System

Abstract

A system is provided.SOLUTION: A system comprising: means for inputting household conditions and desires; means for collecting childcare support policies and financial AI of nationwide local authorities using generated information; means for calculating a fitness score of each local authority based on the input information and the collected information; means for selecting an optimal local authority based on the calculated score; and means for visualizing detailed information of the selected local authority.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] Childcare support policies vary greatly from one local government to another, making it difficult to understand and compare the specific support provided by each local government and its financial situation. This makes it difficult for families raising children to select the local government that best suits their needs. As a result, the burden on families raising children increases due to a shortage of childcare facilities and disparities in childcare support funds, contributing to the declining birthrate problem. The purpose of this invention is to solve these problems and enable families raising children to select a residential area that suits their situation and satisfaction. [Means for solving the problem]

[0005] The present invention provides a system including a means for inputting a family's situation and aspirations, a means for using a generation AI to collect data on childcare support policies and finances of local governments nationwide, a means for calculating a suitability score for each local government based on the input information and the collected information, a means for selecting the most suitable local government based on the calculated score, and a means for visualizing detailed information on the selected local government, thereby enabling a user to easily find the most suitable local government based on their family's situation and aspirations and select a place to live based on the detailed information.

[0006] "Family situation" refers to specific information about the household related to child-rearing, including the age of the children, the number of children, annual household income, and the need for childcare facilities.

[0007] "Generative AI" refers to a system or program that uses artificial intelligence techniques to automatically generate, collect, and analyze data.

[0008] "Local government" refers to a local government, such as a city, town, village, or prefecture, that provides public services and bears administrative responsibilities in a specific area.

[0009] "Childcare support policies" refer to various childcare support initiatives provided by local governments, such as nursery school operations, childcare allowances, and educational expense subsidies.

[0010] "Financial data" refers to economic data such as budgets, tax revenues, and expenditures held by local governments.

[0011] The "relevance score" is a numerical indicator that compares the information provided by the user with the child-rearing support policies and financial situation of local governments, and quantifies how well it matches the user's needs.

[0012] "Detailed information" refers to information such as the specific child-rearing support provided by the selected local government, tax revenue, financial budget, and procedures.

[0013] "Visualization" refers to the process of presenting data or information in a visually understandable format. [Brief explanation of the drawings]

[0014] [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. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0015] 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.

[0016] First, the terms used in the following description will be explained.

[0017] 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, a 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), and an APU (Accelerated Processing Unit).

[0018] 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.

[0019] 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.

[0020] 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), Bluetooth (registered trademark), etc.

[0021] 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."

[0022] [First embodiment]

[0023] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0024] 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.

[0025] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. 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).

[0026] 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.

[0027] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. 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 acquires the data indicating the user input.

[0028] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The 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.

[0029] 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.

[0030] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0031] 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.

[0032] 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.

[0033] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0034] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0035] This invention is a system that selects the most suitable local government based on the household's circumstances and preferences and provides the user with detailed information. This system mainly involves a series of processes: user input, data collection using generative AI, calculation of compatibility scores, selection of the most suitable local government, and visualization of detailed information.

[0036] 1. User Input

[0037] The user enters information about their family situation and wishes into the device's input screen, such as the ages of their children, the number of children, the household's annual income, and the need for a nursery school. This clarifies the user's specific needs.

[0038] 2. Generative AI data collection

[0039] The device sends the information entered by the user to a server, which uses generative AI to collect data on childcare support policies and finances from local governments across the country, including the use of online databases and APIs to efficiently obtain the latest information.

[0040] 3. Server Calculation of Relevance Score

[0041] The server compares the collected data on local governments with the information entered by the user and calculates a compatibility score for each local government. The compatibility score is a numerical representation of the degree of match between the user's needs and the support provided by the local government. For example, the score is calculated by taking into account multiple conditions, such as the amount of support for two children, availability of nursery schools, and support policies based on annual household income.

[0042] 4. Server selection of the most suitable local government

[0043] Based on the relevance score, the server selects the local government with the highest score. This selection process aims to identify the local government that best matches the user's input information with the services offered by the local government. For example, for a family with two children and an income of less than 6 million yen, the server will select a local government that offers priority admission to daycare centers or provides specific childcare benefits.

[0044] 5. Visualization and transmission of detailed information by the server

[0045] The server then compiles detailed information about the selected local government and sends it to the terminal. This information includes the local government's tax revenue, financial budget, child-rearing support policies, procedures, etc. The user can then use this information to make a decision about where to live.

[0046] As a concrete example, suppose a user inputs "two children," "annual household income of 6 million yen," and "needs nursery school." In this case, the server collects and analyzes data on local governments across the country and selects the municipality with the highest suitability score. For example, City X is selected as the most suitable municipality, and detailed information is presented, such as "nursery school vacancies available, no children on waiting lists," "generous childcare allowances for households with annual incomes of 6 million yen or less," and "stable tax revenues, with a sufficient budget for childcare support." The user can view this information and select City X as the municipality that best suits their family situation.

[0047] This invention allows families raising children to easily select the local government that best suits their needs, reducing the burden of raising children. This will promote competition among local governments in providing services to residents, and is expected to improve the overall environment for raising children.

[0048] The processing flow will be explained below.

[0049] Step 1:

[0050] The user uses the terminal to input information about the household (children's ages, number of children, annual household income, need for childcare facilities, etc.).

[0051] Step 2:

[0052] The device sends information entered by the user to the server, including the ages of the children, the number of children, the annual household income, and the need for childcare facilities.

[0053] Step 3:

[0054] The server uses generative AI to collect childcare support policy and financial data from local governments across the country, including retrieving the latest information from online databases and APIs.

[0055] Step 4:

[0056] The server analyzes the collected local government data and extracts the child-rearing support provided by each local government and its financial situation.

[0057] Step 5:

[0058] The server compares the household situation sent by the user with the support provided by the local government and calculates a compatibility score, which is a numerical representation of the degree of match between the user's needs and the services provided by the local government.

[0059] Step 6:

[0060] The server selects the local government with the highest score based on the calculated relevance scores, which involves a process of assigning a score to each local government based on each criterion and identifying the local government with the highest score.

[0061] Step 7:

[0062] The server compiles detailed information about the selected local governments (tax revenue, financial budget, details of child-rearing support policies, procedures, etc.) and sends it to the terminal.

[0063] Step 8:

[0064] The terminal displays detailed information about local governments received from the server to the user, who can then use this information to determine which local government best suits their household situation.

[0065] Step 9:

[0066] The user selects the local government that best suits their needs from the presented candidate locations and proceeds with the relocation and administrative procedures.

[0067] As described above, this system identifies the most suitable local government based on the information entered by the user and provides detailed information about it, thereby helping the user make a rational choice.

[0068] Example 1

[0069] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0070] In modern society, it is a complex and time-consuming task for families to select the public organization that best suits their situation and wishes. It is especially important for families raising children to accurately understand and compare each local government's child-rearing support policies and financial situation, but this requires collecting and analyzing a lot of information, which is a significant burden. Furthermore, because the process for selecting the appropriate local government is unclear, there is a risk of making a wrong decision.

[0071] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0072] In this invention, the server includes a means for inputting the user's family situation and wishes, a means for using a generation AI to collect data on child-rearing support policies and finances of public organizations nationwide, and a means for calculating a suitability score for each public organization based on the input information and the collected information. This makes it possible to quickly and accurately select the public organization that best suits the user's family situation and wishes and visualize its detailed information.

[0073] "Family situation and wishes" is information entered by the user, such as the ages of minors, the number of minors, household income, and the need for childcare facilities.

[0074] "Generative AI" is a model for generating and collecting information using artificial intelligence technology.

[0075] "Public bodies" are local government bodies such as local governments and cities, towns, and villages.

[0076] "Childcare support policies" refer to childcare support services and programs provided by public organizations.

[0077] "Financial data" means information about the income, expenditure and budget of a public body.

[0078] The "suitability score" is an evaluation score that quantifies the suitability of each public organization to the user's family situation and preferences.

[0079] A "selected public entity" is a public entity that is determined to be most suitable for the user based on the relevance score.

[0080] "Detailed information" refers to specific information such as the selected public body's income, financial plan, funding allocation, child-rearing support content, and procedures.

[0081] "Visualization" means displaying collected information and calculation results in a form that is easy for users to understand.

[0082] This invention is a system that selects the most suitable public organization based on the household's situation and preferences and provides the user with detailed information. This system involves a series of processes, including user input, data collection using generative AI, calculation of compatibility scores, selection of the most suitable public organization, and visualization of detailed information.

[0083] 1. User Input

[0084] The user enters their household situation and wishes via the device's input screen, such as the ages of minors, the number of minors, household income, and the need for childcare facilities. This operation conveys the user's specific needs to the system.

[0085] 2. Generative AI data collection

[0086] The device sends the information entered by the user to a server, which then uses a generative AI model to collect data on childcare support policies and finances of public organizations. Specifically, the server uses online databases and APIs to obtain the latest information on public organizations.

[0087] 3. Server Calculation of Relevance Score

[0088] The server compares the public organization data collected by the generative AI model with the information entered by the user and calculates a compatibility score for each public organization. The compatibility score is a numerical representation of the degree of match between the user's needs and the support provided by the public organization. For example, the score is calculated taking into account multiple conditions, such as the amount of support for two minors, the availability of childcare facilities, and support policies based on household income.

[0089] 4. Server selection of the most suitable public organization

[0090] The server selects the public organization with the highest score based on the calculated relevance score. This process aims to identify the organization whose services best match the user's family situation and preferences. For example, if a family with an income of less than 6 million yen has two minor children, the server will select public organizations that offer priority admission to childcare facilities or that offer specific childcare allowances.

[0091] 5. Visualization and transmission of detailed information by the server

[0092] The server compiles detailed information about the selected public organization and sends it to the terminal. This information includes details such as the organization's revenue, financial plan, fund allocation, childcare support details, and procedures. Users can use this information to make decisions about where to live.

[0093] Specific examples

[0094] For example, if a user inputs "two minors," "household income of 6 million yen," and "needs childcare facilities," the server collects and analyzes data on public organizations across the country. It then identifies the public organization with the highest compatibility score. For example, City X may be selected as the most suitable public organization, and detailed information such as "childcare facilities available, no children on waiting lists," "generous childcare allowances for households with incomes of 6 million yen or less," and "stable income, with a sufficient budget for childcare support" may be displayed.

[0095] Example prompts for generative AI models

[0096] Below is an example of a prompt sentence to input to the generative AI model.

[0097] Family situation: 2 minors, household income of 6 million yen, childcare facility required

[0098] Select the public organization that best suits your situation.

[0099] This system will enable families with children to easily select the public organization that best meets their needs, reducing the burden of child-rearing. It will also promote competition among public organizations in providing resident services, which is expected to improve the overall child-rearing environment.

[0100] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0101] Step 1:

[0102] The user enters their family situation and wishes into the device's input screen. Specifically, they enter information such as the ages of minors, the number of minors, household income, and the need for childcare facilities. This information is temporarily saved by the device. For example, the user might enter "two minors, ages 5 and 3," "household income 6 million yen," and "need childcare facilities."

[0103] Input: User's family situation and desired information

[0104] Output: User input information temporarily saved to the device

[0105] Step 2:

[0106] The device sends the input information to the server, which then passes the received user information to the generative AI model to create a prompt. The generated prompt is then input into the generative AI model, which then collects data from appropriate public organizations.

[0107] Input: User input information

[0108] Output: The prompt sentence that is input to the generative AI model

[0109] Specific actions

[0110] The device sends information such as "two minors, annual income of 6 million yen, needing childcare facilities" to the server, which then inputs the following prompt into the generative AI model: "Family situation: two minors, household income of 6 million yen, needing childcare facilities. Please select the public organization that best suits this situation."

[0111] Step 3:

[0112] The server uses the information obtained from the generative AI model to obtain data on public organizations across the country, using online databases and APIs to collect the latest public organization data.

[0113] Input: Prompt sentence for the generative AI model

[0114] Output: Latest data for public organizations nationwide

[0115] Specific actions

[0116] For example, the server accesses the databases of City X, Town Y, and City Z to obtain child-rearing support policies and financial data for each local government.

[0117] Step 4:

[0118] The server compares the collected data on public organizations with the user's input information and calculates a relevance score, taking into account factors such as the amount of support for two minors, availability of childcare facilities, and support policies based on household income.

[0119] Input: User input and collected public data

[0120] Output: Relevance score for each public body

[0121] Specific actions

[0122] For example, the server calculates the relevance score for each item based on information such as "the amount of support for two children in City X" and "availability of childcare facilities in Town Y."

[0123] Step 5:

[0124] The server selects the public entity with the highest relevance score based on the calculated relevance scores and prepares detailed information about the selected public entity.

[0125] Input: Relevance score

[0126] Output: Selected public organizations and their details

[0127] Specific actions

[0128] For example, if "City X was judged to be the most suitable municipality," the system will compile detailed information such as the reason for this, such as "there is a good availability of childcare facilities and childcare allowances are generous."

[0129] Step 6:

[0130] The server compiles detailed information about the selected public organizations and sends it to the terminal, which displays the received information to the user.

[0131] Input: Details of the selected public body

[0132] Output: sent to terminal, displayed to user

[0133] Specific actions

[0134] For example, the device will display "Detailed information about City X," including information such as "Childcare facilities are available and there are no children on waiting lists," "Childcare allowances are generous for households with incomes of 6 million yen or less," and "Income is stable and there is a sufficient budget for childcare support."

[0135] The above is the flow of specific program processing in the system of the present invention. This processing allows users to easily find the public organization that best suits their family situation and wishes.

[0136] (Application example 1)

[0137] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0138] There is a need for a system that not only selects the most suitable local government based on a family's circumstances and preferences and provides detailed information about the local government, but also provides local safety information to give families raising children a sense of security. However, existing systems have the problem of only handling local government child-rearing support policies and financial data, and not including safety information. By solving this problem, there is a need to enable users to select a place to live with peace of mind.

[0139] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0140] In this invention, the server includes means for inputting the family's situation and preferences, means for using a generation AI to collect child-rearing support policies and financial data of local governments nationwide and local safety information, means for calculating a suitability score for each local government based on the input information and the collected information, means for selecting the most suitable local government based on the calculated score, and means for visualizing detailed information about the selected local government and local safety information. This allows users to not only select the most suitable local government but also to select a place to live with peace of mind, taking into account local safety information.

[0141] "Family situation" refers to basic information about the family, such as the age of children, the number of children, annual household income, and the need for childcare facilities.

[0142] "Hope" refers to requirements regarding the living conditions and environment desired by the user, specifically, requests for housing, education, medical care, public safety, etc.

[0143] "Generative AI" is an artificial intelligence technology that automates text generation and data collection, and is designed to collect and provide information in response to user requests.

[0144] "Local governments" refer to public institutions such as local governments and municipalities, which are organizations that provide various administrative services and support to local residents.

[0145] "Childcare support policies" refer to support measures and policies related to childcare provided by local governments, including the provision of daycare centers, childcare allowances, and childcare consultations.

[0146] "Financial data" refers to information about the financial situation of local governments, including data on tax revenues, financial budgets, and allocations.

[0147] "Local safety information" refers to information related to safety, such as local crime statistics, disaster prevention information, and contact information for police stations.

[0148] The "relevance score" is a numerical representation of the degree of match between the user's needs and the services provided by local governments.

[0149] "Detailed information" refers to specific data including the selected local government's tax revenue, financial budget, allocation, child care support provided, procedures, and local safety information.

[0150] An embodiment of the present invention will be described. The present invention is a system that selects an optimal local government based on a family's situation and preferences, and provides the user with detailed information about the local government and local safety information. This system includes a means for inputting the family's situation and preferences, a means for using a generation AI to collect child-rearing support policies and financial data of local governments nationwide and local safety information, a means for calculating a compatibility score for each local government based on the input information and the collected information, a means for selecting the optimal local government based on the calculated score, and a means for visualizing detailed information about the selected local government and local safety information.

[0151] First, a user uses a smartphone or tablet to input information about their household situation and preferences into the application, including the ages and number of children, annual household income, and the need for childcare facilities. The device then sends this information to the server.

[0152] The server uses generative AI to collect childcare support policies, financial data, and local safety information from local governments across the country. This data collection utilizes APIs and public databases on the internet. Specific generative AI models used include GPT-4 (registered trademark) and BERT.

[0153] Based on the collected data, the server compares the user's input information with the data of the local government and calculates a relevance score. This score quantifies the degree of match between the user's needs and the services provided by the local government. For example, it takes into account the amount of support for two children, availability of nursery schools, and support policies based on annual household income.

[0154] Based on the calculated relevance scores, the server selects the local government with the highest score. This selection process identifies the local government whose services best match the user's household situation.

[0155] Finally, the server compiles and transmits detailed information about the selected local government and local safety information to the device. The detailed information includes the local government's tax revenue, financial budget, allocation, childcare support provided, procedures, local crime statistics, and contact information for the police station. Based on this information, users can choose the local government that best suits their family situation.

[0156] As a concrete example, if a user inputs "two children, annual household income of 6 million yen, needing nursery school," the server uses a generative AI model to collect and analyze data from across the country. City X with the highest relevance score is selected, and detailed information such as "nursery school availability, no waiting list, generous childcare allowance for households with annual income of 6 million yen or less, stable tax revenue" is displayed. Safety information for City X, including "low crime rate and contact information for the police station," is also provided.

[0157] An example prompt might look like this:

[0158] "Search for a local government that is suitable for a family with two children, an annual household income of 6 million yen, and who needs nursery school."

[0159] The above is a specific embodiment for carrying out the invention. This system enables users to easily and safely select the most suitable local government.

[0160] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0161] Step 1:

[0162] The user uses a smartphone or tablet to input information about their household situation and preferences into the application. Specifically, they input necessary information such as "children's ages," "number of children," "annual household income," and "need for childcare facilities" on the input screen. The input information is temporarily stored on the device and prepared for transmission to the server.

[0163] Input: Age of children, number of children, annual household income, need for childcare facilities

[0164] Output: User's home information temporarily stored on the device

[0165] Step 2:

[0166] The device sends the user information entered in the previous step to the server, which analyzes the received information and begins processing. The server uses the generative AI model to collect child-rearing support policies and financial data from local governments across the country, as well as local safety information.

[0167] Input: User's home information sent from the device

[0168] Output: Server that started data collection based on user information

[0169] Step 3:

[0170] The server uses a generative AI model (e.g., GPT-4 or BERT) to collect childcare support policies, financial data, and local safety information from APIs and online databases across the country. The collected data is stored in a database on the server.

[0171] Input: User's home information

[0172] Output: Collected childcare support policies, financial data, and local safety information of local governments

[0173] Step 4:

[0174] The server compares the user's input information with the collected data of each local government and calculates a compatibility score, which is calculated by taking into account multiple conditions, such as the amount of support for two children, availability of nursery schools, support policies based on annual household income, and the safety of the area.

[0175] Input: User's household information, collected data from local government organizations

[0176] Output: Relevance score for each local government

[0177] Step 5:

[0178] Based on the calculated relevance score, the server selects the local government that best matches the user's household situation. In this process, the local government with the highest score is selected.

[0179] Input: Relevance score

[0180] Output: Selected optimal local government

[0181] Step 6:

[0182] The server then compiles detailed information about the selected local governments and local safety information, generating data for visualization, including the local government's tax revenue, financial budget, allocation, childcare support provided, procedures, local crime statistics, and contact information for the police station.

[0183] Input: Selected local government

[0184] Output: Detailed information on local governments and local safety information

[0185] Step 7:

[0186] The server sends the generated detailed information and local safety information to the device, which then displays the received information to the user. Specifically, the device displays child-rearing environment and safety information from local governments in an easy-to-read format.

[0187] Input: Detailed information about local government and local safety information

[0188] Output: Information displayed on the user's terminal

[0189] For example:

[0190] Consider the case where a user inputs "two children, annual household income of 6 million yen, needing nursery school." This information is sent from the device to the server, and the generative AI model collects and analyzes data from across the country. The server selects City X with the highest relevance score, and detailed information about the selected City X, along with information that it is a safe area with a low crime rate, is displayed on the user's device.

[0191] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0192] This invention is a system that selects the most suitable local government based on the household's situation and preferences, provides the user with detailed information about the local government, and further combines it with an emotion engine that recognizes the user's emotions. This system mainly involves a series of processes: user input, data collection using generative AI, calculation of compatibility scores, adjustment of scores based on the user's emotional state, selection of the most suitable local government, and visualization of detailed information.

[0193] 1. User Input

[0194] The user enters information about their family situation and wishes into the device's input screen, such as the ages of their children, the number of children, the household's annual income, and the need for a nursery school. This clarifies the user's specific needs.

[0195] 2. Emotion Recognition by Emotion Engine

[0196] The device recognizes the user's emotional state from facial expressions, voice tone, and text input. The emotion engine analyzes the user's emotions and sends the information to the server. This emotion information detects emotional states such as stress and anxiety.

[0197] 3. Generative AI data collection

[0198] The device sends the information and emotional information input by the user to a server, which uses generative AI to collect childcare support policies and financial data from local governments across the country. This includes using online databases and APIs to efficiently obtain the latest information.

[0199] 4. Server Calculation of Relevance Score

[0200] The server calculates a relevance score for each local government based on the collected local government data, the user's input information, and the user's emotional information. The relevance score is a numerical representation of the degree of match between the user's needs and the support provided by the local government.

[0201] 5. Server-Based Relevance Score Adjustment

[0202] The server adjusts the relevance score based on the user's emotional state. For example, if the user is under high stress, the server will tend to prioritize local governments that offer comprehensive childcare support. This adjustment allows the server to select the local government that best suits the user's emotional state.

[0203] 6. Server selection of the most suitable local government

[0204] Based on the adjusted relevance scores, the server selects the local government with the highest score. This selection process aims to identify the local government that best matches the user's input information with the services provided by the local government.

[0205] 7. Visualization and transmission of detailed information by the server

[0206] The server compiles detailed information about the selected local governments (tax revenue, financial budget, details of child-rearing support policies, procedures, etc.) and sends it to the terminal.

[0207] 8. Displaying detailed information on the terminal

[0208] The terminal displays detailed information about local governments received from the server to the user, who can then use this information to determine which local government best suits their family situation and emotional state.

[0209] As a specific example, suppose a user inputs "two children," "annual household income of 6 million yen," "needs nursery school," and "high stress level." In this case, the server collects and analyzes data from local governments across the country and selects the municipality with the highest compatibility score. For example, City X is selected as the most suitable municipality, and detailed information about it is presented, including "vacant nursery schools and no children on waiting lists," "generous childcare allowances for households with annual incomes of 6 million yen or less," and "stable tax revenues and a sufficient budget for childcare support." The user can view this information and select City X as the municipality that best suits their family situation and emotional state.

[0210] This invention allows families raising children to easily find the most suitable local government based on their needs and emotional state, and make rational choices based on the detailed information. This will promote competition among local governments in providing resident services, and is expected to improve the overall child-rearing environment.

[0211] The processing flow will be explained below.

[0212] Step 1:

[0213] The user uses the terminal to input their household situation (children's ages, number of children, annual household income, need for childcare facilities, etc.) and their wishes, which clarifies the user's specific needs.

[0214] Step 2:

[0215] When a user inputs information, the device uses an emotion engine to recognize the user's emotional state from their facial expressions, voice tone, and text input. The emotion engine analyzes the user's emotional state (e.g., stress, anxiety, joy, etc.).

[0216] Step 3:

[0217] The device sends the home situation and wishes entered by the user, as well as the recognized emotion information, to the server, which then aggregates the necessary information.

[0218] Step 4:

[0219] The server uses generative AI to collect childcare support policies and financial data from local governments across the country, retrieving the latest information from online databases and APIs and storing it in a database.

[0220] Step 5:

[0221] The server analyzes the collected data from local governments and extracts details of child-rearing support and financial status for each local government, allowing the information on each local government to be organized.

[0222] Step 6:

[0223] The server compares the household situation and wishes sent by the user with the support offered by each local government and calculates a compatibility score, which is a numerical representation of the degree of match between the user's needs and the services offered by the local government.

[0224] Step 7:

[0225] The server adjusts the relevance score calculated in step 6, taking into account the user's emotional state. For example, if the user is in a high stress state, the score is adjusted to prioritize local governments with substantial childcare support.

[0226] Step 8:

[0227] The server selects the local government with the highest score based on the adjusted relevance score. This process identifies the local government that best matches the user's input information with the services provided by the local government.

[0228] Step 9:

[0229] The server compiles detailed information about the selected local governments (e.g., tax revenue, financial budget, details of child-rearing support policies, procedures) and sends it to the terminal.

[0230] Step 10:

[0231] The terminal displays detailed information about local governments received from the server to the user, who can then use this information to determine which local government best suits their family situation and emotional state.

[0232] As a concrete example, consider the case where a user inputs "two children," "annual household income of 6 million yen," "needs nursery school," and "high stress level." This information is sent from the device to the server, which uses generative AI to collect and analyze data on local governments across the country. The local governments that best fit the user's needs are then scored and adjusted based on the emotion engine. The municipality with the highest score is selected, and its details are sent to the device. Ultimately, the user can make a rational decision based on the information provided and choose the municipality that best suits their family situation and emotional state.

[0233] Example 2

[0234] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0235] Conventional systems have difficulty selecting an appropriate local government based on the user's household situation, and are unable to take the user's emotional state into account, making it impossible to make an optimal selection. As a result, it is difficult for users to make decisions based on appropriate information, resulting in issues such as reduced satisfaction and increased stress.

[0236] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for inputting family situation and wishes, means for recognizing and analyzing the user's emotional state, means for collecting child-rearing support policies and financial data of local governments nationwide using a generation AI, means for calculating a suitability score for each local government based on the input information and the collected information, means for adjusting the suitability score based on the emotional state, means for selecting the optimal local government based on the calculated and adjusted score, and means for visualizing detailed information about the selected local government. This enables the user to select the local government that is most suitable for their family situation and emotional state.

[0237] "Family situation" refers to specific matters and conditions within the home, such as the age and number of children, annual household income, and the need for childcare facilities.

[0238] "User's emotional state" refers to the user's current psychological state, including, for example, stress, anxiety, and satisfaction.

[0239] "Generative AI" refers to the use of artificial intelligence to generate and analyze data, particularly as a means of gathering up-to-date information using extensive databases and APIs.

[0240] The "relevance score" is a numerical representation of the degree of match between the user's needs and the support provided by the local government.

[0241] "Local governments" refer to organizations that provide administrative services in each region, and typically include cities, towns, villages, prefectures, etc.

[0242] "Detailed information" refers to specific data about the selected local governments, including, for example, tax revenue, financial budget, content of child-rearing support policies, and procedures.

[0243] This invention is a system that selects the most suitable local government based on the household's situation and preferences and provides detailed information to the user. This system involves a series of processes: user input, data collection using generative AI, calculation of compatibility scores, adjustment of scores based on the user's emotional state, selection of the most suitable local government, and visualization of detailed information.

[0244] 1. User Input

[0245] Users input their household situation and preferences through the device's input screen. Specifically, they input information such as the ages and number of children, annual household income, and the need for childcare facilities. This input clarifies the user's specific needs.

[0246] 2. Emotion Recognition by Emotion Engine

[0247] The device recognizes the user's emotional state from facial expressions, voice tone, and text input content. The emotion engine analyzes the user's emotions using the device's built-in camera and microphone. The analysis results are sent to the server and used as emotion information.

[0248] 3. Generative AI data collection

[0249] The device sends the household situation information and emotional information entered by the user to a server, which then uses generative AI to collect childcare support policy and financial data from local governments across the country. This collection includes the use of online databases and APIs to obtain the latest information.

[0250] 4. Server Calculation of Relevance Score

[0251] The server calculates a relevance score based on the collected local government data, the user's input information, and the user's emotional information. The relevance score is a numerical representation of the degree of match between the user's needs and the support provided by the local government.

[0252] 5. Server-Based Relevance Score Adjustment

[0253] The server adjusts the relevance score based on the user's emotional state. For example, if the user is under high stress, it will prioritize local governments that offer comprehensive childcare support. This adjustment allows the server to select the local government that best suits the user's emotional state.

[0254] 6. Server selection of the most suitable local government

[0255] Based on the adjusted relevance scores, the server selects the local government with the highest score. This selection process aims to identify the local government that best matches the user's input information with the services provided by the local government.

[0256] 7. Visualization and transmission of detailed information by the server

[0257] The server compiles detailed information about the selected local governments (tax revenue, financial budget, details of child-rearing support policies, procedures, etc.) and sends it to the terminal.

[0258] 8. Displaying detailed information on the terminal

[0259] The terminal displays detailed information about local governments received from the server to the user, who can then use this information to make a decision about which local government best suits their family situation and emotional state.

[0260] Examples of concrete examples and prompts

[0261] As a concrete example, consider the case where a user enters the following information:

[0262] 2 children

[0263] Annual household income: 6 million yen

[0264] Nursery school needed

[0265] High stress

[0266] The server collects and analyzes data on local governments across the country and selects the municipality with the highest relevance score. For example, a city may be selected as the best municipality, and its detailed information will be presented as follows:

[0267] There are vacant nursery schools and no children on waiting lists.

[0268] Enhanced childcare allowance for households with an annual income of 6 million yen or less

[0269] Tax revenues are stable and there is a sufficient budget for childcare support.

[0270] With this information, users can select the municipality that best suits their home situation and emotional state.

[0271] Example prompt sentence:

[0272] Enter "2 children," "annual household income of 6 million yen," "need nursery school," and "high stress level," and provide the most suitable local government and its details.

[0273] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0274] Step 1: User Input

[0275] The user enters information about their household situation and preferences into the device's input screen. Specifically, they enter information such as the ages of their children, the number of children, their annual household income, and the need for childcare facilities. This clarifies the user's specific needs. The entered information is temporarily saved on the device.

[0276] Specific behavior:

[0277] The user connects to the device and opens the input screen.

[0278] Enter the required information for each item using text boxes and radio buttons.

[0279] Check the information you entered and click the Confirm button.

[0280] The entered data is stored in the terminal and sent to the next processing step.

[0281] Input: Age of children, number of children, annual household income, need for childcare facilities, etc.

[0282] Output: User's home situation information

[0283] Step 2: Emotion recognition by the emotion engine

[0284] The device recognizes the user's emotional state from facial expressions, tone of voice, and text content when the user types. The emotion engine analyzes the user's emotions using the device's built-in camera and microphone. This information is sent to the server.

[0285] Specific behavior:

[0286] The device's camera records the user's facial expressions.

[0287] The device's microphone records the user's voice.

[0288] The emotion engine analyzes this data in real time to determine the emotional state.

[0289] Emotion data is generated and sent to a server.

[0290] Input: User facial expressions, voice, text

[0291] Output: Emotional state data

[0292] Step 3: Data collection with generative AI

[0293] The device sends the household situation information and emotional information entered by the user to a server, which then uses generative AI to collect childcare support policy and financial data from local governments across the country. This collection involves the use of databases and APIs.

[0294] Specific behavior:

[0295] The user's input data and emotion data are sent to the server.

[0296] The server launches the generation AI and accesses the necessary databases and APIs to collect information.

[0297] The collected data is stored on a server and sent to the next processing step.

[0298] Input: User's home situation information, emotional state data

[0299] Output: Childcare support policy data and financial data of local governments

[0300] Step 4: Server calculates relevance score

[0301] The server calculates a compatibility score for each local government based on the collected local government data and the user's household situation and emotional information. The compatibility score is a numerical representation of the degree of match between the user's needs and the support provided by the local government.

[0302] Specific behavior:

[0303] The collected local government data is subjected to an analytical algorithm.

[0304] The user's home situation information and emotional information are subjected to an analysis algorithm.

[0305] A relevance score is calculated for each local government and sent to the next processing step.

[0306] Input: Childcare support policy data of local governments, financial data, user's household situation information, emotional state data

[0307] Output: Relevance score

[0308] Step 5: Server adjusts relevance scores

[0309] The server adjusts the relevance score based on the user's emotional state. For example, if the user is under high stress, it will prioritize local governments that offer comprehensive childcare support. This adjustment allows the server to select the local government that best suits the user's emotional state.

[0310] Specific behavior:

[0311] Emotional state data is analyzed to assess factors such as stress.

[0312] A weight corresponding to the emotional state is added to the relevance score.

[0313] The suitability scores are recalculated and the local government with the best score is selected.

[0314] Input: Relevance score, emotional state data

[0315] Output: Adjusted fitness score

[0316] Step 6: The server selects the most suitable local government.

[0317] Based on the adjusted relevance score, the server selects the local government with the highest score. This selection process aims to identify the municipality that best matches the user's household situation and the services provided by the local government.

[0318] Specific behavior:

[0319] The suitability scores of each local government are listed in a ranking format.

[0320] Select the local government with the highest score.

[0321] The selected local governments will be listed.

[0322] Input: Adjusted relevance score

[0323] Output: Selected local governments

[0324] Step 7: Server visualizes and sends detailed information

[0325] The server then compiles detailed information about the selected local governments and sends it to the terminal, including information on child-rearing support policies, financial status, and procedures.

[0326] Specific behavior:

[0327] Relevant information on selected local governments is extracted from the database.

[0328] Format the data in a way that is easy for users to understand.

[0329] The organized data is sent to the device.

[0330] Input: Selected local government

[0331] Output:Detailed information of local government

[0332] Step 8: Viewing detailed information via terminal

[0333] The terminal displays detailed information about local governments received from the server to the user, who can then use this information to make a decision about which local government best suits their family situation and emotional state.

[0334] Specific behavior:

[0335] The terminal receives the data received from the server.

[0336] Detailed information is displayed in a GUI (graphical user interface).

[0337] The user views the displayed information and makes a final selection.

[0338] Input: Detailed information of local government

[0339] Output: Final selection result

[0340] (Application example 2)

[0341] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0342] Conventional local government selection systems present candidates based on the user's family situation and preferences, but do not consider the user's emotional state. This can lead to stress and an inappropriate selection. Furthermore, detailed information about the selected local government is not displayed properly, providing insufficient reference information for users to use when making decisions. Therefore, there is a need for a system that can select a more appropriate local government and provide detailed information, taking into account not only the user's family situation and preferences, but also the user's emotional state.

[0343] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for inputting the family's situation and wishes, means for collecting child-rearing support policies and financial data of local governments nationwide using a generation AI, means for calculating a suitability score for each local government based on the input information and the collected information, means for recognizing the user's emotional state, means for adjusting the calculated score based on the emotional state, means for selecting the most suitable local government based on the adjusted score, means for visualizing detailed information about the selected local government, and means for displaying the detailed information to the user. This makes it possible to select the most suitable local government that comprehensively takes into account the family's situation, wishes, and emotional state, and to provide detailed information.

[0344] "Family situation" refers to information such as the user's family structure, the number of children, their ages, annual household income, and the need for childcare facilities.

[0345] "Desire" includes elements such as the user's desired living environment, support content, budget, and specific conditions.

[0346] "Generative AI" is an artificial intelligence technology that collects and analyzes data, and has the means to obtain childcare support policies and financial data from local governments.

[0347] The "relevance score" is an evaluation index that quantifies the degree of match between the user's input information and the collected data of local governments.

[0348] "Emotional state" refers to the psychological and emotional state, such as stress, anxiety, or excitement, that a user expresses when entering input.

[0349] "Emotion recognition means" refers to a means that uses technology to detect and analyze emotions from a user's facial expressions, voice, text input, etc.

[0350] "Detailed information" refers to specific data such as local government tax revenues, financial budgets, allocations, childcare support provided, and procedures.

[0351] "Visualization" includes the process of displaying collected and analyzed information in a way that is easy for users to understand.

[0352] "Display means" refers to a function that allows a user to visually check information through a terminal.

[0353] This invention is a system that selects the most suitable local government based on the user's household situation and preferences, and provides detailed information. It also incorporates an emotion engine that recognizes the user's emotional state and utilizes that information. This system includes the following main means:

[0354] System Configuration

[0355] A means of inputting family circumstances and wishes

[0356] The device provides an interface for users to input their family situation and preferences. For example, users input information such as "family structure," "number of children," "ages," "annual household income," and "need for childcare facilities." This information is used to clarify the specific needs of the family.

[0357] A means of recognizing emotional states

[0358] The device is equipped with a camera and microphone to recognize the user's emotional state. This drives an emotion engine that analyzes the user's facial expressions and voice tone to detect their emotional state (e.g., stress, anxiety, excitement). The emotion engine uses TENSORFLOW (registered trademark), and emotion analysis is based on a deep learning model.

[0359] Collecting data and calculating relevance scores

[0360] The server uses generative AI to collect childcare support policy and financial data from local governments across the country from online databases and APIs. This data is then compared with the user's input information to calculate a relevance score. The relevance score is a numerical representation of how closely the user's needs match the services provided by the local government.

[0361] Score adjustment and selection of optimal local governments

[0362] The server adjusts the relevance score to reflect the detected emotional state of the user. For example, if the user is in a high stress state, it will prioritize local governments that offer comprehensive childcare support. Based on the adjusted relevance score, the server selects the most suitable local government.

[0363] Visualization and display of detailed information

[0364] The server compiles detailed information about the selected local government (e.g., tax revenue, financial budget, childcare support provided, procedures, etc.) and sends it to the terminal. The terminal displays this information to the user, who then makes a decision based on it.

[0365] Hardware and software used

[0366] Hardware: Smartphone, smart glasses, camera, microphone

[0367] Software: TensorFlow (deep learning model for sentiment analysis), OpenCV (image processing), Flask (data collection and server-side processing), SQLite (database)

[0368] Specific examples

[0369] Suppose a user inputs "Family composition: 2 parents, 2 children," "Children's ages: 3 and 5 years old," "Annual household income: 6 million yen," "Childcare facilities: needed," and "Emotional state: high stress." In this case, the server collects data on local governments across the country and selects the municipality that best meets the user's needs. For example, a certain municipality may have "vacant nursery schools and no children on waiting lists," "generous childcare allowances for households with an annual income of 6 million yen or less," and "extensive childcare support systems," and provide these results to the user.

[0370] Prompt Sentence Examples

[0371] Example user input:

[0372] Family composition: 2 parents, 2 children

[0373] "Children's ages: 3 and 5 years old"

[0374] "Household annual income: 6 million yen"

[0375] "Childcare facilities: necessary"

[0376] "Emotional state: High stress"

[0377] Based on this information, the system can identify the local government that best meets the user's needs and provide detailed information.

[0378] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0379] Step 1:

[0380] The terminal provides an interface for inputting the user's household situation and wishes. For example, the user might enter information such as "Family composition: 2 parents, 2 children," "Children's ages: 3 and 5 years old," "Household annual income: 6 million yen," and "Childcare facilities: necessary." The input data is sent to the server by the terminal.

[0381] Step 2:

[0382] To recognize the user's emotional state, the device uses a camera and microphone to capture the user's facial expressions and voice tone. The captured data is analyzed by the emotion engine, which uses TensorFlow to measure the user's emotional state (e.g., stress, anxiety, excitement, etc.).

[0383] Step 3:

[0384] The server uses generative AI to collect data on childcare support policies and finances from local governments across the country. The data is obtained from online databases and APIs. This collected data is stored in a local database (SQLite).

[0385] Step 4:

[0386] The server calculates a relevance score for each local government based on the input information and emotional information received from the user. The score is calculated using an algorithm that evaluates the degree of match between the user's needs and the services provided by the local government. The calculation results are converted into numerical data and stored on the server.

[0387] Step 5:

[0388] The server adjusts the relevance score based on the user's emotional state. For example, if the user is under high stress, the server will prioritize and increase the scores of local governments that offer comprehensive childcare support. The adjusted scores are then saved back to the server.

[0389] Step 6:

[0390] Based on the adjusted relevance score, the server selects the most suitable local government. The local government with the highest score is prioritized in the selection process. The selection results are organized with detailed information about the most suitable local government.

[0391] Step 7:

[0392] The server formats detailed information about the selected local government (tax revenue, financial budget, childcare support provided, procedures, etc.) for the user and sends it to the terminal.

[0393] Step 8:

[0394] The device receives detailed information about the local government from the server and displays it to the user through a user-friendly interface, such as on the display of a smartphone or smart glasses. The user can then review the detailed information and make decisions based on it.

[0395] These steps allow for the selection of the most suitable local government taking into account the user's household situation, wishes, and emotional state, and provide the user with detailed information.

[0396] 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.

[0397] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. 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 voice, text data indicating text, and image data indicating an image is also input. 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.

[0398] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0399] [Second embodiment]

[0400] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0401] 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.

[0402] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. 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).

[0403] 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.

[0404] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0405] 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 surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0406] 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. 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.

[0407] 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.

[0408] 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 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.

[0409] 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.

[0410] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0411] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0412] This invention is a system that selects the most suitable local government based on the household's circumstances and preferences and provides the user with detailed information. This system mainly involves a series of processes: user input, data collection using generative AI, calculation of compatibility scores, selection of the most suitable local government, and visualization of detailed information.

[0413] 1. User Input

[0414] The user enters information about their family situation and wishes into the device's input screen, such as the ages of their children, the number of children, the household's annual income, and the need for a nursery school. This clarifies the user's specific needs.

[0415] 2. Generative AI data collection

[0416] The device sends the information entered by the user to a server, which uses generative AI to collect data on childcare support policies and finances from local governments across the country, including the use of online databases and APIs to efficiently obtain the latest information.

[0417] 3. Server Calculation of Relevance Score

[0418] The server compares the collected data on local governments with the information entered by the user and calculates a compatibility score for each local government. The compatibility score is a numerical representation of the degree of match between the user's needs and the support provided by the local government. For example, the score is calculated by taking into account multiple conditions, such as the amount of support for two children, availability of nursery schools, and support policies based on annual household income.

[0419] 4. Server selection of the most suitable local government

[0420] Based on the relevance score, the server selects the local government with the highest score. This selection process aims to identify the local government that best matches the user's input information with the services offered by the local government. For example, for a family with two children and an income of less than 6 million yen, the server will select a local government that offers priority admission to daycare centers or provides specific childcare benefits.

[0421] 5. Visualization and transmission of detailed information by the server

[0422] The server then compiles detailed information about the selected local government and sends it to the terminal. This information includes the local government's tax revenue, financial budget, child-rearing support policies, procedures, etc. The user can then use this information to make a decision about where to live.

[0423] As a concrete example, suppose a user inputs "two children," "annual household income of 6 million yen," and "needs nursery school." In this case, the server collects and analyzes data on local governments across the country and selects the municipality with the highest suitability score. For example, City X is selected as the most suitable municipality, and detailed information is presented, such as "nursery school vacancies available, no children on waiting lists," "generous childcare allowances for households with annual incomes of 6 million yen or less," and "stable tax revenues, with a sufficient budget for childcare support." The user can view this information and select City X as the municipality that best suits their family situation.

[0424] This invention allows families raising children to easily select the local government that best suits their needs, reducing the burden of raising children. This will promote competition among local governments in providing services to residents, and is expected to improve the overall environment for raising children.

[0425] The processing flow will be explained below.

[0426] Step 1:

[0427] The user uses the terminal to input information about the household (children's ages, number of children, annual household income, need for childcare facilities, etc.).

[0428] Step 2:

[0429] The device sends information entered by the user to the server, including the ages of the children, the number of children, the annual household income, and the need for childcare facilities.

[0430] Step 3:

[0431] The server uses generative AI to collect childcare support policy and financial data from local governments across the country, including retrieving the latest information from online databases and APIs.

[0432] Step 4:

[0433] The server analyzes the collected local government data and extracts the child-rearing support provided by each local government and its financial situation.

[0434] Step 5:

[0435] The server compares the household situation sent by the user with the support provided by the local government and calculates a compatibility score, which is a numerical representation of the degree of match between the user's needs and the services provided by the local government.

[0436] Step 6:

[0437] The server selects the local government with the highest score based on the calculated relevance scores, which involves a process of assigning a score to each local government based on each criterion and identifying the local government with the highest score.

[0438] Step 7:

[0439] The server compiles detailed information about the selected local governments (tax revenue, financial budget, details of child-rearing support policies, procedures, etc.) and sends it to the terminal.

[0440] Step 8:

[0441] The terminal displays detailed information about local governments received from the server to the user, who can then use this information to determine which local government best suits their household situation.

[0442] Step 9:

[0443] The user selects the local government that best suits their needs from the presented candidate locations and proceeds with the relocation and administrative procedures.

[0444] As described above, this system identifies the most suitable local government based on the information entered by the user and provides detailed information about it, thereby helping the user make a rational choice.

[0445] Example 1

[0446] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0447] In modern society, it is a complex and time-consuming task for families to select the public organization that best suits their situation and wishes. It is especially important for families raising children to accurately understand and compare each local government's child-rearing support policies and financial situation, but this requires collecting and analyzing a lot of information, which is a significant burden. Furthermore, because the process for selecting the appropriate local government is unclear, there is a risk of making a wrong decision.

[0448] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0449] In this invention, the server includes a means for inputting the user's family situation and wishes, a means for using a generation AI to collect data on child-rearing support policies and finances of public organizations nationwide, and a means for calculating a suitability score for each public organization based on the input information and the collected information. This makes it possible to quickly and accurately select the public organization that best suits the user's family situation and wishes and visualize its detailed information.

[0450] "Family situation and wishes" is information entered by the user, such as the ages of minors, the number of minors, household income, and the need for childcare facilities.

[0451] "Generative AI" is a model for generating and collecting information using artificial intelligence technology.

[0452] "Public bodies" are local government bodies such as local governments and cities, towns, and villages.

[0453] "Childcare support policies" refer to childcare support services and programs provided by public organizations.

[0454] "Financial data" means information about the income, expenditure and budget of a public body.

[0455] The "suitability score" is an evaluation score that quantifies the suitability of each public organization to the user's family situation and preferences.

[0456] A "selected public entity" is a public entity that is determined to be most suitable for the user based on the relevance score.

[0457] "Detailed information" refers to specific information such as the selected public body's income, financial plan, funding allocation, child-rearing support content, and procedures.

[0458] "Visualization" means displaying collected information and calculation results in a form that is easy for users to understand.

[0459] This invention is a system that selects the most suitable public organization based on the household's situation and preferences and provides the user with detailed information. This system involves a series of processes, including user input, data collection using generative AI, calculation of compatibility scores, selection of the most suitable public organization, and visualization of detailed information.

[0460] 1. User Input

[0461] The user enters their household situation and wishes via the device's input screen, such as the ages of minors, the number of minors, household income, and the need for childcare facilities. This operation conveys the user's specific needs to the system.

[0462] 2. Generative AI data collection

[0463] The device sends the information entered by the user to a server, which then uses a generative AI model to collect data on childcare support policies and finances of public organizations. Specifically, the server uses online databases and APIs to obtain the latest information on public organizations.

[0464] 3. Server Calculation of Relevance Score

[0465] The server compares the public organization data collected by the generative AI model with the information entered by the user and calculates a compatibility score for each public organization. The compatibility score is a numerical representation of the degree of match between the user's needs and the support provided by the public organization. For example, the score is calculated taking into account multiple conditions, such as the amount of support for two minors, the availability of childcare facilities, and support policies based on household income.

[0466] 4. Server selection of the most suitable public organization

[0467] The server selects the public organization with the highest score based on the calculated relevance score. This process aims to identify the organization whose services best match the user's family situation and preferences. For example, if a family with an income of less than 6 million yen has two minor children, the server will select public organizations that offer priority admission to childcare facilities or that offer specific childcare allowances.

[0468] 5. Visualization and transmission of detailed information by the server

[0469] The server compiles detailed information about the selected public organization and sends it to the terminal. This information includes details such as the organization's revenue, financial plan, fund allocation, childcare support details, and procedures. Users can use this information to make decisions about where to live.

[0470] Specific examples

[0471] For example, if a user inputs "two minors," "household income of 6 million yen," and "needs childcare facilities," the server collects and analyzes data on public organizations across the country. It then identifies the public organization with the highest compatibility score. For example, City X may be selected as the most suitable public organization, and detailed information such as "childcare facilities available, no children on waiting lists," "generous childcare allowances for households with incomes of 6 million yen or less," and "stable income, with a sufficient budget for childcare support" may be displayed.

[0472] Example prompts for generative AI models

[0473] Below is an example of a prompt sentence to input to the generative AI model.

[0474] Family situation: 2 minors, household income of 6 million yen, childcare facility required

[0475] Select the public organization that best suits your situation.

[0476] This system will enable families with children to easily select the public organization that best meets their needs, reducing the burden of child-rearing. It will also promote competition among public organizations in providing resident services, which is expected to improve the overall child-rearing environment.

[0477] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0478] Step 1:

[0479] The user enters their family situation and wishes into the device's input screen. Specifically, they enter information such as the ages of minors, the number of minors, household income, and the need for childcare facilities. This information is temporarily saved by the device. For example, the user might enter "two minors, ages 5 and 3," "household income 6 million yen," and "need childcare facilities."

[0480] Input: User's family situation and desired information

[0481] Output: User input information temporarily saved to the device

[0482] Step 2:

[0483] The device sends the input information to the server, which then passes the received user information to the generative AI model to create a prompt. The generated prompt is then input into the generative AI model, which then collects data from appropriate public organizations.

[0484] Input: User input information

[0485] Output: The prompt sentence that is input to the generative AI model

[0486] Specific actions

[0487] The device sends information such as "two minors, annual income of 6 million yen, needing childcare facilities" to the server, which then inputs the following prompt into the generative AI model: "Family situation: two minors, household income of 6 million yen, needing childcare facilities. Please select the public organization that best suits this situation."

[0488] Step 3:

[0489] The server uses the information obtained from the generative AI model to obtain data on public organizations across the country, using online databases and APIs to collect the latest public organization data.

[0490] Input: Prompt sentence for the generative AI model

[0491] Output: Latest data for public organizations nationwide

[0492] Specific actions

[0493] For example, the server accesses the databases of City X, Town Y, and City Z to obtain child-rearing support policies and financial data for each local government.

[0494] Step 4:

[0495] The server compares the collected data on public organizations with the user's input information and calculates a relevance score, taking into account factors such as the amount of support for two minors, availability of childcare facilities, and support policies based on household income.

[0496] Input: User input and collected public data

[0497] Output: Relevance score for each public body

[0498] Specific actions

[0499] For example, the server calculates the relevance score for each item based on information such as "the amount of support for two children in City X" and "availability of childcare facilities in Town Y."

[0500] Step 5:

[0501] The server selects the public entity with the highest relevance score based on the calculated relevance scores and prepares detailed information about the selected public entity.

[0502] Input: Relevance score

[0503] Output: Selected public organizations and their details

[0504] Specific actions

[0505] For example, if "City X was judged to be the most suitable municipality," the system will compile detailed information such as the reason for this, such as "there is a good availability of childcare facilities and childcare allowances are generous."

[0506] Step 6:

[0507] The server compiles detailed information about the selected public organizations and sends it to the terminal, which displays the received information to the user.

[0508] Input: Details of the selected public body

[0509] Output: sent to terminal, displayed to user

[0510] Specific actions

[0511] For example, the device will display "Detailed information about City X," including information such as "Childcare facilities are available and there are no children on waiting lists," "Childcare allowances are generous for households with incomes of 6 million yen or less," and "Income is stable and there is a sufficient budget for childcare support."

[0512] The above is the flow of specific program processing in the system of the present invention. This processing allows users to easily find the public organization that best suits their family situation and wishes.

[0513] (Application example 1)

[0514] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0515] There is a need for a system that not only selects the most suitable local government based on a family's circumstances and preferences and provides detailed information about the local government, but also provides local safety information to give families raising children a sense of security. However, existing systems have the problem of only handling local government child-rearing support policies and financial data, and not including safety information. By solving this problem, there is a need to enable users to select a place to live with peace of mind.

[0516] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0517] In this invention, the server includes means for inputting the family's situation and preferences, means for using a generation AI to collect child-rearing support policies and financial data of local governments nationwide and local safety information, means for calculating a suitability score for each local government based on the input information and the collected information, means for selecting the most suitable local government based on the calculated score, and means for visualizing detailed information about the selected local government and local safety information. This allows users to not only select the most suitable local government but also to select a place to live with peace of mind, taking into account local safety information.

[0518] "Family situation" refers to basic information about the family, such as the age of children, the number of children, annual household income, and the need for childcare facilities.

[0519] "Hope" refers to requirements regarding the living conditions and environment desired by the user, specifically, requests for housing, education, medical care, public safety, etc.

[0520] "Generative AI" is an artificial intelligence technology that automates text generation and data collection, and is designed to collect and provide information in response to user requests.

[0521] "Local governments" refer to public institutions such as local governments and municipalities, which are organizations that provide various administrative services and support to local residents.

[0522] "Childcare support policies" refer to support measures and policies related to childcare provided by local governments, including the provision of daycare centers, childcare allowances, and childcare consultations.

[0523] "Financial data" refers to information about the financial situation of local governments, including data on tax revenues, financial budgets, and allocations.

[0524] "Local safety information" refers to information related to safety, such as local crime statistics, disaster prevention information, and contact information for police stations.

[0525] The "relevance score" is a numerical representation of the degree of match between the user's needs and the services provided by local governments.

[0526] "Detailed information" refers to specific data including the selected local government's tax revenue, financial budget, allocation, child care support provided, procedures, and local safety information.

[0527] An embodiment of the present invention will be described. The present invention is a system that selects an optimal local government based on a family's situation and preferences, and provides the user with detailed information about the local government and local safety information. This system includes a means for inputting the family's situation and preferences, a means for using a generation AI to collect child-rearing support policies and financial data of local governments nationwide and local safety information, a means for calculating a compatibility score for each local government based on the input information and the collected information, a means for selecting the optimal local government based on the calculated score, and a means for visualizing detailed information about the selected local government and local safety information.

[0528] First, a user uses a smartphone or tablet to input information about their household situation and preferences into the application, including the ages and number of children, annual household income, and the need for childcare facilities. The device then sends this information to the server.

[0529] The server uses generative AI to collect data on childcare support policies, financial data, and local safety information from local governments across the country. This data collection utilizes APIs and public databases on the internet. Specific generative AI models used include GPT-4 and BERT.

[0530] Based on the collected data, the server compares the user's input information with the data of the local government and calculates a relevance score. This score quantifies the degree of match between the user's needs and the services provided by the local government. For example, it takes into account the amount of support for two children, availability of nursery schools, and support policies based on annual household income.

[0531] Based on the calculated relevance scores, the server selects the local government with the highest score. This selection process identifies the local government whose services best match the user's household situation.

[0532] Finally, the server compiles and transmits detailed information about the selected local government and local safety information to the device. The detailed information includes the local government's tax revenue, financial budget, allocation, childcare support provided, procedures, local crime statistics, and contact information for the police station. Based on this information, users can choose the local government that best suits their family situation.

[0533] As a concrete example, if a user inputs "two children, annual household income of 6 million yen, needing nursery school," the server uses a generative AI model to collect and analyze data from across the country. City X with the highest relevance score is selected, and detailed information such as "nursery school availability, no waiting list, generous childcare allowance for households with annual income of 6 million yen or less, stable tax revenue" is displayed. Safety information for City X, including "low crime rate and contact information for the police station," is also provided.

[0534] An example prompt might look like this:

[0535] "Search for a local government that is suitable for a family with two children, an annual household income of 6 million yen, and who needs nursery school."

[0536] The above is a specific embodiment for carrying out the invention. This system enables users to easily and safely select the most suitable local government.

[0537] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0538] Step 1:

[0539] The user uses a smartphone or tablet to input information about their household situation and preferences into the application. Specifically, they input necessary information such as "children's ages," "number of children," "annual household income," and "need for childcare facilities" on the input screen. The input information is temporarily stored on the device and prepared for transmission to the server.

[0540] Input: Age of children, number of children, annual household income, need for childcare facilities

[0541] Output: User's home information temporarily stored on the device

[0542] Step 2:

[0543] The device sends the user information entered in the previous step to the server, which analyzes the received information and begins processing. The server uses the generative AI model to collect child-rearing support policies and financial data from local governments across the country, as well as local safety information.

[0544] Input: User's home information sent from the device

[0545] Output: Server that started data collection based on user information

[0546] Step 3:

[0547] The server uses a generative AI model (e.g., GPT-4 or BERT) to collect childcare support policies, financial data, and local safety information from APIs and online databases across the country. The collected data is stored in a database on the server.

[0548] Input: User's home information

[0549] Output: Collected childcare support policies, financial data, and local safety information of local governments

[0550] Step 4:

[0551] The server compares the user's input information with the collected data of each local government and calculates a compatibility score, which is calculated by taking into account multiple conditions, such as the amount of support for two children, availability of nursery schools, support policies based on annual household income, and the safety of the area.

[0552] Input: User's household information, collected data from local government organizations

[0553] Output: Relevance score for each local government

[0554] Step 5:

[0555] Based on the calculated relevance score, the server selects the local government that best matches the user's household situation. In this process, the local government with the highest score is selected.

[0556] Input: Relevance score

[0557] Output: Selected optimal local government

[0558] Step 6:

[0559] The server then compiles detailed information about the selected local governments and local safety information, generating data for visualization, including the local government's tax revenue, financial budget, allocation, childcare support provided, procedures, local crime statistics, and contact information for the police station.

[0560] Input: Selected local government

[0561] Output: Detailed information on local governments and local safety information

[0562] Step 7:

[0563] The server sends the generated detailed information and local safety information to the device, which then displays the received information to the user. Specifically, the device displays child-rearing environment and safety information from local governments in an easy-to-read format.

[0564] Input: Detailed information about local government and local safety information

[0565] Output: Information displayed on the user's terminal

[0566] For example:

[0567] Consider the case where a user inputs "two children, annual household income of 6 million yen, needing nursery school." This information is sent from the device to the server, and the generative AI model collects and analyzes data from across the country. The server selects City X with the highest relevance score, and detailed information about the selected City X, along with information that it is a safe area with a low crime rate, is displayed on the user's device.

[0568] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0569] This invention is a system that selects the most suitable local government based on the household's situation and preferences, provides the user with detailed information about the local government, and further combines it with an emotion engine that recognizes the user's emotions. This system mainly involves a series of processes: user input, data collection using generative AI, calculation of compatibility scores, adjustment of scores based on the user's emotional state, selection of the most suitable local government, and visualization of detailed information.

[0570] 1. User Input

[0571] The user enters information about their family situation and wishes into the device's input screen, such as the ages of their children, the number of children, the household's annual income, and the need for a nursery school. This clarifies the user's specific needs.

[0572] 2. Emotion Recognition by Emotion Engine

[0573] The device recognizes the user's emotional state from facial expressions, voice tone, and text input. The emotion engine analyzes the user's emotions and sends the information to the server. This emotion information detects emotional states such as stress and anxiety.

[0574] 3. Generative AI data collection

[0575] The device sends the information and emotional information input by the user to a server, which uses generative AI to collect childcare support policies and financial data from local governments across the country. This includes using online databases and APIs to efficiently obtain the latest information.

[0576] 4. Server Calculation of Relevance Score

[0577] The server calculates a relevance score for each local government based on the collected local government data, the user's input information, and the user's emotional information. The relevance score is a numerical representation of the degree of match between the user's needs and the support provided by the local government.

[0578] 5. Server-Based Relevance Score Adjustment

[0579] The server adjusts the relevance score based on the user's emotional state. For example, if the user is under high stress, the server will tend to prioritize local governments that offer comprehensive childcare support. This adjustment allows the server to select the local government that best suits the user's emotional state.

[0580] 6. Server selection of the most suitable local government

[0581] Based on the adjusted relevance scores, the server selects the local government with the highest score. This selection process aims to identify the local government that best matches the user's input information with the services provided by the local government.

[0582] 7. Visualization and transmission of detailed information by the server

[0583] The server compiles detailed information about the selected local governments (tax revenue, financial budget, details of child-rearing support policies, procedures, etc.) and sends it to the terminal.

[0584] 8. Displaying detailed information on the terminal

[0585] The terminal displays detailed information about local governments received from the server to the user, who can then use this information to determine which local government best suits their family situation and emotional state.

[0586] As a specific example, suppose a user inputs "two children," "annual household income of 6 million yen," "needs nursery school," and "high stress level." In this case, the server collects and analyzes data from local governments across the country and selects the municipality with the highest compatibility score. For example, City X is selected as the most suitable municipality, and detailed information about it is presented, including "vacant nursery schools and no children on waiting lists," "generous childcare allowances for households with annual incomes of 6 million yen or less," and "stable tax revenues and a sufficient budget for childcare support." The user can view this information and select City X as the municipality that best suits their family situation and emotional state.

[0587] This invention allows families raising children to easily find the most suitable local government based on their needs and emotional state, and make rational choices based on the detailed information. This will promote competition among local governments in providing resident services, and is expected to improve the overall child-rearing environment.

[0588] The processing flow will be explained below.

[0589] Step 1:

[0590] The user uses the terminal to input their household situation (children's ages, number of children, annual household income, need for childcare facilities, etc.) and their wishes, which clarifies the user's specific needs.

[0591] Step 2:

[0592] When a user inputs information, the device uses an emotion engine to recognize the user's emotional state from their facial expressions, voice tone, and text input. The emotion engine analyzes the user's emotional state (e.g., stress, anxiety, joy, etc.).

[0593] Step 3:

[0594] The device sends the home situation and wishes entered by the user, as well as the recognized emotion information, to the server, which then aggregates the necessary information.

[0595] Step 4:

[0596] The server uses generative AI to collect childcare support policies and financial data from local governments across the country, retrieving the latest information from online databases and APIs and storing it in a database.

[0597] Step 5:

[0598] The server analyzes the collected data from local governments and extracts details of child-rearing support and financial status for each local government, allowing the information on each local government to be organized.

[0599] Step 6:

[0600] The server compares the household situation and wishes sent by the user with the support offered by each local government and calculates a compatibility score, which is a numerical representation of the degree of match between the user's needs and the services offered by the local government.

[0601] Step 7:

[0602] The server adjusts the relevance score calculated in step 6, taking into account the user's emotional state. For example, if the user is in a high stress state, the score is adjusted to prioritize local governments with substantial childcare support.

[0603] Step 8:

[0604] The server selects the local government with the highest score based on the adjusted relevance score. This process identifies the local government that best matches the user's input information with the services provided by the local government.

[0605] Step 9:

[0606] The server compiles detailed information about the selected local governments (e.g., tax revenue, financial budget, details of child-rearing support policies, procedures) and sends it to the terminal.

[0607] Step 10:

[0608] The terminal displays detailed information about local governments received from the server to the user, who can then use this information to determine which local government best suits their family situation and emotional state.

[0609] As a concrete example, consider the case where a user inputs "two children," "annual household income of 6 million yen," "needs nursery school," and "high stress level." This information is sent from the device to the server, which uses generative AI to collect and analyze data on local governments across the country. The local governments that best fit the user's needs are then scored and adjusted based on the emotion engine. The municipality with the highest score is selected, and its details are sent to the device. Ultimately, the user can make a rational decision based on the information provided and choose the municipality that best suits their family situation and emotional state.

[0610] Example 2

[0611] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0612] Conventional systems have difficulty selecting an appropriate local government based on the user's household situation, and are unable to take the user's emotional state into account, making it impossible to make an optimal selection. As a result, it is difficult for users to make decisions based on appropriate information, resulting in issues such as reduced satisfaction and increased stress.

[0613] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for inputting family situation and wishes, means for recognizing and analyzing the user's emotional state, means for collecting child-rearing support policies and financial data of local governments nationwide using a generation AI, means for calculating a suitability score for each local government based on the input information and the collected information, means for adjusting the suitability score based on the emotional state, means for selecting the optimal local government based on the calculated and adjusted score, and means for visualizing detailed information about the selected local government. This enables the user to select the local government that is most suitable for their family situation and emotional state.

[0614] "Family situation" refers to specific matters and conditions within the home, such as the age and number of children, annual household income, and the need for childcare facilities.

[0615] "User's emotional state" refers to the user's current psychological state, including, for example, stress, anxiety, and satisfaction.

[0616] "Generative AI" refers to the use of artificial intelligence to generate and analyze data, particularly as a means of gathering up-to-date information using extensive databases and APIs.

[0617] The "relevance score" is a numerical representation of the degree of match between the user's needs and the support provided by the local government.

[0618] "Local governments" refer to organizations that provide administrative services in each region, and typically include cities, towns, villages, prefectures, etc.

[0619] "Detailed information" refers to specific data about the selected local governments, including, for example, tax revenue, financial budget, content of child-rearing support policies, and procedures.

[0620] This invention is a system that selects the most suitable local government based on the household's situation and preferences and provides detailed information to the user. This system involves a series of processes: user input, data collection using generative AI, calculation of compatibility scores, adjustment of scores based on the user's emotional state, selection of the most suitable local government, and visualization of detailed information.

[0621] 1. User Input

[0622] Users input their household situation and preferences through the device's input screen. Specifically, they input information such as the ages and number of children, annual household income, and the need for childcare facilities. This input clarifies the user's specific needs.

[0623] 2. Emotion Recognition by Emotion Engine

[0624] The device recognizes the user's emotional state from facial expressions, voice tone, and text input content. The emotion engine analyzes the user's emotions using the device's built-in camera and microphone. The analysis results are sent to the server and used as emotion information.

[0625] 3. Generative AI data collection

[0626] The device sends the household situation information and emotional information entered by the user to a server, which then uses generative AI to collect childcare support policy and financial data from local governments across the country. This collection includes the use of online databases and APIs to obtain the latest information.

[0627] 4. Server Calculation of Relevance Score

[0628] The server calculates a relevance score based on the collected local government data, the user's input information, and the user's emotional information. The relevance score is a numerical representation of the degree of match between the user's needs and the support provided by the local government.

[0629] 5. Server-Based Relevance Score Adjustment

[0630] The server adjusts the relevance score based on the user's emotional state. For example, if the user is under high stress, it will prioritize local governments that offer comprehensive childcare support. This adjustment allows the server to select the local government that best suits the user's emotional state.

[0631] 6. Server selection of the most suitable local government

[0632] Based on the adjusted relevance scores, the server selects the local government with the highest score. This selection process aims to identify the local government that best matches the user's input information with the services provided by the local government.

[0633] 7. Visualization and transmission of detailed information by the server

[0634] The server compiles detailed information about the selected local governments (tax revenue, financial budget, details of child-rearing support policies, procedures, etc.) and sends it to the terminal.

[0635] 8. Displaying detailed information on the terminal

[0636] The terminal displays detailed information about local governments received from the server to the user, who can then use this information to make a decision about which local government best suits their family situation and emotional state.

[0637] Examples of concrete examples and prompts

[0638] As a concrete example, consider the case where a user enters the following information:

[0639] 2 children

[0640] Annual household income: 6 million yen

[0641] Nursery school needed

[0642] High stress

[0643] The server collects and analyzes data on local governments across the country and selects the municipality with the highest relevance score. For example, a city may be selected as the best municipality, and its detailed information will be presented as follows:

[0644] There are vacant nursery schools and no children on waiting lists.

[0645] Enhanced childcare allowance for households with an annual income of 6 million yen or less

[0646] Tax revenues are stable and there is a sufficient budget for childcare support.

[0647] With this information, users can select the municipality that best suits their home situation and emotional state.

[0648] Example prompt sentence:

[0649] Enter "2 children," "annual household income of 6 million yen," "need nursery school," and "high stress level," and provide the most suitable local government and its details.

[0650] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0651] Step 1: User Input

[0652] The user enters information about their household situation and preferences into the device's input screen. Specifically, they enter information such as the ages of their children, the number of children, their annual household income, and the need for childcare facilities. This clarifies the user's specific needs. The entered information is temporarily saved on the device.

[0653] Specific behavior:

[0654] The user connects to the device and opens the input screen.

[0655] Enter the required information for each item using text boxes and radio buttons.

[0656] Check the information you entered and click the Confirm button.

[0657] The entered data is stored in the terminal and sent to the next processing step.

[0658] Input: Age of children, number of children, annual household income, need for childcare facilities, etc.

[0659] Output: User's home situation information

[0660] Step 2: Emotion recognition by the emotion engine

[0661] The device recognizes the user's emotional state from facial expressions, tone of voice, and text content when the user types. The emotion engine analyzes the user's emotions using the device's built-in camera and microphone. This information is sent to the server.

[0662] Specific behavior:

[0663] The device's camera records the user's facial expressions.

[0664] The device's microphone records the user's voice.

[0665] The emotion engine analyzes this data in real time to determine the emotional state.

[0666] Emotion data is generated and sent to a server.

[0667] Input: User facial expressions, voice, text

[0668] Output: Emotional state data

[0669] Step 3: Data collection with generative AI

[0670] The device sends the household situation information and emotional information entered by the user to a server, which then uses generative AI to collect childcare support policy and financial data from local governments across the country. This collection involves the use of databases and APIs.

[0671] Specific behavior:

[0672] The user's input data and emotion data are sent to the server.

[0673] The server launches the generation AI and accesses the necessary databases and APIs to collect information.

[0674] The collected data is stored on a server and sent to the next processing step.

[0675] Input: User's home situation information, emotional state data

[0676] Output: Childcare support policy data and financial data of local governments

[0677] Step 4: Server calculates relevance score

[0678] The server calculates a compatibility score for each local government based on the collected local government data and the user's household situation and emotional information. The compatibility score is a numerical representation of the degree of match between the user's needs and the support provided by the local government.

[0679] Specific behavior:

[0680] The collected local government data is subjected to an analytical algorithm.

[0681] The user's home situation information and emotional information are subjected to an analysis algorithm.

[0682] A relevance score is calculated for each local government and sent to the next processing step.

[0683] Input: Childcare support policy data of local governments, financial data, user's household situation information, emotional state data

[0684] Output: Relevance score

[0685] Step 5: Server adjusts relevance scores

[0686] The server adjusts the relevance score based on the user's emotional state. For example, if the user is under high stress, it will prioritize local governments that offer comprehensive childcare support. This adjustment allows the server to select the local government that best suits the user's emotional state.

[0687] Specific behavior:

[0688] Emotional state data is analyzed to assess factors such as stress.

[0689] A weight corresponding to the emotional state is added to the relevance score.

[0690] The suitability scores are recalculated and the local government with the best score is selected.

[0691] Input: Relevance score, emotional state data

[0692] Output: Adjusted fitness score

[0693] Step 6: The server selects the most suitable local government.

[0694] Based on the adjusted relevance score, the server selects the local government with the highest score. This selection process aims to identify the municipality that best matches the user's household situation and the services provided by the local government.

[0695] Specific behavior:

[0696] The suitability scores of each local government are listed in a ranking format.

[0697] Select the local government with the highest score.

[0698] The selected local governments will be listed.

[0699] Input: Adjusted relevance score

[0700] Output: Selected local governments

[0701] Step 7: Server visualizes and sends detailed information

[0702] The server then compiles detailed information about the selected local governments and sends it to the terminal, including information on child-rearing support policies, financial status, and procedures.

[0703] Specific behavior:

[0704] Relevant information on selected local governments is extracted from the database.

[0705] Format the data in a way that is easy for users to understand.

[0706] The organized data is sent to the device.

[0707] Input: Selected local government

[0708] Output:Detailed information of local government

[0709] Step 8: Viewing detailed information via terminal

[0710] The terminal displays detailed information about local governments received from the server to the user, who can then use this information to make a decision about which local government best suits their family situation and emotional state.

[0711] Specific behavior:

[0712] The terminal receives the data received from the server.

[0713] Detailed information is displayed in a GUI (graphical user interface).

[0714] The user views the displayed information and makes a final selection.

[0715] Input: Detailed information of local government

[0716] Output: Final selection result

[0717] (Application example 2)

[0718] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0719] Conventional local government selection systems present candidates based on the user's family situation and preferences, but do not consider the user's emotional state. This can lead to stress and an inappropriate selection. Furthermore, detailed information about the selected local government is not displayed properly, providing insufficient reference information for users to use when making decisions. Therefore, there is a need for a system that can select a more appropriate local government and provide detailed information, taking into account not only the user's family situation and preferences, but also the user's emotional state.

[0720] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for inputting the family's situation and wishes, means for collecting child-rearing support policies and financial data of local governments nationwide using a generation AI, means for calculating a suitability score for each local government based on the input information and the collected information, means for recognizing the user's emotional state, means for adjusting the calculated score based on the emotional state, means for selecting the most suitable local government based on the adjusted score, means for visualizing detailed information about the selected local government, and means for displaying the detailed information to the user. This makes it possible to select the most suitable local government that comprehensively takes into account the family's situation, wishes, and emotional state, and to provide detailed information.

[0721] "Family situation" refers to information such as the user's family structure, the number of children, their ages, annual household income, and the need for childcare facilities.

[0722] "Desire" includes elements such as the user's desired living environment, support content, budget, and specific conditions.

[0723] "Generative AI" is an artificial intelligence technology that collects and analyzes data, and has the means to obtain childcare support policies and financial data from local governments.

[0724] The "relevance score" is an evaluation index that quantifies the degree of match between the user's input information and the collected data of local governments.

[0725] "Emotional state" refers to the psychological and emotional state, such as stress, anxiety, or excitement, that a user expresses when entering input.

[0726] "Emotion recognition means" refers to a means that uses technology to detect and analyze emotions from a user's facial expressions, voice, text input, etc.

[0727] "Detailed information" refers to specific data such as local government tax revenues, financial budgets, allocations, childcare support provided, and procedures.

[0728] "Visualization" includes the process of displaying collected and analyzed information in a way that is easy for users to understand.

[0729] "Display means" refers to a function that allows a user to visually check information through a terminal.

[0730] This invention is a system that selects the most suitable local government based on the user's household situation and preferences, and provides detailed information. It also incorporates an emotion engine that recognizes the user's emotional state and utilizes that information. This system includes the following main means:

[0731] System Configuration

[0732] A means of inputting family circumstances and wishes

[0733] The device provides an interface for users to input their family situation and preferences. For example, users input information such as "family structure," "number of children," "ages," "annual household income," and "need for childcare facilities." This information is used to clarify the specific needs of the family.

[0734] A means of recognizing emotional states

[0735] The device is equipped with a camera and microphone to recognize the user's emotional state. This drives an emotion engine that analyzes the user's facial expressions and voice tone to detect emotional states (e.g., stress, anxiety, excitement). The emotion engine uses TensorFlow, and emotion analysis is based on deep learning models.

[0736] Collecting data and calculating relevance scores

[0737] The server uses generative AI to collect childcare support policy and financial data from local governments across the country from online databases and APIs. This data is then compared with the user's input information to calculate a relevance score. The relevance score is a numerical representation of how closely the user's needs match the services provided by the local government.

[0738] Score adjustment and selection of optimal local governments

[0739] The server adjusts the relevance score to reflect the detected emotional state of the user. For example, if the user is in a high stress state, it will prioritize local governments that offer comprehensive childcare support. Based on the adjusted relevance score, the server selects the most suitable local government.

[0740] Visualization and display of detailed information

[0741] The server compiles detailed information about the selected local government (e.g., tax revenue, financial budget, childcare support provided, procedures, etc.) and sends it to the terminal. The terminal displays this information to the user, who then makes a decision based on it.

[0742] Hardware and software used

[0743] Hardware: Smartphone, smart glasses, camera, microphone

[0744] Software: TensorFlow (deep learning model for sentiment analysis), OpenCV (image processing), Flask (data collection and server-side processing), SQLite (database)

[0745] Specific examples

[0746] Suppose a user inputs "Family composition: 2 parents, 2 children," "Children's ages: 3 and 5 years old," "Annual household income: 6 million yen," "Childcare facilities: needed," and "Emotional state: high stress." In this case, the server collects data on local governments across the country and selects the municipality that best meets the user's needs. For example, a certain municipality may have "vacant nursery schools and no children on waiting lists," "generous childcare allowances for households with an annual income of 6 million yen or less," and "extensive childcare support systems," and provide these results to the user.

[0747] Prompt Sentence Examples

[0748] Example user input:

[0749] Family composition: 2 parents, 2 children

[0750] "Children's ages: 3 and 5 years old"

[0751] "Household annual income: 6 million yen"

[0752] "Childcare facilities: necessary"

[0753] "Emotional state: High stress"

[0754] Based on this information, the system can identify the local government that best meets the user's needs and provide detailed information.

[0755] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0756] Step 1:

[0757] The terminal provides an interface for inputting the user's household situation and wishes. For example, the user might enter information such as "Family composition: 2 parents, 2 children," "Children's ages: 3 and 5 years old," "Household annual income: 6 million yen," and "Childcare facilities: necessary." The input data is sent to the server by the terminal.

[0758] Step 2:

[0759] To recognize the user's emotional state, the device uses a camera and microphone to capture the user's facial expressions and voice tone. The captured data is analyzed by the emotion engine, which uses TensorFlow to measure the user's emotional state (e.g., stress, anxiety, excitement, etc.).

[0760] Step 3:

[0761] The server uses generative AI to collect data on childcare support policies and finances from local governments across the country. The data is obtained from online databases and APIs. This collected data is stored in a local database (SQLite).

[0762] Step 4:

[0763] The server calculates a relevance score for each local government based on the input information and emotional information received from the user. The score is calculated using an algorithm that evaluates the degree of match between the user's needs and the services provided by the local government. The calculation results are converted into numerical data and stored on the server.

[0764] Step 5:

[0765] The server adjusts the relevance score based on the user's emotional state. For example, if the user is under high stress, the server will prioritize and increase the scores of local governments that offer comprehensive childcare support. The adjusted scores are then saved back to the server.

[0766] Step 6:

[0767] Based on the adjusted relevance score, the server selects the most suitable local government. The local government with the highest score is prioritized in the selection process. The selection results are organized with detailed information about the most suitable local government.

[0768] Step 7:

[0769] The server formats detailed information about the selected local government (tax revenue, financial budget, childcare support provided, procedures, etc.) for the user and sends it to the terminal.

[0770] Step 8:

[0771] The device receives detailed information about the local government from the server and displays it to the user through a user-friendly interface, such as on the display of a smartphone or smart glasses. The user can then review the detailed information and make decisions based on it.

[0772] These steps allow for the selection of the most suitable local government taking into account the user's household situation, wishes, and emotional state, and provide the user with detailed information.

[0773] 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.

[0774] 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> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. 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 voice, text data indicating text, and image data indicating an image is also input. 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.

[0775] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0776] [Third embodiment]

[0777] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0778] 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.

[0779] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. 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).

[0780] 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.

[0781] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0782] 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 surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0783] 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. 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.

[0784] 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.

[0785] 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 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.

[0786] 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.

[0787] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0788] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[0789] This invention is a system that selects the most suitable local government based on the household's circumstances and preferences and provides the user with detailed information. This system mainly involves a series of processes: user input, data collection using generative AI, calculation of compatibility scores, selection of the most suitable local government, and visualization of detailed information.

[0790] 1. User Input

[0791] The user enters information about their family situation and wishes into the device's input screen, such as the ages of their children, the number of children, the household's annual income, and the need for a nursery school. This clarifies the user's specific needs.

[0792] 2. Generative AI data collection

[0793] The device sends the information entered by the user to a server, which uses generative AI to collect data on childcare support policies and finances from local governments across the country, including the use of online databases and APIs to efficiently obtain the latest information.

[0794] 3. Server Calculation of Relevance Score

[0795] The server compares the collected data on local governments with the information entered by the user and calculates a compatibility score for each local government. The compatibility score is a numerical representation of the degree of match between the user's needs and the support provided by the local government. For example, the score is calculated by taking into account multiple conditions, such as the amount of support for two children, availability of nursery schools, and support policies based on annual household income.

[0796] 4. Server selection of the most suitable local government

[0797] Based on the relevance score, the server selects the local government with the highest score. This selection process aims to identify the local government that best matches the user's input information with the services offered by the local government. For example, for a family with two children and an income of less than 6 million yen, the server will select a local government that offers priority admission to daycare centers or provides specific childcare benefits.

[0798] 5. Visualization and transmission of detailed information by the server

[0799] The server then compiles detailed information about the selected local government and sends it to the terminal. This information includes the local government's tax revenue, financial budget, child-rearing support policies, procedures, etc. The user can then use this information to make a decision about where to live.

[0800] As a concrete example, suppose a user inputs "two children," "annual household income of 6 million yen," and "needs nursery school." In this case, the server collects and analyzes data on local governments across the country and selects the municipality with the highest suitability score. For example, City X is selected as the most suitable municipality, and detailed information is presented, such as "nursery school vacancies available, no children on waiting lists," "generous childcare allowances for households with annual incomes of 6 million yen or less," and "stable tax revenues, with a sufficient budget for childcare support." The user can view this information and select City X as the municipality that best suits their family situation.

[0801] This invention allows families raising children to easily select the local government that best suits their needs, reducing the burden of raising children. This will promote competition among local governments in providing services to residents, and is expected to improve the overall environment for raising children.

[0802] The processing flow will be explained below.

[0803] Step 1:

[0804] The user uses the terminal to input information about the household (children's ages, number of children, annual household income, need for childcare facilities, etc.).

[0805] Step 2:

[0806] The device sends information entered by the user to the server, including the ages of the children, the number of children, the annual household income, and the need for childcare facilities.

[0807] Step 3:

[0808] The server uses generative AI to collect childcare support policy and financial data from local governments across the country, including retrieving the latest information from online databases and APIs.

[0809] Step 4:

[0810] The server analyzes the collected local government data and extracts the child-rearing support provided by each local government and its financial situation.

[0811] Step 5:

[0812] The server compares the household situation sent by the user with the support provided by the local government and calculates a compatibility score, which is a numerical representation of the degree of match between the user's needs and the services provided by the local government.

[0813] Step 6:

[0814] The server selects the local government with the highest score based on the calculated relevance scores, which involves a process of assigning a score to each local government based on each criterion and identifying the local government with the highest score.

[0815] Step 7:

[0816] The server compiles detailed information about the selected local governments (tax revenue, financial budget, details of child-rearing support policies, procedures, etc.) and sends it to the terminal.

[0817] Step 8:

[0818] The terminal displays detailed information about local governments received from the server to the user, who can then use this information to determine which local government best suits their household situation.

[0819] Step 9:

[0820] The user selects the local government that best suits their needs from the presented candidate locations and proceeds with the relocation and administrative procedures.

[0821] As described above, this system identifies the most suitable local government based on the information entered by the user and provides detailed information about it, thereby helping the user make a rational choice.

[0822] Example 1

[0823] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0824] In modern society, it is a complex and time-consuming task for families to select the public organization that best suits their situation and wishes. It is especially important for families raising children to accurately understand and compare each local government's child-rearing support policies and financial situation, but this requires collecting and analyzing a lot of information, which is a significant burden. Furthermore, because the process for selecting the appropriate local government is unclear, there is a risk of making a wrong decision.

[0825] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0826] In this invention, the server includes a means for inputting the user's family situation and wishes, a means for using a generation AI to collect data on child-rearing support policies and finances of public organizations nationwide, and a means for calculating a suitability score for each public organization based on the input information and the collected information. This makes it possible to quickly and accurately select the public organization that best suits the user's family situation and wishes and visualize its detailed information.

[0827] "Family situation and wishes" is information entered by the user, such as the ages of minors, the number of minors, household income, and the need for childcare facilities.

[0828] "Generative AI" is a model for generating and collecting information using artificial intelligence technology.

[0829] "Public bodies" are local government bodies such as local governments and cities, towns, and villages.

[0830] "Childcare support policies" refer to childcare support services and programs provided by public organizations.

[0831] "Financial data" means information about the income, expenditure and budget of a public body.

[0832] The "suitability score" is an evaluation score that quantifies the suitability of each public organization to the user's family situation and preferences.

[0833] A "selected public entity" is a public entity that is determined to be most suitable for the user based on the relevance score.

[0834] "Detailed information" refers to specific information such as the selected public body's income, financial plan, funding allocation, child-rearing support content, and procedures.

[0835] "Visualization" means displaying collected information and calculation results in a form that is easy for users to understand.

[0836] This invention is a system that selects the most suitable public organization based on the household's situation and preferences and provides the user with detailed information. This system involves a series of processes, including user input, data collection using generative AI, calculation of compatibility scores, selection of the most suitable public organization, and visualization of detailed information.

[0837] 1. User Input

[0838] The user enters their household situation and wishes via the device's input screen, such as the ages of minors, the number of minors, household income, and the need for childcare facilities. This operation conveys the user's specific needs to the system.

[0839] 2. Generative AI data collection

[0840] The device sends the information entered by the user to a server, which then uses a generative AI model to collect data on childcare support policies and finances of public organizations. Specifically, the server uses online databases and APIs to obtain the latest information on public organizations.

[0841] 3. Server Calculation of Relevance Score

[0842] The server compares the public organization data collected by the generative AI model with the information entered by the user and calculates a compatibility score for each public organization. The compatibility score is a numerical representation of the degree of match between the user's needs and the support provided by the public organization. For example, the score is calculated taking into account multiple conditions, such as the amount of support for two minors, the availability of childcare facilities, and support policies based on household income.

[0843] 4. Server selection of the most suitable public organization

[0844] The server selects the public organization with the highest score based on the calculated relevance score. This process aims to identify the organization whose services best match the user's family situation and preferences. For example, if a family with an income of less than 6 million yen has two minor children, the server will select public organizations that offer priority admission to childcare facilities or that offer specific childcare allowances.

[0845] 5. Visualization and transmission of detailed information by the server

[0846] The server compiles detailed information about the selected public organization and sends it to the terminal. This information includes details such as the organization's revenue, financial plan, fund allocation, childcare support details, and procedures. Users can use this information to make decisions about where to live.

[0847] Specific examples

[0848] For example, if a user inputs "two minors," "household income of 6 million yen," and "needs childcare facilities," the server collects and analyzes data on public organizations across the country. It then identifies the public organization with the highest compatibility score. For example, City X may be selected as the most suitable public organization, and detailed information such as "childcare facilities available, no children on waiting lists," "generous childcare allowances for households with incomes of 6 million yen or less," and "stable income, with a sufficient budget for childcare support" may be displayed.

[0849] Example prompts for generative AI models

[0850] Below is an example of a prompt sentence to input to the generative AI model.

[0851] Family situation: 2 minors, household income of 6 million yen, childcare facility required

[0852] Select the public organization that best suits your situation.

[0853] This system will enable families with children to easily select the public organization that best meets their needs, reducing the burden of child-rearing. It will also promote competition among public organizations in providing resident services, which is expected to improve the overall child-rearing environment.

[0854] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0855] Step 1:

[0856] The user enters their family situation and wishes into the device's input screen. Specifically, they enter information such as the ages of minors, the number of minors, household income, and the need for childcare facilities. This information is temporarily saved by the device. For example, the user might enter "two minors, ages 5 and 3," "household income 6 million yen," and "need childcare facilities."

[0857] Input: User's family situation and desired information

[0858] Output: User input information temporarily saved to the device

[0859] Step 2:

[0860] The device sends the input information to the server, which then passes the received user information to the generative AI model to create a prompt. The generated prompt is then input into the generative AI model, which then collects data from appropriate public organizations.

[0861] Input: User input information

[0862] Output: The prompt sentence that is input to the generative AI model

[0863] Specific actions

[0864] The device sends information such as "two minors, annual income of 6 million yen, needing childcare facilities" to the server, which then inputs the following prompt into the generative AI model: "Family situation: two minors, household income of 6 million yen, needing childcare facilities. Please select the public organization that best suits this situation."

[0865] Step 3:

[0866] The server uses the information obtained from the generative AI model to obtain data on public organizations across the country, using online databases and APIs to collect the latest public organization data.

[0867] Input: Prompt sentence for the generative AI model

[0868] Output: Latest data for public organizations nationwide

[0869] Specific actions

[0870] For example, the server accesses the databases of City X, Town Y, and City Z to obtain child-rearing support policies and financial data for each local government.

[0871] Step 4:

[0872] The server compares the collected data on public organizations with the user's input information and calculates a relevance score, taking into account factors such as the amount of support for two minors, availability of childcare facilities, and support policies based on household income.

[0873] Input: User input and collected public data

[0874] Output: Relevance score for each public body

[0875] Specific actions

[0876] For example, the server calculates the relevance score for each item based on information such as "the amount of support for two children in City X" and "availability of childcare facilities in Town Y."

[0877] Step 5:

[0878] The server selects the public entity with the highest relevance score based on the calculated relevance scores and prepares detailed information about the selected public entity.

[0879] Input: Relevance score

[0880] Output: Selected public organizations and their details

[0881] Specific actions

[0882] For example, if "City X was judged to be the most suitable municipality," the system will compile detailed information such as the reason for this, such as "there is a good availability of childcare facilities and childcare allowances are generous."

[0883] Step 6:

[0884] The server compiles detailed information about the selected public organizations and sends it to the terminal, which displays the received information to the user.

[0885] Input: Details of the selected public body

[0886] Output: sent to terminal, displayed to user

[0887] Specific actions

[0888] For example, the device will display "Detailed information about City X," including information such as "Childcare facilities are available and there are no children on waiting lists," "Childcare allowances are generous for households with incomes of 6 million yen or less," and "Income is stable and there is a sufficient budget for childcare support."

[0889] The above is the flow of specific program processing in the system of the present invention. This processing allows users to easily find the public organization that best suits their family situation and wishes.

[0890] (Application example 1)

[0891] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0892] There is a need for a system that not only selects the most suitable local government based on a family's circumstances and preferences and provides detailed information about the local government, but also provides local safety information to give families raising children a sense of security. However, existing systems have the problem of only handling local government child-rearing support policies and financial data, and not including safety information. By solving this problem, there is a need to enable users to select a place to live with peace of mind.

[0893] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0894] In this invention, the server includes means for inputting the family's situation and preferences, means for using a generation AI to collect child-rearing support policies and financial data of local governments nationwide and local safety information, means for calculating a suitability score for each local government based on the input information and the collected information, means for selecting the most suitable local government based on the calculated score, and means for visualizing detailed information about the selected local government and local safety information. This allows users to not only select the most suitable local government but also to select a place to live with peace of mind, taking into account local safety information.

[0895] "Family situation" refers to basic information about the family, such as the age of children, the number of children, annual household income, and the need for childcare facilities.

[0896] "Hope" refers to requirements regarding the living conditions and environment desired by the user, specifically, requests for housing, education, medical care, public safety, etc.

[0897] "Generative AI" is an artificial intelligence technology that automates text generation and data collection, and is designed to collect and provide information in response to user requests.

[0898] "Local governments" refer to public institutions such as local governments and municipalities, which are organizations that provide various administrative services and support to local residents.

[0899] "Childcare support policies" refer to support measures and policies related to childcare provided by local governments, including the provision of daycare centers, childcare allowances, and childcare consultations.

[0900] "Financial data" refers to information about the financial situation of local governments, including data on tax revenues, financial budgets, and allocations.

[0901] "Local safety information" refers to information related to safety, such as local crime statistics, disaster prevention information, and contact information for police stations.

[0902] The "relevance score" is a numerical representation of the degree of match between the user's needs and the services provided by local governments.

[0903] "Detailed information" refers to specific data including the selected local government's tax revenue, financial budget, allocation, child care support provided, procedures, and local safety information.

[0904] An embodiment of the present invention will be described. The present invention is a system that selects an optimal local government based on a family's situation and preferences, and provides the user with detailed information about the local government and local safety information. This system includes a means for inputting the family's situation and preferences, a means for using a generation AI to collect child-rearing support policies and financial data of local governments nationwide and local safety information, a means for calculating a compatibility score for each local government based on the input information and the collected information, a means for selecting the optimal local government based on the calculated score, and a means for visualizing detailed information about the selected local government and local safety information.

[0905] First, a user uses a smartphone or tablet to input information about their household situation and preferences into the application, including the ages and number of children, annual household income, and the need for childcare facilities. The device then sends this information to the server.

[0906] The server uses generative AI to collect data on childcare support policies, financial data, and local safety information from local governments across the country. This data collection utilizes APIs and public databases on the internet. Specific generative AI models used include GPT-4 and BERT.

[0907] Based on the collected data, the server compares the user's input information with the data of the local government and calculates a relevance score. This score quantifies the degree of match between the user's needs and the services provided by the local government. For example, it takes into account the amount of support for two children, availability of nursery schools, and support policies based on annual household income.

[0908] Based on the calculated relevance scores, the server selects the local government with the highest score. This selection process identifies the local government whose services best match the user's household situation.

[0909] Finally, the server compiles and transmits detailed information about the selected local government and local safety information to the device. The detailed information includes the local government's tax revenue, financial budget, allocation, childcare support provided, procedures, local crime statistics, and contact information for the police station. Based on this information, users can choose the local government that best suits their family situation.

[0910] As a concrete example, if a user inputs "two children, annual household income of 6 million yen, needing nursery school," the server uses a generative AI model to collect and analyze data from across the country. City X with the highest relevance score is selected, and detailed information such as "nursery school availability, no waiting list, generous childcare allowance for households with annual income of 6 million yen or less, stable tax revenue" is displayed. Safety information for City X, including "low crime rate and contact information for the police station," is also provided.

[0911] An example prompt might look like this:

[0912] "Search for a local government that is suitable for a family with two children, an annual household income of 6 million yen, and who needs nursery school."

[0913] The above is a specific embodiment for carrying out the invention. This system enables users to easily and safely select the most suitable local government.

[0914] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0915] Step 1:

[0916] The user uses a smartphone or tablet to input information about their household situation and preferences into the application. Specifically, they input necessary information such as "children's ages," "number of children," "annual household income," and "need for childcare facilities" on the input screen. The input information is temporarily stored on the device and prepared for transmission to the server.

[0917] Input: Age of children, number of children, annual household income, need for childcare facilities

[0918] Output: User's home information temporarily stored on the device

[0919] Step 2:

[0920] The device sends the user information entered in the previous step to the server, which analyzes the received information and begins processing. The server uses the generative AI model to collect child-rearing support policies and financial data from local governments across the country, as well as local safety information.

[0921] Input: User's home information sent from the device

[0922] Output: Server that started data collection based on user information

[0923] Step 3:

[0924] The server uses a generative AI model (e.g., GPT-4 or BERT) to collect childcare support policies, financial data, and local safety information from APIs and online databases across the country. The collected data is stored in a database on the server.

[0925] Input: User's home information

[0926] Output: Collected childcare support policies, financial data, and local safety information of local governments

[0927] Step 4:

[0928] The server compares the user's input information with the collected data of each local government and calculates a compatibility score, which is calculated by taking into account multiple conditions, such as the amount of support for two children, availability of nursery schools, support policies based on annual household income, and the safety of the area.

[0929] Input: User's household information, collected data from local government organizations

[0930] Output: Relevance score for each local government

[0931] Step 5:

[0932] Based on the calculated relevance score, the server selects the local government that best matches the user's household situation. In this process, the local government with the highest score is selected.

[0933] Input: Relevance score

[0934] Output: Selected optimal local government

[0935] Step 6:

[0936] The server then compiles detailed information about the selected local governments and local safety information, generating data for visualization, including the local government's tax revenue, financial budget, allocation, childcare support provided, procedures, local crime statistics, and contact information for the police station.

[0937] Input: Selected local government

[0938] Output: Detailed information on local governments and local safety information

[0939] Step 7:

[0940] The server sends the generated detailed information and local safety information to the device, which then displays the received information to the user. Specifically, the device displays child-rearing environment and safety information from local governments in an easy-to-read format.

[0941] Input: Detailed information about local government and local safety information

[0942] Output: Information displayed on the user's terminal

[0943] For example:

[0944] Consider the case where a user inputs "two children, annual household income of 6 million yen, needing nursery school." This information is sent from the device to the server, and the generative AI model collects and analyzes data from across the country. The server selects City X with the highest relevance score, and detailed information about the selected City X, along with information that it is a safe area with a low crime rate, is displayed on the user's device.

[0945] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0946] This invention is a system that selects the most suitable local government based on the household's situation and preferences, provides the user with detailed information about the local government, and further combines it with an emotion engine that recognizes the user's emotions. This system mainly involves a series of processes: user input, data collection using generative AI, calculation of compatibility scores, adjustment of scores based on the user's emotional state, selection of the most suitable local government, and visualization of detailed information.

[0947] 1. User Input

[0948] The user enters information about their family situation and wishes into the device's input screen, such as the ages of their children, the number of children, the household's annual income, and the need for a nursery school. This clarifies the user's specific needs.

[0949] 2. Emotion Recognition by Emotion Engine

[0950] The device recognizes the user's emotional state from facial expressions, voice tone, and text input. The emotion engine analyzes the user's emotions and sends the information to the server. This emotion information detects emotional states such as stress and anxiety.

[0951] 3. Generative AI data collection

[0952] The device sends the information and emotional information input by the user to a server, which uses generative AI to collect childcare support policies and financial data from local governments across the country. This includes using online databases and APIs to efficiently obtain the latest information.

[0953] 4. Server Calculation of Relevance Score

[0954] The server calculates a relevance score for each local government based on the collected local government data, the user's input information, and the user's emotional information. The relevance score is a numerical representation of the degree of match between the user's needs and the support provided by the local government.

[0955] 5. Server-Based Relevance Score Adjustment

[0956] The server adjusts the relevance score based on the user's emotional state. For example, if the user is under high stress, the server will tend to prioritize local governments that offer comprehensive childcare support. This adjustment allows the server to select the local government that best suits the user's emotional state.

[0957] 6. Server selection of the most suitable local government

[0958] Based on the adjusted relevance scores, the server selects the local government with the highest score. This selection process aims to identify the local government that best matches the user's input information with the services provided by the local government.

[0959] 7. Visualization and transmission of detailed information by the server

[0960] The server compiles detailed information about the selected local governments (tax revenue, financial budget, details of child-rearing support policies, procedures, etc.) and sends it to the terminal.

[0961] 8. Displaying detailed information on the terminal

[0962] The terminal displays detailed information about local governments received from the server to the user, who can then use this information to determine which local government best suits their family situation and emotional state.

[0963] As a specific example, suppose a user inputs "two children," "annual household income of 6 million yen," "needs nursery school," and "high stress level." In this case, the server collects and analyzes data from local governments across the country and selects the municipality with the highest compatibility score. For example, City X is selected as the most suitable municipality, and detailed information about it is presented, including "vacant nursery schools and no children on waiting lists," "generous childcare allowances for households with annual incomes of 6 million yen or less," and "stable tax revenues and a sufficient budget for childcare support." The user can view this information and select City X as the municipality that best suits their family situation and emotional state.

[0964] This invention allows families raising children to easily find the most suitable local government based on their needs and emotional state, and make rational choices based on the detailed information. This will promote competition among local governments in providing resident services, and is expected to improve the overall child-rearing environment.

[0965] The processing flow will be explained below.

[0966] Step 1:

[0967] The user uses the terminal to input their household situation (children's ages, number of children, annual household income, need for childcare facilities, etc.) and their wishes, which clarifies the user's specific needs.

[0968] Step 2:

[0969] When a user inputs information, the device uses an emotion engine to recognize the user's emotional state from their facial expressions, voice tone, and text input. The emotion engine analyzes the user's emotional state (e.g., stress, anxiety, joy, etc.).

[0970] Step 3:

[0971] The device sends the home situation and wishes entered by the user, as well as the recognized emotion information, to the server, which then aggregates the necessary information.

[0972] Step 4:

[0973] The server uses generative AI to collect childcare support policies and financial data from local governments across the country, retrieving the latest information from online databases and APIs and storing it in a database.

[0974] Step 5:

[0975] The server analyzes the collected data from local governments and extracts details of child-rearing support and financial status for each local government, allowing the information on each local government to be organized.

[0976] Step 6:

[0977] The server compares the household situation and wishes sent by the user with the support offered by each local government and calculates a compatibility score, which is a numerical representation of the degree of match between the user's needs and the services offered by the local government.

[0978] Step 7:

[0979] The server adjusts the relevance score calculated in step 6, taking into account the user's emotional state. For example, if the user is in a high stress state, the score is adjusted to prioritize local governments with substantial childcare support.

[0980] Step 8:

[0981] The server selects the local government with the highest score based on the adjusted relevance score. This process identifies the local government that best matches the user's input information with the services provided by the local government.

[0982] Step 9:

[0983] The server compiles detailed information about the selected local governments (e.g., tax revenue, financial budget, details of child-rearing support policies, procedures) and sends it to the terminal.

[0984] Step 10:

[0985] The terminal displays detailed information about local governments received from the server to the user, who can then use this information to determine which local government best suits their family situation and emotional state.

[0986] As a concrete example, consider the case where a user inputs "two children," "annual household income of 6 million yen," "needs nursery school," and "high stress level." This information is sent from the device to the server, which uses generative AI to collect and analyze data on local governments across the country. The local governments that best fit the user's needs are then scored and adjusted based on the emotion engine. The municipality with the highest score is selected, and its details are sent to the device. Ultimately, the user can make a rational decision based on the information provided and choose the municipality that best suits their family situation and emotional state.

[0987] Example 2

[0988] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0989] Conventional systems have difficulty selecting an appropriate local government based on the user's household situation, and are unable to take the user's emotional state into account, making it impossible to make an optimal selection. As a result, it is difficult for users to make decisions based on appropriate information, resulting in issues such as reduced satisfaction and increased stress.

[0990] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for inputting family situation and wishes, means for recognizing and analyzing the user's emotional state, means for collecting child-rearing support policies and financial data of local governments nationwide using a generation AI, means for calculating a suitability score for each local government based on the input information and the collected information, means for adjusting the suitability score based on the emotional state, means for selecting the optimal local government based on the calculated and adjusted score, and means for visualizing detailed information about the selected local government. This enables the user to select the local government that is most suitable for their family situation and emotional state.

[0991] "Family situation" refers to specific matters and conditions within the home, such as the age and number of children, annual household income, and the need for childcare facilities.

[0992] "User's emotional state" refers to the user's current psychological state, including, for example, stress, anxiety, and satisfaction.

[0993] "Generative AI" refers to the use of artificial intelligence to generate and analyze data, particularly as a means of gathering up-to-date information using extensive databases and APIs.

[0994] The "relevance score" is a numerical representation of the degree of match between the user's needs and the support provided by the local government.

[0995] "Local governments" refer to organizations that provide administrative services in each region, and typically include cities, towns, villages, prefectures, etc.

[0996] "Detailed information" refers to specific data about the selected local governments, including, for example, tax revenue, financial budget, content of child-rearing support policies, and procedures.

[0997] This invention is a system that selects the most suitable local government based on the household's situation and preferences and provides detailed information to the user. This system involves a series of processes: user input, data collection using generative AI, calculation of compatibility scores, adjustment of scores based on the user's emotional state, selection of the most suitable local government, and visualization of detailed information.

[0998] 1. User Input

[0999] Users input their household situation and preferences through the device's input screen. Specifically, they input information such as the ages and number of children, annual household income, and the need for childcare facilities. This input clarifies the user's specific needs.

[1000] 2. Emotion Recognition by Emotion Engine

[1001] The device recognizes the user's emotional state from facial expressions, voice tone, and text input content. The emotion engine analyzes the user's emotions using the device's built-in camera and microphone. The analysis results are sent to the server and used as emotion information.

[1002] 3. Generative AI data collection

[1003] The device sends the household situation information and emotional information entered by the user to a server, which then uses generative AI to collect childcare support policy and financial data from local governments across the country. This collection includes the use of online databases and APIs to obtain the latest information.

[1004] 4. Server Calculation of Relevance Score

[1005] The server calculates a relevance score based on the collected local government data, the user's input information, and the user's emotional information. The relevance score is a numerical representation of the degree of match between the user's needs and the support provided by the local government.

[1006] 5. Server-Based Relevance Score Adjustment

[1007] The server adjusts the relevance score based on the user's emotional state. For example, if the user is under high stress, it will prioritize local governments that offer comprehensive childcare support. This adjustment allows the server to select the local government that best suits the user's emotional state.

[1008] 6. Server selection of the most suitable local government

[1009] Based on the adjusted relevance scores, the server selects the local government with the highest score. This selection process aims to identify the local government that best matches the user's input information with the services provided by the local government.

[1010] 7. Visualization and transmission of detailed information by the server

[1011] The server compiles detailed information about the selected local governments (tax revenue, financial budget, details of child-rearing support policies, procedures, etc.) and sends it to the terminal.

[1012] 8. Displaying detailed information on the terminal

[1013] The terminal displays detailed information about local governments received from the server to the user, who can then use this information to make a decision about which local government best suits their family situation and emotional state.

[1014] Examples of concrete examples and prompts

[1015] As a concrete example, consider the case where a user enters the following information:

[1016] 2 children

[1017] Annual household income: 6 million yen

[1018] Nursery school needed

[1019] High stress

[1020] The server collects and analyzes data on local governments across the country and selects the municipality with the highest relevance score. For example, a city may be selected as the best municipality, and its detailed information will be presented as follows:

[1021] There are vacant nursery schools and no children on waiting lists.

[1022] Enhanced childcare allowance for households with an annual income of 6 million yen or less

[1023] Tax revenues are stable and there is a sufficient budget for childcare support.

[1024] With this information, users can select the municipality that best suits their home situation and emotional state.

[1025] Example prompt sentence:

[1026] Enter "2 children," "annual household income of 6 million yen," "need nursery school," and "high stress level," and provide the most suitable local government and its details.

[1027] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1028] Step 1: User Input

[1029] The user enters information about their household situation and preferences into the device's input screen. Specifically, they enter information such as the ages of their children, the number of children, their annual household income, and the need for childcare facilities. This clarifies the user's specific needs. The entered information is temporarily saved on the device.

[1030] Specific behavior:

[1031] The user connects to the device and opens the input screen.

[1032] Enter the required information for each item using text boxes and radio buttons.

[1033] Check the information you entered and click the Confirm button.

[1034] The entered data is stored in the terminal and sent to the next processing step.

[1035] Input: Age of children, number of children, annual household income, need for childcare facilities, etc.

[1036] Output: User's home situation information

[1037] Step 2: Emotion recognition by the emotion engine

[1038] The device recognizes the user's emotional state from facial expressions, tone of voice, and text content when the user types. The emotion engine analyzes the user's emotions using the device's built-in camera and microphone. This information is sent to the server.

[1039] Specific behavior:

[1040] The device's camera records the user's facial expressions.

[1041] The device's microphone records the user's voice.

[1042] The emotion engine analyzes this data in real time to determine the emotional state.

[1043] Emotion data is generated and sent to a server.

[1044] Input: User facial expressions, voice, text

[1045] Output: Emotional state data

[1046] Step 3: Data collection with generative AI

[1047] The device sends the household situation information and emotional information entered by the user to a server, which then uses generative AI to collect childcare support policy and financial data from local governments across the country. This collection involves the use of databases and APIs.

[1048] Specific behavior:

[1049] The user's input data and emotion data are sent to the server.

[1050] The server launches the generation AI and accesses the necessary databases and APIs to collect information.

[1051] The collected data is stored on a server and sent to the next processing step.

[1052] Input: User's home situation information, emotional state data

[1053] Output: Childcare support policy data and financial data of local governments

[1054] Step 4: Server calculates relevance score

[1055] The server calculates a compatibility score for each local government based on the collected local government data and the user's household situation and emotional information. The compatibility score is a numerical representation of the degree of match between the user's needs and the support provided by the local government.

[1056] Specific behavior:

[1057] The collected local government data is subjected to an analytical algorithm.

[1058] The user's home situation information and emotional information are subjected to an analysis algorithm.

[1059] A relevance score is calculated for each local government and sent to the next processing step.

[1060] Input: Childcare support policy data of local governments, financial data, user's household situation information, emotional state data

[1061] Output: Relevance score

[1062] Step 5: Server adjusts relevance scores

[1063] The server adjusts the relevance score based on the user's emotional state. For example, if the user is under high stress, it will prioritize local governments that offer comprehensive childcare support. This adjustment allows the server to select the local government that best suits the user's emotional state.

[1064] Specific behavior:

[1065] Emotional state data is analyzed to assess factors such as stress.

[1066] A weight corresponding to the emotional state is added to the relevance score.

[1067] The suitability scores are recalculated and the local government with the best score is selected.

[1068] Input: Relevance score, emotional state data

[1069] Output: Adjusted fitness score

[1070] Step 6: The server selects the most suitable local government.

[1071] Based on the adjusted relevance score, the server selects the local government with the highest score. This selection process aims to identify the municipality that best matches the user's household situation and the services provided by the local government.

[1072] Specific behavior:

[1073] The suitability scores of each local government are listed in a ranking format.

[1074] Select the local government with the highest score.

[1075] The selected local governments will be listed.

[1076] Input: Adjusted relevance score

[1077] Output: Selected local governments

[1078] Step 7: Server visualizes and sends detailed information

[1079] The server then compiles detailed information about the selected local governments and sends it to the terminal, including information on child-rearing support policies, financial status, and procedures.

[1080] Specific behavior:

[1081] Relevant information on selected local governments is extracted from the database.

[1082] Format the data in a way that is easy for users to understand.

[1083] The organized data is sent to the device.

[1084] Input: Selected local government

[1085] Output:Detailed information of local government

[1086] Step 8: Viewing detailed information via terminal

[1087] The terminal displays detailed information about local governments received from the server to the user, who can then use this information to make a decision about which local government best suits their family situation and emotional state.

[1088] Specific behavior:

[1089] The terminal receives the data received from the server.

[1090] Detailed information is displayed in a GUI (graphical user interface).

[1091] The user views the displayed information and makes a final selection.

[1092] Input: Detailed information of local government

[1093] Output: Final selection result

[1094] (Application example 2)

[1095] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1096] Conventional local government selection systems present candidates based on the user's family situation and preferences, but do not consider the user's emotional state. This can lead to stress and an inappropriate selection. Furthermore, detailed information about the selected local government is not displayed properly, providing insufficient reference information for users to use when making decisions. Therefore, there is a need for a system that can select a more appropriate local government and provide detailed information, taking into account not only the user's family situation and preferences, but also the user's emotional state.

[1097] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for inputting the family's situation and wishes, means for collecting child-rearing support policies and financial data of local governments nationwide using a generation AI, means for calculating a suitability score for each local government based on the input information and the collected information, means for recognizing the user's emotional state, means for adjusting the calculated score based on the emotional state, means for selecting the most suitable local government based on the adjusted score, means for visualizing detailed information about the selected local government, and means for displaying the detailed information to the user. This makes it possible to select the most suitable local government that comprehensively takes into account the family's situation, wishes, and emotional state, and to provide detailed information.

[1098] "Family situation" refers to information such as the user's family structure, the number of children, their ages, annual household income, and the need for childcare facilities.

[1099] "Desire" includes elements such as the user's desired living environment, support content, budget, and specific conditions.

[1100] "Generative AI" is an artificial intelligence technology that collects and analyzes data, and has the means to obtain childcare support policies and financial data from local governments.

[1101] The "relevance score" is an evaluation index that quantifies the degree of match between the user's input information and the collected data of local governments.

[1102] "Emotional state" refers to the psychological and emotional state, such as stress, anxiety, or excitement, that a user expresses when entering input.

[1103] "Emotion recognition means" refers to a means that uses technology to detect and analyze emotions from a user's facial expressions, voice, text input, etc.

[1104] "Detailed information" refers to specific data such as local government tax revenues, financial budgets, allocations, childcare support provided, and procedures.

[1105] "Visualization" includes the process of displaying collected and analyzed information in a way that is easy for users to understand.

[1106] "Display means" refers to a function that allows a user to visually check information through a terminal.

[1107] This invention is a system that selects the most suitable local government based on the user's household situation and preferences, and provides detailed information. It also incorporates an emotion engine that recognizes the user's emotional state and utilizes that information. This system includes the following main means:

[1108] System Configuration

[1109] A means of inputting family circumstances and wishes

[1110] The device provides an interface for users to input their family situation and preferences. For example, users input information such as "family structure," "number of children," "ages," "annual household income," and "need for childcare facilities." This information is used to clarify the specific needs of the family.

[1111] A means of recognizing emotional states

[1112] The device is equipped with a camera and microphone to recognize the user's emotional state. This drives an emotion engine that analyzes the user's facial expressions and voice tone to detect emotional states (e.g., stress, anxiety, excitement). The emotion engine uses TensorFlow, and emotion analysis is based on deep learning models.

[1113] Collecting data and calculating relevance scores

[1114] The server uses generative AI to collect childcare support policy and financial data from local governments across the country from online databases and APIs. This data is then compared with the user's input information to calculate a relevance score. The relevance score is a numerical representation of how closely the user's needs match the services provided by the local government.

[1115] Score adjustment and selection of optimal local governments

[1116] The server adjusts the relevance score to reflect the detected emotional state of the user. For example, if the user is in a high stress state, it will prioritize local governments that offer comprehensive childcare support. Based on the adjusted relevance score, the server selects the most suitable local government.

[1117] Visualization and display of detailed information

[1118] The server compiles detailed information about the selected local government (e.g., tax revenue, financial budget, childcare support provided, procedures, etc.) and sends it to the terminal. The terminal displays this information to the user, who then makes a decision based on it.

[1119] Hardware and software used

[1120] Hardware: Smartphone, smart glasses, camera, microphone

[1121] Software: TensorFlow (deep learning model for sentiment analysis), OpenCV (image processing), Flask (data collection and server-side processing), SQLite (database)

[1122] Specific examples

[1123] Suppose a user inputs "Family composition: 2 parents, 2 children," "Children's ages: 3 and 5 years old," "Annual household income: 6 million yen," "Childcare facilities: needed," and "Emotional state: high stress." In this case, the server collects data on local governments across the country and selects the municipality that best meets the user's needs. For example, a certain municipality may have "vacant nursery schools and no children on waiting lists," "generous childcare allowances for households with an annual income of 6 million yen or less," and "extensive childcare support systems," and provide these results to the user.

[1124] Prompt Sentence Examples

[1125] Example user input:

[1126] Family composition: 2 parents, 2 children

[1127] "Children's ages: 3 and 5 years old"

[1128] "Household annual income: 6 million yen"

[1129] "Childcare facilities: necessary"

[1130] "Emotional state: High stress"

[1131] Based on this information, the system can identify the local government that best meets the user's needs and provide detailed information.

[1132] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1133] Step 1:

[1134] The terminal provides an interface for inputting the user's household situation and wishes. For example, the user might enter information such as "Family composition: 2 parents, 2 children," "Children's ages: 3 and 5 years old," "Household annual income: 6 million yen," and "Childcare facilities: necessary." The input data is sent to the server by the terminal.

[1135] Step 2:

[1136] To recognize the user's emotional state, the device uses a camera and microphone to capture the user's facial expressions and voice tone. The captured data is analyzed by the emotion engine, which uses TensorFlow to measure the user's emotional state (e.g., stress, anxiety, excitement, etc.).

[1137] Step 3:

[1138] The server uses generative AI to collect data on childcare support policies and finances from local governments across the country. The data is obtained from online databases and APIs. This collected data is stored in a local database (SQLite).

[1139] Step 4:

[1140] The server calculates a relevance score for each local government based on the input information and emotional information received from the user. The score is calculated using an algorithm that evaluates the degree of match between the user's needs and the services provided by the local government. The calculation results are converted into numerical data and stored on the server.

[1141] Step 5:

[1142] The server adjusts the relevance score based on the user's emotional state. For example, if the user is under high stress, the server will prioritize and increase the scores of local governments that offer comprehensive childcare support. The adjusted scores are then saved back to the server.

[1143] Step 6:

[1144] Based on the adjusted relevance score, the server selects the most suitable local government. The local government with the highest score is prioritized in the selection process. The selection results are organized with detailed information about the most suitable local government.

[1145] Step 7:

[1146] The server formats detailed information about the selected local government (tax revenue, financial budget, childcare support provided, procedures, etc.) for the user and sends it to the terminal.

[1147] Step 8:

[1148] The device receives detailed information about the local government from the server and displays it to the user through a user-friendly interface, such as on the display of a smartphone or smart glasses. The user can then review the detailed information and make decisions based on it.

[1149] These steps allow for the selection of the most suitable local government taking into account the user's household situation, wishes, and emotional state, and provide the user with detailed information.

[1150] 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.

[1151] 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> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. 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 voice, text data indicating text, and image data indicating an image is also input. 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.

[1152] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1153] [Fourth embodiment]

[1154] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1155] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1156] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. 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).

[1157] 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.

[1158] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1159] 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 surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1160] 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. 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.

[1161] The control object 443 includes a display device, LEDs in the eyes, and motors for driving 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.

[1162] 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.

[1163] 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 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.

[1164] 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.

[1165] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1166] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1167] This invention is a system that selects the most suitable local government based on the household's circumstances and preferences and provides the user with detailed information. This system mainly involves a series of processes: user input, data collection using generative AI, calculation of compatibility scores, selection of the most suitable local government, and visualization of detailed information.

[1168] 1. User Input

[1169] The user enters information about their family situation and wishes into the device's input screen, such as the ages of their children, the number of children, the household's annual income, and the need for a nursery school. This clarifies the user's specific needs.

[1170] 2. Generative AI data collection

[1171] The device sends the information entered by the user to a server, which uses generative AI to collect data on childcare support policies and finances from local governments across the country, including the use of online databases and APIs to efficiently obtain the latest information.

[1172] 3. Server Calculation of Relevance Score

[1173] The server compares the collected data on local governments with the information entered by the user and calculates a compatibility score for each local government. The compatibility score is a numerical representation of the degree of match between the user's needs and the support provided by the local government. For example, the score is calculated by taking into account multiple conditions, such as the amount of support for two children, availability of nursery schools, and support policies based on annual household income.

[1174] 4. Server selection of the most suitable local government

[1175] Based on the relevance score, the server selects the local government with the highest score. This selection process aims to identify the local government that best matches the user's input information with the services offered by the local government. For example, for a family with two children and an income of less than 6 million yen, the server will select a local government that offers priority admission to daycare centers or provides specific childcare benefits.

[1176] 5. Visualization and transmission of detailed information by the server

[1177] The server then compiles detailed information about the selected local government and sends it to the terminal. This information includes the local government's tax revenue, financial budget, child-rearing support policies, procedures, etc. The user can then use this information to make a decision about where to live.

[1178] As a concrete example, suppose a user inputs "two children," "annual household income of 6 million yen," and "needs nursery school." In this case, the server collects and analyzes data on local governments across the country and selects the municipality with the highest suitability score. For example, City X is selected as the most suitable municipality, and detailed information is presented, such as "nursery school vacancies available, no children on waiting lists," "generous childcare allowances for households with annual incomes of 6 million yen or less," and "stable tax revenues, with a sufficient budget for childcare support." The user can view this information and select City X as the municipality that best suits their family situation.

[1179] This invention allows families raising children to easily select the local government that best suits their needs, reducing the burden of raising children. This will promote competition among local governments in providing services to residents, and is expected to improve the overall environment for raising children.

[1180] The processing flow will be explained below.

[1181] Step 1:

[1182] The user uses the terminal to input information about the household (children's ages, number of children, annual household income, need for childcare facilities, etc.).

[1183] Step 2:

[1184] The device sends information entered by the user to the server, including the ages of the children, the number of children, the annual household income, and the need for childcare facilities.

[1185] Step 3:

[1186] The server uses generative AI to collect childcare support policy and financial data from local governments across the country, including retrieving the latest information from online databases and APIs.

[1187] Step 4:

[1188] The server analyzes the collected local government data and extracts the child-rearing support provided by each local government and its financial situation.

[1189] Step 5:

[1190] The server compares the household situation sent by the user with the support provided by the local government and calculates a compatibility score, which is a numerical representation of the degree of match between the user's needs and the services provided by the local government.

[1191] Step 6:

[1192] The server selects the local government with the highest score based on the calculated relevance scores, which involves a process of assigning a score to each local government based on each criterion and identifying the local government with the highest score.

[1193] Step 7:

[1194] The server compiles detailed information about the selected local governments (tax revenue, financial budget, details of child-rearing support policies, procedures, etc.) and sends it to the terminal.

[1195] Step 8:

[1196] The terminal displays detailed information about local governments received from the server to the user, who can then use this information to determine which local government best suits their household situation.

[1197] Step 9:

[1198] The user selects the local government that best suits their needs from the presented candidate locations and proceeds with the relocation and administrative procedures.

[1199] As described above, this system identifies the most suitable local government based on the information entered by the user and provides detailed information about it, thereby helping the user make a rational choice.

[1200] Example 1

[1201] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1202] In modern society, it is a complex and time-consuming task for families to select the public organization that best suits their situation and wishes. It is especially important for families raising children to accurately understand and compare each local government's child-rearing support policies and financial situation, but this requires collecting and analyzing a lot of information, which is a significant burden. Furthermore, because the process for selecting the appropriate local government is unclear, there is a risk of making a wrong decision.

[1203] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1204] In this invention, the server includes a means for inputting the user's family situation and wishes, a means for using a generation AI to collect data on child-rearing support policies and finances of public organizations nationwide, and a means for calculating a suitability score for each public organization based on the input information and the collected information. This makes it possible to quickly and accurately select the public organization that best suits the user's family situation and wishes and visualize its detailed information.

[1205] "Family situation and wishes" is information entered by the user, such as the ages of minors, the number of minors, household income, and the need for childcare facilities.

[1206] "Generative AI" is a model for generating and collecting information using artificial intelligence technology.

[1207] "Public bodies" are local government bodies such as local governments and cities, towns, and villages.

[1208] "Childcare support policies" refer to childcare support services and programs provided by public organizations.

[1209] "Financial data" means information about the income, expenditure and budget of a public body.

[1210] The "suitability score" is an evaluation score that quantifies the suitability of each public organization to the user's family situation and preferences.

[1211] A "selected public entity" is a public entity that is determined to be most suitable for the user based on the relevance score.

[1212] "Detailed information" refers to specific information such as the selected public body's income, financial plan, funding allocation, child-rearing support content, and procedures.

[1213] "Visualization" means displaying collected information and calculation results in a form that is easy for users to understand.

[1214] This invention is a system that selects the most suitable public organization based on the household's situation and preferences and provides the user with detailed information. This system involves a series of processes, including user input, data collection using generative AI, calculation of compatibility scores, selection of the most suitable public organization, and visualization of detailed information.

[1215] 1. User Input

[1216] The user enters their household situation and wishes via the device's input screen, such as the ages of minors, the number of minors, household income, and the need for childcare facilities. This operation conveys the user's specific needs to the system.

[1217] 2. Generative AI data collection

[1218] The device sends the information entered by the user to a server, which then uses a generative AI model to collect data on childcare support policies and finances of public organizations. Specifically, the server uses online databases and APIs to obtain the latest information on public organizations.

[1219] 3. Server Calculation of Relevance Score

[1220] The server compares the public organization data collected by the generative AI model with the information entered by the user and calculates a compatibility score for each public organization. The compatibility score is a numerical representation of the degree of match between the user's needs and the support provided by the public organization. For example, the score is calculated taking into account multiple conditions, such as the amount of support for two minors, the availability of childcare facilities, and support policies based on household income.

[1221] 4. Server selection of the most suitable public organization

[1222] The server selects the public organization with the highest score based on the calculated relevance score. This process aims to identify the organization whose services best match the user's family situation and preferences. For example, if a family with an income of less than 6 million yen has two minor children, the server will select public organizations that offer priority admission to childcare facilities or that offer specific childcare allowances.

[1223] 5. Visualization and transmission of detailed information by the server

[1224] The server compiles detailed information about the selected public organization and sends it to the terminal. This information includes details such as the organization's revenue, financial plan, fund allocation, childcare support details, and procedures. Users can use this information to make decisions about where to live.

[1225] Specific examples

[1226] For example, if a user inputs "two minors," "household income of 6 million yen," and "needs childcare facilities," the server collects and analyzes data on public organizations across the country. It then identifies the public organization with the highest compatibility score. For example, City X may be selected as the most suitable public organization, and detailed information such as "childcare facilities available, no children on waiting lists," "generous childcare allowances for households with incomes of 6 million yen or less," and "stable income, with a sufficient budget for childcare support" may be displayed.

[1227] Example prompts for generative AI models

[1228] Below is an example of a prompt sentence to input to the generative AI model.

[1229] Family situation: 2 minors, household income of 6 million yen, childcare facility required

[1230] Select the public organization that best suits your situation.

[1231] This system will enable families with children to easily select the public organization that best meets their needs, reducing the burden of child-rearing. It will also promote competition among public organizations in providing resident services, which is expected to improve the overall child-rearing environment.

[1232] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1233] Step 1:

[1234] The user enters their family situation and wishes into the device's input screen. Specifically, they enter information such as the ages of minors, the number of minors, household income, and the need for childcare facilities. This information is temporarily saved by the device. For example, the user might enter "two minors, ages 5 and 3," "household income 6 million yen," and "need childcare facilities."

[1235] Input: User's family situation and desired information

[1236] Output: User input information temporarily saved to the device

[1237] Step 2:

[1238] The device sends the input information to the server, which then passes the received user information to the generative AI model to create a prompt. The generated prompt is then input into the generative AI model, which then collects data from appropriate public organizations.

[1239] Input: User input information

[1240] Output: The prompt sentence that is input to the generative AI model

[1241] Specific actions

[1242] The device sends information such as "two minors, annual income of 6 million yen, needing childcare facilities" to the server, which then inputs the following prompt into the generative AI model: "Family situation: two minors, household income of 6 million yen, needing childcare facilities. Please select the public organization that best suits this situation."

[1243] Step 3:

[1244] The server uses the information obtained from the generative AI model to obtain data on public organizations across the country, using online databases and APIs to collect the latest public organization data.

[1245] Input: Prompt sentence for the generative AI model

[1246] Output: Latest data for public organizations nationwide

[1247] Specific actions

[1248] For example, the server accesses the databases of City X, Town Y, and City Z to obtain child-rearing support policies and financial data for each local government.

[1249] Step 4:

[1250] The server compares the collected data on public organizations with the user's input information and calculates a relevance score, taking into account factors such as the amount of support for two minors, availability of childcare facilities, and support policies based on household income.

[1251] Input: User input and collected public data

[1252] Output: Relevance score for each public body

[1253] Specific actions

[1254] For example, the server calculates the relevance score for each item based on information such as "the amount of support for two children in City X" and "availability of childcare facilities in Town Y."

[1255] Step 5:

[1256] The server selects the public entity with the highest relevance score based on the calculated relevance scores and prepares detailed information about the selected public entity.

[1257] Input: Relevance score

[1258] Output: Selected public organizations and their details

[1259] Specific actions

[1260] For example, if "City X was judged to be the most suitable municipality," the system will compile detailed information such as the reason for this, such as "there is a good availability of childcare facilities and childcare allowances are generous."

[1261] Step 6:

[1262] The server compiles detailed information about the selected public organizations and sends it to the terminal, which displays the received information to the user.

[1263] Input: Details of the selected public body

[1264] Output: sent to terminal, displayed to user

[1265] Specific actions

[1266] For example, the device will display "Detailed information about City X," including information such as "Childcare facilities are available and there are no children on waiting lists," "Childcare allowances are generous for households with incomes of 6 million yen or less," and "Income is stable and there is a sufficient budget for childcare support."

[1267] The above is the flow of specific program processing in the system of the present invention. This processing allows users to easily find the public organization that best suits their family situation and wishes.

[1268] (Application example 1)

[1269] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1270] There is a need for a system that not only selects the most suitable local government based on a family's circumstances and preferences and provides detailed information about the local government, but also provides local safety information to give families raising children a sense of security. However, existing systems have the problem of only handling local government child-rearing support policies and financial data, and not including safety information. By solving this problem, there is a need to enable users to select a place to live with peace of mind.

[1271] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1272] In this invention, the server includes means for inputting the family's situation and preferences, means for using a generation AI to collect child-rearing support policies and financial data of local governments nationwide and local safety information, means for calculating a suitability score for each local government based on the input information and the collected information, means for selecting the most suitable local government based on the calculated score, and means for visualizing detailed information about the selected local government and local safety information. This allows users to not only select the most suitable local government but also to select a place to live with peace of mind, taking into account local safety information.

[1273] "Family situation" refers to basic information about the family, such as the age of children, the number of children, annual household income, and the need for childcare facilities.

[1274] "Hope" refers to requirements regarding the living conditions and environment desired by the user, specifically, requests for housing, education, medical care, public safety, etc.

[1275] "Generative AI" is an artificial intelligence technology that automates text generation and data collection, and is designed to collect and provide information in response to user requests.

[1276] "Local governments" refer to public institutions such as local governments and municipalities, which are organizations that provide various administrative services and support to local residents.

[1277] "Childcare support policies" refer to support measures and policies related to childcare provided by local governments, including the provision of daycare centers, childcare allowances, and childcare consultations.

[1278] "Financial data" refers to information about the financial situation of local governments, including data on tax revenues, financial budgets, and allocations.

[1279] "Local safety information" refers to information related to safety, such as local crime statistics, disaster prevention information, and contact information for police stations.

[1280] The "relevance score" is a numerical representation of the degree of match between the user's needs and the services provided by local governments.

[1281] "Detailed information" refers to specific data including the selected local government's tax revenue, financial budget, allocation, child care support provided, procedures, and local safety information.

[1282] An embodiment of the present invention will be described. The present invention is a system that selects an optimal local government based on a family's situation and preferences, and provides the user with detailed information about the local government and local safety information. This system includes a means for inputting the family's situation and preferences, a means for using a generation AI to collect child-rearing support policies and financial data of local governments nationwide and local safety information, a means for calculating a compatibility score for each local government based on the input information and the collected information, a means for selecting the optimal local government based on the calculated score, and a means for visualizing detailed information about the selected local government and local safety information.

[1283] First, a user uses a smartphone or tablet to input information about their household situation and preferences into the application, including the ages and number of children, annual household income, and the need for childcare facilities. The device then sends this information to the server.

[1284] The server uses generative AI to collect data on childcare support policies, financial data, and local safety information from local governments across the country. This data collection utilizes APIs and public databases on the internet. Specific generative AI models used include GPT-4 and BERT.

[1285] Based on the collected data, the server compares the user's input information with the data of the local government and calculates a relevance score. This score quantifies the degree of match between the user's needs and the services provided by the local government. For example, it takes into account the amount of support for two children, availability of nursery schools, and support policies based on annual household income.

[1286] Based on the calculated relevance scores, the server selects the local government with the highest score. This selection process identifies the local government whose services best match the user's household situation.

[1287] Finally, the server compiles and transmits detailed information about the selected local government and local safety information to the device. The detailed information includes the local government's tax revenue, financial budget, allocation, childcare support provided, procedures, local crime statistics, and contact information for the police station. Based on this information, users can choose the local government that best suits their family situation.

[1288] As a concrete example, if a user inputs "two children, annual household income of 6 million yen, needing nursery school," the server uses a generative AI model to collect and analyze data from across the country. City X with the highest relevance score is selected, and detailed information such as "nursery school availability, no waiting list, generous childcare allowance for households with annual income of 6 million yen or less, stable tax revenue" is displayed. Safety information for City X, including "low crime rate and contact information for the police station," is also provided.

[1289] An example prompt might look like this:

[1290] "Search for a local government that is suitable for a family with two children, an annual household income of 6 million yen, and who needs nursery school."

[1291] The above is a specific embodiment for carrying out the invention. This system enables users to easily and safely select the most suitable local government.

[1292] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1293] Step 1:

[1294] The user uses a smartphone or tablet to input information about their household situation and preferences into the application. Specifically, they input necessary information such as "children's ages," "number of children," "annual household income," and "need for childcare facilities" on the input screen. The input information is temporarily stored on the device and prepared for transmission to the server.

[1295] Input: Age of children, number of children, annual household income, need for childcare facilities

[1296] Output: User's home information temporarily stored on the device

[1297] Step 2:

[1298] The device sends the user information entered in the previous step to the server, which analyzes the received information and begins processing. The server uses the generative AI model to collect child-rearing support policies and financial data from local governments across the country, as well as local safety information.

[1299] Input: User's home information sent from the device

[1300] Output: Server that started data collection based on user information

[1301] Step 3:

[1302] The server uses a generative AI model (e.g., GPT-4 or BERT) to collect childcare support policies, financial data, and local safety information from APIs and online databases across the country. The collected data is stored in a database on the server.

[1303] Input: User's home information

[1304] Output: Collected childcare support policies, financial data, and local safety information of local governments

[1305] Step 4:

[1306] The server compares the user's input information with the collected data of each local government and calculates a compatibility score, which is calculated by taking into account multiple conditions, such as the amount of support for two children, availability of nursery schools, support policies based on annual household income, and the safety of the area.

[1307] Input: User's household information, collected data from local government organizations

[1308] Output: Relevance score for each local government

[1309] Step 5:

[1310] Based on the calculated relevance score, the server selects the local government that best matches the user's household situation. In this process, the local government with the highest score is selected.

[1311] Input: Relevance score

[1312] Output: Selected optimal local government

[1313] Step 6:

[1314] The server then compiles detailed information about the selected local governments and local safety information, generating data for visualization, including the local government's tax revenue, financial budget, allocation, childcare support provided, procedures, local crime statistics, and contact information for the police station.

[1315] Input: Selected local government

[1316] Output: Detailed information on local governments and local safety information

[1317] Step 7:

[1318] The server sends the generated detailed information and local safety information to the device, which then displays the received information to the user. Specifically, the device displays child-rearing environment and safety information from local governments in an easy-to-read format.

[1319] Input: Detailed information about local government and local safety information

[1320] Output: Information displayed on the user's terminal

[1321] For example:

[1322] Consider the case where a user inputs "two children, annual household income of 6 million yen, needing nursery school." This information is sent from the device to the server, and the generative AI model collects and analyzes data from across the country. The server selects City X with the highest relevance score, and detailed information about the selected City X, along with information that it is a safe area with a low crime rate, is displayed on the user's device.

[1323] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1324] This invention is a system that selects the most suitable local government based on the household's situation and preferences, provides the user with detailed information about the local government, and further combines it with an emotion engine that recognizes the user's emotions. This system mainly involves a series of processes: user input, data collection using generative AI, calculation of compatibility scores, adjustment of scores based on the user's emotional state, selection of the most suitable local government, and visualization of detailed information.

[1325] 1. User Input

[1326] The user enters information about their family situation and wishes into the device's input screen, such as the ages of their children, the number of children, the household's annual income, and the need for a nursery school. This clarifies the user's specific needs.

[1327] 2. Emotion Recognition by Emotion Engine

[1328] The device recognizes the user's emotional state from facial expressions, voice tone, and text input. The emotion engine analyzes the user's emotions and sends the information to the server. This emotion information detects emotional states such as stress and anxiety.

[1329] 3. Generative AI data collection

[1330] The device sends the information and emotional information input by the user to a server, which uses generative AI to collect childcare support policies and financial data from local governments across the country. This includes using online databases and APIs to efficiently obtain the latest information.

[1331] 4. Server Calculation of Relevance Score

[1332] The server calculates a relevance score for each local government based on the collected local government data, the user's input information, and the user's emotional information. The relevance score is a numerical representation of the degree of match between the user's needs and the support provided by the local government.

[1333] 5. Server-Based Relevance Score Adjustment

[1334] The server adjusts the relevance score based on the user's emotional state. For example, if the user is under high stress, the server will tend to prioritize local governments that offer comprehensive childcare support. This adjustment allows the server to select the local government that best suits the user's emotional state.

[1335] 6. Server selection of the most suitable local government

[1336] Based on the adjusted relevance scores, the server selects the local government with the highest score. This selection process aims to identify the local government that best matches the user's input information with the services provided by the local government.

[1337] 7. Visualization and transmission of detailed information by the server

[1338] The server compiles detailed information about the selected local governments (tax revenue, financial budget, details of child-rearing support policies, procedures, etc.) and sends it to the terminal.

[1339] 8. Displaying detailed information on the terminal

[1340] The terminal displays detailed information about local governments received from the server to the user, who can then use this information to determine which local government best suits their family situation and emotional state.

[1341] As a specific example, suppose a user inputs "two children," "annual household income of 6 million yen," "needs nursery school," and "high stress level." In this case, the server collects and analyzes data from local governments across the country and selects the municipality with the highest compatibility score. For example, City X is selected as the most suitable municipality, and detailed information about it is presented, including "vacant nursery schools and no children on waiting lists," "generous childcare allowances for households with annual incomes of 6 million yen or less," and "stable tax revenues and a sufficient budget for childcare support." The user can view this information and select City X as the municipality that best suits their family situation and emotional state.

[1342] This invention allows families raising children to easily find the most suitable local government based on their needs and emotional state, and make rational choices based on the detailed information. This will promote competition among local governments in providing resident services, and is expected to improve the overall child-rearing environment.

[1343] The processing flow will be explained below.

[1344] Step 1:

[1345] The user uses the terminal to input their household situation (children's ages, number of children, annual household income, need for childcare facilities, etc.) and their wishes, which clarifies the user's specific needs.

[1346] Step 2:

[1347] When a user inputs information, the device uses an emotion engine to recognize the user's emotional state from their facial expressions, voice tone, and text input. The emotion engine analyzes the user's emotional state (e.g., stress, anxiety, joy, etc.).

[1348] Step 3:

[1349] The device sends the home situation and wishes entered by the user, as well as the recognized emotion information, to the server, which then aggregates the necessary information.

[1350] Step 4:

[1351] The server uses generative AI to collect childcare support policies and financial data from local governments across the country, retrieving the latest information from online databases and APIs and storing it in a database.

[1352] Step 5:

[1353] The server analyzes the collected data from local governments and extracts details of child-rearing support and financial status for each local government, allowing the information on each local government to be organized.

[1354] Step 6:

[1355] The server compares the household situation and wishes sent by the user with the support offered by each local government and calculates a compatibility score, which is a numerical representation of the degree of match between the user's needs and the services offered by the local government.

[1356] Step 7:

[1357] The server adjusts the relevance score calculated in step 6, taking into account the user's emotional state. For example, if the user is in a high stress state, the score is adjusted to prioritize local governments with substantial childcare support.

[1358] Step 8:

[1359] The server selects the local government with the highest score based on the adjusted relevance score. This process identifies the local government that best matches the user's input information with the services provided by the local government.

[1360] Step 9:

[1361] The server compiles detailed information about the selected local governments (e.g., tax revenue, financial budget, details of child-rearing support policies, procedures) and sends it to the terminal.

[1362] Step 10:

[1363] The terminal displays detailed information about local governments received from the server to the user, who can then use this information to determine which local government best suits their family situation and emotional state.

[1364] As a concrete example, consider the case where a user inputs "two children," "annual household income of 6 million yen," "needs nursery school," and "high stress level." This information is sent from the device to the server, which uses generative AI to collect and analyze data on local governments across the country. The local governments that best fit the user's needs are then scored and adjusted based on the emotion engine. The municipality with the highest score is selected, and its details are sent to the device. Ultimately, the user can make a rational decision based on the information provided and choose the municipality that best suits their family situation and emotional state.

[1365] Example 2

[1366] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1367] Conventional systems have difficulty selecting an appropriate local government based on the user's household situation, and are unable to take the user's emotional state into account, making it impossible to make an optimal selection. As a result, it is difficult for users to make decisions based on appropriate information, resulting in issues such as reduced satisfaction and increased stress.

[1368] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for inputting family situation and wishes, means for recognizing and analyzing the user's emotional state, means for collecting child-rearing support policies and financial data of local governments nationwide using a generation AI, means for calculating a suitability score for each local government based on the input information and the collected information, means for adjusting the suitability score based on the emotional state, means for selecting the optimal local government based on the calculated and adjusted score, and means for visualizing detailed information about the selected local government. This enables the user to select the local government that is most suitable for their family situation and emotional state.

[1369] "Family situation" refers to specific matters and conditions within the home, such as the age and number of children, annual household income, and the need for childcare facilities.

[1370] "User's emotional state" refers to the user's current psychological state, including, for example, stress, anxiety, and satisfaction.

[1371] "Generative AI" refers to the use of artificial intelligence to generate and analyze data, particularly as a means of gathering up-to-date information using extensive databases and APIs.

[1372] The "relevance score" is a numerical representation of the degree of match between the user's needs and the support provided by the local government.

[1373] "Local governments" refer to organizations that provide administrative services in each region, and typically include cities, towns, villages, prefectures, etc.

[1374] "Detailed information" refers to specific data about the selected local governments, including, for example, tax revenue, financial budget, content of child-rearing support policies, and procedures.

[1375] This invention is a system that selects the most suitable local government based on the household's situation and preferences and provides detailed information to the user. This system involves a series of processes: user input, data collection using generative AI, calculation of compatibility scores, adjustment of scores based on the user's emotional state, selection of the most suitable local government, and visualization of detailed information.

[1376] 1. User Input

[1377] Users input their household situation and preferences through the device's input screen. Specifically, they input information such as the ages and number of children, annual household income, and the need for childcare facilities. This input clarifies the user's specific needs.

[1378] 2. Emotion Recognition by Emotion Engine

[1379] The device recognizes the user's emotional state from facial expressions, voice tone, and text input content. The emotion engine analyzes the user's emotions using the device's built-in camera and microphone. The analysis results are sent to the server and used as emotion information.

[1380] 3. Generative AI data collection

[1381] The device sends the household situation information and emotional information entered by the user to a server, which then uses generative AI to collect childcare support policy and financial data from local governments across the country. This collection includes the use of online databases and APIs to obtain the latest information.

[1382] 4. Server Calculation of Relevance Score

[1383] The server calculates a relevance score based on the collected local government data, the user's input information, and the user's emotional information. The relevance score is a numerical representation of the degree of match between the user's needs and the support provided by the local government.

[1384] 5. Server-Based Relevance Score Adjustment

[1385] The server adjusts the relevance score based on the user's emotional state. For example, if the user is under high stress, it will prioritize local governments that offer comprehensive childcare support. This adjustment allows the server to select the local government that best suits the user's emotional state.

[1386] 6. Server selection of the most suitable local government

[1387] Based on the adjusted relevance scores, the server selects the local government with the highest score. This selection process aims to identify the local government that best matches the user's input information with the services provided by the local government.

[1388] 7. Visualization and transmission of detailed information by the server

[1389] The server compiles detailed information about the selected local governments (tax revenue, financial budget, details of child-rearing support policies, procedures, etc.) and sends it to the terminal.

[1390] 8. Displaying detailed information on the terminal

[1391] The terminal displays detailed information about local governments received from the server to the user, who can then use this information to make a decision about which local government best suits their family situation and emotional state.

[1392] Examples of concrete examples and prompts

[1393] As a concrete example, consider the case where a user enters the following information:

[1394] 2 children

[1395] Annual household income: 6 million yen

[1396] Nursery school needed

[1397] High stress

[1398] The server collects and analyzes data on local governments across the country and selects the municipality with the highest relevance score. For example, a city may be selected as the best municipality, and its detailed information will be presented as follows:

[1399] There are vacant nursery schools and no children on waiting lists.

[1400] Enhanced childcare allowance for households with an annual income of 6 million yen or less

[1401] Tax revenues are stable and there is a sufficient budget for childcare support.

[1402] With this information, users can select the municipality that best suits their home situation and emotional state.

[1403] Example prompt sentence:

[1404] Enter "2 children," "annual household income of 6 million yen," "need nursery school," and "high stress level," and provide the most suitable local government and its details.

[1405] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1406] Step 1: User Input

[1407] The user enters information about their household situation and preferences into the device's input screen. Specifically, they enter information such as the ages of their children, the number of children, their annual household income, and the need for childcare facilities. This clarifies the user's specific needs. The entered information is temporarily saved on the device.

[1408] Specific behavior:

[1409] The user connects to the device and opens the input screen.

[1410] Enter the required information for each item using text boxes and radio buttons.

[1411] Check the information you entered and click the Confirm button.

[1412] The entered data is stored in the terminal and sent to the next processing step.

[1413] Input: Age of children, number of children, annual household income, need for childcare facilities, etc.

[1414] Output: User's home situation information

[1415] Step 2: Emotion recognition by the emotion engine

[1416] The device recognizes the user's emotional state from facial expressions, tone of voice, and text content when the user types. The emotion engine analyzes the user's emotions using the device's built-in camera and microphone. This information is sent to the server.

[1417] Specific behavior:

[1418] The device's camera records the user's facial expressions.

[1419] The device's microphone records the user's voice.

[1420] The emotion engine analyzes this data in real time to determine the emotional state.

[1421] Emotion data is generated and sent to a server.

[1422] Input: User facial expressions, voice, text

[1423] Output: Emotional state data

[1424] Step 3: Data collection with generative AI

[1425] The device sends the household situation information and emotional information entered by the user to a server, which then uses generative AI to collect childcare support policy and financial data from local governments across the country. This collection involves the use of databases and APIs.

[1426] Specific behavior:

[1427] The user's input data and emotion data are sent to the server.

[1428] The server launches the generation AI and accesses the necessary databases and APIs to collect information.

[1429] The collected data is stored on a server and sent to the next processing step.

[1430] Input: User's home situation information, emotional state data

[1431] Output: Childcare support policy data and financial data of local governments

[1432] Step 4: Server calculates relevance score

[1433] The server calculates a compatibility score for each local government based on the collected local government data and the user's household situation and emotional information. The compatibility score is a numerical representation of the degree of match between the user's needs and the support provided by the local government.

[1434] Specific behavior:

[1435] The collected local government data is subjected to an analytical algorithm.

[1436] The user's home situation information and emotional information are subjected to an analysis algorithm.

[1437] A relevance score is calculated for each local government and sent to the next processing step.

[1438] Input: Childcare support policy data of local governments, financial data, user's household situation information, emotional state data

[1439] Output: Relevance score

[1440] Step 5: Server adjusts relevance scores

[1441] The server adjusts the relevance score based on the user's emotional state. For example, if the user is under high stress, it will prioritize local governments that offer comprehensive childcare support. This adjustment allows the server to select the local government that best suits the user's emotional state.

[1442] Specific behavior:

[1443] Emotional state data is analyzed to assess factors such as stress.

[1444] A weight corresponding to the emotional state is added to the relevance score.

[1445] The suitability scores are recalculated and the local government with the best score is selected.

[1446] Input: Relevance score, emotional state data

[1447] Output: Adjusted fitness score

[1448] Step 6: The server selects the most suitable local government.

[1449] Based on the adjusted relevance score, the server selects the local government with the highest score. This selection process aims to identify the municipality that best matches the user's household situation and the services provided by the local government.

[1450] Specific behavior:

[1451] The suitability scores of each local government are listed in a ranking format.

[1452] Select the local government with the highest score.

[1453] The selected local governments will be listed.

[1454] Input: Adjusted relevance score

[1455] Output: Selected local governments

[1456] Step 7: Server visualizes and sends detailed information

[1457] The server then compiles detailed information about the selected local governments and sends it to the terminal, including information on child-rearing support policies, financial status, and procedures.

[1458] Specific behavior:

[1459] Relevant information on selected local governments is extracted from the database.

[1460] Format the data in a way that is easy for users to understand.

[1461] The organized data is sent to the device.

[1462] Input: Selected local government

[1463] Output:Detailed information of local government

[1464] Step 8: Viewing detailed information via terminal

[1465] The terminal displays detailed information about local governments received from the server to the user, who can then use this information to make a decision about which local government best suits their family situation and emotional state.

[1466] Specific behavior:

[1467] The terminal receives the data received from the server.

[1468] Detailed information is displayed in a GUI (graphical user interface).

[1469] The user views the displayed information and makes a final selection.

[1470] Input: Detailed information of local government

[1471] Output: Final selection result

[1472] (Application example 2)

[1473] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1474] Conventional local government selection systems present candidates based on the user's family situation and preferences, but do not consider the user's emotional state. This can lead to stress and an inappropriate selection. Furthermore, detailed information about the selected local government is not displayed properly, providing insufficient reference information for users to use when making decisions. Therefore, there is a need for a system that can select a more appropriate local government and provide detailed information, taking into account not only the user's family situation and preferences, but also the user's emotional state.

[1475] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for inputting the family's situation and wishes, means for collecting child-rearing support policies and financial data of local governments nationwide using a generation AI, means for calculating a suitability score for each local government based on the input information and the collected information, means for recognizing the user's emotional state, means for adjusting the calculated score based on the emotional state, means for selecting the most suitable local government based on the adjusted score, means for visualizing detailed information about the selected local government, and means for displaying the detailed information to the user. This makes it possible to select the most suitable local government that comprehensively takes into account the family's situation, wishes, and emotional state, and to provide detailed information.

[1476] "Family situation" refers to information such as the user's family structure, the number of children, their ages, annual household income, and the need for childcare facilities.

[1477] "Desire" includes elements such as the user's desired living environment, support content, budget, and specific conditions.

[1478] "Generative AI" is an artificial intelligence technology that collects and analyzes data, and has the means to obtain childcare support policies and financial data from local governments.

[1479] The "relevance score" is an evaluation index that quantifies the degree of match between the user's input information and the collected data of local governments.

[1480] "Emotional state" refers to the psychological and emotional state, such as stress, anxiety, or excitement, that a user expresses when entering input.

[1481] "Emotion recognition means" refers to a means that uses technology to detect and analyze emotions from a user's facial expressions, voice, text input, etc.

[1482] "Detailed information" refers to specific data such as local government tax revenues, financial budgets, allocations, childcare support provided, and procedures.

[1483] "Visualization" includes the process of displaying collected and analyzed information in a way that is easy for users to understand.

[1484] "Display means" refers to a function that allows a user to visually check information through a terminal.

[1485] This invention is a system that selects the most suitable local government based on the user's household situation and preferences, and provides detailed information. It also incorporates an emotion engine that recognizes the user's emotional state and utilizes that information. This system includes the following main means:

[1486] System Configuration

[1487] A means of inputting family circumstances and wishes

[1488] The device provides an interface for users to input their family situation and preferences. For example, users input information such as "family structure," "number of children," "ages," "annual household income," and "need for childcare facilities." This information is used to clarify the specific needs of the family.

[1489] A means of recognizing emotional states

[1490] The device is equipped with a camera and microphone to recognize the user's emotional state. This drives an emotion engine that analyzes the user's facial expressions and voice tone to detect emotional states (e.g., stress, anxiety, excitement). The emotion engine uses TensorFlow, and emotion analysis is based on deep learning models.

[1491] Collecting data and calculating relevance scores

[1492] The server uses generative AI to collect childcare support policy and financial data from local governments across the country from online databases and APIs. This data is then compared with the user's input information to calculate a relevance score. The relevance score is a numerical representation of how closely the user's needs match the services provided by the local government.

[1493] Score adjustment and selection of optimal local governments

[1494] The server adjusts the relevance score to reflect the detected emotional state of the user. For example, if the user is in a high stress state, it will prioritize local governments that offer comprehensive childcare support. Based on the adjusted relevance score, the server selects the most suitable local government.

[1495] Visualization and display of detailed information

[1496] The server compiles detailed information about the selected local government (e.g., tax revenue, financial budget, childcare support provided, procedures, etc.) and sends it to the terminal. The terminal displays this information to the user, who then makes a decision based on it.

[1497] Hardware and software used

[1498] Hardware: Smartphone, smart glasses, camera, microphone

[1499] Software: TensorFlow (deep learning model for sentiment analysis), OpenCV (image processing), Flask (data collection and server-side processing), SQLite (database)

[1500] Specific examples

[1501] Suppose a user inputs "Family composition: 2 parents, 2 children," "Children's ages: 3 and 5 years old," "Annual household income: 6 million yen," "Childcare facilities: needed," and "Emotional state: high stress." In this case, the server collects data on local governments across the country and selects the municipality that best meets the user's needs. For example, a certain municipality may have "vacant nursery schools and no children on waiting lists," "generous childcare allowances for households with an annual income of 6 million yen or less," and "extensive childcare support systems," and provide these results to the user.

[1502] Prompt Sentence Examples

[1503] Example user input:

[1504] Family composition: 2 parents, 2 children

[1505] "Children's ages: 3 and 5 years old"

[1506] "Household annual income: 6 million yen"

[1507] "Childcare facilities: necessary"

[1508] "Emotional state: High stress"

[1509] Based on this information, the system can identify the local government that best meets the user's needs and provide detailed information.

[1510] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1511] Step 1:

[1512] The terminal provides an interface for inputting the user's household situation and wishes. For example, the user might enter information such as "Family composition: 2 parents, 2 children," "Children's ages: 3 and 5 years old," "Household annual income: 6 million yen," and "Childcare facilities: necessary." The input data is sent to the server by the terminal.

[1513] Step 2:

[1514] To recognize the user's emotional state, the device uses a camera and microphone to capture the user's facial expressions and voice tone. The captured data is analyzed by the emotion engine, which uses TensorFlow to measure the user's emotional state (e.g., stress, anxiety, excitement, etc.).

[1515] Step 3:

[1516] The server uses generative AI to collect data on childcare support policies and finances from local governments across the country. The data is obtained from online databases and APIs. This collected data is stored in a local database (SQLite).

[1517] Step 4:

[1518] The server calculates a relevance score for each local government based on the input information and emotional information received from the user. The score is calculated using an algorithm that evaluates the degree of match between the user's needs and the services provided by the local government. The calculation results are converted into numerical data and stored on the server.

[1519] Step 5:

[1520] The server adjusts the relevance score based on the user's emotional state. For example, if the user is under high stress, the server will prioritize and increase the scores of local governments that offer comprehensive childcare support. The adjusted scores are then saved back to the server.

[1521] Step 6:

[1522] Based on the adjusted relevance score, the server selects the most suitable local government. The local government with the highest score is prioritized in the selection process. The selection results are organized with detailed information about the most suitable local government.

[1523] Step 7:

[1524] The server formats detailed information about the selected local government (tax revenue, financial budget, childcare support provided, procedures, etc.) for the user and sends it to the terminal.

[1525] Step 8:

[1526] The device receives detailed information about the local government from the server and displays it to the user through a user-friendly interface, such as on the display of a smartphone or smart glasses. The user can then review the detailed information and make decisions based on it.

[1527] These steps allow for the selection of the most suitable local government taking into account the user's household situation, wishes, and emotional state, and provide the user with detailed information.

[1528] 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.

[1529] 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> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. 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 voice, text data indicating text, and image data indicating an image is also input. 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.

[1530] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1531] 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.

[1532] FIG. 9 is a diagram illustrating 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 actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect 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.

[1533] 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.

[1534] 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).

[1535] 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 indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, 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 indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1536] 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."

[1537] 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.

[1538] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1539] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1540] 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.

[1541] 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.

[1542] 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.

[1543] The hardware resource for executing a specific process can be any of the following processors: An example of a processor 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. Another example of a processor is 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.

[1544] The hardware resource that executes the specific processing 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 processing may be a single processor.

[1545] 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.

[1546] 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.

[1547] 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.

[1548] 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.

[1549] The following is further disclosed regarding the above embodiment.

[1550] (Claim 1)

[1551] A means of inputting family circumstances and wishes;

[1552] Using generative AI, we will collect data on childcare support policies and finances from local governments across the country.

[1553] A means for calculating a relevance score for each local government based on the input information and the collected information;

[1554] A means for selecting an optimal local government based on the calculated score;

[1555] A means for visualizing detailed information of the selected local government;

[1556] A system including:

[1557] (Claim 2)

[1558] 2. The system of claim 1, wherein the input household information includes the ages of children, the number of children, annual household income, and the need for childcare facilities.

[1559] (Claim 3)

[1560] 2. The system of claim 1, wherein the detailed information includes the local government's tax revenue, financial budget, allocation, child care support provided, and procedures.

[1561] "Example 1"

[1562] (Claim 1)

[1563] A means of inputting family circumstances and wishes;

[1564] Using generative AI, we will collect childcare support policies and financial data from public organizations across the country,

[1565] A means for calculating a relevance score for each public entity based on the input information and the collected information;

[1566] means for selecting the most suitable public entity based on the calculated score;

[1567] A means for organizing and visualizing detailed information about the selected public entities;

[1568] A system including:

[1569] (Claim 2)

[1570] 2. The system of claim 1, wherein the input household information includes the ages of minor children, the number of minor children, household income, and the need for childcare facilities.

[1571] (Claim 3)

[1572] 2. The system of claim 1, wherein the detailed information includes the public entity's revenue, financial plan, allocation of funds, child care support provided, and procedures.

[1573] "Application Example 1"

[1574] (Claim 1)

[1575] A means of inputting family circumstances and wishes;

[1576] Using generative AI, we will provide a means to collect childcare support policies, financial data, and local safety information from local governments across the country.

[1577] A means for calculating a relevance score for each local government based on the input information and the collected information;

[1578] A means for selecting an optimal local government based on the calculated score;

[1579] A means for visualizing detailed information about the selected local government and safety information about the area;

[1580] A system including:

[1581] (Claim 2)

[1582] 2. The system of claim 1, wherein the input household information includes the ages of children, the number of children, annual household income, and the need for childcare facilities.

[1583] (Claim 3)

[1584] 2. The system of claim 1, wherein the detailed information includes local government tax revenue, financial budget, allocation, child care support provided, procedures, and local safety information.

[1585] "Example 2: Combining Emotion Engines"

[1586] (Claim 1)

[1587] A means of inputting family circumstances and wishes;

[1588] means for recognizing a user's emotional state and analyzing that information;

[1589] Using generative AI, we will collect data on childcare support policies and finances from local governments across the country.

[1590] A means for calculating a relevance score for each local government based on the input information and the collected information;

[1591] means for adjusting a fitness score based on said emotional state;

[1592] means for selecting the most suitable local government based on the calculated and adjusted scores;

[1593] A means for visualizing detailed information of the selected local government;

[1594] A system including:

[1595] (Claim 2)

[1596] 2. The system of claim 1, wherein the input household information includes the ages of children, the number of children, annual household income, and the need for childcare facilities.

[1597] (Claim 3)

[1598] 2. The system of claim 1, wherein the detailed information includes the local government's tax revenue, financial budget, allocation, child care support provided, and procedures.

[1599] "Application example 2 when combining emotion engines"

[1600] (Claim 1)

[1601] A means of inputting family circumstances and wishes;

[1602] Using generative AI, we will collect data on childcare support policies and finances from local governments across the country.

[1603] A means for calculating a relevance score for each local government based on the input information and the collected information;

[1604] means for recognizing the emotional state of a user;

[1605] means for adjusting the calculated score based on the emotional state;

[1606] means for selecting the most suitable local government based on the adjusted scores;

[1607] A means for visualizing detailed information of the selected local government;

[1608] means for displaying the detailed information to a user;

[1609] A system including:

[1610] (Claim 2)

[1611] 2. The system of claim 1, wherein the input household information includes the ages of children, the number of children, annual household income, and the need for childcare facilities.

[1612] (Claim 3)

[1613] 2. The system of claim 1, wherein the detailed information includes the local government's tax revenue, financial budget, allocation, child care support provided, and procedures. [Explanation of symbols]

[1614] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. A means of inputting family circumstances and wishes; Using generative AI, we will collect data on childcare support policies and finances of local governments across the country. A means for calculating a relevance score for each local government based on the input information and the collected information; A means for selecting an optimal local government based on the calculated score; A means for visualizing detailed information of the selected local government; A system including:

2. The system according to claim 1 , wherein the input household information includes the ages of children, the number of children, annual household income, and the need for childcare facilities.

3. The system according to claim 1 , wherein the detailed information includes tax revenues, financial budgets, allocations, child care support provided, and procedures for providing the support.

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