system

Abstract

The system according to the embodiment aims to support child-rearing by providing information and coaching on child-rearing during pregnancy and after birth. [Solution] A system according to an embodiment includes an information providing unit, a coaching unit, and a monitoring unit. The information providing unit provides information during pregnancy and after childbirth. The coaching unit provides parenting coaching based on the information provided by the information providing unit. The monitoring unit monitors the child's growth based on the coaching provided by the coaching unit.

Description

[Technical Field]

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

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

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

[0004] Current technologies do not provide sufficient information and coaching on parenting during pregnancy and after birth, and there is room for improvement.

[0005] The system according to the embodiment aims to support child-rearing by providing information and coaching on child-rearing during pregnancy and after birth. [Means for solving the problem]

[0006] The system according to the embodiment includes an information providing unit, a coaching unit, and a monitoring unit. The information providing unit provides information during pregnancy and after childbirth. The coaching unit provides childcare coaching based on the information provided by the information providing unit. The monitoring unit monitors the child's growth based on the coaching provided by the coaching unit. [Effects of the Invention]

[0007] The system according to the embodiment can support child-rearing by providing information and coaching on child-rearing during pregnancy and after birth. [Brief explanation of the drawings]

[0008] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. DETAILED DESCRIPTION OF THE INVENTION

[0009] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0010] First, the terms used in the following description will be explained.

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

[0012] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

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

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

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

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

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

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

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

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

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

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

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

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

[0025] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0026] In the smart device 14, the specific processing is performed by the processor 46. The storage 50 stores a specific processing program 60. The specific processing program 60 is used together with the specific processing program 56 by the data processing system 10. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. Note that the smart device 14 has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can also perform processing similar to that of the specific processing unit 290 using these models.

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

[0028] (Example 1) A childcare support system according to an embodiment of the present invention utilizes generative AI to provide parenting coaching and support to parents struggling with childcare, thereby addressing Japan's trend toward later marriage. This childcare support system includes an information provider that provides information during pregnancy and after childbirth, a coaching unit that provides parenting coaching based on the information provided by the information provider, and a monitoring unit that monitors the child's growth based on the coaching provided by the coaching unit. For example, a database of tasks and precautions for parents according to the pregnancy cycle is compiled and provided daily. Specifically, the system creates dietary management and menus for pregnant women that are beneficial for the baby's growth and recommends recommended apps. After birth, the system provides parents with information necessary for the baby's diet and growth. Next, the system provides parenting coaching to parents. Specifically, the system supports the child's learning methods, child discipline, and parent-child relationship building. Furthermore, the system monitors the child's growth and supports language and physical development through sleep, diet, and other aspects. This system reduces the burden of childcare, allowing parents to focus on childcare with peace of mind. Furthermore, through childcare support, the system contributes to addressing Japan's trend toward later marriage. This system will reduce the burden of childcare and allow parents to focus on raising their children with peace of mind. Furthermore, through childcare support, it will also contribute to addressing Japan's trend of late marriage.

[0029] A childcare support system according to an embodiment includes an information providing unit, a coaching unit, and a monitoring unit. The information providing unit provides information during pregnancy and after birth. Examples of information during pregnancy and after birth include, but are not limited to, health management, nutrition, exercise, and mental health. The information providing unit, for example, creates a database of tasks and precautions for moms and dads according to the pregnancy cycle and provides the information daily. The information providing unit can also create dietary management and menus for pregnant women that are good for the baby's growth and recommend apps. For example, the information providing unit can suggest nutritionally balanced meal menus based on the pregnant woman's health status. The information providing unit can also provide exercise programs tailored to the pregnant woman's lifestyle. Furthermore, the information providing unit can suggest relaxation methods to support the pregnant woman's mental health. The coaching unit provides childcare coaching based on the information provided by the information providing unit. Examples of childcare coaching include, but are not limited to, parenting techniques and parent-child communication methods. For example, the coaching unit can provide advice to support a child's learning methods. The coaching unit may also suggest specific methods for disciplining the child. Furthermore, the coaching unit may also suggest communication methods to support the building of parent-child relationships. For example, the coaching unit may provide ideas for collaborative activities and play to deepen the parent-child relationship. The monitoring unit monitors the child's growth based on the coaching provided by the coaching unit. Monitoring the child's growth may include, but is not limited to, growth indicators, data collection methods, and the like. For example, the monitoring unit may monitor the child's language development stage. The monitoring unit may also monitor the child's physical development. Furthermore, the monitoring unit may monitor the child's sleep and eating patterns. For example, the monitoring unit may provide advice on improving the child's sleep quality. The monitoring unit may also suggest a meal plan to manage the child's nutritional balance.As a result, the childcare support system according to the embodiment is capable of providing information during pregnancy and after birth, childcare coaching, and monitoring the growth of children.

[0030] The information providing unit can provide necessary information to fathers and mothers during pregnancy and after birth. Necessary information includes, but is not limited to, medical information, childcare information, and lifestyle information. For example, the information providing unit can provide pregnant fathers and mothers with health management advice according to the progress of the pregnancy. The information providing unit can also provide postpartum fathers and mothers with nutritional information necessary for the baby's growth. Furthermore, the information providing unit can suggest relaxation methods to support the mental health of fathers and mothers. For example, the information providing unit can suggest stress management methods to pregnant fathers and mothers. The information providing unit can also provide postpartum fathers and mothers with support information to reduce the burden of childcare. In this way, by providing necessary information to pregnant fathers and mothers and after birth, support for childcare is strengthened.

[0031] The coaching department can support a child's learning methods, discipline the child, and building a parent-child relationship. Examples of learning methods include, but are not limited to, practicing reading and writing, understanding number concepts, etc. The coaching department, for example, provides advice to support a child's learning methods. For example, the coaching department can suggest specific methods for a child to practice reading and writing. The coaching department can also suggest practice methods for a child to understand number concepts. Examples of discipline include, but are not limited to, etiquette and understanding rules. For example, the coaching department can suggest specific methods for disciplining a child. For example, the coaching department can suggest specific methods for a child to learn etiquette. The coaching department can also suggest discipline methods for a child to understand rules. Examples of building a parent-child relationship include, but are not limited to, collaborative activities and promoting communication. For example, the coaching department provides ideas for collaborative activities and games to deepen the parent-child relationship. For example, the coaching department can suggest activities that parents and children can enjoy together. The coaching department can also suggest specific methods to promote communication between parents and children, which will improve the quality of parenting by supporting children's learning methods, discipline, and parent-child relationship building.

[0032] The monitoring unit can monitor the child's language and physical development and provide support for sleep or diet. Examples of language and physical development include, but are not limited to, language development stages and physical development status. For example, the monitoring unit monitors the child's language development stages. For example, the monitoring unit records what words the child begins to use. The monitoring unit can also monitor the child's physical development status. For example, the monitoring unit records changes in the child's height and weight. Examples of support for sleep or diet include, but are not limited to, improving sleep quality and managing nutritional balance. For example, the monitoring unit provides advice for improving the child's sleep quality. For example, the monitoring unit suggests ways to create an environment that allows the child to get good quality sleep. The monitoring unit can also suggest a meal plan for managing the child's nutritional balance. For example, the monitoring unit suggests a meal menu that allows the child to consume necessary nutrients. In this way, monitoring the child's language and physical development and providing appropriate support promotes the child's healthy growth.

[0033] The information providing unit can create dietary management and menus for the pregnant woman that are good for the baby's growth and recommend recommended apps. Examples of dietary management and menus include, but are not limited to, nutritionally balanced meals and menus containing specific nutrients. For example, the information providing unit can suggest nutritionally balanced meal menus based on the health status of the pregnant woman. For example, the information providing unit can suggest meal menus that allow the pregnant woman to consume necessary nutrients. The information providing unit can also provide exercise programs tailored to the lifestyle of the pregnant woman. For example, the information providing unit can suggest exercise programs that the pregnant woman can continue without difficulty. Recommended apps include, but are not limited to, dietary management apps and health management apps. For example, the information providing unit can recommend apps that support dietary management to the pregnant woman. For example, the information providing unit can recommend apps that allow the pregnant woman to easily record her meals. The information providing unit can also recommend apps that support the health management of the pregnant woman. For example, the information providing unit can recommend apps that allow the pregnant woman to monitor her health status. This will improve health management for pregnant women by providing them with dietary management and menus that are good for their baby's growth and introducing them to appropriate apps.

[0034] The coaching unit can provide parenting coaching using generative AI. Examples of generative AI include, but are not limited to, natural language generation and image generation. The coaching unit can provide parenting coaching using generative AI. For example, the coaching unit can use generative AI to provide advice on children's learning methods. The coaching unit can also use generative AI to suggest specific methods for disciplining children. Furthermore, the coaching unit can use generative AI to suggest communication methods to support the building of parent-child relationships. For example, the coaching unit can use generative AI to provide ideas for collaborative activities and games to deepen parent-child relationships. In this way, the use of generative AI improves the accuracy of parenting coaching.

[0035] The information providing unit can analyze the user's past information browsing history and select an appropriate information provision method. For example, the information providing unit can prioritize providing information that the user frequently viewed in the past. For example, the information providing unit can select an information provision format (text, video, etc.) that the user previously preferred. The information providing unit can also select information to provide during a specific time period based on the user's past browsing history. Methods for analyzing the information browsing history include, but are not limited to, browsing frequency and browsing time. For example, the information providing unit can determine the priority of information provision based on the user's browsing frequency. The information providing unit can also adjust the timing of information provision based on the user's browsing time. Appropriate information provision methods include, but are not limited to, email notifications, in-app notifications, etc. For example, the information providing unit can provide information to the user using email notifications. The information providing unit can also provide information using in-app notifications. In this way, the optimal information provision method can be selected by analyzing the user's past information browsing history.

[0036] The information providing unit may perform filtering based on the user's current living situation and areas of interest when providing information. The information providing unit may, for example, prioritize information related to areas in which the user is currently interested. For example, the information providing unit may provide appropriate information according to the user's living situation (e.g., pregnancy, postpartum, etc.). The information providing unit may also provide information tailored to the user's current lifestyle. Examples of living situations and areas of interest include, but are not limited to, occupation, hobbies, and family structure. For example, the information providing unit may provide related information based on the user's occupation. The information providing unit may also provide related information based on the user's hobbies. Criteria for filtering information include, but are not limited to, highly relevant information and highly important information. For example, the information providing unit may prioritize information that is highly relevant to the user. The information providing unit may also prioritize information that is highly important to the user. In this way, more appropriate information can be provided by filtering information based on the user's current living situation and areas of interest.

[0037] When providing information, the information providing unit can prioritize providing highly relevant information based on the user's geographical location information. The information providing unit, for example, provides childcare information related to the area where the user is currently located. For example, the information providing unit can provide information about nearby childcare support facilities based on the user's geographical location. The information providing unit can also provide local childcare event information based on the user's geographical location. Examples of geographical location information include, but are not limited to, cities, regions, and countries. For example, the information providing unit can provide information related to the city in which the user lives. The information providing unit can also provide information related to the area in which the user lives. Examples of highly relevant information include, but are not limited to, local event information and local news. For example, the information providing unit can provide local event information that is highly relevant to the user. The information providing unit can also provide local news that is highly relevant to the user. In this way, highly relevant information can be provided by taking the user's geographical location information into consideration.

[0038] The information providing unit can analyze the user's social media activity and provide related information when providing information. The information providing unit can provide, for example, childcare information in which the user has shown interest on social media. For example, the information providing unit can analyze childcare topics of interest from the user's social media activity and provide related information. The information providing unit can also provide information on childcare experts the user follows. Social media activity includes, for example, but is not limited to, the content of posts, the number of likes, and comments. For example, the information providing unit can analyze the content of posts by the user to identify topics of interest. The information providing unit can also analyze the number of likes and comments by the user to provide information of interest. Related information can include, for example, but is not limited to, information on the same topic, related news, and the like. For example, the information providing unit can provide information on the same topic that is highly relevant to the user. The information providing unit can also provide related news that is highly relevant to the user. In this way, related information can be provided by analyzing the user's social media activity.

[0039] The coaching department can select an appropriate coaching method based on the child's age and developmental stage during coaching. For example, if the child is a toddler, the coaching department selects a coaching method that involves play. For example, if the child is an elementary school student, the coaching department can select a coaching method that involves learning. Furthermore, if the child is a junior high school student, the coaching department can select a coaching method that encourages self-management. Ages and developmental stages include, but are not limited to, infancy, early childhood, and school-age children. For example, the coaching department can suggest an experience-based learning method for infants. Furthermore, the coaching department can suggest a play-based learning method for toddlers. Appropriate coaching methods include, but are not limited to, learning through play and understanding rules. For example, the coaching department can suggest specific methods for children to learn through play. Furthermore, the coaching department can suggest a coaching method for children to understand rules. This enables more effective parenting coaching by selecting an optimal coaching method based on the child's age and developmental stage.

[0040] During coaching, the coaching unit can provide customized advice based on the user's past child-rearing experience. For example, the coaching unit provides advice by referring to the child-rearing methods that the user has used successfully in the past. For example, the coaching unit provides advice to help the user avoid child-rearing methods that have failed in the past. The coaching unit can also suggest optimal child-rearing methods based on the user's past child-rearing experience. Past child-rearing experience includes, but is not limited to, examples of past child-rearing successes and failures. For example, the coaching unit can analyze the user's past child-rearing successes and provide advice for similar situations. The coaching unit can also analyze the user's past child-rearing failures and provide advice to avoid similar failures in similar situations. Customized advice includes, but is not limited to, solutions to individual problems and advice tailored to specific situations. For example, the coaching unit can suggest specific solutions to the user's individual problems. The coaching unit can also provide advice tailored to the user's specific situations. This makes it possible to provide more appropriate advice by taking the user's past child-rearing experience into consideration.

[0041] During coaching, the coaching unit may select an appropriate coaching method based on the child's learning style. For example, if the child is a visual learner, the coaching unit may select a coaching method using visual aids. For example, if the child is an auditory learner, the coaching unit may select a coaching method that emphasizes audio. Furthermore, if the child is an experiential learner, the coaching unit may select a coaching method through hands-on experience. Learning styles include, but are not limited to, visual, auditory, and experiential. For example, the coaching unit may suggest a coaching method using visual learning materials based on the child's visual learning style. Furthermore, the coaching unit may suggest a coaching method that emphasizes audio based on the child's auditory learning style. Appropriate coaching methods include, but are not limited to, the use of visual learning materials, practical activities, and the like. For example, the coaching unit may suggest a specific method for the child to learn visually. Furthermore, the coaching unit may suggest a coaching method for the child to learn through hands-on experience. This enables more effective parenting coaching by selecting an optimal coaching method based on the child's learning style.

[0042] During coaching, the coaching unit can provide advice at optimal timing based on the user's lifestyle rhythm. For example, if the user is a morning person, the coaching unit provides advice in the morning. For example, if the user is a night owl, the coaching unit provides advice in the evening. The coaching unit can also provide advice at optimal timing in accordance with the user's lifestyle rhythm. Lifestyle rhythms include, but are not limited to, sleep times, meal times, and activity times. For example, the coaching unit can adjust the timing of advice based on the user's sleep times. The coaching unit can also adjust the timing of advice based on the user's meal times. The optimal timing includes, but is not limited to, the user's activity pattern and past behavior history. For example, the coaching unit can adjust the timing of advice based on the user's activity pattern. The coaching unit can also adjust the timing of advice based on the user's past behavior history. This enables more effective parenting coaching by providing advice at optimal timing based on the user's lifestyle rhythm.

[0043] During monitoring, the monitoring unit can analyze the child's health condition in real time and provide appropriate advice. For example, the monitoring unit can monitor the child's body temperature in real time and provide advice if an abnormality is detected. For example, the monitoring unit can monitor the child's sleep patterns in real time and provide appropriate sleep advice. The monitoring unit can also monitor the child's diet in real time and provide advice on nutritional balance. Methods for analyzing the health condition in real time include, but are not limited to, vital sign monitoring and behavior analysis. For example, the monitoring unit can monitor the child's vital signs and issue an alert if an abnormality is detected. The monitoring unit can also analyze the child's behavior and evaluate the health condition. Appropriate advice can include, but is not limited to, health management methods and lifestyle improvement measures. For example, the monitoring unit can suggest specific methods for managing the child's health. The monitoring unit can also provide advice for improving the child's lifestyle. This improves child health management by analyzing the child's health condition in real time and providing appropriate advice.

[0044] The monitoring unit can select an optimal monitoring method based on the child's developmental stage during monitoring. For example, if the child is an infant, the monitoring unit can prioritize monitoring of weight and height. For example, if the child is a toddler, the monitoring unit can prioritize monitoring of language development. Furthermore, if the child is an elementary school student, the monitoring unit can also prioritize monitoring of learning progress. Developmental stages include, but are not limited to, infancy, early childhood, and school-age children. For example, the monitoring unit can record changes in weight and height during the child's infancy. Furthermore, the monitoring unit can record the child's language development stage during the toddler stage. Optimal monitoring methods include, but are not limited to, regular health checks and behavioral observations. For example, the monitoring unit can regularly check the child's health. Furthermore, the monitoring unit can observe the child's behavior and evaluate the child's developmental status. This enables more effective monitoring by selecting an optimal monitoring method based on the child's developmental stage.

[0045] The monitoring unit may collect data based on the child's geographical environment during monitoring. For example, if the child lives in an urban area, the monitoring unit may collect data taking into account environmental factors specific to the city. For example, if the child lives in a rural area, the monitoring unit may collect data taking into account environmental factors specific to the rural area. Furthermore, if the child lives overseas, the monitoring unit may collect data taking into account environmental factors of the local area. Examples of geographical environments include, but are not limited to, urban areas, rural areas, and climate conditions. For example, the monitoring unit may collect environmental data for the urban area where the child lives. Furthermore, the monitoring unit may collect environmental data for the rural area where the child lives. Methods of collecting data include, but are not limited to, environmental data, health data, and the like. For example, the monitoring unit may collect data regarding the child's living environment to evaluate the child's health condition. Furthermore, the monitoring unit may collect data regarding the child's living environment to evaluate the child's growth status. This enables more appropriate monitoring by collecting data taking into account the child's geographical environment.

[0046] During monitoring, the monitoring unit may analyze the child's social media activities and collect related data. For example, the monitoring unit may monitor the child's health status based on information shared by the child on social media. For example, the monitoring unit may analyze the child's interests from the child's social media activities and collect related data. The monitoring unit may also collect information on influences from accounts the child follows on social media. Social media activities include, but are not limited to, the content of posts, the number of likes, and comments. For example, the monitoring unit may analyze the content of the child's posts to assess the child's health status. The monitoring unit may also analyze the number of likes and comments of the child to identify the child's interests. Related data may include, but are not limited to, data on the same topic and related news. For example, the monitoring unit may collect data on topics in which the child is interested. The monitoring unit may also collect information on the child's influences. This allows for more appropriate monitoring by collecting related data through analysis of the child's social media activities.

[0047] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0048] The information providing unit can analyze the user's past child-rearing experience and provide success stories of other users in similar situations. For example, the information providing unit can identify child-rearing problems the user has experienced in the past and introduce cases of other users who have solved similar problems. The information providing unit can also refer to the child-rearing methods that the user has used successfully in the past and suggest similar methods to other users. Furthermore, the information providing unit can provide information that will be useful in the future based on the user's past child-rearing experience. This makes it possible to provide more effective information by utilizing the user's past child-rearing experience.

[0049] The monitoring unit can monitor a child's health condition in real time and issue an alert if an abnormality is detected. For example, if a child's body temperature is abnormally high, an alert can be issued to provide appropriate countermeasures. Also, if a child's heart rate is abnormally low, an alert can be issued to encourage the child to visit a medical institution. Furthermore, if an abnormality is detected in a child's sleep pattern, an alert can be issued to suggest improvements to the sleep environment. This makes it possible to monitor a child's health condition in real time and respond quickly.

[0050] The coaching unit can analyze the user's past child-rearing experience and provide customized advice. For example, the coaching unit can provide advice for similar situations by referring to the child-rearing methods that the user has used successfully in the past. The coaching unit can also provide advice to help the user avoid child-rearing methods that have failed in the past. Furthermore, the coaching unit can suggest optimal child-rearing methods based on the user's past child-rearing experience. This makes it possible to provide customized advice that takes the user's past child-rearing experience into consideration.

[0051] The information providing unit can provide region-specific childcare information based on the user's geographical location information. For example, if the user lives in an urban area, city-specific childcare support facility and event information can be provided. If the user lives in a rural area, rural childcare information and community support information can be provided. Furthermore, if the user lives overseas, childcare information and support services for that region can also be provided. This makes it possible to provide appropriate childcare information that takes into account the user's geographical location information.

[0052] The monitoring unit can select the optimal monitoring method based on the child's developmental stage. For example, if the child is an infant, emphasis can be placed on monitoring weight and height. If the child is a toddler, emphasis can be placed on monitoring language development. Furthermore, if the child is an elementary school student, emphasis can be placed on monitoring learning progress. This allows for more effective monitoring by selecting the optimal monitoring method based on the child's developmental stage.

[0053] The processing flow of the first embodiment will be briefly explained below.

[0054] Step 1: The information provider provides information on pregnancy and postpartum. This information includes health management, nutrition, exercise, and mental health. For example, the information provider creates a database of things that moms and dads should do and be careful of according to the pregnancy cycle, and provides this information daily. The information provider can also create dietary management and menus that are good for the baby's development for pregnant women, and introduce recommended apps. Furthermore, the information provider can suggest nutritionally balanced meal menus based on the pregnant woman's health status, and provide exercise programs that fit her lifestyle and relaxation methods to support her mental health. Step 2: The coaching department provides parenting coaching based on the information provided by the information provider. Parenting coaching includes parenting techniques and parent-child communication methods. For example, it provides advice on how to support children's learning and suggests specific methods for disciplining children. It also provides ideas for collaborative activities and play to deepen parent-child relationships. Step 3: The monitoring department monitors the child's growth based on the coaching provided by the coaching department. Monitoring the child's growth includes growth indicators and data collection methods. For example, the department monitors the child's language development stage, physical development, sleep, and eating patterns. In addition, the department can provide advice on improving the child's sleep quality and propose a meal plan to manage nutritional balance.

[0055] (Example 2) A childcare support system according to an embodiment of the present invention utilizes generative AI to provide parenting coaching and support to parents struggling with childcare, thereby addressing Japan's trend toward later marriage. This childcare support system includes an information provider that provides information during pregnancy and after childbirth, a coaching unit that provides parenting coaching based on the information provided by the information provider, and a monitoring unit that monitors the child's growth based on the coaching provided by the coaching unit. For example, a database of tasks and precautions for parents according to the pregnancy cycle is compiled and provided daily. Specifically, the system creates dietary management and menus for pregnant women that are beneficial for the baby's growth and recommends recommended apps. After birth, the system provides parents with information necessary for the baby's diet and growth. Next, the system provides parenting coaching to parents. Specifically, the system supports the child's learning methods, child discipline, and parent-child relationship building. Furthermore, the system monitors the child's growth and supports language and physical development through sleep, diet, and other aspects. This system reduces the burden of childcare, allowing parents to focus on childcare with peace of mind. Furthermore, through childcare support, the system contributes to addressing Japan's trend toward later marriage. This system will reduce the burden of childcare and allow parents to focus on raising their children with peace of mind. Furthermore, through childcare support, it will also contribute to addressing Japan's trend of late marriage.

[0056] A childcare support system according to an embodiment includes an information providing unit, a coaching unit, and a monitoring unit. The information providing unit provides information during pregnancy and after birth. Examples of information during pregnancy and after birth include, but are not limited to, health management, nutrition, exercise, and mental health. The information providing unit, for example, creates a database of tasks and precautions for moms and dads according to the pregnancy cycle and provides the information daily. The information providing unit can also create dietary management and menus for pregnant women that are good for the baby's growth and recommend apps. For example, the information providing unit can suggest nutritionally balanced meal menus based on the pregnant woman's health status. The information providing unit can also provide exercise programs tailored to the pregnant woman's lifestyle. Furthermore, the information providing unit can suggest relaxation methods to support the pregnant woman's mental health. The coaching unit provides childcare coaching based on the information provided by the information providing unit. Examples of childcare coaching include, but are not limited to, parenting techniques and parent-child communication methods. For example, the coaching unit can provide advice to support a child's learning methods. The coaching unit may also suggest specific methods for disciplining the child. Furthermore, the coaching unit may also suggest communication methods to support the building of parent-child relationships. For example, the coaching unit may provide ideas for collaborative activities and play to deepen the parent-child relationship. The monitoring unit monitors the child's growth based on the coaching provided by the coaching unit. Monitoring the child's growth may include, but is not limited to, growth indicators, data collection methods, and the like. For example, the monitoring unit may monitor the child's language development stage. The monitoring unit may also monitor the child's physical development. Furthermore, the monitoring unit may monitor the child's sleep and eating patterns. For example, the monitoring unit may provide advice on improving the child's sleep quality. The monitoring unit may also suggest a meal plan to manage the child's nutritional balance.As a result, the childcare support system according to the embodiment is capable of providing information during pregnancy and after birth, childcare coaching, and monitoring the growth of children.

[0057] The information providing unit can provide necessary information to fathers and mothers during pregnancy and after birth. Necessary information includes, but is not limited to, medical information, childcare information, and lifestyle information. For example, the information providing unit can provide pregnant fathers and mothers with health management advice according to the progress of the pregnancy. The information providing unit can also provide postpartum fathers and mothers with nutritional information necessary for the baby's growth. Furthermore, the information providing unit can suggest relaxation methods to support the mental health of fathers and mothers. For example, the information providing unit can suggest stress management methods to pregnant fathers and mothers. The information providing unit can also provide postpartum fathers and mothers with support information to reduce the burden of childcare. In this way, by providing necessary information to pregnant fathers and mothers and after birth, support for childcare is strengthened.

[0058] The coaching department can support a child's learning methods, discipline the child, and building a parent-child relationship. Examples of learning methods include, but are not limited to, practicing reading and writing, understanding number concepts, etc. The coaching department, for example, provides advice to support a child's learning methods. For example, the coaching department can suggest specific methods for a child to practice reading and writing. The coaching department can also suggest practice methods for a child to understand number concepts. Examples of discipline include, but are not limited to, etiquette and understanding rules. For example, the coaching department can suggest specific methods for disciplining a child. For example, the coaching department can suggest specific methods for a child to learn etiquette. The coaching department can also suggest discipline methods for a child to understand rules. Examples of building a parent-child relationship include, but are not limited to, collaborative activities and promoting communication. For example, the coaching department provides ideas for collaborative activities and games to deepen the parent-child relationship. For example, the coaching department can suggest activities that parents and children can enjoy together. The coaching department can also suggest specific methods to promote communication between parents and children, which will improve the quality of parenting by supporting children's learning methods, discipline, and parent-child relationship building.

[0059] The monitoring unit can monitor the child's language and physical development and provide support for sleep or diet. Examples of language and physical development include, but are not limited to, language development stages and physical development status. For example, the monitoring unit monitors the child's language development stages. For example, the monitoring unit records what words the child begins to use. The monitoring unit can also monitor the child's physical development status. For example, the monitoring unit records changes in the child's height and weight. Examples of support for sleep or diet include, but are not limited to, improving sleep quality and managing nutritional balance. For example, the monitoring unit provides advice for improving the child's sleep quality. For example, the monitoring unit suggests ways to create an environment that allows the child to get good quality sleep. The monitoring unit can also suggest a meal plan for managing the child's nutritional balance. For example, the monitoring unit suggests a meal menu that allows the child to consume necessary nutrients. In this way, monitoring the child's language and physical development and providing appropriate support promotes the child's healthy growth.

[0060] The information providing unit can create dietary management and menus for the pregnant woman that are good for the baby's growth and recommend recommended apps. Examples of dietary management and menus include, but are not limited to, nutritionally balanced meals and menus containing specific nutrients. For example, the information providing unit can suggest nutritionally balanced meal menus based on the health status of the pregnant woman. For example, the information providing unit can suggest meal menus that allow the pregnant woman to consume necessary nutrients. The information providing unit can also provide exercise programs tailored to the lifestyle of the pregnant woman. For example, the information providing unit can suggest exercise programs that the pregnant woman can continue without difficulty. Recommended apps include, but are not limited to, dietary management apps and health management apps. For example, the information providing unit can recommend apps that support dietary management to the pregnant woman. For example, the information providing unit can recommend apps that allow the pregnant woman to easily record her meals. The information providing unit can also recommend apps that support the health management of the pregnant woman. For example, the information providing unit can recommend apps that allow the pregnant woman to monitor her health status. This will improve health management for pregnant women by providing them with dietary management and menus that are good for their baby's growth and introducing them to appropriate apps.

[0061] The coaching unit can provide parenting coaching using generative AI. Examples of generative AI include, but are not limited to, natural language generation and image generation. The coaching unit can provide parenting coaching using generative AI. For example, the coaching unit can use generative AI to provide advice on children's learning methods. The coaching unit can also use generative AI to suggest specific methods for disciplining children. Furthermore, the coaching unit can use generative AI to suggest communication methods to support the building of parent-child relationships. For example, the coaching unit can use generative AI to provide ideas for collaborative activities and games to deepen parent-child relationships. In this way, the use of generative AI improves the accuracy of parenting coaching.

[0062] The information providing unit can estimate the user's emotions and adjust the timing of information provision based on the estimated user's emotions. For example, if the user is feeling stressed, the information providing unit can provide information during a time period when the user is able to relax. For example, if the user is relaxed, the information providing unit can provide detailed information. Furthermore, if the user is busy, the information providing unit can provide concise information. Methods for estimating the user's emotions include, but are not limited to, facial expression recognition and voice analysis. For example, the information providing unit can capture the user's facial expression with a camera and estimate the emotion using an emotion estimation algorithm. Furthermore, the information providing unit can record the user's voice and estimate the emotion using voice analysis technology. Criteria for adjusting the timing of information provision include, but are not limited to, the user's emotional state and past behavioral patterns. For example, the information providing unit can adjust the timing of information provision based on the user's emotional state. Furthermore, the information providing unit can adjust the timing of information provision based on the user's past behavioral patterns. In this way, by adjusting the timing of information provision according to the user's emotions, information can be provided at a more appropriate time.

[0063] The information providing unit can analyze the user's past information browsing history and select an appropriate information provision method. For example, the information providing unit can prioritize providing information that the user frequently viewed in the past. For example, the information providing unit can select an information provision format (text, video, etc.) that the user previously preferred. The information providing unit can also select information to provide during a specific time period based on the user's past browsing history. Methods for analyzing the information browsing history include, but are not limited to, browsing frequency and browsing time. For example, the information providing unit can determine the priority of information provision based on the user's browsing frequency. The information providing unit can also adjust the timing of information provision based on the user's browsing time. Appropriate information provision methods include, but are not limited to, email notifications, in-app notifications, etc. For example, the information providing unit can provide information to the user using email notifications. The information providing unit can also provide information using in-app notifications. In this way, the optimal information provision method can be selected by analyzing the user's past information browsing history.

[0064] The information providing unit may perform filtering based on the user's current living situation and areas of interest when providing information. The information providing unit may, for example, prioritize information related to areas in which the user is currently interested. For example, the information providing unit may provide appropriate information according to the user's living situation (e.g., pregnancy, postpartum, etc.). The information providing unit may also provide information tailored to the user's current lifestyle. Examples of living situations and areas of interest include, but are not limited to, occupation, hobbies, and family structure. For example, the information providing unit may provide related information based on the user's occupation. The information providing unit may also provide related information based on the user's hobbies. Criteria for filtering information include, but are not limited to, highly relevant information and highly important information. For example, the information providing unit may prioritize information that is highly relevant to the user. The information providing unit may also prioritize information that is highly important to the user. In this way, more appropriate information can be provided by filtering information based on the user's current living situation and areas of interest.

[0065] The information providing unit can estimate the user's emotions and determine the priority of information to be provided based on the estimated user's emotions. For example, when the user is feeling stressed, the information providing unit can prioritize providing information that helps the user relax. For example, when the user is relaxed, the information providing unit can prioritize providing detailed information. Furthermore, when the user is busy, the information providing unit can also prioritize providing concise information. Criteria for determining the priority of information include, but are not limited to, urgency and importance. For example, the information providing unit can prioritize providing information that is highly urgent to the user. Furthermore, the information providing unit can prioritize providing information that is highly important to the user. In this way, by determining the priority of information to be provided according to the user's emotions, more appropriate information can be provided.

[0066] When providing information, the information providing unit can prioritize providing highly relevant information based on the user's geographical location information. The information providing unit, for example, provides childcare information related to the area where the user is currently located. For example, the information providing unit can provide information about nearby childcare support facilities based on the user's geographical location. The information providing unit can also provide local childcare event information based on the user's geographical location. Examples of geographical location information include, but are not limited to, cities, regions, and countries. For example, the information providing unit can provide information related to the city in which the user lives. The information providing unit can also provide information related to the area in which the user lives. Examples of highly relevant information include, but are not limited to, local event information and local news. For example, the information providing unit can provide local event information that is highly relevant to the user. The information providing unit can also provide local news that is highly relevant to the user. In this way, highly relevant information can be provided by taking the user's geographical location information into consideration.

[0067] The information providing unit can analyze the user's social media activity and provide related information when providing information. The information providing unit can provide, for example, childcare information in which the user has shown interest on social media. For example, the information providing unit can analyze childcare topics of interest from the user's social media activity and provide related information. The information providing unit can also provide information on childcare experts the user follows. Social media activity includes, for example, but is not limited to, the content of posts, the number of likes, and comments. For example, the information providing unit can analyze the content of posts by the user to identify topics of interest. The information providing unit can also analyze the number of likes and comments by the user to provide information of interest. Related information can include, for example, but is not limited to, information on the same topic, related news, and the like. For example, the information providing unit can provide information on the same topic that is highly relevant to the user. The information providing unit can also provide related news that is highly relevant to the user. In this way, related information can be provided by analyzing the user's social media activity.

[0068] The coaching unit can estimate the user's emotions and adjust the coaching expression method based on the estimated user's emotions. For example, if the user is feeling stressed, the coaching unit can provide coaching in a way that allows the user to relax. For example, if the user is relaxed, the coaching unit can provide coaching in a detailed way. Furthermore, if the user is busy, the coaching unit can provide coaching in a concise way. Criteria for adjusting the coaching expression method include, but are not limited to, the wording, tone, and depth of content. For example, the coaching unit can adjust the wording and tone based on the user's emotional state. Furthermore, the coaching unit can adjust the depth of content based on the user's emotional state. This enables more effective coaching by adjusting the coaching expression method according to the user's emotions.

[0069] The coaching department can select an appropriate coaching method based on the child's age and developmental stage during coaching. For example, if the child is a toddler, the coaching department selects a coaching method that involves play. For example, if the child is an elementary school student, the coaching department can select a coaching method that involves learning. Furthermore, if the child is a junior high school student, the coaching department can select a coaching method that encourages self-management. Ages and developmental stages include, but are not limited to, infancy, early childhood, and school-age children. For example, the coaching department can suggest an experience-based learning method for infants. Furthermore, the coaching department can suggest a play-based learning method for toddlers. Appropriate coaching methods include, but are not limited to, learning through play and understanding rules. For example, the coaching department can suggest specific methods for children to learn through play. Furthermore, the coaching department can suggest a coaching method for children to understand rules. This enables more effective parenting coaching by selecting an optimal coaching method based on the child's age and developmental stage.

[0070] During coaching, the coaching unit can provide customized advice based on the user's past child-rearing experience. For example, the coaching unit provides advice by referring to the child-rearing methods that the user has used successfully in the past. For example, the coaching unit provides advice to help the user avoid child-rearing methods that have failed in the past. The coaching unit can also suggest optimal child-rearing methods based on the user's past child-rearing experience. Past child-rearing experience includes, but is not limited to, examples of past child-rearing successes and failures. For example, the coaching unit can analyze the user's past child-rearing successes and provide advice for similar situations. The coaching unit can also analyze the user's past child-rearing failures and provide advice to avoid similar failures in similar situations. Customized advice includes, but is not limited to, solutions to individual problems and advice tailored to specific situations. For example, the coaching unit can suggest specific solutions to the user's individual problems. The coaching unit can also provide advice tailored to the user's specific situations. This makes it possible to provide more appropriate advice by taking the user's past child-rearing experience into consideration.

[0071] The coaching unit can estimate the user's emotions and adjust the length of coaching based on the estimated user's emotions. For example, the coaching unit provides a short coaching session when the user is stressed. For example, the coaching unit provides a long coaching session when the user is relaxed. The coaching unit can also provide a brief coaching session when the user is busy. Criteria for adjusting the length of coaching include, but are not limited to, the user's concentration level and the complexity of the content. For example, the coaching unit adjusts the length of coaching based on the user's concentration level. The coaching unit can also adjust the length of coaching based on the complexity of the coaching content. This enables more effective coaching by adjusting the length of coaching according to the user's emotions.

[0072] During coaching, the coaching unit may select an appropriate coaching method based on the child's learning style. For example, if the child is a visual learner, the coaching unit may select a coaching method using visual aids. For example, if the child is an auditory learner, the coaching unit may select a coaching method that emphasizes audio. Furthermore, if the child is an experiential learner, the coaching unit may select a coaching method through hands-on experience. Learning styles include, but are not limited to, visual, auditory, and experiential. For example, the coaching unit may suggest a coaching method using visual learning materials based on the child's visual learning style. Furthermore, the coaching unit may suggest a coaching method that emphasizes audio based on the child's auditory learning style. Appropriate coaching methods include, but are not limited to, the use of visual learning materials, practical activities, and the like. For example, the coaching unit may suggest a specific method for the child to learn visually. Furthermore, the coaching unit may suggest a coaching method for the child to learn through hands-on experience. This enables more effective parenting coaching by selecting an optimal coaching method based on the child's learning style.

[0073] During coaching, the coaching unit can provide advice at optimal timing based on the user's lifestyle rhythm. For example, if the user is a morning person, the coaching unit provides advice in the morning. For example, if the user is a night owl, the coaching unit provides advice in the evening. The coaching unit can also provide advice at optimal timing in accordance with the user's lifestyle rhythm. Lifestyle rhythms include, but are not limited to, sleep times, meal times, and activity times. For example, the coaching unit can adjust the timing of advice based on the user's sleep times. The coaching unit can also adjust the timing of advice based on the user's meal times. The optimal timing includes, but is not limited to, the user's activity pattern and past behavior history. For example, the coaching unit can adjust the timing of advice based on the user's activity pattern. The coaching unit can also adjust the timing of advice based on the user's past behavior history. This enables more effective parenting coaching by providing advice at optimal timing based on the user's lifestyle rhythm.

[0074] The monitoring unit can estimate the user's emotions and adjust the monitoring frequency based on the estimated user's emotions. For example, the monitoring unit reduces the monitoring frequency when the user is feeling stressed. For example, the monitoring unit increases the monitoring frequency when the user is relaxed. The monitoring unit can also adjust the monitoring frequency when the user is busy. Criteria for adjusting the monitoring frequency include, but are not limited to, the user's emotional state and past monitoring results. For example, the monitoring unit adjusts the monitoring frequency based on the user's emotional state. The monitoring unit can also adjust the monitoring frequency based on the user's past monitoring results. This enables more appropriate monitoring by adjusting the monitoring frequency according to the user's emotions.

[0075] During monitoring, the monitoring unit can analyze the child's health condition in real time and provide appropriate advice. For example, the monitoring unit can monitor the child's body temperature in real time and provide advice if an abnormality is detected. For example, the monitoring unit can monitor the child's sleep patterns in real time and provide appropriate sleep advice. The monitoring unit can also monitor the child's diet in real time and provide advice on nutritional balance. Methods for analyzing the health condition in real time include, but are not limited to, vital sign monitoring and behavior analysis. For example, the monitoring unit can monitor the child's vital signs and issue an alert if an abnormality is detected. The monitoring unit can also analyze the child's behavior and evaluate the health condition. Appropriate advice can include, but is not limited to, health management methods and lifestyle improvement measures. For example, the monitoring unit can suggest specific methods for managing the child's health. The monitoring unit can also provide advice for improving the child's lifestyle. This improves child health management by analyzing the child's health condition in real time and providing appropriate advice.

[0076] The monitoring unit can select an optimal monitoring method based on the child's developmental stage during monitoring. For example, if the child is an infant, the monitoring unit can prioritize monitoring of weight and height. For example, if the child is a toddler, the monitoring unit can prioritize monitoring of language development. Furthermore, if the child is an elementary school student, the monitoring unit can also prioritize monitoring of learning progress. Developmental stages include, but are not limited to, infancy, early childhood, and school-age children. For example, the monitoring unit can record changes in weight and height during the child's infancy. Furthermore, the monitoring unit can record the child's language development stage during the toddler stage. Optimal monitoring methods include, but are not limited to, regular health checks and behavioral observations. For example, the monitoring unit can regularly check the child's health. Furthermore, the monitoring unit can observe the child's behavior and evaluate the child's developmental status. This enables more effective monitoring by selecting an optimal monitoring method based on the child's developmental stage.

[0077] The monitoring unit can estimate the user's emotions and adjust the order in which the monitoring results are displayed based on the estimated user's emotions. For example, if the user is feeling stressed, the monitoring unit can display important results first. For example, if the user is relaxed, the monitoring unit can display detailed results. Furthermore, if the user is busy, the monitoring unit can also display concise results first. Criteria for adjusting the order in which the monitoring results are displayed include, but are not limited to, importance and urgency. For example, the monitoring unit can prioritize displaying results that are highly important to the user. Furthermore, the monitoring unit can prioritize displaying results that are highly urgent to the user. In this way, by adjusting the order in which the monitoring results are displayed according to the user's emotions, more appropriate information can be provided.

[0078] The monitoring unit may collect data based on the child's geographical environment during monitoring. For example, if the child lives in an urban area, the monitoring unit may collect data taking into account environmental factors specific to the city. For example, if the child lives in a rural area, the monitoring unit may collect data taking into account environmental factors specific to the rural area. Furthermore, if the child lives overseas, the monitoring unit may collect data taking into account environmental factors of the local area. Examples of geographical environments include, but are not limited to, urban areas, rural areas, and climate conditions. For example, the monitoring unit may collect environmental data for the urban area where the child lives. Furthermore, the monitoring unit may collect environmental data for the rural area where the child lives. Methods of collecting data include, but are not limited to, environmental data, health data, and the like. For example, the monitoring unit may collect data regarding the child's living environment to evaluate the child's health condition. Furthermore, the monitoring unit may collect data regarding the child's living environment to evaluate the child's growth status. This enables more appropriate monitoring by collecting data taking into account the child's geographical environment.

[0079] During monitoring, the monitoring unit may analyze the child's social media activities and collect related data. For example, the monitoring unit may monitor the child's health status based on information shared by the child on social media. For example, the monitoring unit may analyze the child's interests from the child's social media activities and collect related data. The monitoring unit may also collect information on influences from accounts the child follows on social media. Social media activities include, but are not limited to, the content of posts, the number of likes, and comments. For example, the monitoring unit may analyze the content of the child's posts to assess the child's health status. The monitoring unit may also analyze the number of likes and comments of the child to identify the child's interests. Related data may include, but are not limited to, data on the same topic and related news. For example, the monitoring unit may collect data on topics in which the child is interested. The monitoring unit may also collect information on the child's influences. This allows for more appropriate monitoring by collecting related data through analysis of the child's social media activities. === Hard Collateral 1-1 === Each of the multiple elements including the information providing unit, coaching unit, and monitoring unit described above is realized, for example, by at least one of the smart device 14 and the data processing device 12. For example, the information providing unit is realized by the control unit 46A of the smart device 14 and provides information during pregnancy and after childbirth. The coaching unit is realized, for example, by the specific processing unit 290 of the data processing device 12 and provides coaching on child rearing. The monitoring unit is realized, for example, by the control unit 46A of the smart device 14 and monitors the child's growth. === Hard Collateral 1-2 === Each of the multiple elements including the information providing unit, coaching unit, and monitoring unit described above is realized, for example, by at least one of the smart glasses 214 and the data processing device 12. For example, the information providing unit is realized by the control unit 46A of the smart glasses 214 and provides information during pregnancy and after childbirth. The coaching unit is realized, for example, by the specific processing unit 290 of the data processing device 12 and provides coaching for child rearing. The monitoring unit is realized, for example, by the control unit 46A of the smart glasses 214 and monitors the child's growth. === Hard Collateral 1-3 === Each of the multiple elements including the information providing unit, coaching unit, and monitoring unit described above is realized, for example, by at least one of the headset type terminal 314 and the data processing device 12. For example, the information providing unit is realized by the control unit 46A of the headset type terminal 314 and provides information during pregnancy and after childbirth. The coaching unit is realized, for example, by the specific processing unit 290 of the data processing device 12 and provides coaching on child rearing. The monitoring unit is realized, for example, by the control unit 46A of the headset type terminal 314 and monitors the growth of the child. === Hard Collateral 1-4 === Each of the multiple elements including the information providing unit, coaching unit, and monitoring unit described above is realized, for example, by at least one of the robot 414 and the data processing device 12. For example, the information providing unit is realized by the control unit 46A of the robot 414 and provides information during pregnancy and after childbirth. The coaching unit is realized, for example, by the specific processing unit 290 of the data processing device 12 and provides coaching on child rearing. The monitoring unit is realized, for example, by the control unit 46A of the robot 414 and monitors the growth of the child.

[0080] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0081] The information providing unit can analyze the user's past child-rearing experience and provide success stories of other users in similar situations. For example, the information providing unit can identify child-rearing problems the user has experienced in the past and introduce cases of other users who have solved similar problems. The information providing unit can also refer to the child-rearing methods that the user has used successfully in the past and suggest similar methods to other users. Furthermore, the information providing unit can provide information that will be useful in the future based on the user's past child-rearing experience. This makes it possible to provide more effective information by utilizing the user's past child-rearing experience.

[0082] The coaching unit can estimate the user's emotions and customize the content of coaching based on the estimated user emotions. For example, if the user is feeling stressed, it can prioritize providing content that helps the user relax. Also, if the user is relaxed, it can provide more detailed coaching content. Furthermore, if the user is busy, it can provide concise and effective coaching content. This allows for more effective parenting coaching by adjusting the content of coaching according to the user's emotions.

[0083] The monitoring unit can monitor a child's health condition in real time and issue an alert if an abnormality is detected. For example, if a child's body temperature is abnormally high, an alert can be issued to provide appropriate countermeasures. Also, if a child's heart rate is abnormally low, an alert can be issued to encourage the child to visit a medical institution. Furthermore, if an abnormality is detected in a child's sleep pattern, an alert can be issued to suggest improvements to the sleep environment. This makes it possible to monitor a child's health condition in real time and respond quickly.

[0084] The information providing unit can estimate the user's emotions and adjust the format of information provision based on the estimated user's emotions. For example, if the user is feeling stressed, visually relaxing images or videos can be provided. If the user is relaxed, detailed text information can be provided. Furthermore, if the user is busy, concise summary information can be provided. In this way, by adjusting the format of information provision according to the user's emotions, more effective information provision is possible.

[0085] The coaching unit can analyze the user's past child-rearing experience and provide customized advice. For example, the coaching unit can provide advice for similar situations by referring to the child-rearing methods that the user has used successfully in the past. The coaching unit can also provide advice to help the user avoid child-rearing methods that have failed in the past. Furthermore, the coaching unit can suggest optimal child-rearing methods based on the user's past child-rearing experience. This makes it possible to provide customized advice that takes the user's past child-rearing experience into consideration.

[0086] The monitoring unit can estimate the user's emotions and adjust the monitoring frequency based on the estimated user's emotions. For example, if the user is feeling stressed, the monitoring frequency can be reduced. Also, if the user is relaxed, the monitoring frequency can be increased. Furthermore, if the user is busy, the monitoring frequency can be adjusted. In this way, more appropriate monitoring can be achieved by adjusting the monitoring frequency according to the user's emotions.

[0087] The information providing unit can provide region-specific childcare information based on the user's geographical location information. For example, if the user lives in an urban area, city-specific childcare support facility and event information can be provided. If the user lives in a rural area, rural childcare information and community support information can be provided. Furthermore, if the user lives overseas, childcare information and support services for that region can also be provided. This makes it possible to provide appropriate childcare information that takes into account the user's geographical location information.

[0088] The coaching unit can estimate the user's emotions and adjust the coaching expression method based on the estimated user's emotions. For example, if the user is feeling stressed, coaching can be performed using expressions that will help the user relax. If the user is relaxed, coaching can be performed using detailed expressions. Furthermore, if the user is busy, coaching can be performed using concise expressions. This allows for more effective coaching by adjusting the coaching expression method according to the user's emotions.

[0089] The monitoring unit can select the optimal monitoring method based on the child's developmental stage. For example, if the child is an infant, emphasis can be placed on monitoring weight and height. If the child is a toddler, emphasis can be placed on monitoring language development. Furthermore, if the child is an elementary school student, emphasis can be placed on monitoring learning progress. This allows for more effective monitoring by selecting the optimal monitoring method based on the child's developmental stage.

[0090] The information providing unit can estimate the user's emotions and determine the priority of information to be provided based on the estimated user's emotions. For example, if the user is feeling stressed, information that helps the user to relax can be provided preferentially. Also, if the user is relaxed, detailed information can be provided preferentially. Furthermore, if the user is busy, concise information can be provided preferentially. In this way, by determining the priority of information to be provided according to the user's emotions, more appropriate information can be provided.

[0091] The processing flow of the second embodiment will be briefly explained below.

[0092] Step 1: The information provider provides information on pregnancy and postpartum. This information includes health management, nutrition, exercise, and mental health. For example, the information provider creates a database of things that moms and dads should do and be careful of according to the pregnancy cycle, and provides this information daily. The information provider can also create dietary management and menus that are good for the baby's development for pregnant women, and introduce recommended apps. Furthermore, the information provider can suggest nutritionally balanced meal menus based on the pregnant woman's health status, and provide exercise programs that fit her lifestyle and relaxation methods to support her mental health. Step 2: The coaching department provides parenting coaching based on the information provided by the information provider. Parenting coaching includes parenting techniques and parent-child communication methods. For example, it provides advice on how to support children's learning and suggests specific methods for disciplining children. It also provides ideas for collaborative activities and play to deepen parent-child relationships. Step 3: The monitoring department monitors the child's growth based on the coaching provided by the coaching department. Monitoring the child's growth includes growth indicators and data collection methods. For example, the department monitors the child's language development stage, physical development, sleep, and eating patterns. In addition, the department can provide advice on improving the child's sleep quality and propose a meal plan to manage nutritional balance.

[0093] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0094] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> Examples of the generative AI include a neural network (NN) and a neural network (NN). The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image (e.g., still image data or video data). The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in one or more data formats of voice data, text data, image data, etc. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specification processing unit 290 performs the above-mentioned specification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and may perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processing of each of the above-mentioned parts is performed by an AI, the processing may be performed in part or entirely by the AI, but is not limited to these examples. The processing performed by an AI including the generative AI may be replaced with rule-based processing, and rule-based processing may be replaced with processing performed by an AI including the generative AI.

[0095] Furthermore, the processing by the data processing system 10 described above is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart device 14, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart device 14. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the smart device 14 or an external device, and the smart device 14 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0096] The correspondence between each part and the device or control part is not limited to the example described above, and various modifications are possible.

[0097] [Second embodiment] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0098] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0099] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0100] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0101] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0102] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0103] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0104] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0105] The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0106] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0107] In the smart glasses 214, the specific processing is performed by the processor 46. A specific processing program 60 is stored in the storage 50. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. The smart glasses 214 also have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0108] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0109] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0110] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt including an instruction, as well as inference data such as audio data indicating speech, text data indicating text, and image data indicating an image (e.g., still image data or video data). The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in one or more data formats, such as audio data, text data, and image data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation models 58 include AIs other than the generation AI. Examples of AIs other than the generation AI include, but are not limited to, 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), and naive Bayes. These AIs can perform various types of processing, but are not limited to these examples. The AI ​​may also be an AI agent. When the processing of each of the above-described parts is performed by an AI, the processing may be performed in part or entirely by the AI, but is not limited to these examples. Processing performed by an AI, including the generation AI, may be replaced with rule-based processing, and rule-based processing may be replaced with processing performed by an AI, including the generation AI.

[0111] The data processing system 210 according to the second embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 210 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart glasses 214, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart glasses 214. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the smart glasses 214 or an external device, etc., and the smart glasses 214 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0112] The correspondence between each part and the device or control part is not limited to the example described above, and various modifications are possible.

[0113] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0114] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0115] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0116] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0117] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0118] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0119] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0120] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0121] The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0122] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0123] In the headset type terminal 314, the identification process is performed by the processor 46. A identification program 60 is stored in the storage 50. The processor 46 reads the identification program 60 from the storage 50 and executes the read identification program 60 on the RAM 48. The identification process is realized by the processor 46 operating as a control unit 46A in accordance with the identification program 60 executed on the RAM 48. Note that the headset type terminal 314 has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can also perform processing similar to that of the identification processing unit 290 using these models.

[0124] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0125] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0126] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt including an instruction, as well as inference data such as audio data indicating speech, text data indicating text, and image data indicating an image (e.g., still image data or video data). The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in one or more data formats, such as audio data, text data, and image data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation models 58 include AIs other than the generation AI. Examples of AIs other than the generation AI include, but are not limited to, 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), and naive Bayes. These AIs can perform various types of processing, but are not limited to these examples. The AI ​​may also be an AI agent. When the processing of each of the above-described parts is performed by an AI, the processing may be performed in part or entirely by the AI, but is not limited to these examples. Processing performed by an AI, including the generation AI, may be replaced with rule-based processing, and rule-based processing may be replaced with processing performed by an AI, including the generation AI.

[0127] The data processing system 310 according to the third embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 310 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the headset type terminal 314, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the headset type terminal 314. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the headset type terminal 314 or an external device, etc., and the headset type terminal 314 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0128] The correspondence between each part and the device or control part is not limited to the example described above, and various modifications are possible.

[0129] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0130] 7, a 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.

[0131] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0132] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[0133] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0134] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS image sensor or a CCD image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0135] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0136] The control object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[0137] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0138] The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0139] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0140] In the robot 414, the processor 46 performs the identification process. The storage 50 stores the identification program 60. The processor 46 reads the identification program 60 from the storage 50 and executes the read identification program 60 on the RAM 48. The identification process is realized by the processor 46 operating as the control unit 46A in accordance with the identification program 60 executed on the RAM 48. The robot 414 also has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can perform the same process as the identification processing unit 290 using these models.

[0141] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0142] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[0143] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt including an instruction, as well as inference data such as audio data indicating speech, text data indicating text, and image data indicating an image (e.g., still image data or video data). The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in one or more data formats, such as audio data, text data, and image data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation models 58 include AIs other than the generation AI. Examples of AIs other than the generation AI include, but are not limited to, 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), and naive Bayes. These AIs can perform various types of processing, but are not limited to these examples. The AI ​​may also be an AI agent. When the processing of each of the above-described parts is performed by an AI, the processing may be performed in part or entirely by the AI, but is not limited to these examples. Processing performed by an AI, including the generation AI, may be replaced with rule-based processing, and rule-based processing may be replaced with processing performed by an AI, including the generation AI.

[0144] The data processing system 410 according to the fourth embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 410 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the robot 414, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the robot 414. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the robot 414 or an external device, etc., and the robot 414 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0145] The correspondence between each part and the device or control part is not limited to the example described above, and various modifications are possible.

[0146] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0147] FIG. 9 illustrates an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and behaviors arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion encompasses both emotions and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[0148] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[0149] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[0150] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is expressed, and when they approach the ideal, a state of pleasure is expressed. Emotions can also be created for robots, cars, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is expressed, and when they approach the ideal, a state of pleasure is expressed. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on speech emotion recognition and brain physiological signal analysis systems for emotions, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the area called "reaction," where sensation is dominant. The right half of the emotion map lists emotions belonging to the area called "situation," where situational awareness is dominant.

[0151] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[0152] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[0153] In the above embodiment, an example was given in which a specific process is performed by one computer 22, but the technology disclosed herein is not limited to this, and distributed processing of the specific process may be performed by multiple computers including computer 22.

[0154] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[0155] 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.

[0156] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[0157] The hardware resource for executing a specific process can be any of the following types of processors: A processor, for example, is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. A processor also includes a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[0158] The hardware resource that executes the specific process may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific process may be a single processor.

[0159] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[0160] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[0161] In the above example, the first to fourth embodiments have been described separately, but some or all of these embodiments may be combined. The smart device 14, smart glasses 214, headset terminal 314, and robot 414 are merely examples, and they may be combined, or other devices may be used. In the above example, the first and second embodiments have been described separately, but they may be combined.

[0162] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[0163] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[0164] [Explanation of symbols]

[0165] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot

Claims

1. an information department that provides information during pregnancy and postpartum; a coaching unit that provides childcare coaching based on the information provided by the information providing unit; a monitoring unit that monitors the child's growth based on the coaching provided by the coaching unit; Equipped with A system characterized by:

2. The information providing unit Providing necessary information for moms and dads during and after pregnancy The system of claim 1 .

3. The coaching department Supporting children's learning, discipline, and parent-child relationship building The system of claim 1 .

4. The monitoring unit Monitor your child's language and physical development and support them with sleep and eating The system of claim 1 .

5. The information providing unit Create dietary management and menus that are good for the baby's growth for pregnant women, and introduce recommended apps The system of claim 1 .

6. The coaching department Parenting coaching using generative AI The system of claim 1 .

7. The information providing unit Estimates the user's emotions and adjusts the timing of providing information based on the estimated user emotions. The system of claim 1 .

8. The information providing unit Analyze the user's past browsing history and select the appropriate method of providing information The system of claim 1 .

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