system

Abstract

An object of a system according to an embodiment is to efficiently provide information according to an age and an area of a child and subsidy information and support childcare of a parent.SOLUTION: A system according to an embodiment includes an information providing unit, a subsidy information providing unit, a consultation handling unit, and a recommendation unit. The information providing unit provides information according to the age of the child and the region. The subsidy information providing unit provides information on available subsidies and subsidies. The consultation handling unit handles a consultation of a parent who is worried about childcare. The recommendation unit recommends a product in cooperation with the EC site.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] Conventional technology has made it difficult to efficiently provide information tailored to a child's age and region, as well as subsidy information, and parents have had to go through a lot of trouble to obtain the information they need.

[0005] The system according to the embodiment aims to efficiently provide information and subsidy information according to the age and region of the child, thereby supporting parents in raising their children. [Means for solving the problem]

[0006] The system according to the embodiment includes an information providing unit, a subsidy information providing unit, a consultation response unit, and a recommendation unit. The information providing unit provides information according to the child's age and region. The subsidy information providing unit provides information on available subsidies and grants. The consultation response unit responds to consultations from parents who are worried about raising their children. The recommendation unit recommends products in cooperation with an e-commerce site. [Effects of the Invention]

[0007] The system according to the embodiment can efficiently provide information and subsidy information according to the age and region of the child, thereby supporting parents in raising their children. [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 the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

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

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

[0028] (Example 1) The child-rearing support system according to the embodiment of the present invention is a system that teaches necessary procedures and things to do according to the child's age (months) and region, provides information on available subsidies and grants, acts as an advisor to parents who are worried about child-rearing, and recommends products in cooperation with e-commerce sites. As a result, the child-rearing support system can reduce the burden on parents and support them in efficient procedures and appropriate product selection.

[0029] A child-rearing support system according to an embodiment includes an information providing unit, a subsidy information providing unit, a consultation response unit, and a recommendation unit. The information providing unit provides information based on the child's age (months) and region. For example, the generation AI analyzes information about the child's age (months) and region input by a user and, based on that information, provides necessary procedures and things to do. The generation AI provides, for example, vaccination schedules and how to apply for daycare. The subsidy information providing unit provides information on available subsidies and grants. For example, the generation AI provides information on subsidies and grants related to child-sitter assistance, moving, home purchases, etc., based on the user's situation. The consultation response unit responds to consultations from parents struggling with child-rearing. For example, the generation AI provides appropriate advice and information in response to questions and concerns from users. For example, the generation AI provides appropriate advice in response to a question such as, "My child cries at night. What should I do?" The recommendation unit recommends products in cooperation with an e-commerce site. For example, the generation AI recommends appropriate products based on the user's purchase history and the child's age. The generation AI suggests products that should be purchased next based on, for example, products that the user has previously purchased and the age of the child. As a result, the child-rearing support system according to the embodiment can reduce the burden on parents and support efficient procedures and appropriate product selection.

[0030] The information providing unit can collect growth data of a child in real time and provide customized advice based on individual growth patterns. For example, the information providing unit collects growth data of a child in real time and provides customized advice based on individual growth patterns. For example, it tracks changes in height and weight and provides advice on appropriate nutrition and exercise. The information providing unit also provides educational advice according to the child's developmental stage based on the growth data. For example, it suggests appropriate picture books and toys according to the progress of language development. Furthermore, the information providing unit provides health management advice based on the growth data. For example, it suggests a schedule for regular health checkups. This makes it possible to provide customized advice based on the child's growth data.

[0031] The information providing unit can provide information optimized for each region based on the characteristics of the region. For example, the information providing unit provides advice on children's health management for each season based on local climate data. For example, in cold regions, it suggests measures to prevent colds. The information providing unit also provides childcare information optimized for each region based on local culture and event information. For example, it provides information on local traditional events and children's events. Furthermore, the information providing unit provides information on local medical institutions and childcare facilities. For example, it provides information on nearby pediatric clinics and nursery schools. This makes it possible to provide information that takes into account the characteristics of the region.

[0032] The information provision unit can collect feedback from other parents and build a platform for parents with children in the same area or age to share information with each other. The information provision unit, for example, collects feedback from other parents and builds a platform for parents with children in the same area or age to share information with each other. For example, it provides a bulletin board for sharing child-rearing information and experiences by area. The information provision unit also forms a community for parents to exchange information and support each other based on the feedback. For example, it provides an online forum or chat function. Furthermore, the information provision unit holds events for parents to exchange information and support each other based on the feedback. For example, it holds local child-rearing seminars or workshops. This enables parents to share information with each other.

[0033] The information providing unit can provide information appropriate to the child's age through the voice assistant, allowing parents to obtain information without using their hands. The information providing unit, for example, provides information appropriate to the child's age (age in months) through the voice assistant, allowing parents to obtain information without using their hands. For example, vaccination schedules and child-rearing advice are provided by voice. The information providing unit also provides a function that allows parents to search for information without using their hands through the voice assistant. For example, child-rearing information can be searched using voice commands. The information providing unit also provides a function that allows parents to obtain information without using their hands through the voice assistant. For example, child-rearing information can be read out loud. This allows parents to obtain information without using their hands.

[0034] The subsidy information provision unit can automate the application process for subsidies and grants, and automatically generate the necessary documents and procedures. The subsidy information provision unit, for example, develops a system that automates the application process for subsidies and grants, and automatically generates the necessary documents and procedures. For example, application documents are automatically generated simply by entering user information. The subsidy information provision unit also automates the application process and automatically generates the necessary documents and procedures. For example, it automatically fills in online forms and automatically generates the necessary documents. Furthermore, the subsidy information provision unit automates the application process and automatically generates the necessary documents and procedures. For example, it automatically generates application forms, certificates, and procedural steps. This makes it possible to automate the application process for subsidies and grants, and automatically generate the necessary documents and procedures.

[0035] The subsidy information providing unit can analyze the user's past application history and suggest the application method with the highest success rate. The subsidy information providing unit, for example, develops a system that analyzes the user's past application history and suggests the application method with the highest success rate. For example, it suggests the optimal application method based on past successful cases. The subsidy information providing unit also analyzes the application history and suggests the application method with the highest success rate. For example, it suggests the optimal application method based on past application content and application results. The subsidy information providing unit also analyzes the application history and suggests the application method with the highest success rate. For example, it suggests the optimal application method based on past application timing and application content. In this way, it is possible to analyze past application history and suggest an application method with a high success rate.

[0036] The subsidy information providing unit can link information on subsidies and grants with seminars and workshops at local community centers and public facilities. The subsidy information providing unit, for example, builds a system that links information on subsidies and grants with seminars and workshops at local community centers and public facilities. For example, it provides subsidy information at local seminars. The subsidy information providing unit also links information on subsidies and grants with seminars and workshops at local community centers and public facilities. For example, it provides subsidy information at local childcare seminars and education workshops. The subsidy information providing unit also links information on subsidies and grants with seminars and workshops at local community centers and public facilities. For example, it provides subsidy information at local health seminars and psychological counseling workshops. This allows information on subsidies and grants to be linked with seminars and workshops at local community centers and public facilities.

[0037] The consultation response unit can analyze the content of the parent's consultation and provide optimal advice based on past consultation history. The consultation response unit, for example, develops a system that analyzes the content of the parent's consultation and provides optimal advice based on past consultation history. For example, if a similar consultation has been made in the past, it proposes a solution. The consultation response unit also analyzes the content of the consultation and provides optimal advice based on past consultation history. For example, it provides optimal advice based on the content and results of the past consultation. Furthermore, the consultation response unit analyzes the content of the consultation and provides optimal advice based on past consultation history. For example, it provides optimal advice based on the timing and content of the past consultation. This makes it possible to analyze the content of the parent's consultation and provide optimal advice based on past consultation history.

[0038] The consultation response unit can automatically collaborate with an expert depending on the content of the consultation. For example, the consultation response unit develops a system that automatically collaborates with an expert (e.g., a doctor or counselor) depending on the content of the consultation. For example, an appropriate expert is automatically introduced for a specific consultation content. The consultation response unit also automatically collaborates with an expert depending on the content of the consultation. For example, online collaboration or telephone collaboration is performed. Furthermore, the consultation response unit automatically collaborates with an expert depending on the content of the consultation. For example, email collaboration or video call collaboration is performed. This makes it possible to automatically collaborate with an expert depending on the content of the consultation.

[0039] The consultation response unit can form a community of parents and provide a platform where parents with the same concerns can exchange information and receive support from each other. The consultation response unit, for example, develops a system that forms a community of parents and provides a platform where parents with the same concerns can exchange information and receive support from each other. For example, it provides an online forum or chat function. The consultation response unit also forms a community of parents and provides a platform where parents with the same concerns can exchange information and receive support from each other. For example, it provides a local parent community or an online forum. The consultation response unit also forms a community of parents and provides a platform where parents with the same concerns can exchange information and receive support from each other. For example, it provides a support group where parenting information is shared and parents can seek advice about their concerns. This makes it possible to form a community of parents and provide a platform where information is exchanged and support is provided.

[0040] The consultation department can anonymize the consultation content and make it publicly available in a Q&A format that can be useful to other parents. For example, the consultation department could develop a system that anonymizes the consultation content and makes it publicly available in a Q&A format that can be useful to other parents. For example, the anonymous consultation content and its answers could be compiled into a database that can be searched. The consultation department could also anonymize the consultation content and make it publicly available in a Q&A format that can be useful to other parents. For example, the consultation department could make it publicly available in an online forum or FAQ page. Furthermore, the consultation department could anonymize the consultation content and make it publicly available in a Q&A format that can be useful to other parents. For example, the consultation content could be made public using an anonymous ID while protecting personal information. This would allow the consultation content to be anonymized and made publicly available in a Q&A format that can be useful to other parents.

[0041] The recommendation unit analyzes not only the purchase history but also the user's search history and browsing history, allowing for more accurate recommendations. The recommendation unit, for example, analyzes not only the purchase history but also the user's search history and browsing history to develop a system that provides more accurate recommendations. For example, products are suggested based on past search keywords and viewed pages. The recommendation unit also analyzes the search history and browsing history to provide more accurate recommendations. For example, products are suggested based on past search keywords and viewed pages. The recommendation unit also analyzes the search history and browsing history to provide more accurate recommendations. For example, products are suggested based on past search keywords and viewed pages. The recommendation unit also analyzes the search history and browsing history to provide more accurate recommendations. For example, products are suggested based on past search keywords and viewed pages. This allows for more accurate recommendations to be provided by analyzing not only the purchase history but also the search history and browsing history.

[0042] The recommendation unit can automatically collect reviews and ratings of recommended products and provide them to the user. The recommendation unit, for example, develops a system that automatically collects reviews and ratings of recommended products and provides them to the user. For example, it automatically displays reviews and ratings from other users. The recommendation unit also automatically collects reviews and ratings of recommended products and provides them to the user. For example, it automatically displays user evaluation comments and star ratings. The recommendation unit also automatically collects reviews and ratings of recommended products and provides them to the user. For example, it automatically displays user evaluation comments and star ratings. In this way, it is possible to automatically collect reviews and ratings of recommended products and provide them to the user.

[0043] The recommendation unit can compare the recommended products with the purchase histories of other users and suggest the most popular products. The recommendation unit, for example, develops a system that compares the recommended products with the purchase histories of other users and suggests the most popular products. For example, it prioritizes recommending products that are purchased frequently. The recommendation unit also compares the recommended products with the purchase histories of other users and suggests the most popular products. For example, it identifies popular products based on sales volume and user ratings. Furthermore, the recommendation unit compares the recommended products with the purchase histories of other users and suggests the most popular products. For example, it identifies popular products based on the number of reviews and rating comments. This makes it possible to compare the recommended products with the purchase histories of other users and suggest the most popular products.

[0044] The recommendation unit can link the recommendation function with other e-commerce sites and apps, allowing users to receive consistent recommendations across multiple platforms. The recommendation unit, for example, develops a system that links the recommendation function with other e-commerce sites and apps, allowing users to receive consistent recommendations across multiple platforms. For example, it integrates purchase histories from different e-commerce sites. The recommendation unit also links the recommendation function with other e-commerce sites and apps, allowing users to receive consistent recommendations across multiple platforms. For example, it shares data and standardizes algorithms. Furthermore, the recommendation unit links the recommendation function with other e-commerce sites and apps, allowing users to receive consistent recommendations across multiple platforms. For example, it integrates purchase histories and search histories from different platforms. This allows the recommendation function to be linked with other e-commerce sites and apps, allowing users to receive consistent recommendations across multiple platforms.

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

[0046] The information providing unit can also provide child-rearing advice customized based on the parents' lifestyles. For example, it can provide time management advice for dual-income households. The information providing unit can also provide support information specialized for single parents. Furthermore, the information providing unit can also provide information useful for child-rearing based on the parents' hobbies and interests. This makes it possible to provide child-rearing advice customized to the parents' lifestyles.

[0047] The information providing unit can also monitor the parent's health condition and detect health problems that may affect child-rearing at an early stage. For example, it can analyze the parent's sleep patterns and provide advice on the impact of lack of sleep on child-rearing. The information providing unit can also monitor the parent's stress level and suggest stress management methods. Furthermore, the information providing unit can monitor the parent's eating habits and suggest nutritionally balanced meals. This makes it possible to provide child-rearing advice that takes the parent's health condition into consideration.

[0048] The information providing unit can also provide child-rearing advice customized based on the parents' lifestyles. For example, it can provide time management advice for dual-income households. The information providing unit can also provide support information specialized for single parents. Furthermore, the information providing unit can also provide information useful for child-rearing based on the parents' hobbies and interests. This makes it possible to provide child-rearing advice customized to the parents' lifestyles.

[0049] The information providing unit can also monitor the parent's health condition and detect health problems that may affect child-rearing at an early stage. For example, it can analyze the parent's sleep patterns and provide advice on the impact of lack of sleep on child-rearing. The information providing unit can also monitor the parent's stress level and suggest stress management methods. Furthermore, the information providing unit can monitor the parent's eating habits and suggest nutritionally balanced meals. This makes it possible to provide child-rearing advice that takes the parent's health condition into consideration.

[0050] The information providing unit can also provide child-rearing advice customized based on the parents' lifestyles. For example, it can provide time management advice for dual-income households. The information providing unit can also provide support information specialized for single parents. Furthermore, the information providing unit can also provide information useful for child-rearing based on the parents' hobbies and interests. This makes it possible to provide child-rearing advice customized to the parents' lifestyles.

[0051] The processing flow of the first embodiment will be briefly explained below.

[0052] Step 1: The information provider provides information based on the child's age (months) and region. For example, the generator AI analyzes the child's age (months) and region information entered by the user, and based on that information, provides instructions on the necessary procedures and things to do. Specifically, it provides vaccination schedules and how to apply for nursery school. Step 2: The subsidy information provider provides information on available subsidies and grants. For example, the generation AI provides information on subsidies and grants related to childcare assistance, moving, home purchases, etc., depending on the user's situation. Step 3: The consultation section responds to inquiries from parents who are worried about raising their children. For example, the generation AI provides appropriate advice and information in response to questions and concerns from users. Specifically, it provides appropriate advice in response to questions such as, "My child cries at night. What should I do?" Step 4: The recommendation unit works with the e-commerce site to recommend products. For example, the generation AI recommends appropriate products based on the user's purchase history and the child's age in months. Specifically, it suggests the next product to purchase based on the user's past purchases and the child's age in months.

[0053] (Example 2) The child-rearing support system according to the embodiment of the present invention is a system that teaches necessary procedures and things to do according to the child's age (months) and region, provides information on available subsidies and grants, acts as an advisor to parents who are worried about child-rearing, and recommends products in cooperation with e-commerce sites. As a result, the child-rearing support system can reduce the burden on parents and support them in efficient procedures and appropriate product selection.

[0054] A child-rearing support system according to an embodiment includes an information providing unit, a subsidy information providing unit, a consultation response unit, and a recommendation unit. The information providing unit provides information based on the child's age (months) and region. For example, the generation AI analyzes information about the child's age (months) and region input by a user and, based on that information, provides necessary procedures and things to do. The generation AI provides, for example, vaccination schedules and how to apply for daycare. The subsidy information providing unit provides information on available subsidies and grants. For example, the generation AI provides information on subsidies and grants related to child-sitter assistance, moving, home purchases, etc., based on the user's situation. The consultation response unit responds to consultations from parents struggling with child-rearing. For example, the generation AI provides appropriate advice and information in response to questions and concerns from users. For example, the generation AI provides appropriate advice in response to a question such as, "My child cries at night. What should I do?" The recommendation unit recommends products in cooperation with an e-commerce site. For example, the generation AI recommends appropriate products based on the user's purchase history and the child's age. The generation AI suggests products that should be purchased next based on, for example, products that the user has previously purchased and the age of the child. As a result, the child-rearing support system according to the embodiment can reduce the burden on parents and support efficient procedures and appropriate product selection.

[0055] The information providing unit can collect growth data of a child in real time and provide customized advice based on individual growth patterns. For example, the information providing unit collects growth data of a child in real time and provides customized advice based on individual growth patterns. For example, it tracks changes in height and weight and provides advice on appropriate nutrition and exercise. The information providing unit also provides educational advice according to the child's developmental stage based on the growth data. For example, it suggests appropriate picture books and toys according to the progress of language development. Furthermore, the information providing unit provides health management advice based on the growth data. For example, it suggests a schedule for regular health checkups. This makes it possible to provide customized advice based on the child's growth data.

[0056] The information providing unit can provide information optimized for each region based on the characteristics of the region. For example, the information providing unit provides advice on children's health management for each season based on local climate data. For example, in cold regions, it suggests measures to prevent colds. The information providing unit also provides childcare information optimized for each region based on local culture and event information. For example, it provides information on local traditional events and children's events. Furthermore, the information providing unit provides information on local medical institutions and childcare facilities. For example, it provides information on nearby pediatric clinics and nursery schools. This makes it possible to provide information that takes into account the characteristics of the region.

[0057] The information providing unit can use the emotion estimation function to analyze the parent's emotional state and provide information that requires particular attention during times of high stress with priority. The information providing unit, for example, analyzes the parent's emotional state in real time and provides information that requires particular attention during times of high stress with priority. For example, it suggests relaxation methods during times of high parenting stress. The information providing unit also uses the emotion estimation function to provide child-rearing advice according to the parent's emotional state. For example, it sends an encouraging message when the emotional state is negative. Furthermore, the information providing unit uses the emotion estimation function to provide health management advice according to the parent's emotional state. For example, it suggests relaxation methods during times of high stress. This makes it possible to provide information according to the parent's emotional state.

[0058] The information provision unit can collect feedback from other parents and build a platform for parents with children in the same area or age to share information with each other. The information provision unit, for example, collects feedback from other parents and builds a platform for parents with children in the same area or age to share information with each other. For example, it provides a bulletin board for sharing child-rearing information and experiences by area. The information provision unit also forms a community for parents to exchange information and support each other based on the feedback. For example, it provides an online forum or chat function. Furthermore, the information provision unit holds events for parents to exchange information and support each other based on the feedback. For example, it holds local child-rearing seminars or workshops. This enables parents to share information with each other.

[0059] The information providing unit can provide information appropriate to the child's age through the voice assistant, allowing parents to obtain information without using their hands. The information providing unit, for example, provides information appropriate to the child's age (age in months) through the voice assistant, allowing parents to obtain information without using their hands. For example, vaccination schedules and child-rearing advice are provided by voice. The information providing unit also provides a function that allows parents to search for information without using their hands through the voice assistant. For example, child-rearing information can be searched using voice commands. The information providing unit also provides a function that allows parents to obtain information without using their hands through the voice assistant. For example, child-rearing information can be read out loud. This allows parents to obtain information without using their hands.

[0060] The information providing unit uses the emotion estimation function to prioritize displaying information that parents are most interested in, thereby optimizing how information is received. The information providing unit, for example, uses the emotion estimation function to prioritize displaying information that parents are most interested in, thereby optimizing how information is received. For example, the information providing unit analyzes the emotional state of the parent and displays information that parents are most interested in at the top. The information providing unit also uses the emotion estimation function to prioritize displaying information that parents are most interested in. For example, childcare tips and educational advice are displayed preferentially. The information providing unit also uses the emotion estimation function to prioritize displaying information that parents are most interested in. For example, health information and local event information are displayed preferentially. This makes it possible to prioritize displaying information that parents are most interested in.

[0061] The subsidy information provision unit can automate the application process for subsidies and grants, and automatically generate the necessary documents and procedures. The subsidy information provision unit, for example, develops a system that automates the application process for subsidies and grants, and automatically generates the necessary documents and procedures. For example, application documents are automatically generated simply by entering user information. The subsidy information provision unit also automates the application process and automatically generates the necessary documents and procedures. For example, it automatically fills in online forms and automatically generates the necessary documents. Furthermore, the subsidy information provision unit automates the application process and automatically generates the necessary documents and procedures. For example, it automatically generates application forms, certificates, and procedural steps. This makes it possible to automate the application process for subsidies and grants, and automatically generate the necessary documents and procedures.

[0062] The subsidy information providing unit can analyze the user's past application history and suggest the application method with the highest success rate. The subsidy information providing unit, for example, develops a system that analyzes the user's past application history and suggests the application method with the highest success rate. For example, it suggests the optimal application method based on past successful cases. The subsidy information providing unit also analyzes the application history and suggests the application method with the highest success rate. For example, it suggests the optimal application method based on past application content and application results. The subsidy information providing unit also analyzes the application history and suggests the application method with the highest success rate. For example, it suggests the optimal application method based on past application timing and application content. In this way, it is possible to analyze past application history and suggest an application method with a high success rate.

[0063] The subsidy information providing unit can use the emotion estimation function to provide support to alleviate concerns and questions about the application in real time. The subsidy information providing unit, for example, uses the emotion estimation function to develop a system that provides support to alleviate concerns and questions about the application in real time. For example, the system analyzes the user's emotional state and provides appropriate support. The subsidy information providing unit also uses the emotion estimation function to provide support to alleviate concerns and questions about the application in real time. For example, the system provides chat support and FAQs. The subsidy information providing unit also uses the emotion estimation function to provide support to alleviate concerns and questions about the application in real time. For example, the system provides guidelines and procedural steps. This makes it possible to provide support to alleviate concerns and questions about the application in real time.

[0064] The subsidy information providing unit can link information on subsidies and grants with seminars and workshops at local community centers and public facilities. The subsidy information providing unit, for example, builds a system that links information on subsidies and grants with seminars and workshops at local community centers and public facilities. For example, it provides subsidy information at local seminars. The subsidy information providing unit also links information on subsidies and grants with seminars and workshops at local community centers and public facilities. For example, it provides subsidy information at local childcare seminars and education workshops. The subsidy information providing unit also links information on subsidies and grants with seminars and workshops at local community centers and public facilities. For example, it provides subsidy information at local health seminars and psychological counseling workshops. This allows information on subsidies and grants to be linked with seminars and workshops at local community centers and public facilities.

[0065] The subsidy information providing unit uses the emotion estimation function to provide information on subsidies and grants that interest the user most, thereby increasing the user's motivation to apply. The subsidy information providing unit develops a system that uses the emotion estimation function to provide information on subsidies and grants that interest the user most, for example. For example, information that is of high interest to the user is displayed based on an emotion score. The subsidy information providing unit also uses the emotion estimation function to provide information on subsidies and grants that interest the user most, for example, by introducing success stories and emphasizing the benefits of applying. Furthermore, the subsidy information providing unit uses the emotion estimation function to provide information on subsidies and grants that interest the user most, for example, by emphasizing the ease of application procedures and post-application support. This allows information on subsidies and grants that interest the user most to be provided preferentially, thereby increasing the user's motivation to apply.

[0066] The consultation response unit can analyze the content of the parent's consultation and provide optimal advice based on past consultation history. The consultation response unit, for example, develops a system that analyzes the content of the parent's consultation and provides optimal advice based on past consultation history. For example, if a similar consultation has been made in the past, it proposes a solution. The consultation response unit also analyzes the content of the consultation and provides optimal advice based on past consultation history. For example, it provides optimal advice based on the content and results of the past consultation. Furthermore, the consultation response unit analyzes the content of the consultation and provides optimal advice based on past consultation history. For example, it provides optimal advice based on the timing and content of the past consultation. This makes it possible to analyze the content of the parent's consultation and provide optimal advice based on past consultation history.

[0067] The consultation response unit can automatically collaborate with an expert depending on the content of the consultation. For example, the consultation response unit develops a system that automatically collaborates with an expert (e.g., a doctor or counselor) depending on the content of the consultation. For example, an appropriate expert is automatically introduced for a specific consultation content. The consultation response unit also automatically collaborates with an expert depending on the content of the consultation. For example, online collaboration or telephone collaboration is performed. Furthermore, the consultation response unit automatically collaborates with an expert depending on the content of the consultation. For example, email collaboration or video call collaboration is performed. This makes it possible to automatically collaborate with an expert depending on the content of the consultation.

[0068] The consultation response unit can use the emotion estimation function to grasp the parent's emotional state in real time and provide encouraging or comforting messages at appropriate times. For example, a system is developed in which the consultation response unit uses the emotion estimation function to grasp the parent's emotional state in real time and provide encouraging or comforting messages at appropriate times. For example, an encouraging message is sent when the emotional state is negative. The consultation response unit also uses the emotion estimation function to grasp the parent's emotional state in real time and provide encouraging or comforting messages at appropriate times. For example, a supportive message is sent when the emotional state is positive. The consultation response unit also uses the emotion estimation function to grasp the parent's emotional state in real time and provide encouraging or comforting messages at appropriate times. For example, a relaxation method is suggested when the emotional state is stressful. This makes it possible to grasp the parent's emotional state in real time and provide encouraging or comforting messages at appropriate times.

[0069] The consultation response unit can form a community of parents and provide a platform where parents with the same concerns can exchange information and receive support from each other. The consultation response unit, for example, develops a system that forms a community of parents and provides a platform where parents with the same concerns can exchange information and receive support from each other. For example, it provides an online forum or chat function. The consultation response unit also forms a community of parents and provides a platform where parents with the same concerns can exchange information and receive support from each other. For example, it provides a local parent community or an online forum. The consultation response unit also forms a community of parents and provides a platform where parents with the same concerns can exchange information and receive support from each other. For example, it provides a support group where parenting information is shared and parents can seek advice about their concerns. This makes it possible to form a community of parents and provide a platform where information is exchanged and support is provided.

[0070] The consultation department can anonymize the consultation content and make it publicly available in a Q&A format that can be useful to other parents. For example, the consultation department could develop a system that anonymizes the consultation content and makes it publicly available in a Q&A format that can be useful to other parents. For example, the anonymous consultation content and its answers could be compiled into a database that can be searched. The consultation department could also anonymize the consultation content and make it publicly available in a Q&A format that can be useful to other parents. For example, the consultation department could make it publicly available in an online forum or FAQ page. Furthermore, the consultation department could anonymize the consultation content and make it publicly available in a Q&A format that can be useful to other parents. For example, the consultation content could be made public using an anonymous ID while protecting personal information. This would allow the consultation content to be anonymized and made publicly available in a Q&A format that can be useful to other parents.

[0071] The consultation response unit uses the emotion estimation function to prioritize providing advice that parents will most likely empathize with, thereby improving the effectiveness of the consultation. The consultation response unit, for example, uses the emotion estimation function to develop a system that prioritizes providing advice that parents will most likely empathize with. For example, by analyzing an emotional state and providing advice that is highly relatable. The consultation response unit also uses the emotion estimation function to prioritize providing advice that parents will most likely empathize with. For example, by providing advice based on actual experience or the opinion of an expert. The consultation response unit also uses the emotion estimation function to prioritize providing advice that parents will most likely empathize with. For example, by providing advice that is highly relatable based on an emotional state. This allows the advice that parents will most likely empathize with to be prioritized, thereby improving the effectiveness of the consultation.

[0072] The recommendation unit analyzes not only the purchase history but also the user's search history and browsing history, allowing for more accurate recommendations. The recommendation unit, for example, analyzes not only the purchase history but also the user's search history and browsing history to develop a system that provides more accurate recommendations. For example, products are suggested based on past search keywords and viewed pages. The recommendation unit also analyzes the search history and browsing history to provide more accurate recommendations. For example, products are suggested based on past search keywords and viewed pages. The recommendation unit also analyzes the search history and browsing history to provide more accurate recommendations. For example, products are suggested based on past search keywords and viewed pages. The recommendation unit also analyzes the search history and browsing history to provide more accurate recommendations. For example, products are suggested based on past search keywords and viewed pages. This allows for more accurate recommendations to be provided by analyzing not only the purchase history but also the search history and browsing history.

[0073] The recommendation unit can automatically collect reviews and ratings of recommended products and provide them to the user. The recommendation unit, for example, develops a system that automatically collects reviews and ratings of recommended products and provides them to the user. For example, it automatically displays reviews and ratings from other users. The recommendation unit also automatically collects reviews and ratings of recommended products and provides them to the user. For example, it automatically displays user evaluation comments and star ratings. The recommendation unit also automatically collects reviews and ratings of recommended products and provides them to the user. For example, it automatically displays user evaluation comments and star ratings. In this way, it is possible to automatically collect reviews and ratings of recommended products and provide them to the user.

[0074] The recommendation unit can compare the recommended products with the purchase histories of other users and suggest the most popular products. The recommendation unit, for example, develops a system that compares the recommended products with the purchase histories of other users and suggests the most popular products. For example, it prioritizes recommending products that are purchased frequently. The recommendation unit also compares the recommended products with the purchase histories of other users and suggests the most popular products. For example, it identifies popular products based on sales volume and user ratings. Furthermore, the recommendation unit compares the recommended products with the purchase histories of other users and suggests the most popular products. For example, it identifies popular products based on the number of reviews and rating comments. This makes it possible to compare the recommended products with the purchase histories of other users and suggest the most popular products.

[0075] The recommendation unit can link the recommendation function with other e-commerce sites and apps, allowing users to receive consistent recommendations across multiple platforms. The recommendation unit, for example, develops a system that links the recommendation function with other e-commerce sites and apps, allowing users to receive consistent recommendations across multiple platforms. For example, it integrates purchase histories from different e-commerce sites. The recommendation unit also links the recommendation function with other e-commerce sites and apps, allowing users to receive consistent recommendations across multiple platforms. For example, it shares data and standardizes algorithms. Furthermore, the recommendation unit links the recommendation function with other e-commerce sites and apps, allowing users to receive consistent recommendations across multiple platforms. For example, it integrates purchase histories and search histories from different platforms. This allows the recommendation function to be linked with other e-commerce sites and apps, allowing users to receive consistent recommendations across multiple platforms.

[0076] The recommendation unit uses the emotion estimation function to preferentially recommend products that evoke the most positive emotions in the user, thereby improving the purchasing experience. The recommendation unit, for example, uses the emotion estimation function to develop a system that preferentially recommends products that evoke the most positive emotions in the user. For example, products that elicit positive emotions based on an emotion score are displayed. The recommendation unit also uses the emotion estimation function to preferentially recommend products that evoke the most positive emotions in the user. For example, products are suggested based on the user's preferences and past purchase history. Furthermore, the recommendation unit uses the emotion estimation function to preferentially recommend products that evoke the most positive emotions in the user. For example, benefits are provided or discount information is presented. This allows the recommendation unit to preferentially recommend products that evoke the most positive emotions in the user, thereby improving the purchasing experience.

[0077] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0078] The information providing unit can also provide child-rearing advice customized based on the parents' lifestyles. For example, it can provide time management advice for dual-income households. The information providing unit can also provide support information specialized for single parents. Furthermore, the information providing unit can also provide information useful for child-rearing based on the parents' hobbies and interests. This makes it possible to provide child-rearing advice customized to the parents' lifestyles.

[0079] The information providing unit can also monitor the parent's health condition and detect health problems that may affect child-rearing at an early stage. For example, it can analyze the parent's sleep patterns and provide advice on the impact of lack of sleep on child-rearing. The information providing unit can also monitor the parent's stress level and suggest stress management methods. Furthermore, the information providing unit can monitor the parent's eating habits and suggest nutritionally balanced meals. This makes it possible to provide child-rearing advice that takes the parent's health condition into consideration.

[0080] The information providing unit can also estimate the emotional state of the parent and provide parenting advice according to the emotion. For example, it can suggest relaxation methods when the parent is feeling stressed. The information providing unit can also share successful parenting experiences when the parent is feeling positive. Furthermore, the information providing unit can send encouraging messages when the parent is feeling anxious. This makes it possible to provide parenting advice according to the parent's emotional state.

[0081] The information providing unit can also estimate the parent's emotional state and provide health management advice according to the emotion. For example, when the parent is feeling stressed, the information providing unit can suggest relaxation methods. The information providing unit can also suggest healthy lifestyle habits when the parent is feeling positive. Furthermore, the information providing unit can also suggest stress management methods when the parent is feeling anxious. In this way, health management advice according to the parent's emotional state can be provided.

[0082] The information providing unit can also estimate the emotional state of the parent and provide educational advice according to the emotion. For example, it can suggest relaxation methods when the parent is feeling stressed. The information providing unit can also share successful educational experiences when the parent is feeling positive. Furthermore, the information providing unit can send encouraging messages when the parent is feeling anxious. This makes it possible to provide educational advice according to the parent's emotional state.

[0083] The information providing unit can also estimate the parent's emotional state and provide local information according to the emotion. For example, when the parent is feeling stressed, the information providing unit can suggest relaxation methods. The information providing unit can also provide local event information when the parent is feeling positive. Furthermore, the information providing unit can send encouraging messages when the parent is feeling anxious. In this way, local information according to the parent's emotional state can be provided.

[0084] The information providing unit can also estimate the emotional state of the parent and provide parenting advice according to the emotion. For example, it can suggest relaxation methods when the parent is feeling stressed. The information providing unit can also share successful parenting experiences when the parent is feeling positive. Furthermore, the information providing unit can send encouraging messages when the parent is feeling anxious. This makes it possible to provide parenting advice according to the parent's emotional state.

[0085] The information providing unit can also provide child-rearing advice customized based on the parents' lifestyles. For example, it can provide time management advice for dual-income households. The information providing unit can also provide support information specialized for single parents. Furthermore, the information providing unit can also provide information useful for child-rearing based on the parents' hobbies and interests. This makes it possible to provide child-rearing advice customized to the parents' lifestyles.

[0086] The information providing unit can also monitor the parent's health condition and detect health problems that may affect child-rearing at an early stage. For example, it can analyze the parent's sleep patterns and provide advice on the impact of lack of sleep on child-rearing. The information providing unit can also monitor the parent's stress level and suggest stress management methods. Furthermore, the information providing unit can monitor the parent's eating habits and suggest nutritionally balanced meals. This makes it possible to provide child-rearing advice that takes the parent's health condition into consideration.

[0087] The information providing unit can also provide child-rearing advice customized based on the parents' lifestyles. For example, it can provide time management advice for dual-income households. The information providing unit can also provide support information specialized for single parents. Furthermore, the information providing unit can also provide information useful for child-rearing based on the parents' hobbies and interests. This makes it possible to provide child-rearing advice customized to the parents' lifestyles.

[0088] The processing flow of the second embodiment will be briefly explained below.

[0089] Step 1: The information provider provides information based on the child's age (months) and region. For example, the generator AI analyzes the child's age (months) and region information entered by the user, and based on that information, provides instructions on the necessary procedures and things to do. Specifically, it provides vaccination schedules and how to apply for nursery school. Step 2: The subsidy information provider provides information on available subsidies and grants. For example, the generation AI provides information on subsidies and grants related to childcare assistance, moving, home purchases, etc., depending on the user's situation. Step 3: The consultation section responds to inquiries from parents who are worried about raising their children. For example, the generation AI provides appropriate advice and information in response to questions and concerns from users. Specifically, it provides appropriate advice in response to questions such as, "My child cries at night. What should I do?" Step 4: The recommendation unit works with the e-commerce site to recommend products. For example, the generation AI recommends appropriate products based on the user's purchase history and the child's age in months. Specifically, it suggests the next product to purchase based on the user's past purchases and the child's age in months.

[0090] 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.

[0091] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> Examples of generative AIs include the data generation model 58, such as a neural network model (e.g., a neural network model), and a neural network model (e.g., a neural network model). The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating speech, text data indicating text, and image data indicating an image is also input to the data generation model 58. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specification processing unit 290 performs the above-mentioned specification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0092] 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.

[0093] [Second embodiment] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0094] 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.

[0095] 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.

[0096] 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.

[0097] 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.

[0098] 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).

[0099] 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.

[0100] 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.

[0101] 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.

[0102] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0103] In the smart glasses 214, the specific processing is performed by the processor 46. A specific processing program 60 is stored in the storage 50. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. Note that the smart glasses 214 may have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59.

[0104] 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.

[0105] 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.

[0106] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0107] 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.

[0108] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0109] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0110] 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.

[0111] 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.

[0112] 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.

[0113] 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).

[0114] 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.

[0115] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type 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.

[0116] 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.

[0117] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0118] In the headset type terminal 314, the identification process is performed by the processor 46. A identification program 60 is stored in the storage 50. The processor 46 reads the identification program 60 from the storage 50 and executes the read identification program 60 on the RAM 48. The identification process is realized by the processor 46 operating as a control unit 46A in accordance with the identification program 60 executed on the RAM 48. Note that the headset type terminal 314 may also have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59.

[0119] 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.

[0120] 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.

[0121] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0122] 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.

[0123] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0124] 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0125] 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.

[0126] 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.

[0127] 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.

[0128] 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).

[0129] 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.

[0130] 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.

[0131] 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.

[0132] 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.

[0133] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0134] In the robot 414, the processor 46 performs the identification process. A identification program 60 is stored in the storage 50. The processor 46 reads the identification program 60 from the storage 50 and executes the read identification program 60 on the RAM 48. The identification process is realized by the processor 46 operating as a control unit 46A in accordance with the identification program 60 executed on the RAM 48. Note that the robot 414 may have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59.

[0135] 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.

[0136] 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.

[0137] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0138] 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.

[0139] 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.

[0140] 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.

[0141] 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.

[0142] 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).

[0143] 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.

[0144] 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."

[0145] 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.

[0146] 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.

[0147] 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.

[0148] 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.

[0149] 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.

[0150] 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.

[0151] 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.

[0152] 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.

[0153] 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.

[0154] 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.

[0155] 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.

[0156] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference. [Explanation of symbols]

[0157] 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 section that provides information according to the child's age and region, and A grant information department that provides information on available grants and subsidies; A consultation department that responds to parents who are worried about raising their children, A recommendation unit that recommends products in cooperation with the EC site. A system characterized by:

2. The information providing unit Collecting the child's growth data in real time and providing customized advice based on individual growth patterns 2. The system of claim 1.

3. The information providing unit Build a platform to collect feedback from other parents and share this information with other parents with children in the same area and age group.

2. The system of claim 1.

4. The subsidy information providing unit Automate the application process for the subsidies and grants, automatically generating the necessary documents and procedures.

2. The system of claim 1.

5. The consultation department Analyze the parent's consultation and provide optimal advice based on past consultation history 2. The system of claim 1.

6. The recommendation unit Analyze not only purchase history but also user search and browsing history to make more accurate recommendations.

2. The system of claim 1.

7. The information providing unit Analyze the parent's emotional state and provide them with information that requires special attention during times of high stress.

2. The system of claim 1.

8. The subsidy information providing unit Providing real-time support to resolve concerns and questions about applications 2. The system of claim 1.

Images