system

Abstract

The system according to this embodiment aims to enable single parents to efficiently create childcare plans according to their baby's age in months and to remind supporters at the appropriate time. [Solution] The system according to the embodiment comprises a reception unit, a generation unit, a management unit, a reminder unit, and a consultation unit. The reception unit inputs information about the baby's age in months. The generation unit analyzes the information input by the reception unit and creates a childcare plan. The management unit manages the schedule based on the childcare plan created by the generation unit. The reminder unit sends reminders to supporters at appropriate times based on the schedule managed by the management unit. The consultation unit provides consultation to supporters who have been reminded by the reminder 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 character of the chatbot, 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, there is a problem that it is difficult for a single parent to efficiently create a childcare plan according to the baby's monthly age and remind the supporter at an appropriate timing.

[0005] The system according to the embodiment aims to enable a single parent to efficiently create a childcare plan according to the baby's monthly age and remind the supporter at an appropriate timing.

Means for Solving the Problems

[0006] The system according to this embodiment comprises a reception unit, a generation unit, a management unit, a reminder unit, and a consultation unit. The reception unit inputs information about the baby's age in months. The generation unit analyzes the information input by the reception unit and creates a childcare plan. The management unit manages the schedule based on the childcare plan created by the generation unit. The reminder unit sends reminders to supporters at appropriate times based on the schedule managed by the management unit. The consultation unit provides consultation to supporters who have been reminded by the reminder unit. [Effects of the Invention]

[0007] The system according to this embodiment allows single parents to efficiently create childcare plans according to their baby's age in months and to remind supporters at the appropriate time. [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 manages communication between multiple computers. Examples of communication standards applicable to the communication I / F include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

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

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

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

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

[0019] The smart device 14 comprises a computer 36, a reception 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 reception 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 childcare support system according to an embodiment of the present invention is a system that uses a generating AI to automatically create a childcare plan tailored to the age of a baby born to a single parent. This childcare support system takes information about the baby's age as input, and the generating AI analyzes this information to create a childcare plan. This childcare plan includes schedules for meals, sleep, play, and health checks. Furthermore, the childcare support system can remind caregivers at appropriate times and provide consultation as needed. This mechanism allows single parents to receive support to help their babies grow. For example, when inputting information about the baby's age, it is only necessary to input the baby's date of birth and current age. For example, "The baby's date of birth is January 1, 2023" is entered. This information is input into the generating AI. Next, the generating AI analyzes the input information and automatically creates a childcare plan tailored to the baby's age. The generating AI calculates the optimal childcare plan according to the baby's age and creates a schedule based on that plan. For example, if the baby is 6 months old, the generating AI creates a schedule for meals, sleep, play, and health checks that is suitable for a 6-month-old baby. The created childcare plan includes schedules for meals, sleep, playtime, and health checks. For example, the meal schedule specifies what the baby should eat and when. The sleep schedule specifies when the baby should sleep. The playtime schedule specifies what kind of play the baby should do and when. The health check schedule specifies when the baby should have health checks. Furthermore, the childcare support system provides reminders at appropriate times. For example, when mealtime approaches, the childcare support system will remind the supporter, "It's time for the baby's meal." Similarly, when health check time approaches, the childcare support system will remind the supporter, "It's time for the baby's health check." The childcare support system can also provide consultation to supporters as needed. For example, if a supporter asks, "My baby cries at night, what should I do?", the childcare support system will provide appropriate advice.In this way, the childcare support system provides support to single parents in raising their babies. This system reduces the burden of childcare for single parents and allows them to support their babies' development. For example, by managing the baby's feeding and sleep schedule, the baby's health can be maintained. Also, by sending reminders to supporters at appropriate times, childcare schedules can be followed without being forgotten. Furthermore, the childcare support system can help resolve childcare-related worries by providing consultation to supporters. In this way, the childcare support system can provide support to single parents in raising their babies.

[0029] The childcare support system according to this embodiment comprises a reception unit, a generation unit, a management unit, a reminder unit, and a consultation unit. The reception unit inputs information about the baby's age in months. This information includes, but is not limited to, the date of birth, weight, and height. For example, the reception unit can calculate the baby's age in months by inputting the baby's date of birth. The reception unit can also input information such as the baby's weight and height. The generation unit uses a generation AI to analyze the information input by the reception unit and create a childcare plan. For example, the generation unit calculates an optimal childcare plan according to the baby's age in months and creates a schedule based on that plan. For example, if the baby is 6 months old, the generation unit creates a schedule for meals, sleep, play, and health checks suitable for a 6-month-old baby. The generation unit can use a generation AI to calculate an optimal childcare plan according to the baby's age in months. The management unit manages the schedule based on the childcare plan created by the generation unit. For example, the management unit manages the schedule for meals, sleep, play, and health checks based on the created childcare plan. The management department manages schedules such as: the meal schedule, which specifies what the baby should eat and when; the sleep schedule, which specifies when the baby should sleep; the play schedule, which specifies what kind of play the baby should do and when; and the health check schedule, which specifies when the baby should have a health check. The reminder department reminds caregivers at appropriate times based on the schedules managed by the management department. For example, when mealtime is approaching, the reminder department will remind caregivers with "It's time for the baby's meal." Similarly, when health check time is approaching, the reminder department will remind caregivers with "It's time for the baby's health check." The reminder department can remind caregivers at appropriate times. The consultation department provides consultation to caregivers who have been reminded by the reminder department. For example, if a caregiver asks, "My baby cries at night, what should I do?", the consultation department will provide appropriate advice. The consultation department can provide consultation to caregivers.As a result, the childcare support system according to this embodiment can automatically create a childcare plan according to the baby's age in months, manage the schedule, send reminders to caregivers at appropriate times, and provide consultation.

[0030] The reception desk inputs information about the baby's age in months. This information includes, but is not limited to, the date of birth, weight, and height. For example, the reception desk can calculate the baby's age in months by inputting the baby's date of birth. The reception desk can also input information such as the baby's weight and height. Specifically, the reception desk provides a field for inputting the baby's date of birth through the user interface. When the user enters the baby's date of birth, the system automatically calculates the baby's age in months by comparing it to the current date. In addition, input fields for weight and height are also provided, and this data is used for growth tracking and health management. For example, by regularly recording weight changes and height growth, the baby's growth pattern can be understood, and any abnormalities can be detected early. The reception desk can centrally manage this information and share data in cooperation with other departments. For example, the entered data is stored in a database accessible to the generation and management departments and used for creating childcare plans and managing schedules. This allows the reception department to accurately and efficiently collect basic information about babies and support the overall operation of the system.

[0031] The generation unit uses a generation AI to analyze information entered by the reception unit and create a childcare plan. For example, the generation unit calculates the optimal childcare plan based on the baby's age in months and creates a schedule based on that plan. Specifically, the generation AI receives data such as the baby's age in months, weight, and height as input, and generates the optimal childcare plan based on past data and expert knowledge. For example, if the baby is 6 months old, it will create a schedule for meals, sleep, play, and health checks that is suitable for a 6-month-old baby. The generation AI considers the nutritional balance and sleep patterns according to the baby's developmental stage and provides an individually customized plan. For example, the meal schedule includes when to start solid foods and how to choose appropriate ingredients, and the sleep schedule includes nap times and nighttime sleep times. The play schedule includes the types and duration of play according to the developmental stage, and the health check schedule includes the timing of regular health checkups and vaccinations. Based on this information, the generation unit provides a comprehensive childcare plan to support the baby's growth. Furthermore, the generation unit can utilize the learning function of the generation AI to improve the accuracy of the plan based on user feedback. This allows the generation unit to constantly provide optimal childcare plans incorporating the latest information and technology, thereby reducing the burden on caregivers.

[0032] The management department manages schedules based on the childcare plans created by the generation department. For example, the management department manages schedules for meals, sleep, play, and health checks based on the created childcare plans. Specifically, the management department receives the childcare plans provided by the generation department and sets detailed schedules for each item. For example, the meal schedule includes what the baby should eat and when. Specifically, it details the times for breakfast, lunch, and dinner, as well as the timing of snacks and the types and amounts of food. The sleep schedule includes when the baby should sleep. Specifically, it sets the times for naps, nighttime bedtime, and wake-up time, and includes advice on how to regulate the baby's sleep rhythm. The play schedule includes what kind of play the baby should do and when. Specifically, it details the types and duration of play according to the developmental stage, as well as the content and methods of play. The health check schedule includes when the baby should receive health checks. Specifically, it includes the timing of regular health checkups and vaccinations, and how to perform health checks at home. The management department centrally manages these schedules and makes them easily accessible to support staff. For example, caregivers can check schedules and make changes or adjustments as needed through smartphone apps or web portals. This allows the management department to efficiently manage the baby's care plan and reduce the burden on caregivers.

[0033] The Reminders Department sends reminders to caregivers at appropriate times based on the schedule managed by the Management Department. For example, when mealtime approaches, the Reminders Department will remind caregivers with "It's time for your baby's meal." Similarly, when health check time approaches, the Reminders Department will remind caregivers with "It's time for your baby's health check." Specifically, the Reminders Department monitors the timing of each event based on the schedule information provided by the Management Department and sends notifications at the appropriate time. For example, when mealtime approaches, it will remind caregivers via smartphone push notifications or voice alerts. Similarly, when health check time approaches, it will send a notification to encourage caregivers to remember to perform the health check. The Reminders Department can customize the notification method and timing, allowing for flexible responses to caregivers' lifestyles and preferences. For example, by allowing caregivers to select the frequency, volume, and method of notification (push notifications, email, SMS, etc.), more effective reminders can be achieved. Furthermore, the Reminders Department can collect feedback from caregivers and continuously improve the accuracy and timing of notifications. This allows the reminder function to support caregivers in ensuring they adhere to the baby's childcare schedule, thereby reducing the burden of childcare.

[0034] The Consultation Department provides support to caregivers who have been reminded by the Reminder Department. For example, if a caregiver asks, "My baby cries at night, what should I do?", the Consultation Department will provide appropriate advice. Specifically, the Consultation Department receives the caregiver's inquiry and provides the best possible advice based on expert knowledge and past data. For example, in the case of a consultation about nighttime crying, the department will check the baby's sleep environment, daytime activity level, and diet, and suggest areas for improvement. The Consultation Department can also provide expert advice and reference information to address caregivers' parenting concerns and questions. For example, it can provide a wide range of parenting information, such as how to introduce solid foods, vaccination schedules, and play methods appropriate for developmental stages. The Consultation Department plays a role in providing appropriate support so that caregivers can raise their children with peace of mind. Furthermore, the Consultation Department can continuously improve the accuracy and content of the advice it provides based on feedback from caregivers. For example, by recording how caregivers reacted to the advice provided and using this information in future consultations, the department can provide more individually customized support. This will enable the consultation department to respond quickly and appropriately to the childcare concerns and questions that supporters have, thereby improving the quality of childcare.

[0035] The generation unit can calculate the optimal childcare plan according to the baby's age in months and create a schedule based on that plan. For example, if the baby is 6 months old, the generation unit will create a schedule for meals, sleep, playtime, and health checks that is suitable for a 6-month-old baby. The generation unit can calculate the optimal childcare plan according to the baby's age in months using generation AI. This improves the efficiency of childcare by calculating the optimal childcare plan according to the baby's age and creating a schedule.

[0036] The management department can manage schedules for meals, sleep, playtime, and health checks based on the created childcare plan. For example, the management department manages schedules for meals, sleep, playtime, and health checks based on the created childcare plan. For example, the meal schedule includes what the baby should eat and when. The sleep schedule includes what the baby should sleep at. The playtime schedule includes what kind of play the baby should do and when. The health check schedule includes what time the baby should have a health check. This makes childcare schedule management easier by managing schedules for meals, sleep, playtime, and health checks. Some or all of the above processes in the management department may be performed using AI, for example, or not using AI. For example, the management department can manage schedules for meals, sleep, playtime, and health checks based on the created childcare plan using an AI model.

[0037] The reminder unit can remind caregivers with a message like "It's time for the baby's meal" when mealtime is approaching. The reminder unit can send reminders to caregivers at the appropriate time. This allows caregivers to manage mealtimes without forgetting by sending reminders when mealtime is approaching. Some or all of the above processing in the reminder unit may be performed using AI, for example, or not using AI. For example, the reminder unit can use an AI model to detect when mealtime is approaching and send a reminder to the caregiver.

[0038] The reminder unit can remind caregivers with a message such as "It's time for your baby's health check" when the time for the health check is approaching. The reminder unit can send reminders to caregivers at the appropriate time. This ensures that caregivers remember to take care of the health check by sending reminders when the time is approaching. Some or all of the above processing in the reminder unit may be performed using AI, for example, or not using AI. For example, the reminder unit can use an AI model to detect when the time for the health check is approaching and send a reminder to the caregiver.

[0039] The consultation department can provide appropriate advice when a supporter asks, for example, "My baby cries at night, what should I do?" The consultation department can provide appropriate advice when a supporter asks, for example, "My baby cries at night, what should I do?" The consultation department can listen to the supporter's concerns. In this way, by providing appropriate advice when a supporter asks for help, it is possible to resolve their worries about childcare. Some or all of the above processing in the consultation department may be performed using AI, for example, or not using AI. For example, the consultation department can input the supporter's consultation content into an AI model and have the AI ​​model output appropriate advice.

[0040] The reception desk can analyze the baby's past health data and select the optimal information input method. For example, the reception desk can select the most effective information input method from the baby's past health data. For example, the reception desk can propose an information input method suitable for the caregiver based on the baby's health data. For example, the reception desk can analyze the baby's health data and select the information input method that is easiest for the caregiver to understand. In this way, the optimal information input method can be selected by analyzing the baby's past health data. Some or all of the above processes in the reception desk may be performed using AI, for example, or without AI. For example, the reception desk can input the baby's health data into a generating AI and have the generating AI select the optimal information input method.

[0041] The reception unit can filter information based on the supporter's current living situation and areas of interest during input. For example, the reception unit inputs only the necessary information based on the supporter's current living situation. For example, the reception unit inputs only the relevant information based on the supporter's areas of interest. For example, the reception unit selects the most relevant information based on the supporter's living situation and areas of interest. This allows only the necessary information to be input by filtering the information based on the supporter's living situation and areas of interest. Some or all of the above processing in the reception unit may be performed using AI, for example, or without AI. For example, the reception unit can input data on the supporter's living situation and areas of interest into a generating AI and have the generating AI perform the information filtering.

[0042] The reception desk can prioritize inputting highly relevant information by considering the geographical location of the supporter when entering information. For example, the reception desk can prioritize inputting information about nearby medical institutions based on the supporter's geographical location. For example, the reception desk can prioritize inputting information about local childcare support services based on the supporter's geographical location. For example, the reception desk can prioritize inputting information about local events based on the supporter's geographical location. In this way, by prioritizing the input of highly relevant information based on the supporter's geographical location, the reception desk can provide supporters with useful 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 input the supporter's geographical location into a generating AI and have the generating AI select highly relevant information.

[0043] The reception desk can analyze the supporter's social media activity and input relevant information when entering data. For example, the reception desk can analyze the supporter's social media activity and input relevant childcare information. For example, the reception desk can analyze the supporter's social media activity and input information about childcare groups of interest. For example, the reception desk can analyze the supporter's social media activity and input relevant event information. In this way, relevant information can be entered by analyzing the supporter's social media activity. 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 input the supporter's social media activity data into a generating AI and have the generating AI select relevant information.

[0044] The generation unit can adjust the level of detail in the childcare plan based on the baby's health condition when generating the plan. For example, if the baby's health is good, the generation unit generates a detailed childcare plan. For example, if the baby's health is unstable, the generation unit generates a simplified childcare plan. For example, the generation unit generates a childcare plan with an appropriate level of detail depending on the baby's health condition. This allows for the provision of an appropriate childcare plan by adjusting the level of detail according to the baby's health condition. Some or all of the above processing in the generation unit may be performed using AI, for example, or without AI. For example, the generation unit can input the baby's health data into a generation AI and have the generation AI perform the adjustment of the plan's level of detail.

[0045] The generation unit can apply different plan generation algorithms depending on the baby's developmental stage when generating a childcare plan. For example, the generation unit applies an appropriate childcare plan generation algorithm depending on the baby's developmental stage. For example, the generation unit selects a different childcare plan generation algorithm depending on the baby's developmental stage. For example, the generation unit applies the optimal childcare plan generation algorithm depending on the baby's developmental stage. By applying different plan generation algorithms depending on the baby's developmental stage, it is possible to provide an appropriate childcare plan that is appropriate for the baby's growth. Some or all of the above-described processes in the generation unit may be performed using AI, for example, or without using AI. For example, the generation unit can input the baby's growth data into a generation AI and have the generation AI execute the application of the plan generation algorithm.

[0046] The generation unit can determine the priority of childcare plans based on the baby's date of birth when generating childcare plans. For example, the generation unit determines the priority of childcare plans based on the baby's date of birth. For example, the generation unit generates important childcare plans preferentially based on the baby's date of birth. For example, the generation unit determines the priority of appropriate childcare plans based on the baby's date of birth. This allows important plans to be provided preferentially by determining the priority of plans based on the baby's date of birth. Some or all of the above processing in the generation unit may be performed using AI, for example, or without AI. For example, the generation unit can input the baby's date of birth data into a generation AI and have the generation AI perform the determination of plan priorities.

[0047] The generation unit can adjust the order of childcare plans based on relevant data about the baby when generating childcare plans. For example, the generation unit adjusts the order of childcare plans based on relevant data about the baby. For example, the generation unit prioritizes generating important childcare plans based on relevant data about the baby. For example, the generation unit adjusts the order of appropriate childcare plans based on relevant data about the baby. This allows the childcare plans to be provided in the appropriate order by adjusting the order of plans based on relevant data about the baby. Some or all of the above processing in the generation unit may be performed using AI, for example, or without AI. For example, the generation unit can input relevant data about the baby into a generation AI and have the generation AI perform the adjustment of the order of plans.

[0048] The management department can improve the accuracy of the schedule by referring to the baby's health data when managing the schedule. For example, the management department can improve the accuracy of the schedule by referring to the baby's health data. For example, the management department can create an optimal schedule based on the baby's health data. For example, the management department can improve the accuracy of the schedule by analyzing the baby's health data. In this way, the accuracy of the schedule can be improved by referring to the baby's health data. Some or all of the above processes in the management department may be performed using AI, for example, or without using AI. For example, the management department can input the baby's health data into a generating AI and have the generating AI perform the schedule accuracy improvement.

[0049] The management department can customize schedules according to the supporter's daily rhythm when managing schedules. For example, the management department customizes the schedule according to the supporter's daily rhythm. For example, the management department creates an optimal schedule based on the supporter's daily rhythm. For example, the management department customizes the schedule taking the supporter's daily rhythm into consideration. This allows the management department to provide the supporter with an optimal schedule by customizing the schedule according to the supporter's daily rhythm. 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 input the supporter's daily rhythm data into a generating AI and have the generating AI perform schedule customization.

[0050] The management department can select the optimal schedule by considering the geographical location information of the supporters when managing schedules. For example, the management department selects the optimal schedule based on the geographical location information of the supporters. For example, the management department customizes the schedule by considering the geographical location information of the supporters. For example, the management department prioritizes important schedules based on the geographical location information of the supporters. This allows the management department to provide supporters with a beneficial schedule by selecting the optimal schedule based on their geographical location information. Some or all of the above processes in the management department may be performed using AI, for example, or not using AI. For example, the management department can input the geographical location information of the supporters into a generating AI and have the generating AI perform the selection of the optimal schedule.

[0051] The management department can analyze supporters' social media activity and adjust schedules accordingly. For example, the management department can analyze supporters' social media activity and create an optimal schedule. For example, the management department can customize schedules based on supporters' social media activity. For example, the management department can adjust schedules taking supporters' social media activity into consideration. This allows the management department to provide an optimal schedule by analyzing supporters' social media activity. Some or all of the above processes in the management department may be performed using AI, for example, or not. For example, the management department can input supporter social media activity data into a generating AI and have the generating AI perform schedule adjustments.

[0052] The reminder unit can optimize the timing of reminders by referring to the baby's health data. For example, the reminder unit can determine the optimal reminder timing by referring to the baby's health data. For example, the reminder unit can adjust the timing of reminders based on the baby's health data. For example, the reminder unit can optimize the timing of reminders by analyzing the baby's health data. In this way, the timing of reminders can be optimized by referring to the baby's health data. Some or all of the above processes in the reminder unit may be performed using AI, for example, or without using AI. For example, the reminder unit can input the baby's health data into a generating AI and have the generating AI perform the optimization of the reminder timing.

[0053] The reminder unit can customize the content of reminders according to the caregiver's daily routine. For example, the reminder unit customizes the content of reminders according to the caregiver's daily routine. For example, the reminder unit provides optimal reminder content based on the caregiver's daily routine. For example, the reminder unit adjusts the content of reminders considering the caregiver's daily routine. By customizing the content of reminders according to the caregiver's daily routine, the system can provide the caregiver with the most suitable reminder. Some or all of the above processing in the reminder unit may be performed using AI, for example, or without AI. For example, the reminder unit can input the caregiver's daily routine data into a generating AI and have the generating AI perform the customization of the reminder content.

[0054] The reminder unit can select the optimal reminder method when sending a reminder, taking into account the geographical location information of the supporter. For example, the reminder unit selects the optimal reminder method based on the geographical location information of the supporter. For example, the reminder unit adjusts the content of the reminder, taking into account the geographical location information of the supporter. For example, the reminder unit prioritizes important reminders based on the geographical location information of the supporter. In this way, by selecting the optimal reminder method based on the geographical location information of the supporter, it is possible to provide helpful reminders to the supporter. Some or all of the above processing in the reminder unit may be performed using AI, for example, or without using AI. For example, the reminder unit can input the geographical location information of the supporter into a generating AI and have the generating AI select the optimal reminder method.

[0055] The reminder unit can analyze the supporter's social media activity and adjust the content of the reminder at the time of sending a reminder. For example, the reminder unit analyzes the supporter's social media activity and provides the most appropriate reminder content. For example, the reminder unit customizes the content of the reminder based on the supporter's social media activity. For example, the reminder unit adjusts the content of the reminder taking the supporter's social media activity into consideration. This allows the system to provide the most appropriate reminder content by analyzing the supporter's social media activity. Some or all of the above processing in the reminder unit may be performed using AI, for example, or without AI. For example, the reminder unit can input the supporter's social media activity data into a generating AI and have the generating AI adjust the reminder content.

[0056] The consultation department can provide optimal advice by referring to the baby's health data when providing consultation. For example, the consultation department can provide optimal advice by referring to the baby's health data. For example, the consultation department can provide advice suitable for the supporter based on the baby's health data. For example, the consultation department can provide optimal advice by analyzing the baby's health data. In this way, optimal advice can be provided by referring to the baby's health data. Some or all of the above processes in the consultation department may be performed using AI, for example, or without using AI. For example, the consultation department can input the baby's health data into a generating AI and have the generating AI perform the task of providing optimal advice.

[0057] The consultation department can customize its response methods when providing consultation by referring to the supporter's past consultation history. For example, the consultation department can refer to the supporter's past consultation history to provide the optimal response method. For example, the consultation department customizes its response methods based on the supporter's past consultation history. For example, the consultation department analyzes the supporter's past consultation history to provide the optimal response method. In this way, the optimal response method can be provided by referring to the supporter's past consultation history. Some or all of the above processes in the consultation department may be performed using AI, for example, or without AI. For example, the consultation department can input the supporter's past consultation history data into a generating AI and have the generating AI perform the customization of the response method.

[0058] The consultation department can provide optimal advice when handling consultations, taking into account the geographical location of the supporter. For example, the consultation department provides optimal advice based on the supporter's geographical location. For example, the consultation department adjusts the content of the advice considering the supporter's geographical location. For example, the consultation department prioritizes providing important advice based on the supporter's geographical location. In this way, by providing optimal advice based on the supporter's geographical location, the consultation department can provide advice that is beneficial to the supporter. Some or all of the above processes in the consultation department may be performed using AI, for example, or without AI. For example, the consultation department can input the supporter's geographical location into a generating AI and have the generating AI perform the task of providing optimal advice.

[0059] The consultation department can analyze the social media activity of the supporter and adjust the content of the advice when providing consultation. For example, the consultation department can analyze the supporter's social media activity and provide optimal advice. For example, the consultation department can customize the content of the advice based on the supporter's social media activity. For example, the consultation department can adjust the content of the advice taking into consideration the supporter's social media activity. In this way, by analyzing the supporter's social media activity, it is possible to provide optimal advice. Some or all of the above processes in the consultation department may be performed using AI, for example, or not using AI. For example, the consultation department can input the supporter's social media activity data into a generating AI and have the generating AI perform the adjustment of the advice content.

[0060] The system according to the embodiment is not limited to the example described above, and various modifications are possible, for example, as follows.

[0061] The generation unit can adjust the level of detail in the childcare plan based on the baby's health condition. For example, if the baby is in good health, a detailed childcare plan can be generated. Conversely, if the baby's health is unstable, a simplified childcare plan can be generated. Furthermore, it can generate a childcare plan with an appropriate level of detail depending on the baby's health condition. In this way, by adjusting the level of detail in the plan according to the baby's health condition, an appropriate childcare plan can be provided.

[0062] The management department can customize schedules according to the supporter's daily rhythm. For example, it can customize schedules according to the supporter's daily rhythm. It can also create an optimal schedule based on the supporter's daily rhythm. Furthermore, it can customize schedules while taking the supporter's daily rhythm into consideration. In this way, by customizing schedules according to the supporter's daily rhythm, it is possible to provide the supporter with the most optimal schedule.

[0063] The reception desk can analyze the baby's past health data and select the most suitable information input method. For example, it can select the most effective information input method based on the baby's past health data. It can also suggest an information input method suitable for the caregiver based on the baby's health data. Furthermore, it can analyze the baby's health data and select the information input method that is easiest for the caregiver to understand. In this way, the optimal information input method can be selected by analyzing the baby's past health data.

[0064] The management department can improve the accuracy of schedules by referring to the baby's health data during schedule management. For example, they can improve the accuracy of schedules by referring to the baby's health data. They can also create an optimal schedule based on the baby's health data. Furthermore, they can analyze the baby's health data to improve the accuracy of schedules. In this way, the accuracy of schedules can be improved by referring to the baby's health data.

[0065] The reminder function can customize the content of reminders according to the caregiver's daily routine. For example, it can customize the content of reminders according to the caregiver's daily routine. It can also provide the most appropriate reminder content based on the caregiver's daily routine. Furthermore, it can adjust the content of reminders while taking the caregiver's daily routine into consideration. In this way, by customizing the content of reminders according to the caregiver's daily routine, it can provide the most appropriate reminder for the caregiver.

[0066] The consultation department can customize its response methods when providing consultations by referring to the supporter's past consultation history. For example, it can provide the most suitable response method by referring to the supporter's past consultation history. It can also customize its response methods based on the supporter's past consultation history. Furthermore, it can analyze the supporter's past consultation history and provide the most suitable response method. In this way, it can provide the most suitable response method by referring to the supporter's past consultation history.

[0067] The following briefly describes the processing flow for example form 1.

[0068] Step 1: The reception desk enters information about the baby's age in months. This information includes, for example, the date of birth, weight, and height. The reception desk can calculate the baby's age in months by entering the baby's date of birth. It can also enter information such as the baby's weight and height. Step 2: The generation unit analyzes the information entered by the reception unit and creates a childcare plan. The generation unit uses generation AI to calculate the optimal childcare plan according to the baby's age in months and creates a schedule based on that plan. For example, if the baby is 6 months old, it will create a schedule for meals, sleep, playtime, and health checks that is suitable for a 6-month-old baby. Step 3: The management department manages the schedule based on the childcare plan created by the generation department. The management department manages the schedules for meals, sleep, playtime, and health checks based on the created childcare plan. For example, the meal schedule specifies what the baby should eat and when. The sleep schedule specifies when the baby should sleep. The playtime schedule specifies what kind of play the baby should do and when. The health check schedule specifies when the baby should have health checks. Step 4: The reminder department will send reminders to caregivers at appropriate times based on the schedule managed by the management department. For example, when mealtime is approaching, they will remind caregivers with "It's time for the baby's meal." Also, when it's time for a health check, they will remind caregivers with "It's time for the baby's health check." Step 5: The consultation department provides support to supporters who have been reminded by the reminder department. For example, if a supporter asks, "My baby cries at night, what should I do?", the consultation department provides appropriate advice.

[0069] (Example of form 2) The childcare support system according to an embodiment of the present invention is a system that uses a generating AI to automatically create a childcare plan tailored to the age of a baby born to a single parent. This childcare support system takes information about the baby's age as input, and the generating AI analyzes this information to create a childcare plan. This childcare plan includes schedules for meals, sleep, play, and health checks. Furthermore, the childcare support system can remind caregivers at appropriate times and provide consultation as needed. This mechanism allows single parents to receive support to help their babies grow. For example, when inputting information about the baby's age, it is only necessary to input the baby's date of birth and current age. For example, "The baby's date of birth is January 1, 2023" is entered. This information is input into the generating AI. Next, the generating AI analyzes the input information and automatically creates a childcare plan tailored to the baby's age. The generating AI calculates the optimal childcare plan according to the baby's age and creates a schedule based on that plan. For example, if the baby is 6 months old, the generating AI creates a schedule for meals, sleep, play, and health checks that is suitable for a 6-month-old baby. The created childcare plan includes schedules for meals, sleep, playtime, and health checks. For example, the meal schedule specifies what the baby should eat and when. The sleep schedule specifies when the baby should sleep. The playtime schedule specifies what kind of play the baby should do and when. The health check schedule specifies when the baby should have health checks. Furthermore, the childcare support system provides reminders at appropriate times. For example, when mealtime approaches, the childcare support system will remind the supporter, "It's time for the baby's meal." Similarly, when health check time approaches, the childcare support system will remind the supporter, "It's time for the baby's health check." The childcare support system can also provide consultation to supporters as needed. For example, if a supporter asks, "My baby cries at night, what should I do?", the childcare support system will provide appropriate advice.In this way, the childcare support system provides support to single parents in raising their babies. This system reduces the burden of childcare for single parents and allows them to support their babies' development. For example, by managing the baby's feeding and sleep schedule, the baby's health can be maintained. Also, by sending reminders to supporters at appropriate times, childcare schedules can be followed without being forgotten. Furthermore, the childcare support system can help resolve childcare-related worries by providing consultation to supporters. In this way, the childcare support system can provide support to single parents in raising their babies.

[0070] The childcare support system according to this embodiment comprises a reception unit, a generation unit, a management unit, a reminder unit, and a consultation unit. The reception unit inputs information about the baby's age in months. This information includes, but is not limited to, the date of birth, weight, and height. For example, the reception unit can calculate the baby's age in months by inputting the baby's date of birth. The reception unit can also input information such as the baby's weight and height. The generation unit uses a generation AI to analyze the information input by the reception unit and create a childcare plan. For example, the generation unit calculates an optimal childcare plan according to the baby's age in months and creates a schedule based on that plan. For example, if the baby is 6 months old, the generation unit creates a schedule for meals, sleep, play, and health checks suitable for a 6-month-old baby. The generation unit can use a generation AI to calculate an optimal childcare plan according to the baby's age in months. The management unit manages the schedule based on the childcare plan created by the generation unit. For example, the management unit manages the schedule for meals, sleep, play, and health checks based on the created childcare plan. The management department manages schedules such as: the meal schedule, which specifies what the baby should eat and when; the sleep schedule, which specifies when the baby should sleep; the play schedule, which specifies what kind of play the baby should do and when; and the health check schedule, which specifies when the baby should have a health check. The reminder department reminds caregivers at appropriate times based on the schedules managed by the management department. For example, when mealtime is approaching, the reminder department will remind caregivers with "It's time for the baby's meal." Similarly, when health check time is approaching, the reminder department will remind caregivers with "It's time for the baby's health check." The reminder department can remind caregivers at appropriate times. The consultation department provides consultation to caregivers who have been reminded by the reminder department. For example, if a caregiver asks, "My baby cries at night, what should I do?", the consultation department will provide appropriate advice. The consultation department can provide consultation to caregivers.As a result, the childcare support system according to this embodiment can automatically create a childcare plan according to the baby's age in months, manage the schedule, send reminders to caregivers at appropriate times, and provide consultation.

[0071] The reception desk inputs information about the baby's age in months. This information includes, but is not limited to, the date of birth, weight, and height. For example, the reception desk can calculate the baby's age in months by inputting the baby's date of birth. The reception desk can also input information such as the baby's weight and height. Specifically, the reception desk provides a field for inputting the baby's date of birth through the user interface. When the user enters the baby's date of birth, the system automatically calculates the baby's age in months by comparing it to the current date. In addition, input fields for weight and height are also provided, and this data is used for growth tracking and health management. For example, by regularly recording weight changes and height growth, the baby's growth pattern can be understood, and any abnormalities can be detected early. The reception desk can centrally manage this information and share data in cooperation with other departments. For example, the entered data is stored in a database accessible to the generation and management departments and used for creating childcare plans and managing schedules. This allows the reception department to accurately and efficiently collect basic information about babies and support the overall operation of the system.

[0072] The generation unit uses a generation AI to analyze information entered by the reception unit and create a childcare plan. For example, the generation unit calculates the optimal childcare plan based on the baby's age in months and creates a schedule based on that plan. Specifically, the generation AI receives data such as the baby's age in months, weight, and height as input, and generates the optimal childcare plan based on past data and expert knowledge. For example, if the baby is 6 months old, it will create a schedule for meals, sleep, play, and health checks that is suitable for a 6-month-old baby. The generation AI considers the nutritional balance and sleep patterns according to the baby's developmental stage and provides an individually customized plan. For example, the meal schedule includes when to start solid foods and how to choose appropriate ingredients, and the sleep schedule includes nap times and nighttime sleep times. The play schedule includes the types and duration of play according to the developmental stage, and the health check schedule includes the timing of regular health checkups and vaccinations. Based on this information, the generation unit provides a comprehensive childcare plan to support the baby's growth. Furthermore, the generation unit can utilize the learning function of the generation AI to improve the accuracy of the plan based on user feedback. This allows the generation unit to constantly provide optimal childcare plans incorporating the latest information and technology, thereby reducing the burden on caregivers.

[0073] The management department manages schedules based on the childcare plans created by the generation department. For example, the management department manages schedules for meals, sleep, play, and health checks based on the created childcare plans. Specifically, the management department receives the childcare plans provided by the generation department and sets detailed schedules for each item. For example, the meal schedule includes what the baby should eat and when. Specifically, it details the times for breakfast, lunch, and dinner, as well as the timing of snacks and the types and amounts of food. The sleep schedule includes when the baby should sleep. Specifically, it sets the times for naps, nighttime bedtime, and wake-up time, and includes advice on how to regulate the baby's sleep rhythm. The play schedule includes what kind of play the baby should do and when. Specifically, it details the types and duration of play according to the developmental stage, as well as the content and methods of play. The health check schedule includes when the baby should receive health checks. Specifically, it includes the timing of regular health checkups and vaccinations, and how to perform health checks at home. The management department centrally manages these schedules and makes them easily accessible to support staff. For example, caregivers can check schedules and make changes or adjustments as needed through smartphone apps or web portals. This allows the management department to efficiently manage the baby's care plan and reduce the burden on caregivers.

[0074] The Reminders Department sends reminders to caregivers at appropriate times based on the schedule managed by the Management Department. For example, when mealtime approaches, the Reminders Department will remind caregivers with "It's time for your baby's meal." Similarly, when health check time approaches, the Reminders Department will remind caregivers with "It's time for your baby's health check." Specifically, the Reminders Department monitors the timing of each event based on the schedule information provided by the Management Department and sends notifications at the appropriate time. For example, when mealtime approaches, it will remind caregivers via smartphone push notifications or voice alerts. Similarly, when health check time approaches, it will send a notification to encourage caregivers to remember to perform the health check. The Reminders Department can customize the notification method and timing, allowing for flexible responses to caregivers' lifestyles and preferences. For example, by allowing caregivers to select the frequency, volume, and method of notification (push notifications, email, SMS, etc.), more effective reminders can be achieved. Furthermore, the Reminders Department can collect feedback from caregivers and continuously improve the accuracy and timing of notifications. This allows the reminder function to support caregivers in ensuring they adhere to the baby's childcare schedule, thereby reducing the burden of childcare.

[0075] The Consultation Department provides support to caregivers who have been reminded by the Reminder Department. For example, if a caregiver asks, "My baby cries at night, what should I do?", the Consultation Department will provide appropriate advice. Specifically, the Consultation Department receives the caregiver's inquiry and provides the best possible advice based on expert knowledge and past data. For example, in the case of a consultation about nighttime crying, the department will check the baby's sleep environment, daytime activity level, and diet, and suggest areas for improvement. The Consultation Department can also provide expert advice and reference information to address caregivers' parenting concerns and questions. For example, it can provide a wide range of parenting information, such as how to introduce solid foods, vaccination schedules, and play methods appropriate for developmental stages. The Consultation Department plays a role in providing appropriate support so that caregivers can raise their children with peace of mind. Furthermore, the Consultation Department can continuously improve the accuracy and content of the advice it provides based on feedback from caregivers. For example, by recording how caregivers reacted to the advice provided and using this information in future consultations, the department can provide more individually customized support. This will enable the consultation department to respond quickly and appropriately to the childcare concerns and questions that supporters have, thereby improving the quality of childcare.

[0076] The generation unit can calculate the optimal childcare plan according to the baby's age in months and create a schedule based on that plan. For example, if the baby is 6 months old, the generation unit will create a schedule for meals, sleep, playtime, and health checks that is suitable for a 6-month-old baby. The generation unit can calculate the optimal childcare plan according to the baby's age in months using generation AI. This improves the efficiency of childcare by calculating the optimal childcare plan according to the baby's age and creating a schedule.

[0077] The management department can manage schedules for meals, sleep, playtime, and health checks based on the created childcare plan. For example, the management department manages schedules for meals, sleep, playtime, and health checks based on the created childcare plan. For example, the meal schedule includes what the baby should eat and when. The sleep schedule includes what the baby should sleep at. The playtime schedule includes what kind of play the baby should do and when. The health check schedule includes what time the baby should have a health check. This makes childcare schedule management easier by managing schedules for meals, sleep, playtime, and health checks. Some or all of the above processes in the management department may be performed using AI, for example, or not using AI. For example, the management department can manage schedules for meals, sleep, playtime, and health checks based on the created childcare plan using an AI model.

[0078] The reminder unit can remind caregivers with a message like "It's time for the baby's meal" when mealtime is approaching. The reminder unit can send reminders to caregivers at the appropriate time. This allows caregivers to manage mealtimes without forgetting by sending reminders when mealtime is approaching. Some or all of the above processing in the reminder unit may be performed using AI, for example, or not using AI. For example, the reminder unit can use an AI model to detect when mealtime is approaching and send a reminder to the caregiver.

[0079] The reminder unit can remind caregivers with a message such as "It's time for your baby's health check" when the time for the health check is approaching. The reminder unit can send reminders to caregivers at the appropriate time. This ensures that caregivers remember to take care of the health check by sending reminders when the time is approaching. Some or all of the above processing in the reminder unit may be performed using AI, for example, or not using AI. For example, the reminder unit can use an AI model to detect when the time for the health check is approaching and send a reminder to the caregiver.

[0080] The consultation department can provide appropriate advice when a supporter asks, for example, "My baby cries at night, what should I do?" The consultation department can provide appropriate advice when a supporter asks, for example, "My baby cries at night, what should I do?" The consultation department can listen to the supporter's concerns. In this way, by providing appropriate advice when a supporter asks for help, it is possible to resolve their worries about childcare. Some or all of the above processing in the consultation department may be performed using AI, for example, or not using AI. For example, the consultation department can input the supporter's consultation content into an AI model and have the AI ​​model output appropriate advice.

[0081] The reception desk can estimate the supporter's emotions and adjust the timing of information input based on the estimated emotions. For example, if the supporter is feeling stressed, the reception desk may prompt them to input information during a time when they can relax. If the supporter is busy, the reception desk may prompt them to input information during a time when they have free time. If the supporter is relaxed, the reception desk may prompt them to input information immediately. This reduces the burden on the supporter by adjusting the timing of information input according to their emotions. Emotion estimation is achieved using an emotion estimation function, for example, using an emotion engine or generative AI. Generative AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the reception desk may be performed using AI, or not using AI. For example, the reception desk may input the supporter's facial expression data into the generative AI and have the generative AI perform the estimation of the supporter's emotions.

[0082] The reception desk can analyze the baby's past health data and select the optimal information input method. For example, the reception desk can select the most effective information input method from the baby's past health data. For example, the reception desk can propose an information input method suitable for the caregiver based on the baby's health data. For example, the reception desk can analyze the baby's health data and select the information input method that is easiest for the caregiver to understand. In this way, the optimal information input method can be selected by analyzing the baby's past health data. Some or all of the above processes in the reception desk may be performed using AI, for example, or without AI. For example, the reception desk can input the baby's health data into a generating AI and have the generating AI select the optimal information input method.

[0083] The reception unit can filter information based on the supporter's current living situation and areas of interest during input. For example, the reception unit inputs only the necessary information based on the supporter's current living situation. For example, the reception unit inputs only the relevant information based on the supporter's areas of interest. For example, the reception unit selects the most relevant information based on the supporter's living situation and areas of interest. This allows only the necessary information to be input by filtering the information based on the supporter's living situation and areas of interest. Some or all of the above processing in the reception unit may be performed using AI, for example, or without AI. For example, the reception unit can input data on the supporter's living situation and areas of interest into a generating AI and have the generating AI perform the information filtering.

[0084] The reception unit can estimate the emotions of the supporter and determine the priority of the information to be entered based on the estimated emotions of the supporter. For example, if the supporter is stressed, the reception unit will prioritize the input of important information. For example, if the supporter is relaxed, the reception unit will prioritize the input of detailed information. For example, if the supporter is busy, the reception unit will prioritize the input of only the minimum necessary information. In this way, by prioritizing information according to the supporter's emotions, important information can be entered preferentially. 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 unit may be performed using AI, for example, or not using AI. For example, the reception unit can input the supporter's facial expression data into the generative AI and have the generative AI perform the estimation of the supporter's emotions.

[0085] The reception desk can prioritize inputting highly relevant information by considering the geographical location of the supporter when entering information. For example, the reception desk can prioritize inputting information about nearby medical institutions based on the supporter's geographical location. For example, the reception desk can prioritize inputting information about local childcare support services based on the supporter's geographical location. For example, the reception desk can prioritize inputting information about local events based on the supporter's geographical location. In this way, by prioritizing the input of highly relevant information based on the supporter's geographical location, the reception desk can provide supporters with useful 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 input the supporter's geographical location into a generating AI and have the generating AI select highly relevant information.

[0086] The reception desk can analyze the supporter's social media activity and input relevant information when entering data. For example, the reception desk can analyze the supporter's social media activity and input relevant childcare information. For example, the reception desk can analyze the supporter's social media activity and input information about childcare groups of interest. For example, the reception desk can analyze the supporter's social media activity and input relevant event information. In this way, relevant information can be entered by analyzing the supporter's social media activity. 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 input the supporter's social media activity data into a generating AI and have the generating AI select relevant information.

[0087] The generation unit can estimate the caregiver's emotions and adjust the way the childcare plan is presented based on the estimated emotions. For example, if the caregiver is stressed, the generation unit will present the childcare plan in a simple way. If the caregiver is relaxed, the generation unit will present the childcare plan in a detailed way. If the caregiver is busy, the generation unit will present the childcare plan in a concise way. By adjusting the way the childcare plan is presented according to the caregiver's emotions, the system can provide a plan that is easy for the caregiver to understand. Emotion estimation is achieved using an emotion estimation function, such as an emotion engine or a generation AI. The generation AI is, but is not limited to, a text generation AI (e.g., LLM) or a multimodal generation AI. Some or all of the above processing in the generation unit may be performed using AI, or not using AI. For example, the generation unit can input the caregiver's facial expression data into the generation AI and have the generation AI adjust the way the childcare plan is presented.

[0088] The generation unit can adjust the level of detail in the childcare plan based on the baby's health condition when generating the plan. For example, if the baby's health is good, the generation unit generates a detailed childcare plan. For example, if the baby's health is unstable, the generation unit generates a simplified childcare plan. For example, the generation unit generates a childcare plan with an appropriate level of detail depending on the baby's health condition. This allows for the provision of an appropriate childcare plan by adjusting the level of detail according to the baby's health condition. Some or all of the above processing in the generation unit may be performed using AI, for example, or without AI. For example, the generation unit can input the baby's health data into a generation AI and have the generation AI perform the adjustment of the plan's level of detail.

[0089] The generation unit can apply different plan generation algorithms depending on the baby's developmental stage when generating a childcare plan. For example, the generation unit applies an appropriate childcare plan generation algorithm depending on the baby's developmental stage. For example, the generation unit selects a different childcare plan generation algorithm depending on the baby's developmental stage. For example, the generation unit applies the optimal childcare plan generation algorithm depending on the baby's developmental stage. By applying different plan generation algorithms depending on the baby's developmental stage, it is possible to provide an appropriate childcare plan that is appropriate for the baby's growth. Some or all of the above-described processes in the generation unit may be performed using AI, for example, or without using AI. For example, the generation unit can input the baby's growth data into a generation AI and have the generation AI execute the application of the plan generation algorithm.

[0090] The generation unit can estimate the caregiver's emotions and adjust the length of the childcare plan based on the estimated emotions. For example, if the caregiver is stressed, the generation unit generates a short childcare plan. For example, if the caregiver is relaxed, the generation unit generates a long childcare plan. For example, if the caregiver is busy, the generation unit generates a concise childcare plan. This allows for the provision of less burdensome plans for the caregiver by adjusting the length of the childcare plan according to their emotions. Emotion estimation is achieved using an emotion estimation function, such as an emotion engine or a generation AI. The generation AI is, but is not limited to, a text generation AI (e.g., LLM) or a multimodal generation AI. Some or all of the above processing in the generation unit may be performed using AI or not. For example, the generation unit can input the caregiver's facial expression data into the generation AI and have the generation AI adjust the length of the childcare plan.

[0091] The generation unit can determine the priority of childcare plans based on the baby's date of birth when generating childcare plans. For example, the generation unit determines the priority of childcare plans based on the baby's date of birth. For example, the generation unit generates important childcare plans preferentially based on the baby's date of birth. For example, the generation unit determines the priority of appropriate childcare plans based on the baby's date of birth. This allows important plans to be provided preferentially by determining the priority of plans based on the baby's date of birth. Some or all of the above processing in the generation unit may be performed using AI, for example, or without AI. For example, the generation unit can input the baby's date of birth data into a generation AI and have the generation AI perform the determination of plan priorities.

[0092] The generation unit can adjust the order of childcare plans based on relevant data about the baby when generating childcare plans. For example, the generation unit adjusts the order of childcare plans based on relevant data about the baby. For example, the generation unit prioritizes generating important childcare plans based on relevant data about the baby. For example, the generation unit adjusts the order of appropriate childcare plans based on relevant data about the baby. This allows the childcare plans to be provided in the appropriate order by adjusting the order of plans based on relevant data about the baby. Some or all of the above processing in the generation unit may be performed using AI, for example, or without AI. For example, the generation unit can input relevant data about the baby into a generation AI and have the generation AI perform the adjustment of the order of plans.

[0093] The management department can estimate the emotions of supporters and adjust the schedule management method based on the estimated emotions. For example, if a supporter is stressed, the management department provides a simple schedule management method. For example, if a supporter is relaxed, the management department provides a detailed schedule management method. For example, if a supporter is busy, the management department provides a concise schedule management method. This allows for less burdensome schedule management for supporters by adjusting the schedule management method according to their emotions. Emotion estimation is achieved using an emotion estimation function, for example, using an emotion engine or generative AI. Generative AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the management department may be performed using AI, for example, or not using AI. For example, the management department can input supporter facial expression data into the generative AI and have the generative AI adjust the schedule management method.

[0094] The management department can improve the accuracy of the schedule by referring to the baby's health data when managing the schedule. For example, the management department can improve the accuracy of the schedule by referring to the baby's health data. For example, the management department can create an optimal schedule based on the baby's health data. For example, the management department can improve the accuracy of the schedule by analyzing the baby's health data. In this way, the accuracy of the schedule can be improved by referring to the baby's health data. Some or all of the above processes in the management department may be performed using AI, for example, or without using AI. For example, the management department can input the baby's health data into a generating AI and have the generating AI perform the schedule accuracy improvement.

[0095] The management department can customize schedules according to the supporter's daily rhythm when managing schedules. For example, the management department customizes the schedule according to the supporter's daily rhythm. For example, the management department creates an optimal schedule based on the supporter's daily rhythm. For example, the management department customizes the schedule taking the supporter's daily rhythm into consideration. This allows the management department to provide the supporter with an optimal schedule by customizing the schedule according to the supporter's daily rhythm. 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 input the supporter's daily rhythm data into a generating AI and have the generating AI perform schedule customization.

[0096] The management department can estimate the emotions of supporters and prioritize schedules based on the estimated emotions. For example, if a supporter is stressed, the management department will prioritize important schedules. For example, if a supporter is relaxed, the management department will manage detailed schedules. For example, if a supporter is busy, the management department will manage only the bare minimum of schedules. This allows for the prioritization of important schedules by determining schedule priorities according to the supporter'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 management department may be performed using AI or not. For example, the management department can input supporter facial expression data into a generative AI and have the generative AI determine schedule priorities.

[0097] The management department can select the optimal schedule by considering the geographical location information of the supporters when managing schedules. For example, the management department selects the optimal schedule based on the geographical location information of the supporters. For example, the management department customizes the schedule by considering the geographical location information of the supporters. For example, the management department prioritizes important schedules based on the geographical location information of the supporters. This allows the management department to provide supporters with a beneficial schedule by selecting the optimal schedule based on their geographical location information. Some or all of the above processes in the management department may be performed using AI, for example, or not using AI. For example, the management department can input the geographical location information of the supporters into a generating AI and have the generating AI perform the selection of the optimal schedule.

[0098] The management department can analyze supporters' social media activity and adjust schedules accordingly. For example, the management department can analyze supporters' social media activity and create an optimal schedule. For example, the management department can customize schedules based on supporters' social media activity. For example, the management department can adjust schedules taking supporters' social media activity into consideration. This allows the management department to provide an optimal schedule by analyzing supporters' social media activity. Some or all of the above processes in the management department may be performed using AI, for example, or not. For example, the management department can input supporter social media activity data into a generating AI and have the generating AI perform schedule adjustments.

[0099] The reminder unit can estimate the caregiver's emotions and adjust the reminder method based on the estimated emotions. For example, if the caregiver is stressed, the reminder unit provides a gentle reminder method. For example, if the caregiver is relaxed, the reminder unit provides a detailed reminder method. For example, if the caregiver is busy, the reminder unit provides a concise reminder method. By adjusting the reminder method according to the caregiver's emotions, it becomes possible to provide reminders that are less burdensome for the caregiver. Emotion estimation is achieved using an emotion estimation function, for example, using an emotion engine or a generative AI. The generative AI is a text generation AI (e.g., LLM) or a multimodal generation AI, but is not limited to such examples. Some or all of the above processing in the reminder unit may be performed using AI, for example, or without AI. For example, the reminder unit can input the caregiver's facial expression data into the generative AI and have the generative AI adjust the reminder method.

[0100] The reminder unit can optimize the timing of reminders by referring to the baby's health data. For example, the reminder unit can determine the optimal reminder timing by referring to the baby's health data. For example, the reminder unit can adjust the timing of reminders based on the baby's health data. For example, the reminder unit can optimize the timing of reminders by analyzing the baby's health data. In this way, the timing of reminders can be optimized by referring to the baby's health data. Some or all of the above processes in the reminder unit may be performed using AI, for example, or without using AI. For example, the reminder unit can input the baby's health data into a generating AI and have the generating AI perform the optimization of the reminder timing.

[0101] The reminder unit can customize the content of reminders according to the caregiver's daily routine. For example, the reminder unit customizes the content of reminders according to the caregiver's daily routine. For example, the reminder unit provides optimal reminder content based on the caregiver's daily routine. For example, the reminder unit adjusts the content of reminders considering the caregiver's daily routine. By customizing the content of reminders according to the caregiver's daily routine, the system can provide the caregiver with the most suitable reminder. Some or all of the above processing in the reminder unit may be performed using AI, for example, or without AI. For example, the reminder unit can input the caregiver's daily routine data into a generating AI and have the generating AI perform the customization of the reminder content.

[0102] The reminder unit can estimate the caregiver's emotions and determine the priority of reminders based on the estimated emotions. For example, if the caregiver is stressed, the reminder unit will prioritize important reminders. For example, if the caregiver is relaxed, the reminder unit will provide detailed reminders. For example, if the caregiver is busy, the reminder unit will provide only the essential reminders. This allows important reminders to be prioritized by determining the priority of reminders according to the caregiver's emotions. Emotion estimation is achieved using an emotion estimation function, for example, an emotion engine or a generative AI. The generative AI is, but is not limited to, a text generation AI (e.g., LLM) or a multimodal generation AI. Some or all of the above processing in the reminder unit may be performed using AI or not. For example, the reminder unit can input the caregiver's facial expression data into the generative AI and have the generative AI determine the reminder priority.

[0103] The reminder unit can select the optimal reminder method when sending a reminder, taking into account the geographical location information of the supporter. For example, the reminder unit selects the optimal reminder method based on the geographical location information of the supporter. For example, the reminder unit adjusts the content of the reminder, taking into account the geographical location information of the supporter. For example, the reminder unit prioritizes important reminders based on the geographical location information of the supporter. In this way, by selecting the optimal reminder method based on the geographical location information of the supporter, it is possible to provide helpful reminders to the supporter. Some or all of the above processing in the reminder unit may be performed using AI, for example, or without using AI. For example, the reminder unit can input the geographical location information of the supporter into a generating AI and have the generating AI select the optimal reminder method.

[0104] The reminder unit can analyze the supporter's social media activity and adjust the content of the reminder at the time of sending a reminder. For example, the reminder unit analyzes the supporter's social media activity and provides the most appropriate reminder content. For example, the reminder unit customizes the content of the reminder based on the supporter's social media activity. For example, the reminder unit adjusts the content of the reminder taking the supporter's social media activity into consideration. This allows the system to provide the most appropriate reminder content by analyzing the supporter's social media activity. Some or all of the above processing in the reminder unit may be performed using AI, for example, or without AI. For example, the reminder unit can input the supporter's social media activity data into a generating AI and have the generating AI adjust the reminder content.

[0105] The consultation department can estimate the emotions of the supporter and adjust the consultation response based on the estimated emotions. For example, if the supporter is stressed, the consultation department will provide a calm response. For example, if the supporter is relaxed, the consultation department will provide a detailed response. For example, if the supporter is busy, the consultation department will provide a concise response. By adjusting the consultation response according to the supporter's emotions, it becomes possible to provide consultation with less burden on the supporter. 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 consultation department may be performed using AI, for example, or not using AI. For example, the consultation department can input the supporter's facial expression data into the generative AI and have the generative AI perform the adjustment of the consultation response.

[0106] The consultation department can provide optimal advice by referring to the baby's health data when providing consultation. For example, the consultation department can provide optimal advice by referring to the baby's health data. For example, the consultation department can provide advice suitable for the supporter based on the baby's health data. For example, the consultation department can provide optimal advice by analyzing the baby's health data. In this way, optimal advice can be provided by referring to the baby's health data. Some or all of the above processes in the consultation department may be performed using AI, for example, or without using AI. For example, the consultation department can input the baby's health data into a generating AI and have the generating AI perform the task of providing optimal advice.

[0107] The consultation department can customize its response methods when providing consultation by referring to the supporter's past consultation history. For example, the consultation department can refer to the supporter's past consultation history to provide the optimal response method. For example, the consultation department customizes its response methods based on the supporter's past consultation history. For example, the consultation department analyzes the supporter's past consultation history to provide the optimal response method. In this way, the optimal response method can be provided by referring to the supporter's past consultation history. Some or all of the above processes in the consultation department may be performed using AI, for example, or without AI. For example, the consultation department can input the supporter's past consultation history data into a generating AI and have the generating AI perform the customization of the response method.

[0108] The consultation department can estimate the emotions of the supporter and determine the priority of consultations based on the estimated emotions. For example, if the supporter is feeling stressed, the consultation department will prioritize important consultations. For example, if the supporter is relaxed, the consultation department will handle detailed consultations. For example, if the supporter is busy, the consultation department will handle only the minimum necessary consultations. In this way, by determining the priority of consultations according to the supporter's emotions, important consultations can be prioritized. 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 consultation department may be performed using AI, for example, or not using AI. For example, the consultation department can input the supporter's facial expression data into the generative AI and have the generative AI perform the determination of consultation priorities.

[0109] The consultation department can provide optimal advice when handling consultations, taking into account the geographical location of the supporter. For example, the consultation department provides optimal advice based on the supporter's geographical location. For example, the consultation department adjusts the content of the advice considering the supporter's geographical location. For example, the consultation department prioritizes providing important advice based on the supporter's geographical location. In this way, by providing optimal advice based on the supporter's geographical location, the consultation department can provide advice that is beneficial to the supporter. Some or all of the above processes in the consultation department may be performed using AI, for example, or without AI. For example, the consultation department can input the supporter's geographical location into a generating AI and have the generating AI perform the task of providing optimal advice.

[0110] The consultation department can analyze the social media activity of the supporter and adjust the content of the advice when providing consultation. For example, the consultation department can analyze the supporter's social media activity and provide optimal advice. For example, the consultation department can customize the content of the advice based on the supporter's social media activity. For example, the consultation department can adjust the content of the advice taking into consideration the supporter's social media activity. In this way, by analyzing the supporter's social media activity, it is possible to provide optimal advice. Some or all of the above processes in the consultation department may be performed using AI, for example, or not using AI. For example, the consultation department can input the supporter's social media activity data into a generating AI and have the generating AI perform the adjustment of the advice content.

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

[0112] The reception desk can estimate the supporter's emotions and adjust the timing of information input based on those estimates. For example, if the supporter is feeling stressed, they can be prompted to input information during a time when they can relax. If the supporter is busy, they can be prompted to input information during a time when they have free time. Furthermore, if the supporter is relaxed, they can be prompted to input information immediately. In this way, the burden on supporters can be reduced by adjusting the timing of information input according to their emotions.

[0113] The generation unit can adjust the level of detail in the childcare plan based on the baby's health condition. For example, if the baby is in good health, a detailed childcare plan can be generated. Conversely, if the baby's health is unstable, a simplified childcare plan can be generated. Furthermore, it can generate a childcare plan with an appropriate level of detail depending on the baby's health condition. In this way, by adjusting the level of detail in the plan according to the baby's health condition, an appropriate childcare plan can be provided.

[0114] The management department can customize schedules according to the supporter's daily rhythm. For example, it can customize schedules according to the supporter's daily rhythm. It can also create an optimal schedule based on the supporter's daily rhythm. Furthermore, it can customize schedules while taking the supporter's daily rhythm into consideration. In this way, by customizing schedules according to the supporter's daily rhythm, it is possible to provide the supporter with the most optimal schedule.

[0115] The reminder function can estimate the caregiver's emotions and adjust the reminder method based on those emotions. For example, if the caregiver is stressed, it can provide a gentle reminder. If the caregiver is relaxed, it can provide a more detailed reminder. Furthermore, if the caregiver is busy, it can provide a concise reminder. By adjusting the reminder method according to the caregiver's emotions, it becomes possible to provide reminders that are less burdensome for the caregiver.

[0116] The counseling department can estimate the emotions of the person seeking support and adjust its approach based on those estimates. For example, if the person is feeling stressed, it can provide a calm approach. If the person is relaxed, it can provide a more detailed approach. Furthermore, if the person is busy, it can provide a concise approach. By adjusting the counseling approach according to the person's emotions, it becomes possible to provide counseling that is less burdensome for the person seeking support.

[0117] The reception desk can analyze the baby's past health data and select the most suitable information input method. For example, it can select the most effective information input method based on the baby's past health data. It can also suggest an information input method suitable for the caregiver based on the baby's health data. Furthermore, it can analyze the baby's health data and select the information input method that is easiest for the caregiver to understand. In this way, the optimal information input method can be selected by analyzing the baby's past health data.

[0118] The generation unit can estimate the caregiver's emotions and adjust the way the childcare plan is presented based on those emotions. For example, if the caregiver is stressed, the childcare plan can be presented in a simple way. If the caregiver is relaxed, the plan can be presented in a more detailed way. Furthermore, if the caregiver is busy, the plan can be presented in a concise way. By adjusting the presentation of the childcare plan according to the caregiver's emotions, it is possible to provide a plan that is easy for the caregiver to understand.

[0119] The management department can improve the accuracy of schedules by referring to the baby's health data during schedule management. For example, they can improve the accuracy of schedules by referring to the baby's health data. They can also create an optimal schedule based on the baby's health data. Furthermore, they can analyze the baby's health data to improve the accuracy of schedules. In this way, the accuracy of schedules can be improved by referring to the baby's health data.

[0120] The reminder function can customize the content of reminders according to the caregiver's daily routine. For example, it can customize the content of reminders according to the caregiver's daily routine. It can also provide the most appropriate reminder content based on the caregiver's daily routine. Furthermore, it can adjust the content of reminders while taking the caregiver's daily routine into consideration. In this way, by customizing the content of reminders according to the caregiver's daily routine, it can provide the most appropriate reminder for the caregiver.

[0121] The consultation department can customize its response methods when providing consultations by referring to the supporter's past consultation history. For example, it can provide the most suitable response method by referring to the supporter's past consultation history. It can also customize its response methods based on the supporter's past consultation history. Furthermore, it can analyze the supporter's past consultation history and provide the most suitable response method. In this way, it can provide the most suitable response method by referring to the supporter's past consultation history.

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

[0123] Step 1: The reception desk enters information about the baby's age in months. This information includes, for example, the date of birth, weight, and height. The reception desk can calculate the baby's age in months by entering the baby's date of birth. It can also enter information such as the baby's weight and height. Step 2: The generation unit analyzes the information entered by the reception unit and creates a childcare plan. The generation unit uses generation AI to calculate the optimal childcare plan according to the baby's age in months and creates a schedule based on that plan. For example, if the baby is 6 months old, it will create a schedule for meals, sleep, playtime, and health checks that is suitable for a 6-month-old baby. Step 3: The management department manages the schedule based on the childcare plan created by the generation department. The management department manages the schedules for meals, sleep, playtime, and health checks based on the created childcare plan. For example, the meal schedule specifies what the baby should eat and when. The sleep schedule specifies when the baby should sleep. The playtime schedule specifies what kind of play the baby should do and when. The health check schedule specifies when the baby should have health checks. Step 4: The reminder department will send reminders to caregivers at appropriate times based on the schedule managed by the management department. For example, when mealtime is approaching, they will remind caregivers with "It's time for the baby's meal." Also, when it's time for a health check, they will remind caregivers with "It's time for the baby's health check." Step 5: The consultation department provides support to supporters who have been reminded by the reminder department. For example, if a supporter asks, "My baby cries at night, what should I do?", the consultation department provides appropriate advice.

[0124] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

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

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

[0127] Each of the multiple elements described above, including the reception unit, generation unit, management unit, reminder unit, and consultation 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 inputs information about the baby's age in months. The generation unit is implemented by, for example, the specific processing unit 290 of the data processing unit 12 and creates a childcare plan using generation AI. The management unit is implemented by, for example, the control unit 46A of the smart device 14 and manages the schedule based on the childcare plan. The reminder unit is implemented by, for example, the control unit 46A of the smart device 14 and sends reminders to caregivers at appropriate times. The consultation unit is implemented by, for example, the specific processing unit 290 of the data processing unit 12 and provides consultation to caregivers. The correspondence between each unit and the device or control unit is not limited to the example described above and can be changed in various ways.

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

[0129] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

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

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

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

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

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

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

[0136] The processor 28 reads a specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 acting as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0137] Storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotions using the emotion identification model 59 and perform identification processing using the user's emotions. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotions, including but not limited to these examples. Furthermore, emotion estimation and prediction also include, for example, emotion analysis.

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

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

[0140] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

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

[0142] The data processing system 210 according to the second embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 210 is performed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart glasses 214, but it may also be performed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart glasses 214. In addition, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the smart glasses 214 or an external device, and the smart glasses 214 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0143] Each of the multiple elements described above, including the reception unit, generation unit, management unit, reminder unit, and consultation 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 inputs information about the baby's age in months. The generation unit is implemented by, for example, the specific processing unit 290 of the data processing unit 12 and creates a childcare plan using generation AI. The management unit is implemented by, for example, the control unit 46A of the smart glasses 214 and manages the schedule based on the childcare plan. The reminder unit is implemented by, for example, the control unit 46A of the smart glasses 214 and sends reminders to the caregiver at the appropriate time. The consultation unit is implemented by, for example, the specific processing unit 290 of the data processing unit 12 and provides consultation to the caregiver. The correspondence between each unit and the device or control unit is not limited to the example described above and can be changed in various ways.

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

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

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

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

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

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

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

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

[0152] The processor 28 reads a specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 acting as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0153] Storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotions using the emotion identification model 59 and perform identification processing using the user's emotions. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotions, including but not limited to these examples. Furthermore, emotion estimation and prediction also include, for example, emotion analysis.

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

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

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

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

[0158] The data processing system 310 according to the third embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 310 is performed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the headset terminal 314, but may also be performed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the headset terminal 314. In addition, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the headset terminal 314 or an external device, and the headset terminal 314 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0159] Each of the multiple elements described above, including the reception unit, generation unit, management unit, reminder unit, and consultation 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 inputs information about the baby's age in months. The generation unit is implemented by, for example, the specific processing unit 290 of the data processing unit 12 and creates a childcare plan using generation AI. The management unit is implemented by, for example, the control unit 46A of the headset terminal 314 and manages the schedule based on the childcare plan. The reminder unit is implemented by, for example, the control unit 46A of the headset terminal 314 and sends reminders to the caregiver at the appropriate time. The consultation unit is implemented by, for example, the specific processing unit 290 of the data processing unit 12 and provides consultation to the caregiver. The correspondence between each unit and the device or control unit is not limited to the example described above and can be changed in various ways.

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

[0161] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

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

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

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

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

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

[0167] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. The robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

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

[0169] The processor 28 reads a specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 acting as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0170] Storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotions using the emotion identification model 59 and perform identification processing using the user's emotions. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotions, including but not limited to these examples. Furthermore, emotion estimation and prediction also include, for example, emotion analysis.

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

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

[0173] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

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

[0175] The data processing system 410 according to the fourth embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 410 is performed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the robot 414, but it may also be performed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the robot 414. In addition, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the robot 414 or an external device, and the robot 414 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0176] Each of the multiple elements described above, including the reception unit, generation unit, management unit, reminder unit, and consultation 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 inputs information about the baby's age in months. The generation unit is implemented by, for example, the specific processing unit 290 of the data processing unit 12 and creates a childcare plan using generation AI. The management unit is implemented by, for example, the control unit 46A of the robot 414 and manages the schedule based on the childcare plan. The reminder unit is implemented by, for example, the control unit 46A of the robot 414 and sends reminders to the caregiver at the appropriate time. The consultation unit is implemented by, for example, the specific processing unit 290 of the data processing unit 12 and provides consultation to the caregiver. The correspondence between each unit and the device or control unit is not limited to the example described above and can be changed in various ways.

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

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

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

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

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

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

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

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

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

[0186] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[0187] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

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

[0189] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

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

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

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

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

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

[0195] (Note 1) A reception area where you enter information about your baby's age in months, A generation unit analyzes the information entered by the reception unit and creates a childcare plan, A management unit manages the schedule based on the childcare plan created by the generation unit, A reminder unit that sends reminders to supporters at appropriate times based on the schedule managed by the aforementioned management unit, The system comprises a consultation unit that provides consultation to supporters who have been reminded by the aforementioned reminder unit. A system characterized by the following features. (Note 2) The generating unit is Calculate the optimal childcare plan based on your baby's age in months and create a schedule based on that plan. The system described in Appendix 1, characterized by the features described herein. (Note 3) The aforementioned management department, Manage meal, sleep, playtime, and health check schedules based on the created childcare plan. The system described in Appendix 1, characterized by the features described herein. (Note 4) The aforementioned reminder unit, When mealtime approaches, remind the caregiver by saying, "It's time for the baby's meal." The system described in Appendix 1, characterized by the features described herein. (Note 5) The aforementioned reminder unit, When it's time for the health check, remind the caregiver by saying, "It's time for the baby's health check." The system described in Appendix 1, characterized by the features described herein. (Note 6) The aforementioned consultation department, When a support worker asks, "My baby cries at night, what should I do?", provide appropriate advice. The system described in Appendix 1, characterized by the features described herein. (Note 7) The aforementioned reception unit is The system estimates the emotions of the supporters and adjusts the timing of information input based on the estimated emotions of the supporters. The system described in Appendix 1, characterized by the features described herein. (Note 8) The aforementioned reception unit is Analyze the baby's past health data and select the optimal method for inputting the information. The system described in Appendix 1, characterized by the features described herein. (Note 9) The aforementioned reception unit is When entering information, filtering is performed based on the supporter's current living situation and areas of interest. The system described in Appendix 1, characterized by the features described herein. (Note 10) The aforementioned reception unit is The system estimates the emotions of the supporters and prioritizes the information to be entered based on the estimated emotions of the supporters. The system described in Appendix 1, characterized by the features described herein. (Note 11) The aforementioned reception unit is When entering information, the system prioritizes inputting highly relevant information, taking into account the geographical location of the supporter. The system described in Appendix 1, characterized by the features described herein. (Note 12) The aforementioned reception unit is When entering information, the social media activity of supporters is analyzed and relevant information is entered. The system described in Appendix 1, characterized by the features described herein. (Note 13) The generating unit is The system estimates the emotions of supporters and adjusts the way the parenting plan is presented based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 14) The generating unit is When creating a childcare plan, adjust the level of detail in the plan based on the baby's health condition. The system described in Appendix 1, characterized by the features described herein. (Note 15) The generating unit is When generating a childcare plan, different plan generation algorithms are applied depending on the baby's developmental stage. The system described in Appendix 1, characterized by the features described herein. (Note 16) The generating unit is The system estimates the emotions of the supporters and adjusts the length of the parenting plan based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 17) The generating unit is When creating a childcare plan, prioritize the plan based on the baby's date of birth. The system described in Appendix 1, characterized by the features described herein. (Note 18) The generating unit is When generating a childcare plan, the order of the plan is adjusted based on relevant data about the baby. The system described in Appendix 1, characterized by the features described herein. (Note 19) The aforementioned management department, The system estimates the emotions of supporters and adjusts the scheduling method based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 20) The aforementioned management department, When managing schedules, refer to your baby's health data to improve the accuracy of the schedule. The system described in Appendix 1, characterized by the features described herein. (Note 21) The aforementioned management department, When managing schedules, customize them according to the supporter's daily routine. The system described in Appendix 1, characterized by the features described herein. (Note 22) The aforementioned management department, The system estimates the emotions of supporters and prioritizes the schedule based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 23) The aforementioned management department, When managing schedules, the optimal schedule is selected by considering the geographical location information of the supporters. The system described in Appendix 1, characterized by the features described herein. (Note 24) The aforementioned management department, When managing the schedule, analyze the supporters' social media activity and adjust the schedule accordingly. The system described in Appendix 1, characterized by the features described herein. (Note 25) The aforementioned reminder unit, The system estimates the supporter's emotions and adjusts the reminder method based on those emotions. The system described in Appendix 1, characterized by the features described herein. (Note 26) The aforementioned reminder unit, When sending reminders, we refer to the baby's health data to optimize the timing of the reminders. The system described in Appendix 1, characterized by the features described herein. (Note 27) The aforementioned reminder unit, When sending a reminder, customize the content of the reminder according to the caregiver's daily routine. The system described in Appendix 1, characterized by the features described herein. (Note 28) The aforementioned reminder unit, The system estimates the emotions of supporters and prioritizes reminders based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 29) The aforementioned reminder unit, When sending a reminder, the system will select the most appropriate reminder method, taking into account the supporter's geographical location. The system described in Appendix 1, characterized by the features described herein. (Note 30) The aforementioned reminder unit, When sending reminders, we analyze the supporters' social media activity and adjust the content of the reminders accordingly. The system described in Appendix 1, characterized by the features described herein. (Note 31) The aforementioned consultation department, The system estimates the emotions of the supporter and adjusts the consultation approach based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 32) The aforementioned consultation department, When providing consultation, we refer to the baby's health data to offer the best possible advice. The system described in Appendix 1, characterized by the features described herein. (Note 33) The aforementioned consultation department, When providing support, customize the approach by referring to the supporter's past consultation history. The system described in Appendix 1, characterized by the features described herein. (Note 34) The aforementioned consultation department, The system estimates the emotions of the supporters and determines the priority of consultations based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 35) The aforementioned consultation department, When providing consultation, we take into account the geographical location of the supporter to provide the most appropriate advice. The system described in Appendix 1, characterized by the features described herein. (Note 36) The aforementioned consultation department, When providing advice, we analyze the social media activity of the supporter and adjust the content of the advice accordingly. The system described in Appendix 1, characterized by the features described herein. [Explanation of symbols]

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

Claims

1. A reception area where you enter information about your baby's age in months, A generation unit analyzes the information entered by the reception unit and creates a childcare plan, A management unit manages the schedule based on the childcare plan created by the generation unit, A reminder unit that sends reminders to supporters at appropriate times based on the schedule managed by the aforementioned management unit, The system comprises a consultation unit that provides consultation to supporters who have been reminded by the aforementioned reminder unit. A system characterized by the following features.

2. The generating unit is Calculate the optimal childcare plan based on your baby's age in months and create a schedule based on that plan. The system according to feature 1.

3. The aforementioned management department, Manage meal, sleep, playtime, and health check schedules based on the created childcare plan. The system according to feature 1.

4. The aforementioned reception unit is The system estimates the emotions of the supporters and adjusts the timing of information input based on the estimated emotions of the supporters. The system according to feature 1.

5. The aforementioned reception unit is Analyze the baby's past health data and select the optimal method for inputting the information. The system according to feature 1.

6. The aforementioned reception unit is When entering information, filtering is performed based on the supporter's current living situation and areas of interest. The system according to feature 1.

Images