generative AI includes, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the management department may be performed using AI or not. For example, the management department can estimate emotions using an AI model that takes parent facial expression data as input.

[0120] The management department proposes the optimal management method while considering the geographical location information of the guardian. For example, the management department proposes the optimal management method based on the guardian's current location. For example, the management department provides local childcare information based on the guardian's geographical location information. The management department also provides local medical institution information based on the guardian's geographical location information. This allows the management department to propose the optimal management method while considering the guardian's geographical location information. Some or all of the above processing in the management department may be performed using AI, for example, or without AI. For example, the management department can propose a management method using an AI model that takes the guardian's geographical location information as input and outputs the optimal management method.

[0121] The protection unit estimates the guardian's emotions and adjusts privacy protection methods based on the estimated emotions. For example, if the guardian is stressed, the protection unit provides simple and intuitive privacy protection settings. If the guardian is relaxed, the protection unit provides detailed privacy protection options and suggests customizable settings. Also, if the guardian is in a hurry, the protection unit quickly sets only the important privacy protection items. This allows the protection unit to adjust privacy protection methods based on the guardian's emotions. Emotion estimation is achieved using emotion estimation functions, such as emotion engines or generative AI. Generative AI includes, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the protection unit may be performed using AI or not. For example, the protection unit can take the guardian's facial expression data as input and estimate emotions using an emotion estimation AI model.

[0122] The protection unit, when protecting data, refers to past protection history to propose the optimal protection method. For example, the protection unit proposes the optimal data protection method based on past protection history. For example, the protection unit prioritizes the data protection method preferred by the guardian based on past protection history. The protection unit also proposes the optimal timing for data protection based on past protection history. In this way, the protection unit can propose the optimal protection method by referring to past protection history. Some or all of the above processing in the protection unit may be performed using AI, for example, or without AI. For example, the protection unit can propose a protection method using an AI model that takes past protection history data as input and outputs the optimal protection method.

[0123] The protection unit estimates the caregiver's emotions and determines protection priorities based on the estimated emotions. For example, if the caregiver is stressed, the protection unit prioritizes important data protection items. If the caregiver is relaxed, the protection unit provides detailed data protection options and suggests customizable settings. If the caregiver is in a hurry, the protection unit quickly configures only the minimum necessary data protection items. This allows the protection unit to determine protection priorities based on the caregiver's emotions. Emotion estimation is achieved using emotion estimation functions, such as emotion engines or generative AI. Generative AI includes, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the protection unit may be performed using AI or not. For example, the protection unit can take the caregiver's facial expression data as input and estimate emotions using an emotion estimation AI model.

[0124] The protection unit proposes the optimal protection method when protecting data, taking into account the guardian's geographical location information. For example, the protection unit proposes the optimal data protection method based on the guardian's current location. For example, the protection unit proposes a method that complies with local data protection regulations based on the guardian's geographical location information. The protection unit also provides data protection information of local medical institutions based on the guardian's geographical location information. This allows the protection unit to propose the optimal protection method considering the guardian's geographical location information. Some or all of the above processing in the protection unit may be performed using AI, for example, or without AI. For example, the protection unit can propose a protection method using an AI model that takes the guardian's geographical location information as input and outputs the optimal protection method.

[0125] The protection unit analyzes the parent's social media activity and suggests relevant protection information when protecting data. For example, the protection unit analyzes the parent's social media activity and suggests relevant data protection information. For example, based on the parent's social media activity, the protection unit suggests data protection information shared by other parents. The protection unit also suggests relevant data protection settings based on the parent's social media activity. This allows the protection unit to analyze the parent's social media activity and suggest relevant protection information. Some or all of the above processing in the protection unit may be performed using AI, for example, or without AI. For example, the protection unit can suggest protection information using an AI model that takes the parent's social media data as input and outputs relevant protection information.

[0126] The system according to the embodiment is not limited to the example described above, and various modifications are possible, for example, as follows.

[0127] The mobile app can also include a health information analysis unit. This unit analyzes the child's health information and detects changes in their health status. For example, it can regularly collect data such as the child's body temperature, weight, and height, and notify parents if there are any abnormal changes. It can also analyze records of the child's diet and exercise and provide advice to maintain healthy lifestyle habits. Furthermore, it can predict health risks associated with the child's growth and suggest preventive measures. As a result, the mobile app can continuously monitor the child's health status, detect abnormalities early, and take appropriate action.

[0128] Mobile apps can also be equipped with an emotion estimation unit. This unit estimates the parent's emotions and adjusts the app's functions based on the estimated emotions. For example, if the parent is stressed, the emotion estimation unit can provide a simple and intuitive interface to reduce the burden of operation. If the parent is relaxed, the emotion estimation unit can provide detailed information and present more options. Furthermore, if the parent is in a hurry, the emotion estimation unit can quickly display only the essential information and simplify operation. In this way, mobile apps can respond flexibly to the parent's emotions and provide a more comfortable user experience.

[0129] The mobile app can also include a vaccination history management section. This section provides detailed management of a child's vaccination history and offers necessary information to parents. For example, it can store records of past vaccinations and notify parents of the timing of the next vaccination. It can also allow parents to easily check detailed information such as the type of vaccination, the date of vaccination, and the location of vaccination. Furthermore, it can provide information on the effectiveness and side effects of vaccinations, supporting parents in ensuring their children receive vaccinations with peace of mind. In this way, the mobile app can centrally manage a child's vaccination history and provide parents with the necessary information.

[0130] The mobile app can also be equipped with an emotion estimation unit. This unit estimates the parent's emotions and adjusts the community space's functions based on those emotions. For example, if the parent is feeling stressed, the emotion estimation unit can prioritize displaying relaxing content to reduce the burden of interaction. Conversely, if the parent is relaxed, the emotion estimation unit can provide content that encourages active interaction, thereby revitalizing the community. Furthermore, if the parent is in a hurry, the emotion estimation unit can quickly display only essential information, streamlining interaction. In this way, the mobile app can flexibly adjust the community space's functions according to the parent's emotions, providing a more comfortable interaction environment.

[0131] The mobile app can also include a parenting advice section. This section provides parents with expert advice on childcare. For example, it can provide parenting methods and points to note according to the child's developmental stage, supporting parents in raising their children appropriately. Furthermore, it can provide personalized advice based on the child's health and developmental stage. In addition, it can quickly and accurately answer parents' questions, alleviating anxieties and doubts about childcare. This allows the mobile app to provide comprehensive parenting support to parents and help their children grow up healthy.

[0132] The mobile app can also include an emotion estimation unit. This unit estimates the parent's emotions and adjusts how the regular check-up schedule is managed based on those emotions. For example, if the parent is feeling stressed, the emotion estimation unit can provide a simple and intuitive schedule management screen to reduce the burden of operation. If the parent is relaxed, the emotion estimation unit can provide detailed schedule management options and suggest a customizable management method. Furthermore, if the parent is in a hurry, the emotion estimation unit can quickly display only the most important check-up dates to streamline management. In this way, the mobile app can flexibly adjust how the regular check-up schedule is managed according to the parent's emotions, providing a more comfortable user experience.

[0133] The mobile app can also include a data analysis unit. This unit analyzes children's health data and identifies trends in their health status. For example, it can collect data such as a child's body temperature, weight, and height over a long period and visually display changes in their health status using graphs and charts. Furthermore, based on the child's health data, the data analysis unit can predict future health risks and suggest preventative measures. It can also compare a child's health data with data from other children, detecting abnormalities by comparing it against standard growth patterns. This allows the mobile app to continuously monitor a child's health, detect abnormalities early, and take appropriate action.

[0134] The mobile app can also include an emotion estimation unit. This unit estimates the parent's emotions and adjusts the data management method based on the estimated emotions. For example, if the parent is stressed, the emotion estimation unit can provide a simple and intuitive data management screen to reduce the burden of operation. If the parent is relaxed, the emotion estimation unit can provide detailed data management options and suggest a customizable management method. Furthermore, if the parent is in a hurry, the emotion estimation unit can quickly display only the important data to streamline management. In this way, the mobile app can flexibly adjust the data management method according to the parent's emotions, providing a more comfortable user experience.

[0135] The mobile app can also include a immunization information section. This section provides parents with the latest immunization information. For example, it can provide the latest immunization guidelines and recommended schedules, giving parents information to ensure their children receive appropriate vaccinations. It can also provide the latest research findings on the effectiveness and side effects of vaccinations, allowing parents to obtain accurate information about immunization. Furthermore, it can provide information on local immunization campaigns and events, helping parents not miss immunization opportunities. In this way, the mobile app can provide parents with the latest immunization information and support them in protecting their children's health.

[0136] Mobile apps can also be equipped with an emotion estimation unit. This unit estimates the parent's emotions and adjusts the privacy settings based on those emotions. For example, if the parent is stressed, the emotion estimation unit can provide a simple and intuitive privacy settings screen, reducing the burden of operation. If the parent is relaxed, the emotion estimation unit can provide detailed privacy options and suggest customizable settings. Furthermore, if the parent is in a hurry, the emotion estimation unit can quickly configure only the most important privacy items, streamlining the process. In this way, mobile apps can flexibly adjust the privacy settings according to the parent's emotions, providing a more comfortable user experience.

[0137] The following briefly describes the processing flow for example form 2.

[0138] Step 1: The reception desk enters the child's birthday and health information. The reception desk provides an interface for parents to enter their child's birthday and health information into the app. For example, it uses text input fields and dropdown menus to make it easy to enter information. It also has a voice input function, allowing parents to enter information by voice. Step 2: The scheduling unit creates an optimal vaccination schedule based on the information entered by the reception unit. The scheduling unit uses AI to calculate the timing of vaccinations based on the child's age and health condition. Furthermore, it can create an optimal vaccination schedule based on medical guidelines and provide an individually optimized schedule that takes into account the child's genetic information and family medical history. Step 3: The notification unit sends reminder notifications based on the schedule created by the schedule creation unit. The notification unit sends a reminder notification the day before the vaccination. Notification methods include in-app notifications, email, and SMS, and can be customized according to the parent's preferences. Step 4: The reservation department makes vaccination appointments based on the schedule created by the schedule creation department. The reservation department automatically makes reservations while checking the availability of local hospitals and clinics. It uses an API to connect with hospital reservation systems and check availability in real time. It also provides an easy-to-use interface for parents to make reservations manually.

[0139] 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.

[0140] 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.

[0141] 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.

[0142] Each of the multiple elements described above, including the reception unit, schedule creation unit, notification unit, reservation unit, provision unit, chatbot unit, management unit, and protection unit, is implemented by, for example, at least one of the smart device 14 and the data processing unit 12. For example, the reception unit is implemented by the control unit 46A of the smart device 14 and provides an interface for parents to input their child's birthday and health information. The schedule creation unit is implemented by, for example, the specific processing unit 290 of the data processing unit 12 and uses AI to create an optimal vaccination schedule. The notification unit is implemented by, for example, the control unit 46A of the smart device 14 and sends reminder notifications. The reservation unit is implemented by, for example, the specific processing unit 290 of the data processing unit 12 and automatically makes reservations while checking the availability of local hospitals and clinics. The provision unit is implemented by, for example, the control unit 46A of the smart device 14 and provides a community space where parents can interact with each other. The chatbot unit is implemented by, for example, the specific processing unit 290 of the data processing unit 12 and answers questions about childcare in real time. The management unit is implemented, for example, by the specific processing unit 290 of the data processing device 12, and manages the regular health check schedule and growth checklist. The protection unit is implemented, for example, by the specific processing unit 290 of the data processing device 12, and performs data management and privacy protection. The correspondence between each unit and the device or control unit is not limited to the examples described above, and various changes are possible.

[0143] [Second Embodiment] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0144] 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.

[0145] 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.

[0146] 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.

[0147] 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.

[0148] 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).

[0149] 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.

[0150] 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.

[0151] 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.

[0152] 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.

[0153] 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.

[0154] 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.).

[0155] 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.

[0156] 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.

[0157] 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.

[0158] Each of the multiple elements described above, including the reception unit, schedule creation unit, notification unit, reservation unit, provision unit, chatbot unit, management unit, and protection unit, is implemented by, for example, at least one of the smart glasses 214 and the data processing unit 12. For example, the reception unit is implemented by the control unit 46A of the smart glasses 214 and provides an interface for parents to input their child's birthday and health information. The schedule creation unit is implemented by, for example, the specific processing unit 290 of the data processing unit 12 and uses AI to create an optimal vaccination schedule. The notification unit is implemented by, for example, the control unit 46A of the smart glasses 214 and sends reminder notifications. The reservation unit is implemented by, for example, the specific processing unit 290 of the data processing unit 12 and automatically makes reservations while checking the availability of local hospitals and clinics. The provision unit is implemented by, for example, the control unit 46A of the smart glasses 214 and provides a community space where parents can interact with each other. The chatbot unit is implemented by, for example, the specific processing unit 290 of the data processing unit 12 and answers questions about childcare in real time. The management unit is implemented, for example, by the specific processing unit 290 of the data processing device 12, and manages the regular health check schedule and growth checklist. The protection unit is implemented, for example, by the specific processing unit 290 of the data processing device 12, and performs data management and privacy protection. The correspondence between each unit and the device or control unit is not limited to the examples described above, and various changes are possible.

[0159] [Third Embodiment] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0160] 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.

[0161] 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.

[0162] 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.

[0163] 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.

[0164] 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).

[0165] 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.

[0166] 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.

[0167] 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.

[0168] 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.

[0169] 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.

[0170] 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.).

[0171] 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.

[0172] 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.

[0173] 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.

[0174] Each of the multiple elements described above, including the reception unit, schedule creation unit, notification unit, reservation unit, provision unit, chatbot unit, management unit, and protection unit, is implemented by, for example, at least one of the headset terminal 314 and the data processing unit 12. For example, the reception unit is implemented by the control unit 46A of the headset terminal 314 and provides an interface for parents to input their child's birthday and health information. The schedule creation unit is implemented by, for example, the specific processing unit 290 of the data processing unit 12 and uses AI to create an optimal vaccination schedule. The notification unit is implemented by, for example, the control unit 46A of the headset terminal 314 and sends reminder notifications. The reservation unit is implemented by, for example, the specific processing unit 290 of the data processing unit 12 and automatically makes reservations while checking the availability of local hospitals and clinics. The provision unit is implemented by, for example, the control unit 46A of the headset terminal 314 and provides a community space where parents can interact with each other. The chatbot unit is implemented by, for example, the specific processing unit 290 of the data processing unit 12 and answers questions about childcare in real time. The management unit is implemented, for example, by the specific processing unit 290 of the data processing device 12, and manages the regular health check schedule and growth checklist. The protection unit is implemented, for example, by the specific processing unit 290 of the data processing device 12, and performs data management and privacy protection. The correspondence between each unit and the device or control unit is not limited to the examples described above, and various changes are possible.

[0175] [Fourth Embodiment] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0176] 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.

[0177] 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.

[0178] 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.

[0179] 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.

[0180] 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).

[0181] 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.

[0182] 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.

[0183] 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.

[0184] 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.

[0185] 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.

[0186] 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.

[0187] 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.).

[0188] 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.

[0189] 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.

[0190] 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.

[0191] Each of the multiple elements described above, including the reception unit, schedule creation unit, notification unit, reservation unit, provision unit, chatbot unit, management unit, and protection unit, is implemented by, for example, at least one of the robot 414 and the data processing unit 12. For example, the reception unit is implemented by the control unit 46A of the robot 414 and provides an interface for parents to input their child's birthday and health information. The schedule creation unit is implemented by, for example, the specific processing unit 290 of the data processing unit 12 and uses AI to create an optimal vaccination schedule. The notification unit is implemented by, for example, the control unit 46A of the robot 414 and sends reminder notifications. The reservation unit is implemented by, for example, the specific processing unit 290 of the data processing unit 12 and automatically makes reservations while checking the availability of local hospitals and clinics. The provision unit is implemented by, for example, the control unit 46A of the robot 414 and provides a community space where parents can interact with each other. The chatbot unit is implemented by, for example, the specific processing unit 290 of the data processing unit 12 and answers questions about childcare in real time. The management unit is implemented, for example, by the specific processing unit 290 of the data processing device 12, and manages the regular health check schedule and growth checklist. The protection unit is implemented, for example, by the specific processing unit 290 of the data processing device 12, and performs data management and privacy protection. The correspondence between each unit and the device or control unit is not limited to the examples described above, and various changes are possible.

[0192] 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.

[0193] 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.

[0194] 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.

[0195] 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.

[0196] 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.

[0197] 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."

[0198] 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.

[0199] 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.

[0200] 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.

[0201] 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.

[0202] 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.

[0203] 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.

[0204] 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.

[0205] 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.

[0206] 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.

[0207] 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.

[0208] 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.

[0209] 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.

[0210] (Note 1) A reception area where you enter your child's birthday and health information, A schedule creation unit creates an optimal vaccination schedule based on the information entered by the reception unit, A notification unit that sends reminder notifications based on the schedule created by the aforementioned schedule creation unit, The system includes a reservation unit that makes reservations for vaccinations based on the schedule created by the aforementioned schedule creation unit. A system characterized by the following features. (Note 2) The aforementioned schedule creation unit, Vaccination schedules are created considering the child's genetic information, place of residence, and family medical history. The system described in Appendix 1, characterized by the features described herein. (Note 3) The aforementioned reservation section is, The system automatically makes reservations while checking the availability of local hospitals and clinics. The system described in Appendix 1, characterized by the features described herein. (Note 4) It includes a section that provides a community space where parents can interact with each other. The system described in Appendix 1, characterized by the features described herein. (Note 5) It includes a chatbot section that answers questions about childcare. The system described in Appendix 1, characterized by the features described herein. (Note 6) The facility includes a management department that manages regular health checkup schedules and developmental checklists tailored to children's growth. The system described in Appendix 1, characterized by the features described herein. (Note 7) It includes a protection unit for data management and privacy protection. The system described in Appendix 1, characterized by the features described herein. (Note 8) The aforementioned reception unit is It estimates the parent's emotions and adjusts the input interface design based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 9) The aforementioned reception unit is When entering a child's health information, past input history can be referenced to reduce the effort required for data entry. The system described in Appendix 1, characterized by the features described herein. (Note 10) The aforementioned reception unit is The system verifies the accuracy of the entered information in real time and prompts for corrections as needed. The system described in Appendix 1, characterized by the features described herein. (Note 11) The aforementioned reception unit is The system estimates the parent's emotions and prioritizes inputs based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 12) The aforementioned reception unit is During input, relevant health information is automatically completed, taking into account the parent's geographical location. The system described in Appendix 1, characterized by the features described herein. (Note 13) The aforementioned reception unit is During input, the system analyzes the parent's social media activity and suggests relevant health information. The system described in Appendix 1, characterized by the features described herein. (Note 14) The aforementioned schedule creation unit, The system estimates the parents' emotions and adjusts the way the schedule is presented based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 15) The aforementioned schedule creation unit, When creating a schedule, we refer to past vaccination data to suggest the optimal schedule. The system described in Appendix 1, characterized by the features described herein. (Note 16) The aforementioned schedule creation unit, When creating a schedule, select the optimal vaccination timing based on the child's daily routine. The system described in Appendix 1, characterized by the features described herein. (Note 17) The aforementioned schedule creation unit, It estimates the parents' emotions and prioritizes the schedule based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 18) The aforementioned schedule creation unit, When creating a vaccination schedule, we will suggest the most suitable vaccination location, taking into account the child's geographical location. The system described in Appendix 1, characterized by the features described herein. (Note 19) The aforementioned schedule creation unit, When creating a schedule, we analyze the child's social media activity and suggest relevant vaccination information. The system described in Appendix 1, characterized by the features described herein. (Note 20) The aforementioned notification unit, It estimates the parent's emotions and adjusts the timing of notifications based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 21) The aforementioned notification unit, When sending a notification, the system will refer to past notification history to select the most suitable notification method. The system described in Appendix 1, characterized by the features described herein. (Note 22) The aforementioned notification unit, When sending a notification, the system will select the optimal notification timing based on the parent's daily routine. The system described in Appendix 1, characterized by the features described herein. (Note 23) The aforementioned notification unit, The system estimates the parents' emotions and prioritizes notifications based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 24) The aforementioned notification unit, When sending notifications, the system will select the most appropriate notification method, taking into account the parent's geographical location. The system described in Appendix 1, characterized by the features described herein. (Note 25) The aforementioned notification unit, When sending notifications, we analyze the parents' social media activity and suggest relevant notification information. The system described in Appendix 1, characterized by the features described herein. (Note 26) The aforementioned reservation section is, We estimate the parents' emotions and adjust the way we present reservations based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 27) The aforementioned reservation section is, When making a reservation, the system will refer to your past reservation history to select the most suitable reservation method. The system described in Appendix 1, characterized by the features described herein. (Note 28) The aforementioned reservation section is, When making a reservation, the optimal reservation timing is selected based on the child's daily routine. The system described in Appendix 1, characterized by the features described herein. (Note 29) The aforementioned reservation section is, The system estimates the parents' emotions and prioritizes reservations based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 30) The aforementioned reservation section is, When making a reservation, we will suggest the most suitable reservation location considering the guardian's geographical location. The system described in Appendix 1, characterized by the features described herein. (Note 31) The aforementioned reservation section is, When you make a reservation, we analyze your social media activity and suggest relevant reservation information. The system described in Appendix 1, characterized by the features described herein. (Note 32) The aforementioned supply unit is, Estimate the emotions of parents and adjust the design of community spaces based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 33) The aforementioned supply unit is, We analyze the history of interactions in community spaces and propose the most suitable methods of interaction. The system described in Appendix 1, characterized by the features described herein. (Note 34) The aforementioned supply unit is, It estimates the emotions of parents and determines the priority of interactions based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 35) The aforementioned supply unit is, When suggesting the most suitable interaction method for parents in community spaces, we take their geographical location into consideration. The system described in Appendix 1, characterized by the features described herein. (Note 36) The aforementioned chatbot section is The system estimates the parent's emotions and adjusts the way the response is expressed based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 37) The aforementioned chatbot section is When the chatbot responds, it refers to past question history to provide the most appropriate answer. The system described in Appendix 1, characterized by the features described herein. (Note 38) The aforementioned chatbot section is The system estimates the parents' emotions and prioritizes responses based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 39) The aforementioned chatbot section is When the chatbot responds, it takes into account the parent's geographical location to provide the most appropriate answer. The system described in Appendix 1, characterized by the features described herein. (Note 40) The aforementioned management department, It estimates the emotions of parents and adjusts the design of the management screen based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 41) The aforementioned management department, During management, we refer to past management history to propose the optimal management method. The system described in Appendix 1, characterized by the features described herein. (Note 42) The aforementioned management department, Estimate the emotions of parents and determine management priorities based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 43) The aforementioned management department, When managing the system, we propose the optimal management method considering the geographical location information of the guardians. The system described in Appendix 1, characterized by the features described herein. (Note 44) The aforementioned protective part is We estimate the feelings of parents and adjust privacy protection methods based on those estimated feelings. The system described in Appendix 1, characterized by the features described herein. (Note 45) The aforementioned protective part is When protecting data, we refer to past protection history to suggest the optimal protection method. The system described in Appendix 1, characterized by the features described herein. (Note 46) The aforementioned protective part is The system estimates the emotions of the guardians and determines the priority of protection based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 47) The aforementioned protective part is When protecting data, we propose the optimal protection method considering the parent's geographical location. The system described in Appendix 1, characterized by the features described herein. (Note 48) The aforementioned protective part is When protecting data, we analyze parents' social media activity and suggest relevant protection information. The system described in Appendix 1, characterized by the features described herein. [Explanation of Symbols]

[0211] 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 reception area where you enter your child's birthday and health information, A schedule creation unit creates an optimal vaccination schedule based on the information entered by the reception unit, A notification unit that sends reminder notifications based on the schedule created by the aforementioned schedule creation unit, The system includes a reservation unit that makes reservations for vaccinations based on the schedule created by the aforementioned schedule creation unit. A system characterized by the following features.

2. The aforementioned schedule creation unit, Vaccination schedules are created considering the child's genetic information, place of residence, and family medical history. The system according to feature 1.

3. The aforementioned reservation section is, The system automatically makes reservations while checking the availability of local hospitals and clinics. The system according to feature 1.

4. It includes a section that provides a community space where parents can interact with each other. The system according to feature 1.

5. It includes a chatbot section that answers questions about childcare. The system according to feature 1.

6. The facility includes a management department that manages regular health checkup schedules and developmental checklists tailored to children's growth. The system according to feature 1.

7. It includes a protection unit for data management and privacy protection. The system according to feature 1.

8. The aforementioned reception unit is It estimates the parent's emotions and adjusts the input interface design based on those estimated emotions. The system according to feature 1.

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