System

Abstract

A system is provided.SOLUTION: A system includes a means for acquiring open data and private data of a local government, a means for integrating the acquired data and cleaning an inconsistency and a missing value, a means for analyzing the integrated data by using an AI algorithm, a means for generating a list of optimal subsidies and grants based on an analysis result and creating a report, and a means for transmitting and displaying the generated report to a user terminal.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] Currently, digital transformation (DX) in local governments is lagging due to a lack of skills and human resources. Furthermore, while data-based decision-making and document preparation are required to effectively utilize limited budgets, there is a shortage of staff with the specialized knowledge necessary for data analysis and document preparation. As a result, applying for grants, evaluating them, and preparing reports takes a great deal of time and effort, hindering the efficient operation of local governments. There is a need for a system that can solve these problems and support data-driven policymaking and the development of attractive towns. [Means for solving the problem]

[0005] This invention is a system that acquires open data and private data from local governments, integrates and cleans them, and analyzes them using AI algorithms. Based on the analysis results, it generates a list of optimal subsidies and grants and creates a report. It also includes a means for sending the generated report to a user's device and displaying it. This system enables local governments to effectively analyze data and prepare documents, even without specialized knowledge, thereby enabling efficient local government operations. It also includes a means for users to input the information required to create a subsidy or grant application, retrieve the relevant data, and automatically generate the application, as well as a means for inputting information to request a social impact assessment of a project, collecting related data, and automatically generating a social impact assessment report using an AI algorithm. This streamlines the creation of a wide range of application documents and assessment reports, helping to promote digitalization and improve business efficiency in local governments.

[0006] "Municipal open data" refers to data such as administrative information and statistical data made public by local governments, which is provided in a format that residents and businesses can use freely.

[0007] "Private data" refers to data collected and held by private companies and organizations, and includes a wide range of information such as consumer behavior and economic activity.

[0008] A "server" is a computer system responsible for collecting, consolidating, and analyzing data, and sending generated reports to user terminals.

[0009] A "terminal" is a device that sends information entered by a user to a server and displays reports, application forms, and evaluation results returned from the server.

[0010] An "AI algorithm" is a series of calculation methods that use artificial intelligence technology to analyze data and make predictions.

[0011] "Data integration" is the process of centralizing and integrating data obtained from different sources while maintaining consistency.

[0012] "Data cleaning" is the process of detecting inconsistencies and missing values ​​in data and correcting or completing them.

[0013] "Analysis results" refers to information that refers to conclusions or insights derived from data analysis.

[0014] The "list of subsidies and grants" refers to a list of various subsidies and grants available to local governments, which is generated to provide the best options.

[0015] A "report" is a document that is automatically generated based on analysis results, application forms, and evaluation results, and is output in PDF or Excel format.

[0016] "Users" are local government employees and related parties who use the system to input data, check reports, and download data.

[0017] "Application Form" means an official document containing the information required to apply for a subsidy or grant, which is automatically generated by the system.

[0018] A "social impact assessment (SIA)" is a general term for an analysis conducted to assess the social impact of a particular project, and is a report automatically generated by an AI algorithm. [Brief explanation of the drawings]

[0019] [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

[0020] 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.

[0021] First, the terms used in the following description will be explained.

[0022] 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).

[0023] 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.

[0024] 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.

[0025] 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.

[0026] 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."

[0027] [First embodiment]

[0028] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0029] 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.

[0030] 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).

[0031] 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.

[0032] 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.

[0033] 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.

[0034] 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.

[0035] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0036] 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.

[0037] 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.

[0038] 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.

[0039] 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."

[0040] The present invention relates to a system that combines open data from local governments with private data to automatically generate applications for subsidies and grants, and also to create detailed reports including social impact assessments. This system includes multiple processing steps that are mainly performed by servers, terminals, and users.

[0041] Utilizing local government open data and private data

[0042] Data Acquisition and Integration

[0043] 1. The server periodically calls the local government's open data API to obtain demographic, economic, and environmental data. The obtained data is stored in an internal database.

[0044] 2. The server also collects data on consumer behavior and economic activity from private data providers and stores it in an internal database. This data is then integrated for later data analysis.

[0045] Data Analysis and Report Generation

[0046] 1. The server applies AI algorithms to the integrated data to analyze the specific needs and challenges of the region. This analysis makes it possible to identify the most appropriate subsidies and grants.

[0047] 2. The server automatically generates a personalized report based on the analysis results, including details of the analysis, related grant information, and recommended actions.

[0048] User Interface

[0049] Automatic generation of application forms

[0050] 1. The user enters the information required to create a grant or subsidy application into the terminal, such as the project name, purpose, and estimated costs.

[0051] 2. The terminal sends the input data to the server.

[0052] 3. The server automatically generates an application form based on the input information, which meets the requirements for the grant or subsidy. This application form contains all the necessary data.

[0053] 4. The server sends the generated application form to the terminal, which displays it to the user. The user can check the application form and make corrections or additions as necessary.

[0054] Automated generation of Social Impact Assessments (SIAs)

[0055] 1. A user inputs information into a terminal to request a social impact assessment of a specific project, such as the project's goals, intended impact area, and target communities.

[0056] 2. The terminal sends the input data to the server.

[0057] 3. The server collects relevant open data and private data based on the input information.

[0058] 4. The server uses AI algorithms to automatically generate a Social Impact Assessment (SIA) for the project, which details the project's potential impact on the local community.

[0059] 5. The server sends the generated SIA report to the terminal, which displays it to the user, who can review the report and make corrections or additions as necessary.

[0060] Cloud-based data sharing

[0061] Permissions and Data Access

[0062] 1. Users set permissions for data sharing on their devices, which determines who can access what data.

[0063] 2. The terminal sends the setting information to the server.

[0064] 3. The server manages data access on the cloud platform based on the received permission settings.

[0065] 4. When the user makes a request to access the required data, the server checks the authorization and provides the appropriate data.

[0066] Open data API provision

[0067] Issuing API keys and providing data

[0068] 1. The user (developer) requests an API key from their device.

[0069] 2. The device sends a request to the server.

[0070] 3. The server generates an API key and sends it to the device.

[0071] 4. The user (developer) uses the acquired API key to make a request to access the open data from their device.

[0072] 5. The server provides the requested data and sends it back to the device.

[0073] Examples:

[0074] When an administrative official (user) from local city A applies for a subsidy for a new child-rearing support program, the server collects child-rearing-related data from the region and uses AI to automatically generate the optimal application form. The application form is displayed on the terminal, and the administrative official can check its contents and prepare to submit it.

[0075] When another municipality B starts a local park development project and needs to evaluate its social impact, the server analyzes the relevant data and automatically generates an SIA report, which can be displayed on the terminals to help stakeholders effectively implement the project.

[0076] As described above, this system provides a wide range of functions to promote the digitalization of local governments and support efficient, data-driven policymaking.

[0077] The processing flow will be explained below.

[0078] Data Acquisition and Integration

[0079] Data Acquisition Steps

[0080] Step 1:

[0081] The server periodically calls the local government's open data API to obtain demographic, economic, and environmental data.

[0082] Step 2:

[0083] The server obtains data on consumer behavior and economic activity from private data providers and stores it in an internal database.

[0084] Step 3:

[0085] The server checks for inconsistencies in the various data stored in the database and performs data cleaning as necessary.

[0086] Data Analysis and Report Generation

[0087] Data Analysis Steps

[0088] Step 4:

[0089] The server analyzes the integrated data using AI algorithms (such as regression analysis and clustering) to identify local needs and challenges.

[0090] Step 5:

[0091] The server generates graphs and charts to visualize the analysis results.

[0092] Report Generation Steps

[0093] Step 6:

[0094] The server creates a list of optimal subsidies and grants based on the analysis results and automatically generates a personalized report.

[0095] Step 7:

[0096] The server outputs the generated report in PDF or Excel format and sends it to the user's device.

[0097] User Interface

[0098] Automatic generation of application forms

[0099] Step 8:

[0100] The user inputs the information required to complete an application for a subsidy or grant into the terminal.

[0101] Step 9:

[0102] The terminal transmits the input information to the server.

[0103] Step 10:

[0104] The server retrieves relevant data from a database based on the input information.

[0105] Step 11:

[0106] The server automatically generates the application form using an AI algorithm.

[0107] Step 12:

[0108] The server sends the generated application to the user terminal, which displays it to the user.

[0109] Automated generation of Social Impact Assessments (SIAs)

[0110] Step 13:

[0111] The user inputs information into the terminal to request a social impact assessment of the project.

[0112] Step 14:

[0113] The terminal transmits the input information to the server.

[0114] Step 15:

[0115] The server collects data related to the project from open and private sources.

[0116] Step 16:

[0117] The server automatically generates a social impact assessment (SIA) using an AI algorithm.

[0118] Step 17:

[0119] The server sends an SIA report containing the generated evaluation results to the user's terminal, which displays it to the user.

[0120] Cloud-based data sharing

[0121] Permissions and Data Access

[0122] Step 18:

[0123] The user inputs information for setting the data sharing authority into the terminal.

[0124] Step 19:

[0125] The terminal transmits the setting information to the server.

[0126] Step 20:

[0127] The server manages data access on the cloud platform based on the received permission settings.

[0128] Step 21:

[0129] When a user requests data access, the server verifies the authorization and provides the appropriate data to the user terminal.

[0130] Open data API provision

[0131] Issuing API keys and providing data

[0132] Step 22:

[0133] The user (developer) enters information into the terminal to request the issuance of an API key.

[0134] Step 23:

[0135] The terminal transmits the request information to the server.

[0136] Step 24:

[0137] The server generates an API key and sends it to the user's device.

[0138] Step 25:

[0139] The user (developer) inputs a data request into the terminal using the API key.

[0140] Step 26:

[0141] The server retrieves the relevant data from the database and returns it to the user's terminal.

[0142] Through these steps, this system will promote the digitalization of local governments and support efficient, data-driven policymaking.

[0143] Example 1

[0144] 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."

[0145] Currently, many local governments and private organizations publish various types of data, but there are only a limited number of systems that can effectively link and utilize this data. In particular, there is a lack of systems that automate the creation of subsidy and grant applications and the associated social impact assessments (SIA). As a result, the creation of applications and evaluations takes a huge amount of time and effort, making it difficult to respond quickly. There is a need for a system that solves these problems.

[0146] 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.

[0147] In this invention, the server includes a means for acquiring public information from local governments and private information, a means for integrating the acquired information and cleaning inconsistencies and missing values, and a means for analyzing the integrated information using an AI model. This enables the efficient generation of optimal lists of subsidies and grants and the efficient performance of social impact assessments (SIAs) by integrating and analyzing data from local governments and private sectors. The server also includes a means for transmitting and displaying generated reports and application forms to a user's terminal, allowing users to quickly and easily create and review necessary documents.

[0148] "Public information from local governments" refers to statistical information, administrative data, economic data, environmental data, etc. that are made public by local governments.

[0149] "Private information" refers to data provided by companies and private organizations, and includes consumer behavior, economic activity, marketing data, etc.

[0150] "Data cleaning" is the process of filling in or removing inconsistencies and missing values ​​from acquired data.

[0151] An "AI model" is an algorithm or framework that uses machine learning and deep learning techniques to analyze data and discover specific patterns and trends.

[0152] "Subsidies and grants" are funds provided by governments, local governments, and private organizations for specific purposes or activities.

[0153] A "report" is a document that summarizes data analysis results, recommended actions, subsidy information, etc.

[0154] "User terminal" means the device or computer that a user uses to access the system, enter information, and view results.

[0155] An "application form" is an official document that contains the information required to receive a grant or assistance fund.

[0156] A "Social Impact Assessment (SIA)" is a process that involves detailed analysis and evaluation of the potential impacts of a particular project on local communities.

[0157] The present invention is a system that combines public information from local governments with private information to automatically generate applications for financial aid and grants, and also prepares detailed reports including social impact assessments (SIAs). The following details explain the procedures and configurations for specifically implementing the present invention.

[0158] Utilizing public information from local governments and private information

[0159] Data Acquisition and Integration

[0160] The server periodically calls the local government's public information API to obtain demographic, economic, and environmental data. The obtained data is stored in an internal database (e.g., PostgreSQL). The server also calls the API of private data providers (e.g., Google (registered trademark) Analytics and other marketing data providers) to obtain data on consumer behavior and economic activity. This data is also stored in a database, and a process is performed to clean inconsistencies and missing values ​​(data cleansing).

[0161] Data Analysis and Report Generation

[0162] The server uses the integrated data to run AI models (e.g., TENSORFLOW® or Scikit-learn) to analyze the specific needs and challenges of the region. Based on this analysis, it generates a list of optimal grants and support programs and automatically generates a personalized report. This report includes details of the analysis, related support program information, and recommended actions. The generated report is sent from the server to the device and can be accessed by the user.

[0163] User Interface

[0164] Automatic generation of application forms

[0165] The user inputs the information required to create an application for a grant or subsidy into the terminal. Specifically, the user inputs the project name, purpose, estimated costs, etc. The terminal then sends this input data to the server. The server then automatically generates an application form based on the input information that meets the requirements of the subsidy or grant. This application form is created based on a template and reflects all necessary information. The generated application form is then sent from the server to the terminal, where the user can review it and make corrections or additions.

[0166] Automated generation of Social Impact Assessments (SIAs)

[0167] Users input information into their device to request a social impact assessment for a specific project. Specifically, they input the project's goals, expected impact area, and target communities. The device then sends this input data to a server. The server then collects relevant public and private information based on the input information and uses an AI model to automatically generate a social impact assessment. This assessment details the project's potential impact on the local community. The generated SIA report is then sent from the server to the device, where the user can review, modify, or add to it.

[0168] Specific examples

[0169] Example 1: Grant application

[0170] When an administrative official (user) from local city A applies for a subsidy for a new child-rearing support program, the server collects child-rearing-related data from the region and uses AI to automatically generate the optimal application form. The application form is displayed on the user's device, and the administrative official can review its contents and prepare for submission.

[0171] Prompt Sentence Examples

[0172] Provide the information you need to create a grant application for a new child care program. Automatically generate the application using historical data to select the optimal format.

[0173] Project name: "City Childcare Support Program"

[0174] Objective: "Enhancing family support"

[0175] Estimated cost: 5 million yen

[0176] Example 2: Social Impact Assessment

[0177] When Municipality B starts a local park development project, the server analyzes the relevant data and automatically generates an SIA report, which can be displayed on the terminals to help stakeholders effectively implement the project.

[0178] Prompt Sentence Examples

[0179] Conduct a social impact assessment of a regional park development project. Provide information such as project goals, intended impact area, and target communities. Generate an SIA report using historical data and AI models.

[0180] Project name: "Citizens' Park Development Project"

[0181] Goal: "Expanding green space and revitalizing the community"

[0182] Affected area: "Residential area surrounding the park"

[0183] Target community: "Local residents"

[0184] The above is a specific embodiment of the present invention. This system collects information from various data sources and uses advanced AI models to analyze and automatically generate data, enabling effective subsidy applications and social impact assessments.

[0185] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0186] Step 1:

[0187] Data Acquisition

[0188] The server runs a scheduled job every day at 2:00 AM to call the local government's public information API, using the API endpoint and authentication information as input.

[0189] The server retrieves public information such as demographic, economic, environmental data, etc. The output is the retrieved dataset.

[0190] The server also calls the APIs of private data providers to obtain data on consumer behavior and economic activity. The API endpoints and authentication information are used as input, and the obtained dataset is output.

[0191] Step 2:

[0192] Data integration and cleaning

[0193] The server stores the retrieved public and private information in a database (e.g., PostgreSQL). It uses the retrieved dataset as input and the output is the stored database.

[0194] The server performs data cleaning, imputing or removing inconsistencies and missing values ​​(for example, using the mean or median for imputation). The input is the stored database, and the output is the cleaned data.

[0195] Step 3:

[0196] Data analysis

[0197] The server runs an AI model (e.g., TensorFlow, Scikit-learn) based on the cleaned data, using the cleaned data and the AI ​​model as input.

[0198] The server analyzes the specific needs and issues of the region, temporarily stores the analysis results in a table, and outputs the analysis result data.

[0199] Step 4:

[0200] Automatic report generation

[0201] The server automatically generates personalized reports based on the analysis results, taking the analysis result data and report template as input.

[0202] The server includes a report with details of the analysis, relevant funding information, and recommended actions. The output is the generated report.

[0203] Step 5:

[0204] Sending and viewing reports

[0205] The server sends the generated report to the terminal. The input is the generated report and the output is the report sent to the terminal.

[0206] The terminal displays the report to the user. The input is the report sent from the server and the output is the report displayed to the user.

[0207] Step 6:

[0208] Enter application information

[0209] Users input the information necessary to complete a grant or support application, such as the project name, purpose, and estimated costs, into the terminal.

[0210] The terminal sends input data to the server, and the output is the data sent to the server.

[0211] Step 7:

[0212] Automatic generation of application forms

[0213] The server receives the input information and automatically generates an application form that meets the requirements of the grant or subsidy. The input is the user's input information and the application form template.

[0214] The server sends the generated application form to the terminal and allows the user to confirm it. The output is the application form sent to the terminal.

[0215] Step 8:

[0216] Check and correct the application form

[0217] The user checks the application form displayed on the terminal and makes corrections or additions as necessary. The input is the application form displayed on the terminal.

[0218] The terminal sends the amended application form back to the server, and the output is the amended application form sent to the server.

[0219] Step 9:

[0220] Entering social impact assessment information

[0221] Users input information into the terminal to request a social impact assessment, such as the project's goals, the expected scope of impact, and the target community.

[0222] The terminal sends the input data to the server, and the output is the data sent to the server.

[0223] Step 10:

[0224] Automatic generation of social impact assessments

[0225] The server collects relevant data based on the input information and automatically generates a social impact assessment using an AI model. The input is user information and related data.

[0226] The server sends the generated social impact assessment report to the terminal for display by the user. The output is the assessment report sent to the terminal.

[0227] Step 11:

[0228] Checking and correcting SIA reports

[0229] The user checks the SIA report displayed on the terminal and makes corrections or additions as necessary. The input is the SIA report displayed on the terminal.

[0230] The terminal sends the modified SIA report back to the server, and the output is the modified assessment report sent to the server.

[0231] The above are the specific steps of the program processing of this system.

[0232] (Application example 1)

[0233] 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."

[0234] The conventional application process for subsidies and grants involves a lot of manual work and insufficient data integration and analysis, making it difficult to obtain subsidies efficiently and effectively. Furthermore, social impact assessments (SIAs) require specialized knowledge, making them difficult for local governments and shopping districts to easily perform. The present invention aims to solve these problems and provide a data-driven, efficient subsidy application and evaluation process.

[0235] 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.

[0236] In this invention, the server includes means for acquiring open data from local governments and private data, means for integrating the acquired data and cleaning inconsistencies and missing values, means for analyzing the integrated data using an AI algorithm, means for generating a list of optimal subsidies and grants and creating a report based on the analysis results, means for sending the generated report to a user terminal and displaying it, means for collecting data provided by each store in a physical store, means for supporting subsidy applications for each store in a shopping district or shopping mall, and means for conducting social impact assessments of shopping districts and shopping malls. This enables local governments and shopping district managers to efficiently and effectively apply for appropriate subsidies and conduct social impact assessments.

[0237] "Municipal open data" refers to information such as demographic, economic, and environmental data made public by local governments.

[0238] "Private data" refers to information on consumer behavior and economic activity provided by companies and private institutions.

[0239] "Data integration methods" refers to methods for combining data from different sources into a single data set, ensuring consistency and uniformity.

[0240] "Measures for cleaning inconsistencies and missing values" refers to methods for correcting or completing errors or gaps in a dataset.

[0241] "Means of analysis using AI algorithms" refers to methods that use artificial intelligence techniques to analyze integrated data and derive specific patterns and insights.

[0242] "Means for generating a list of grants and subsidies" refers to a method for creating a list of appropriate grants and subsidies based on the analysis results.

[0243] "Means for creating a report" refers to a method for organizing the analysis results and generating a report in an easy-to-understand format.

[0244] The "means for transmitting the generated report to the user terminal and displaying it" refers to a method for transmitting the automatically generated report to the user terminal and displaying it so that the user can check it.

[0245] "Means of collecting data provided by each store within a physical store" refers to methods of collecting information on sales and services from each store within a shopping district or shopping mall.

[0246] "Measures to support each store in a shopping district or shopping mall in applying for subsidies" refers to methods to support each store in applying for subsidies effectively.

[0247] "Methods for conducting social impact assessments of shopping districts and shopping malls" refers to methods for assessing the impact that shopping districts and shopping malls have on local communities and compiling the results into a report.

[0248] MODE FOR CARRYING OUT THE INVENTION

[0249] This invention relates to a system that enables each store in a brick-and-mortar store to efficiently apply for subsidies and conduct social impact assessments (SIAs). This system is realized by combining a server and smart glasses or mobile devices as user terminals.

[0250] System Overview

[0251] The system consists of the following main components:

[0252] 1. Server:

[0253] Hardware: High-performance server

[0254] Software: MySQL (registered trademark) (database management system), requests (API call library), pandas (data analysis library), Scikit-learn (AI analysis library), TensorFlow (AI algorithm)

[0255] The server periodically acquires open data from local governments and private data, and integrates and cleans this data. It then analyzes the integrated data using AI algorithms to generate optimal subsidy and grant lists and prepare reports. It also collects data from each store within the physical store, and uses this data to support subsidy applications and conduct social impact assessments (SIA).

[0256] 2. User device (smart glasses or mobile device):

[0257] Hardware: Smart glasses (VR device), smartphone

[0258] Software: Form generation tool (Flask), LaTeX (report generation tool), AWS (registered trademark) (cloud platform), OAuth (access control library)

[0259] Users can input the information required for grant applications using smart glasses or a mobile device. The input information is sent to a server, where it is analyzed by AI and the appropriate application form is automatically generated. Users can also input information to request a social impact assessment of a project, and the results of the AI ​​analysis can be visually confirmed as a report.

[0260] Specific examples

[0261] For example, each store in a shopping district can use smart glasses to input its own sales data and service information. Based on this, the server automatically generates an optimal subsidy application form and displays it on the smart glasses. The system can also conduct a social impact assessment (SIA) on the impact the entire shopping district has on the local community and generate a detailed report. Shopping district managers and store owners can use these reports to develop effective management strategies.

[0262] Prompt Sentence Examples

[0263] We would like to use smart glasses to streamline the process of applying for subsidies for the entire shopping district. Please develop a system that automatically generates optimal subsidy application forms based on the sales data and services offered by each store in the shopping district. Also, please automatically generate social impact assessments of shopping district projects and provide the results as a report.

[0264] In the above-described manner, the present invention makes it possible to efficiently and effectively carry out subsidy applications and social impact assessments within physical stores.

[0265] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0266] Step 1:

[0267] The server periodically accesses the local government's open data API to obtain demographic, economic, and environmental data. The data is then stored in an internal database. This data includes the local population structure and economic situation.

[0268] Step 2:

[0269] The server obtains data on consumer behavior and economic activity from private data providers. This data is also stored in the internal database. The private data includes sales data for each store and customer purchasing information.

[0270] Step 3:

[0271] The server integrates the acquired municipal and private data and cleans it up for inconsistencies and missing values. Data cleaning includes correcting inconsistent data and filling in missing values.

[0272] Step 4:

[0273] The server applies AI algorithms (such as Scikit-learn and TensorFlow) to the integrated data to analyze the specific needs and challenges of the region. This analysis makes it possible to identify optimal subsidies and grants. The input data includes integrated open data and private data, and the analysis results are obtained as the output.

[0274] Step 5:

[0275] The server automatically generates a personalized report based on the analysis results, including details of the analysis, related grant information, and recommended actions. The generated report uses LaTeX formatting.

[0276] Step 6:

[0277] Users use smart glasses or a mobile device to input information required for grant applications, such as the project name, purpose, and estimated costs. The input data is then sent from the device to the server.

[0278] Step 7:

[0279] The server automatically generates an application form based on the input data, meeting the requirements for the subsidy or grant. The application form reflects the information entered by the user and recommended subsidy information based on the analysis results. The generated application form is sent to the terminal.

[0280] Step 8:

[0281] The terminal displays the generated application form to the user, who can then check it and make corrections or additions as necessary.

[0282] Step 9:

[0283] To request a Social Impact Assessment (SIA), users input project information, such as the project's goals, the intended impact area, and the target community. The input data is sent from the device to the server.

[0284] Step 10:

[0285] The server collects and analyzes relevant open data and private data based on project information provided by users, and uses AI algorithms to automatically generate a social impact assessment (SIA) for the project.

[0286] Step 11:

[0287] The server then sends the generated SIA report to the device, which details the project's potential impact on the local community.

[0288] Step 12:

[0289] The terminal displays the generated SIA report to the user, who can then review the report and make corrections or additions as necessary.

[0290] 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.

[0291] This invention adds an emotion engine that recognizes user emotions to a system that combines open data from local governments and private data, enabling more effective preparation of applications for subsidies and grants and social impact assessments. This system includes a server, a terminal, an emotion engine, and multiple processing steps that are user-driven.

[0292] Utilizing local government open data and private data

[0293] Data Acquisition and Integration

[0294] 1. The server periodically calls the local government's open data API to obtain demographic, economic, and environmental data, which is then stored in an internal database.

[0295] 2. The server also acquires data on consumer behavior and economic activity from private data providers and stores it in an internal database. This data is then integrated for later data analysis.

[0296] User Interface and Emotion Engine

[0297] Automatic generation of application forms

[0298] 1. The user enters the information needed to complete a grant or subsidy application into the device. The emotion engine uses facial recognition and voice analysis to recognize the user's emotional state in real time.

[0299] 2. The device sends the input data and the user's emotional state to the server.

[0300] 3. The server retrieves relevant data from the database based on the input information and automatically generates an application form using an AI algorithm. Based on information from the emotion engine, it displays supplementary information and advice if the user is feeling stressed or anxious.

[0301] 4. The server sends the generated application to the terminal, which displays it to the user. If the user is relaxed, they are given the option to confirm the application contents with a short confirmation procedure.

[0302] Automated generation of Social Impact Assessments (SIAs)

[0303] 1. A user inputs information into a terminal to request a social impact assessment of a specific project. The emotion engine also recognizes the user's emotions during this process.

[0304] 2. The device sends the input data and emotional state to the server.

[0305] 3. The server collects project-related data from open and private sources, automatically generates a Social Impact Assessment (SIA) using AI algorithms, and provides feedback based on an emotion engine.

[0306] 4. The server sends the generated SIA report containing the evaluation results to the device, which displays it to the user. If the user's stress level is high, the device adds information suggesting a specific action plan.

[0307] Cloud-based data sharing and emotion engine

[0308] Permissions and Data Access

[0309] 1. The user inputs information into the device to set up permissions for data sharing. The emotion engine recognizes the user's emotional state during this process.

[0310] 2. The device sends the setting information and emotional state to the server.

[0311] 3. The server manages data access on the cloud platform based on the received permission settings.

[0312] 4. When a user requests data access, the server verifies the user's authorization and provides the appropriate data to the user's device. The server also adjusts the data display method and supplementary information according to the user's emotional state.

[0313] Open data API provision and emotion engine

[0314] Issuing API keys and providing data

[0315] 1. The user (developer) inputs information to request the issuance of an API key into the device. The emotion engine also recognizes the emotional state during this process.

[0316] 2. The device sends the request information and emotional state to the server.

[0317] 3. The server generates an API key and sends it to the user's device. Emotional state may affect how applicable information is provided.

[0318] 4. The user (developer) enters a data request into the device using the API key, and the server retrieves the relevant data from the database and returns it to the user's device.

[0319] Examples:

[0320] When a local city A's administrative official (user) applies for a subsidy for a new child-rearing support program, the server collects data related to child-rearing in the area and uses AI to automatically generate the optimal application form. If the emotion engine detects a state of stress, the device provides additional information and advice, and adjusts the platform for reviewing the final application form taking into account the user's state of relaxation.

[0321] When another local government B starts a local park development project, it uses an emotion engine to recognize the emotional state of the project manager and automatically generates a social impact assessment (SIA) through AI analysis. When displaying the assessment results, the device provides feedback according to the user's emotions.

[0322] In this way, by incorporating an emotion engine, the present invention aims to promote the digitalization of local governments, improve user experience, and support efficient, data-driven policymaking.

[0323] The processing flow will be explained below.

[0324] Specific processing steps for creating an application form incorporating an emotion engine

[0325] Data Acquisition and Integration

[0326] Step 1:

[0327] The server periodically calls the local government's open data API to obtain demographic, economic, and environmental data.

[0328] Step 2:

[0329] The server obtains data on consumer behavior and economic activity from private data providers and stores it in an internal database.

[0330] Step 3:

[0331] The server checks for inconsistencies in the various data stored in the database and performs data cleaning as necessary.

[0332] Application Form Creation Process

[0333] Step 4:

[0334] Users input the information necessary to complete a grant or subsidy application into the device, and the emotion engine analyzes the user's facial expressions and tone of voice in real time to recognize their emotional state.

[0335] Step 5:

[0336] The terminal transmits the input data and emotional state to the server.

[0337] Step 6:

[0338] The server retrieves relevant open and private data from a database based on the input information. If the emotion engine determines that the user's stress level is high, it provides supplementary information and input assistance.

[0339] Step 7:

[0340] The server uses AI algorithms to analyze the acquired data and automatically generate the optimal application form, including supplementary information and confirmation messages that take the user's emotional state into account.

[0341] Step 8:

[0342] The server sends the generated application form to the terminal, which displays it to the user. The emotion engine checks the user's stress level and displays an appropriate feedback message.

[0343] Automated generation process for Social Impact Assessments (SIA)

[0344] Step 9:

[0345] Users input information into the terminal to request a social impact assessment of their project, and the emotion engine monitors the user's psychological state in real time.

[0346] Step 10:

[0347] The terminal transmits the input data and emotional state to the server.

[0348] Step 11:

[0349] The server collects data related to the project from open and private sources. If the emotion engine detects negative emotions, it displays supplemental information offering advice to the user on how to relax.

[0350] Step 12:

[0351] The server uses an AI algorithm to automatically generate a social impact assessment (SIA), adding explanatory notes to the assessment based on feedback from the emotion engine.

[0352] Step 13:

[0353] The server sends the generated SIA report to the terminal, which displays it to the user. The emotion engine displays a support message to help the user smoothly receive and understand the evaluation results.

[0354] Cloud-based data sharing process

[0355] Step 14:

[0356] The user inputs permission to share data into the device, and the emotion engine monitors the user's stress level and displays appropriate feedback messages.

[0357] Step 15:

[0358] The terminal transmits the authority setting information to the server.

[0359] Step 16:

[0360] The server manages data access on the cloud platform based on the received permission settings.

[0361] Step 17:

[0362] When a user requests data access, the server verifies the user's authorization and provides the appropriate data to the user's device. The server adjusts the display format of the data and supplementary information according to the user's emotional state.

[0363] Open data API provision process

[0364] Step 18:

[0365] The user (developer) inputs information to request the issuance of an API key into the device. The emotion engine also recognizes the user's emotional state during this process.

[0366] Step 19:

[0367] The terminal transmits the request information and the emotional state to the server.

[0368] Step 20:

[0369] The server generates an API key and sends it to the device, along with supplementary explanations that take into account the user's emotional state.

[0370] Step 21:

[0371] The user (developer) inputs a data request into the terminal using the API key.

[0372] Step 22:

[0373] The server retrieves the relevant data from the database and sends it back to the user's device, where the emotion engine provides feedback according to the emotion.

[0374] Through these steps, a system incorporating an emotion engine will efficiently promote digitalization in local governments, data-driven policy making, and improve user experience.

[0375] Example 2

[0376] 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."

[0377] The traditional process for applying for local government subsidies and grants, as well as for social impact assessments, required a lot of time and effort and was inefficient. Furthermore, there was a lack of ingenuity to reduce the stress and anxiety users felt while applying and creating assessments. This resulted in a poor user experience and sometimes led to processes that did not proceed smoothly. Furthermore, there was a need for flexible responses, such as cleaning data inconsistencies and missing values, and emotion recognition.

[0378] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0379] In this invention, the server includes: means for acquiring open data from local governments and private data; means for integrating the acquired data and cleaning inconsistencies and missing values; means for analyzing the integrated data using an AI algorithm; means for generating a list of optimal subsidies and grants and creating a report based on the analysis results; means for sending the generated report to a user terminal and displaying it; means for recognizing the user's emotional state; and means for displaying supplementary information and advice if the user is feeling stressed or anxious. This improves the user experience and enables efficient, data-driven policy planning and application processes. It also enables flexible responses based on the user's emotional state, reducing stress and anxiety.

[0380] "Municipal open data" refers to public data such as demographic, economic, and environmental data made public by local governments.

[0381] "Private data" refers to data on consumer behavior, economic activity, marketing research, etc. provided by commercial companies and non-profit organizations.

[0382] "Data integration" is the process of bringing together data from different sources into a single unified format.

[0383] "Inconsistent data" is data that is inconsistent and contradictory and requires correction before it can be used in data analysis.

[0384] "Missing value cleaning" is the process of properly handling missing values ​​in a dataset to improve data quality.

[0385] An "AI algorithm" is a series of processes and methods that use artificial intelligence technology to analyze data, make predictions, and perform optimization.

[0386] "Grants and grants" are funds provided by governments or local governments to support specific projects or activities.

[0387] "Report generation" refers to the automatic creation of reports tailored to specific purposes based on the analysis results.

[0388] A "user terminal" is a device operated by a user, such as a personal computer, smartphone, or tablet.

[0389] An "emotional state" is the emotional state a user is feeling at a particular moment, and is detected through facial recognition and voice analysis.

[0390] "Supporting information and advice" is any additional information or suggestions that can help users navigate the application or evaluation process.

[0391] "Automatic application generation" refers to the automatic creation of grant and subsidy applications based on user-provided information and related data.

[0392] A "social impact assessment" is the process of assessing the impact that a particular project will have on society or a community.

[0393] An "action plan" is a specific plan or proposal to be implemented to achieve a specific goal.

[0394] The present invention relates to a system that combines open data from local governments with private data and recognizes user emotions. The system includes a server, a terminal, an emotion engine, and multiple processing steps that are user-driven.

[0395] Data Acquisition and Integration

[0396] The server uses the Autonomous Data acquisition module to retrieve demographic, economic, and environmental data from the local government's open data API. This is done using the Python requests library. The retrieved data is stored in an internal database such as MySQL. The server also retrieves data from private data providers and stores this in the internal database. For this purpose, the Pandas library is used to integrate, clean, and resolve inconsistencies in the data.

[0397] Emotion engine and application generation

[0398] The user inputs the information needed to complete a grant or subsidy application into the device. The endpoint uses Azure® Cognitive Services or a similar emotion engine to recognize emotions in real time through facial recognition and voice analysis. The device then transmits the input data and emotional state to a server.

[0399] The server retrieves relevant data from the database and automatically generates an application form using an AI algorithm (e.g., a natural language processing model) powered by TensorFlow. It also provides supplementary information and advice depending on the user's emotional state.

[0400] Generating a Social Impact Assessment (SIA)

[0401] Users input information about a specific project into the device. The device then uses an emotion engine to recognize the user's emotional state. The device then sends the input data and emotional state to a server. The server then collects relevant data from open and private sources and automatically generates a social impact assessment (SIA) using a Python AI algorithm. The generated report is then displayed to the user, providing feedback and an action plan based on the user's emotions.

[0402] Cloud-based data sharing

[0403] The user inputs information into the device that sets permissions for data sharing. The emotion engine recognizes the user's emotional state and sends that information to the server. The server manages data access permissions on a cloud platform and provides data according to the user's request.

[0404] Open data API provision

[0405] A user as a developer inputs information to request the issuance of an API key into the device, and the emotional state is recognized by the emotion engine. The device sends this information to the server, which generates and returns an API key. The user makes a data request using the API key, and the server provides the data.

[0406] Prompt Sentence Examples

[0407] For example, consider the following prompt:

[0408] "Auto-generate a child care grant application. Enter your project summary, goals, and required budget."

[0409] "Conduct a social impact assessment of this project. Enter the project objectives, target area, and stakeholders."

[0410] "Give specific users access to specific data."

[0411] This will enable the invention to promote the digitalization of local governments and improve user experience. Furthermore, by incorporating an emotion engine, it will reduce stress and anxiety felt by users and realize efficient data-driven policy planning and application processes.

[0412] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0413] Step 1:

[0414] The server periodically calls the local government's open data API to obtain demographic, economic, and environmental data. The input is the API endpoint, and the output is JSON-formatted data. Specifically, it uses Python's requests library to obtain data using response = requests.get('https: / / api.example.com / data'). This data is stored in an internal database (such as MySQL). It is written to the database using session.add(data_object) and session.commit().

[0415] Step 2:

[0416] The server also retrieves data from private data providers and stores it in its internal database. The input is a request including an activated API key, and the output is JSON-formatted data. For example, set authentication information as headers = {'Authorization': 'Bearer YOUR_API_KEY'} and retrieve data as follows: response = requests.get('https: / / privateapi.example.com / data', headers=headers). This data is also converted to a data frame using the Pandas library and stored in the database.

[0417] Step 3:

[0418] The server combines the acquired open data and private data. The input is multiple datasets, and the output is a unified dataset. Specifically, the Pandas library is used to combine data frames and concatenate the data using combined_data = pd.concat([open_data, private_data], axis=0). Furthermore, operations such as combined_data.dropna() and combined_data.fillna(method='ffill') are performed to clean inconsistencies and missing values. The combined dataset is then saved back to the database.

[0419] Step 4:

[0420] A user enters the information needed to complete a grant or subsidy application into a device. The input is information provided through a web form or application fields, and the output is JSON-formatted data sent to a server. Specifically, data is collected using an HTML form, validated in real time with JavaScript®, and sent as follows: fetch('https: / / server.example.com / submit', {method: 'POST', body: JSON.stringify(formData)}).

[0421] Step 5:

[0422] The device recognizes the user's input data and emotional state. The input is data including the user's facial recognition and voice analysis, and the output is JSON data containing emotional state information. The emotion engine uses Azure Cognitive Services and uses the camera and microphone with navigator.mediaDevices.getUserMedia({ video: true, audio: true}). The data obtained from this is sent to the API to obtain the emotional state.

[0423] Step 6:

[0424] The device sends input data and emotional state to the server. The input is JSON format data containing user information and emotional data, and the output is data sent to the server. Specifically, data is sent as follows: fetch('https: / / server.example.com / emotion', {method: 'POST', body: JSON.stringify(emotionData)}).

[0425] Step 7:

[0426] The server retrieves relevant data from the database based on the input information and uses an AI algorithm to automatically generate an application form. The input is user information, emotion data, and an integrated dataset, and the output is an automatically generated application form. Specifically, it uses a TensorFlow model to automatically generate a draft application form as follows: model.predict(input_data).

[0427] Step 8:

[0428] The server sends the generated application form to the terminal, which displays it to the user. The input is the automatically generated application form data, and the output is the information displayed on the user's terminal. Specifically, the DOM is manipulated as follows: document.getElementById('generated_document').innerHTML = generated_content, and the generated content is inserted into the HTML element.

[0429] Step 9:

[0430] Users input information into their device to request a social impact assessment of a specific project. The input is detailed information about the project, and the output is JSON-formatted data that is sent to the server. Specifically, similar to the application creation process described above, data is collected using a web form and sent to the server.

[0431] Step 10:

[0432] The device sends input data and the user's emotional state to the server. The input is project information and emotional data from the user, and the output is data sent to the server. Specifically, data is sent as follows: fetch('https: / / server.example.com / project', {method: 'POST', body: JSON.stringify(projectData)}).

[0433] Step 11:

[0434] The server collects data related to the project and automatically generates a Social Impact Assessment (SIA) using an AI algorithm. The input is user information, sentiment data, and an integrated dataset, and the output is an automatically generated SIA report. Specifically, the model is used to generate the assessment: siaevaluation_model.evaluate(project_data).

[0435] Step 12:

[0436] The server sends the generated SIA report to the terminal, which displays it to the user. The input is the automatically generated SIA report data, and the output is the information displayed on the user's terminal. Specifically, the DOM is manipulated as follows: document.getElementById('sia_report').innerHTML = sia_content to insert the generated content into the HTML element.

[0437] Step 13:

[0438] The user inputs information into the device to set data sharing permissions. The input is detailed information about data sharing, and the output is JSON-formatted data that is sent to the server. Specifically, the setting information is entered into a form and sent to the server.

[0439] Step 14:

[0440] The device sends setting information and emotional state to the server. The input is setting information and emotional data, and the output is data sent to the server. Specifically, data is sent as follows: fetch('https: / / server.example.com / settings', {method: 'POST', body: JSON.stringify(settingsData)}).

[0441] Step 15:

[0442] The server uses AWS IAM and other cloud services to set sharing permissions and manage data access. The input is configuration information and emotion data, and the output is the completion of permission settings. Specifically, permission settings are performed using iam.createUser({UserName: 'username'}) and iam.attachUserPolicy.

[0443] Step 16:

[0444] When a user requests data access, the server checks the authorization and provides the appropriate data to the user's device. The input is the data access request, and the output is the requested data. Specifically, the data is retrieved using an AJAX request and displayed through the aforementioned DOM manipulation.

[0445] Step 17:

[0446] The user (developer) enters information into the terminal to request the issuance of an API key. The input is detailed information about the API key request, and the output is JSON format data that is sent to the server. Specifically, the user fills in the form and sends it as follows: fetch('https: / / server.example.com / apikey', {method: 'POST', body: JSON.stringify(apikeyRequest)}).

[0447] Step 18:

[0448] The device sends request information and emotional state to the server. The input is the request information and emotional data, and the output is data transmission to the server. Specifically, it sends an API request as described above.

[0449] Step 19:

[0450] The server generates an API key and sends it to the user's device. The input is the request information and emotional state, and the output is the generated API key. Specifically, it runs a script that generates an API key and sends it as fetch('https: / / server.example.com / apikey', {method: 'POST', body: JSON.stringify(apikeyResponse)}).

[0451] Step 20:

[0452] The user (developer) uses an API key to input a data request into their device, and the server retrieves the relevant data from the database and sends it back to the user's device. The input is the API key and data request, and the output is the requested data. Specifically, an AJAX request is used to retrieve the data and perform the appropriate processing.

[0453] (Application example 2)

[0454] 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."

[0455] Conventional systems that combine open data from local governments with private data can integrate and analyze data, but they are unable to provide appropriate feedback based on the user's emotional state, and therefore do not adequately improve the user experience or support efficient work.Furthermore, in the security field, there was no system that could recognize user emotions in real time and take appropriate action based on that, making it difficult to fully ensure users' sense of security.

[0456] 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 acquiring open data from local governments and private data, means for integrating the acquired data and cleaning inconsistencies and missing values, means for analyzing the integrated data using an AI algorithm, means for generating a list of optimal subsidies and grants and creating a report based on the analysis results, means for sending the generated report to a user terminal and displaying it, and means for using an emotion engine to recognize the user's emotions and provide corresponding feedback. This makes it possible to provide appropriate feedback according to the user's emotional state, thereby improving work efficiency and security.

[0457] "Municipal open data" refers to diverse datasets on the economy, environment, population, etc. provided by public institutions, and is generally accessible through APIs.

[0458] "Private data" refers to data obtained from private organizations such as companies and non-profit organizations, and includes information on consumer behavior and economic activity.

[0459] "Integration" is the process of combining data from multiple different data sources into a single dataset, including the process of correcting inconsistencies and missing values ​​to ensure consistency.

[0460] "AI algorithm" is a general term for mathematical models and methods that use artificial intelligence technology to analyze data and extract patterns and insights.

[0461] The "emotion engine" is a system that recognizes the user's emotional state from their facial expressions and voice and analyzes their emotions in real time.

[0462] A "security alarm system" is a system that detects security risks based on specified conditions and issues an alarm, and in this case, it also analyzes emotional state data.

[0463] A "user terminal" is a device that allows a user to access the system, input information, and receive analysis results and feedback, and includes smartphones, PCs, smart glasses, etc.

[0464] "Subsidies and grants" are financial assistance provided by the government or local governments for specific purposes, and are funds that are granted upon application.

[0465] A "social impact assessment" is the process of assessing the social impact of a particular project or policy, and in this case it is carried out automatically using AI algorithms.

[0466] "Real-time" refers to the extremely short time between data acquisition and the provision of analysis results, and the processing being carried out in accordance with real-time.

[0467] These definitions clarify each element of the invention.

[0468] System Overview

[0469] This invention is a system that realizes more effective subsidy and grant application preparation and social impact assessment by combining open data from local governments with private data and adding an emotion engine that recognizes user emotions. This system includes multiple processing steps, mainly consisting of a server, user terminals, and the emotion engine.

[0470] Data Acquisition and Integration

[0471] The server periodically accesses the local government's open data API to obtain demographic, economic, and environmental data. The obtained data is stored in an internal database. The server also obtains data on consumer behavior and economic activity from private data providers and stores this data in an internal database. This data is then integrated for later data analysis.

[0472] Emotion Recognition and Feedback

[0473] The user device provides an interface for inputting the information necessary to complete applications for subsidies and grants. At this time, the emotion engine uses facial recognition and voice analysis to recognize the user's emotional state in real time. The input data and the user's emotional state are sent to the server, which then analyzes them.

[0474] Automatic generation of application forms

[0475] The server retrieves relevant data from a database based on the input information and uses an AI algorithm to automatically generate an application form. Based on information from an emotion engine, the server displays supplementary information and advice if the user is feeling stressed or anxious. The generated application form is sent to the user's device, and if the user is relaxed, they are given the option to confirm the application contents through a short confirmation process.

[0476] Automatic generation of social impact assessments

[0477] When a user inputs information into their device to request a social impact assessment of a specific project, the emotion engine also recognizes the user's emotions during this process. The user's device then sends the input data and emotional state to the server, which then collects project-related data from open and private sources and uses AI algorithms to automatically generate a social impact assessment (SIA). The generated SIA report containing the assessment results is then sent to the user's device, and if the user's stress level is high, additional information is added suggesting a specific action plan.

[0478] Cloud-based data sharing

[0479] The server manages permission settings and data access for data sharing. When a user accesses the data, an emotion engine recognizes the user's emotional state and adjusts the way the data is displayed and supplementary information is provided. This functionality allows data visualization and presentation methods to be flexibly adapted to the user's needs.

[0480] The specific hardware and software used

[0481] Hardware: Smart glasses, PC, server

[0482] Software: Python, OpenCV (image processing library), EmotionEngine (emotion analysis module), SecurityAlertSystem (security system module)

[0483] Prompt Sentence Examples

[0484] As a concrete example, we will show an example of a prompt sentence to be input to the generative AI model used by the emotion engine.

[0485] Generate safety alerts based on climate data

[0486] Prompt: "If the user's facial expression indicates stress, suggest additional security alerts due to severe weather based on the last 30 minutes of weather data."

[0487] Input data:

[0488] Expression: "Stressed"

[0489] Weather: "Thunderstorm"

[0490] Sample output: "Current stress state detected. Thunderstorms expected. Additional sheltering and lock checks recommended."

[0491] This allows users to intuitively understand how protected they are in real time.

[0492] effect

[0493] This system integrates and analyzes open data from local governments and private sector data, and uses an emotion engine to research users' emotional states, enabling efficient preparation of subsidy and grant applications and social impact assessments. It also provides appropriate feedback in real time based on users' emotions in the field of security services, improving users' sense of security and convenience.

[0494] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0495] Step 1:

[0496] The server periodically calls the local government's open data API to obtain demographic, economic, and environmental data. The input is the open data API, and the output is the obtained data. This data is stored in the server's internal database. The server then obtains data on consumer behavior and economic activity from private data providers and stores that data in its internal database.

[0497] Step 2:

[0498] The server integrates the acquired open data and private data, cleaning up inconsistencies and missing values. The input is the acquired diverse data, and the output is an integrated, clean dataset. Data cleaning and consistency checks are performed to ensure the data is integrated accurately.

[0499] Step 3:

[0500] The server analyzes the integrated dataset using AI algorithms. The input is the integrated dataset and the output is the analysis results. The AI ​​algorithms extract patterns and trends from the data and provide useful insights relevant to grants and other funding.

[0501] Step 4:

[0502] The user inputs the information required to create a grant or subsidy application into the device. The input is information from the user, and the output is data stored locally on the device. At this time, the emotion engine recognizes the user's emotions in real time, which are also stored on the device.

[0503] Step 5:

[0504] The terminal transmits the information input by the user and the emotional state obtained from the emotion engine to the server. The input is the locally stored data and the emotional state, and the output is the data transmitted to the server.

[0505] Step 6:

[0506] The server retrieves relevant data from the database based on the information submitted by the user and uses an AI algorithm to automatically generate an application form. The input is user information, emotional state, and the integrated dataset, and the output is the generated application form. Information from the emotion engine is also included in the analysis, and supplementary advice is added if the user feels anxious.

[0507] Step 7:

[0508] The server sends the generated application to the terminal, which displays it to the user. The input is the generated application, and the output is the application displayed on the user's terminal. If the user is relaxed, a simple confirmation procedure and options are provided.

[0509] Step 8:

[0510] When a user inputs information to request a social impact assessment (SIA) into the terminal, the terminal transmits this information and the user's emotional state to the server. The input is the project information and the emotional state, and the output is the data transmitted to the server.

[0511] Step 9:

[0512] The server collects project-related data from open and private sources and uses AI algorithms to automatically generate a social impact assessment. The inputs are project information, sentiment state, and the integrated dataset, and the output is a social impact assessment report, which may also include feedback from the sentiment engine.

[0513] Step 10:

[0514] The server sends the generated evaluation report to the terminal, which displays it to the user. The input is the generated report, and the output is the report displayed on the user terminal. If the user's stress level is high, a specific action plan is proposed.

[0515] 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.

[0516] 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.

[0517] 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.

[0518] [Second embodiment]

[0519] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0520] 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.

[0521] 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).

[0522] 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.

[0523] 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.

[0524] 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).

[0525] 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.

[0526] 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.

[0527] 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.

[0528] 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.

[0529] In the smart glasses 214, 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.

[0530] 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."

[0531] The present invention relates to a system that combines open data from local governments with private data to automatically generate applications for subsidies and grants, and also to create detailed reports including social impact assessments. This system includes multiple processing steps that are mainly performed by servers, terminals, and users.

[0532] Utilizing local government open data and private data

[0533] Data Acquisition and Integration

[0534] 1. The server periodically calls the local government's open data API to obtain demographic, economic, and environmental data. The obtained data is stored in an internal database.

[0535] 2. The server also collects data on consumer behavior and economic activity from private data providers and stores it in an internal database. This data is then integrated for later data analysis.

[0536] Data Analysis and Report Generation

[0537] 1. The server applies AI algorithms to the integrated data to analyze the specific needs and challenges of the region. This analysis makes it possible to identify the most appropriate subsidies and grants.

[0538] 2. The server automatically generates a personalized report based on the analysis results, including details of the analysis, related grant information, and recommended actions.

[0539] User Interface

[0540] Automatic generation of application forms

[0541] 1. The user enters the information required to create a grant or subsidy application into the terminal, such as the project name, purpose, and estimated costs.

[0542] 2. The terminal sends the input data to the server.

[0543] 3. The server automatically generates an application form based on the input information, which meets the requirements for the grant or subsidy. This application form contains all the necessary data.

[0544] 4. The server sends the generated application form to the terminal, which displays it to the user. The user can check the application form and make corrections or additions as necessary.

[0545] Automated generation of Social Impact Assessments (SIAs)

[0546] 1. A user inputs information into a terminal to request a social impact assessment of a specific project, such as the project's goals, intended impact area, and target communities.

[0547] 2. The terminal sends the input data to the server.

[0548] 3. The server collects relevant open data and private data based on the input information.

[0549] 4. The server uses AI algorithms to automatically generate a Social Impact Assessment (SIA) for the project, which details the project's potential impact on the local community.

[0550] 5. The server sends the generated SIA report to the terminal, which displays it to the user, who can review the report and make corrections or additions as necessary.

[0551] Cloud-based data sharing

[0552] Permissions and Data Access

[0553] 1. Users set permissions for data sharing on their devices, which determines who can access what data.

[0554] 2. The terminal sends the setting information to the server.

[0555] 3. The server manages data access on the cloud platform based on the received permission settings.

[0556] 4. When the user makes a request to access the required data, the server checks the authorization and provides the appropriate data.

[0557] Open data API provision

[0558] Issuing API keys and providing data

[0559] 1. The user (developer) requests an API key from their device.

[0560] 2. The device sends a request to the server.

[0561] 3. The server generates an API key and sends it to the device.

[0562] 4. The user (developer) uses the acquired API key to make a request to access the open data from their device.

[0563] 5. The server provides the requested data and sends it back to the device.

[0564] Examples:

[0565] When an administrative official (user) from local city A applies for a subsidy for a new child-rearing support program, the server collects child-rearing-related data from the region and uses AI to automatically generate the optimal application form. The application form is displayed on the terminal, and the administrative official can check its contents and prepare to submit it.

[0566] When another municipality B starts a local park development project and needs to evaluate its social impact, the server analyzes the relevant data and automatically generates an SIA report, which can be displayed on the terminals to help stakeholders effectively implement the project.

[0567] As described above, this system provides a wide range of functions to promote the digitalization of local governments and support efficient, data-driven policymaking.

[0568] The processing flow will be explained below.

[0569] Data Acquisition and Integration

[0570] Data Acquisition Steps

[0571] Step 1:

[0572] The server periodically calls the local government's open data API to obtain demographic, economic, and environmental data.

[0573] Step 2:

[0574] The server obtains data on consumer behavior and economic activity from private data providers and stores it in an internal database.

[0575] Step 3:

[0576] The server checks for inconsistencies in the various data stored in the database and performs data cleaning as necessary.

[0577] Data Analysis and Report Generation

[0578] Data Analysis Steps

[0579] Step 4:

[0580] The server analyzes the integrated data using AI algorithms (such as regression analysis and clustering) to identify local needs and challenges.

[0581] Step 5:

[0582] The server generates graphs and charts to visualize the analysis results.

[0583] Report Generation Steps

[0584] Step 6:

[0585] The server creates a list of optimal subsidies and grants based on the analysis results and automatically generates a personalized report.

[0586] Step 7:

[0587] The server outputs the generated report in PDF or Excel format and sends it to the user's device.

[0588] User Interface

[0589] Automatic generation of application forms

[0590] Step 8:

[0591] The user inputs the information required to complete an application for a subsidy or grant into the terminal.

[0592] Step 9:

[0593] The terminal transmits the input information to the server.

[0594] Step 10:

[0595] The server retrieves relevant data from a database based on the input information.

[0596] Step 11:

[0597] The server automatically generates the application form using an AI algorithm.

[0598] Step 12:

[0599] The server sends the generated application to the user terminal, which displays it to the user.

[0600] Automated generation of Social Impact Assessments (SIAs)

[0601] Step 13:

[0602] The user inputs information into the terminal to request a social impact assessment of the project.

[0603] Step 14:

[0604] The terminal transmits the input information to the server.

[0605] Step 15:

[0606] The server collects data related to the project from open and private sources.

[0607] Step 16:

[0608] The server automatically generates a social impact assessment (SIA) using an AI algorithm.

[0609] Step 17:

[0610] The server sends an SIA report containing the generated evaluation results to the user's terminal, which displays it to the user.

[0611] Cloud-based data sharing

[0612] Permissions and Data Access

[0613] Step 18:

[0614] The user inputs information for setting the data sharing authority into the terminal.

[0615] Step 19:

[0616] The terminal transmits the setting information to the server.

[0617] Step 20:

[0618] The server manages data access on the cloud platform based on the received permission settings.

[0619] Step 21:

[0620] When a user requests data access, the server verifies the authorization and provides the appropriate data to the user terminal.

[0621] Open data API provision

[0622] Issuing API keys and providing data

[0623] Step 22:

[0624] The user (developer) enters information into the terminal to request the issuance of an API key.

[0625] Step 23:

[0626] The terminal transmits the request information to the server.

[0627] Step 24:

[0628] The server generates an API key and sends it to the user's device.

[0629] Step 25:

[0630] The user (developer) inputs a data request into the terminal using the API key.

[0631] Step 26:

[0632] The server retrieves the relevant data from the database and returns it to the user's terminal.

[0633] Through these steps, this system will promote the digitalization of local governments and support efficient, data-driven policymaking.

[0634] Example 1

[0635] 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."

[0636] Currently, many local governments and private organizations publish various types of data, but there are only a limited number of systems that can effectively link and utilize this data. In particular, there is a lack of systems that automate the creation of subsidy and grant applications and the associated social impact assessments (SIA). As a result, the creation of applications and evaluations takes a huge amount of time and effort, making it difficult to respond quickly. There is a need for a system that solves these problems.

[0637] 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.

[0638] In this invention, the server includes a means for acquiring public information from local governments and private information, a means for integrating the acquired information and cleaning inconsistencies and missing values, and a means for analyzing the integrated information using an AI model. This enables the efficient generation of optimal lists of subsidies and grants and the efficient performance of social impact assessments (SIAs) by integrating and analyzing data from local governments and private sectors. The server also includes a means for transmitting and displaying generated reports and application forms to a user's terminal, allowing users to quickly and easily create and review necessary documents.

[0639] "Public information from local governments" refers to statistical information, administrative data, economic data, environmental data, etc. that are made public by local governments.

[0640] "Private information" refers to data provided by companies and private organizations, and includes consumer behavior, economic activity, marketing data, etc.

[0641] "Data cleaning" is the process of filling in or removing inconsistencies and missing values ​​from acquired data.

[0642] An "AI model" is an algorithm or framework that uses machine learning and deep learning techniques to analyze data and discover specific patterns and trends.

[0643] "Subsidies and grants" are funds provided by governments, local governments, and private organizations for specific purposes or activities.

[0644] A "report" is a document that summarizes data analysis results, recommended actions, subsidy information, etc.

[0645] "User terminal" means the device or computer that a user uses to access the system, enter information, and view results.

[0646] An "application form" is an official document that contains the information required to receive a grant or assistance fund.

[0647] A "Social Impact Assessment (SIA)" is a process that involves detailed analysis and evaluation of the potential impacts of a particular project on local communities.

[0648] The present invention is a system that combines public information from local governments with private information to automatically generate applications for financial aid and grants, and also prepares detailed reports including social impact assessments (SIAs). The following details explain the procedures and configurations for specifically implementing the present invention.

[0649] Utilizing public information from local governments and private information

[0650] Data Acquisition and Integration

[0651] The server periodically calls the local government's public information API to obtain demographic, economic, and environmental data. The obtained data is stored in an internal database (e.g., PostgreSQL). The server also calls the API of private data providers (e.g., Google Analytics and other marketing data providers) to obtain data on consumer behavior and economic activity. This data is also stored in a database, and a process is performed to clean inconsistencies and missing values ​​(data cleansing).

[0652] Data Analysis and Report Generation

[0653] The server runs AI models (e.g., TensorFlow and Scikit-learn) on the integrated data to analyze the specific needs and challenges of the region. Based on this analysis, it generates a list of optimal grants and support programs and automatically generates a personalized report. The report includes details of the analysis, relevant support program information, and recommended actions. The generated report is then sent from the server to the device and can be accessed by the user.

[0654] User Interface

[0655] Automatic generation of application forms

[0656] The user inputs the information required to create an application for a grant or subsidy into the terminal. Specifically, the user inputs the project name, purpose, estimated costs, etc. The terminal then sends this input data to the server. The server then automatically generates an application form based on the input information that meets the requirements of the subsidy or grant. This application form is created based on a template and reflects all necessary information. The generated application form is then sent from the server to the terminal, where the user can review it and make corrections or additions.

[0657] Automated generation of Social Impact Assessments (SIAs)

[0658] Users input information into their device to request a social impact assessment for a specific project. Specifically, they input the project's goals, expected impact area, and target communities. The device then sends this input data to a server. The server then collects relevant public and private information based on the input information and uses an AI model to automatically generate a social impact assessment. This assessment details the project's potential impact on the local community. The generated SIA report is then sent from the server to the device, where the user can review, modify, or add to it.

[0659] Specific examples

[0660] Example 1: Grant application

[0661] When an administrative official (user) from local city A applies for a subsidy for a new child-rearing support program, the server collects child-rearing-related data from the region and uses AI to automatically generate the optimal application form. The application form is displayed on the user's device, and the administrative official can review its contents and prepare for submission.

[0662] Prompt Sentence Examples

[0663] Provide the information you need to create a grant application for a new child care program. Automatically generate the application using historical data to select the optimal format.

[0664] Project name: "City Childcare Support Program"

[0665] Objective: "Enhancing family support"

[0666] Estimated cost: 5 million yen

[0667] Example 2: Social Impact Assessment

[0668] When Municipality B starts a local park development project, the server analyzes the relevant data and automatically generates an SIA report, which can be displayed on the terminals to help stakeholders effectively implement the project.

[0669] Prompt Sentence Examples

[0670] Conduct a social impact assessment of a regional park development project. Provide information such as project goals, intended impact area, and target communities. Generate an SIA report using historical data and AI models.

[0671] Project name: "Citizens' Park Development Project"

[0672] Goal: "Expanding green space and revitalizing the community"

[0673] Affected area: "Residential area surrounding the park"

[0674] Target community: "Local residents"

[0675] The above is a specific embodiment of the present invention. This system collects information from various data sources and uses advanced AI models to analyze and automatically generate data, enabling effective subsidy applications and social impact assessments.

[0676] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0677] Step 1:

[0678] Data Acquisition

[0679] The server runs a scheduled job every day at 2:00 AM to call the local government's public information API, using the API endpoint and authentication information as input.

[0680] The server retrieves public information such as demographic, economic, environmental data, etc. The output is the retrieved dataset.

[0681] The server also calls the APIs of private data providers to obtain data on consumer behavior and economic activity. The API endpoints and authentication information are used as input, and the obtained dataset is output.

[0682] Step 2:

[0683] Data integration and cleaning

[0684] The server stores the retrieved public and private information in a database (e.g., PostgreSQL). It uses the retrieved dataset as input and the output is the stored database.

[0685] The server performs data cleaning, imputing or removing inconsistencies and missing values ​​(for example, using the mean or median for imputation). The input is the stored database, and the output is the cleaned data.

[0686] Step 3:

[0687] Data analysis

[0688] The server runs an AI model (e.g., TensorFlow, Scikit-learn) based on the cleaned data, using the cleaned data and the AI ​​model as input.

[0689] The server analyzes the specific needs and issues of the region, temporarily stores the analysis results in a table, and outputs the analysis result data.

[0690] Step 4:

[0691] Automatic report generation

[0692] The server automatically generates personalized reports based on the analysis results, taking the analysis result data and report template as input.

[0693] The server includes a report with details of the analysis, relevant funding information, and recommended actions. The output is the generated report.

[0694] Step 5:

[0695] Sending and viewing reports

[0696] The server sends the generated report to the terminal. The input is the generated report and the output is the report sent to the terminal.

[0697] The terminal displays the report to the user. The input is the report sent from the server and the output is the report displayed to the user.

[0698] Step 6:

[0699] Enter application information

[0700] Users input the information necessary to complete a grant or support application, such as the project name, purpose, and estimated costs, into the terminal.

[0701] The terminal sends input data to the server, and the output is the data sent to the server.

[0702] Step 7:

[0703] Automatic generation of application forms

[0704] The server receives the input information and automatically generates an application form that meets the requirements of the grant or subsidy. The input is the user's input information and the application form template.

[0705] The server sends the generated application form to the terminal and allows the user to confirm it. The output is the application form sent to the terminal.

[0706] Step 8:

[0707] Check and correct the application form

[0708] The user checks the application form displayed on the terminal and makes corrections or additions as necessary. The input is the application form displayed on the terminal.

[0709] The terminal sends the amended application form back to the server, and the output is the amended application form sent to the server.

[0710] Step 9:

[0711] Entering social impact assessment information

[0712] Users input information into the terminal to request a social impact assessment, such as the project's goals, the expected scope of impact, and the target community.

[0713] The terminal sends the input data to the server, and the output is the data sent to the server.

[0714] Step 10:

[0715] Automatic generation of social impact assessments

[0716] The server collects relevant data based on the input information and automatically generates a social impact assessment using an AI model. The input is user information and related data.

[0717] The server sends the generated social impact assessment report to the terminal for display by the user. The output is the assessment report sent to the terminal.

[0718] Step 11:

[0719] Checking and correcting SIA reports

[0720] The user checks the SIA report displayed on the terminal and makes corrections or additions as necessary. The input is the SIA report displayed on the terminal.

[0721] The terminal sends the modified SIA report back to the server, and the output is the modified assessment report sent to the server.

[0722] The above are the specific steps of the program processing of this system.

[0723] (Application example 1)

[0724] 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."

[0725] The conventional application process for subsidies and grants involves a lot of manual work and insufficient data integration and analysis, making it difficult to obtain subsidies efficiently and effectively. Furthermore, social impact assessments (SIAs) require specialized knowledge, making them difficult for local governments and shopping districts to easily perform. The present invention aims to solve these problems and provide a data-driven, efficient subsidy application and evaluation process.

[0726] 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.

[0727] In this invention, the server includes means for acquiring open data from local governments and private data, means for integrating the acquired data and cleaning inconsistencies and missing values, means for analyzing the integrated data using an AI algorithm, means for generating a list of optimal subsidies and grants and creating a report based on the analysis results, means for sending the generated report to a user terminal and displaying it, means for collecting data provided by each store in a physical store, means for supporting subsidy applications for each store in a shopping district or shopping mall, and means for conducting social impact assessments of shopping districts and shopping malls. This enables local governments and shopping district managers to efficiently and effectively apply for appropriate subsidies and conduct social impact assessments.

[0728] "Municipal open data" refers to information such as demographic, economic, and environmental data made public by local governments.

[0729] "Private data" refers to information on consumer behavior and economic activity provided by companies and private institutions.

[0730] "Data integration methods" refers to methods for combining data from different sources into a single data set, ensuring consistency and uniformity.

[0731] "Measures for cleaning inconsistencies and missing values" refers to methods for correcting or completing errors or gaps in a dataset.

[0732] "Means of analysis using AI algorithms" refers to methods that use artificial intelligence techniques to analyze integrated data and derive specific patterns and insights.

[0733] "Means for generating a list of grants and subsidies" refers to a method for creating a list of appropriate grants and subsidies based on the analysis results.

[0734] "Means for creating a report" refers to a method for organizing the analysis results and generating a report in an easy-to-understand format.

[0735] The "means for transmitting the generated report to the user terminal and displaying it" refers to a method for transmitting the automatically generated report to the user terminal and displaying it so that the user can check it.

[0736] "Means of collecting data provided by each store within a physical store" refers to methods of collecting information on sales and services from each store within a shopping district or shopping mall.

[0737] "Measures to support each store in a shopping district or shopping mall in applying for subsidies" refers to methods to support each store in applying for subsidies effectively.

[0738] "Methods for conducting social impact assessments of shopping districts and shopping malls" refers to methods for assessing the impact that shopping districts and shopping malls have on local communities and compiling the results into a report.

[0739] MODE FOR CARRYING OUT THE INVENTION

[0740] This invention relates to a system that enables each store in a brick-and-mortar store to efficiently apply for subsidies and conduct social impact assessments (SIAs). This system is realized by combining a server and smart glasses or mobile devices as user terminals.

[0741] System Overview

[0742] The system consists of the following main components:

[0743] 1. Server:

[0744] Hardware: High-performance server

[0745] Software: MySQL (database management system), requests (API call library), pandas (data analysis library), Scikit-learn (AI analysis library), TensorFlow (AI algorithms)

[0746] The server periodically acquires open data from local governments and private data, and integrates and cleans this data. It then analyzes the integrated data using AI algorithms to generate optimal subsidy and grant lists and prepare reports. It also collects data from each store within the physical store, and uses this data to support subsidy applications and conduct social impact assessments (SIA).

[0747] 2. User device (smart glasses or mobile device):

[0748] Hardware: Smart glasses (VR device), smartphone

[0749] Software: Form generation tool (Flask), LaTeX (report generation tool), AWS (cloud platform), OAuth (access control library)

[0750] Users can input the information required for grant applications using smart glasses or a mobile device. The input information is sent to a server, where it is analyzed by AI and the appropriate application form is automatically generated. Users can also input information to request a social impact assessment of a project, and the results of the AI ​​analysis can be visually confirmed as a report.

[0751] Specific examples

[0752] For example, each store in a shopping district can use smart glasses to input its own sales data and service information. Based on this, the server automatically generates an optimal subsidy application form and displays it on the smart glasses. The system can also conduct a social impact assessment (SIA) on the impact the entire shopping district has on the local community and generate a detailed report. Shopping district managers and store owners can use these reports to develop effective management strategies.

[0753] Prompt Sentence Examples

[0754] We would like to use smart glasses to streamline the process of applying for subsidies for the entire shopping district. Please develop a system that automatically generates optimal subsidy application forms based on the sales data and services offered by each store in the shopping district. Also, please automatically generate social impact assessments of shopping district projects and provide the results as a report.

[0755] In the above-described manner, the present invention makes it possible to efficiently and effectively carry out subsidy applications and social impact assessments within physical stores.

[0756] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0757] Step 1:

[0758] The server periodically accesses the local government's open data API to obtain demographic, economic, and environmental data. The data is then stored in an internal database. This data includes the local population structure and economic situation.

[0759] Step 2:

[0760] The server obtains data on consumer behavior and economic activity from private data providers. This data is also stored in the internal database. The private data includes sales data for each store and customer purchasing information.

[0761] Step 3:

[0762] The server integrates the acquired municipal and private data and cleans it up for inconsistencies and missing values. Data cleaning includes correcting inconsistent data and filling in missing values.

[0763] Step 4:

[0764] The server applies AI algorithms (such as Scikit-learn and TensorFlow) to the integrated data to analyze the specific needs and challenges of the region. This analysis makes it possible to identify optimal subsidies and grants. The input data includes integrated open data and private data, and the analysis results are obtained as the output.

[0765] Step 5:

[0766] The server automatically generates a personalized report based on the analysis results, including details of the analysis, related grant information, and recommended actions. The generated report uses LaTeX formatting.

[0767] Step 6:

[0768] Users use smart glasses or a mobile device to input information required for grant applications, such as the project name, purpose, and estimated costs. The input data is then sent from the device to the server.

[0769] Step 7:

[0770] The server automatically generates an application form based on the input data, meeting the requirements for the subsidy or grant. The application form reflects the information entered by the user and recommended subsidy information based on the analysis results. The generated application form is sent to the terminal.

[0771] Step 8:

[0772] The terminal displays the generated application form to the user, who can then check it and make corrections or additions as necessary.

[0773] Step 9:

[0774] To request a Social Impact Assessment (SIA), users input project information, such as the project's goals, the intended impact area, and the target community. The input data is sent from the device to the server.

[0775] Step 10:

[0776] The server collects and analyzes relevant open data and private data based on project information provided by users, and uses AI algorithms to automatically generate a social impact assessment (SIA) for the project.

[0777] Step 11:

[0778] The server then sends the generated SIA report to the device, which details the project's potential impact on the local community.

[0779] Step 12:

[0780] The terminal displays the generated SIA report to the user, who can then review the report and make corrections or additions as necessary.

[0781] 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.

[0782] This invention adds an emotion engine that recognizes user emotions to a system that combines open data from local governments and private data, enabling more effective preparation of applications for subsidies and grants and social impact assessments. This system includes a server, a terminal, an emotion engine, and multiple processing steps that are user-driven.

[0783] Utilizing local government open data and private data

[0784] Data Acquisition and Integration

[0785] 1. The server periodically calls the local government's open data API to obtain demographic, economic, and environmental data, which is then stored in an internal database.

[0786] 2. The server also acquires data on consumer behavior and economic activity from private data providers and stores it in an internal database. This data is then integrated for later data analysis.

[0787] User Interface and Emotion Engine

[0788] Automatic generation of application forms

[0789] 1. The user enters the information needed to complete a grant or subsidy application into the device. The emotion engine uses facial recognition and voice analysis to recognize the user's emotional state in real time.

[0790] 2. The device sends the input data and the user's emotional state to the server.

[0791] 3. The server retrieves relevant data from the database based on the input information and automatically generates an application form using an AI algorithm. Based on information from the emotion engine, it displays supplementary information and advice if the user is feeling stressed or anxious.

[0792] 4. The server sends the generated application to the terminal, which displays it to the user. If the user is relaxed, they are given the option to confirm the application contents with a short confirmation procedure.

[0793] Automated generation of Social Impact Assessments (SIAs)

[0794] 1. A user inputs information into a terminal to request a social impact assessment of a specific project. The emotion engine also recognizes the user's emotions during this process.

[0795] 2. The device sends the input data and emotional state to the server.

[0796] 3. The server collects project-related data from open and private sources, automatically generates a Social Impact Assessment (SIA) using AI algorithms, and provides feedback based on an emotion engine.

[0797] 4. The server sends the generated SIA report containing the evaluation results to the device, which displays it to the user. If the user's stress level is high, the device adds information suggesting a specific action plan.

[0798] Cloud-based data sharing and emotion engine

[0799] Permissions and Data Access

[0800] 1. The user inputs information into the device to set up permissions for data sharing. The emotion engine recognizes the user's emotional state during this process.

[0801] 2. The device sends the setting information and emotional state to the server.

[0802] 3. The server manages data access on the cloud platform based on the received permission settings.

[0803] 4. When a user requests data access, the server verifies the user's authorization and provides the appropriate data to the user's device. The server also adjusts the data display method and supplementary information according to the user's emotional state.

[0804] Open data API provision and emotion engine

[0805] Issuing API keys and providing data

[0806] 1. The user (developer) inputs information to request the issuance of an API key into the device. The emotion engine also recognizes the emotional state during this process.

[0807] 2. The device sends the request information and emotional state to the server.

[0808] 3. The server generates an API key and sends it to the user's device. Emotional state may affect how applicable information is provided.

[0809] 4. The user (developer) enters a data request into the device using the API key, and the server retrieves the relevant data from the database and returns it to the user's device.

[0810] Examples:

[0811] When a local city A's administrative official (user) applies for a subsidy for a new child-rearing support program, the server collects data related to child-rearing in the area and uses AI to automatically generate the optimal application form. If the emotion engine detects a state of stress, the device provides additional information and advice, and adjusts the platform for reviewing the final application form taking into account the user's state of relaxation.

[0812] When another local government B starts a local park development project, it uses an emotion engine to recognize the emotional state of the project manager and automatically generates a social impact assessment (SIA) through AI analysis. When displaying the assessment results, the device provides feedback according to the user's emotions.

[0813] In this way, by incorporating an emotion engine, the present invention aims to promote the digitalization of local governments, improve user experience, and support efficient, data-driven policymaking.

[0814] The processing flow will be explained below.

[0815] Specific processing steps for creating an application form incorporating an emotion engine

[0816] Data Acquisition and Integration

[0817] Step 1:

[0818] The server periodically calls the local government's open data API to obtain demographic, economic, and environmental data.

[0819] Step 2:

[0820] The server obtains data on consumer behavior and economic activity from private data providers and stores it in an internal database.

[0821] Step 3:

[0822] The server checks for inconsistencies in the various data stored in the database and performs data cleaning as necessary.

[0823] Application Form Creation Process

[0824] Step 4:

[0825] Users input the information necessary to complete a grant or subsidy application into the device, and the emotion engine analyzes the user's facial expressions and tone of voice in real time to recognize their emotional state.

[0826] Step 5:

[0827] The terminal transmits the input data and emotional state to the server.

[0828] Step 6:

[0829] The server retrieves relevant open and private data from a database based on the input information. If the emotion engine determines that the user's stress level is high, it provides supplementary information and input assistance.

[0830] Step 7:

[0831] The server uses AI algorithms to analyze the acquired data and automatically generate the optimal application form, including supplementary information and confirmation messages that take the user's emotional state into account.

[0832] Step 8:

[0833] The server sends the generated application form to the terminal, which displays it to the user. The emotion engine checks the user's stress level and displays an appropriate feedback message.

[0834] Automated generation process for Social Impact Assessments (SIA)

[0835] Step 9:

[0836] Users input information into the terminal to request a social impact assessment of their project, and the emotion engine monitors the user's psychological state in real time.

[0837] Step 10:

[0838] The terminal transmits the input data and emotional state to the server.

[0839] Step 11:

[0840] The server collects data related to the project from open and private sources. If the emotion engine detects negative emotions, it displays supplemental information offering advice to the user on how to relax.

[0841] Step 12:

[0842] The server uses an AI algorithm to automatically generate a social impact assessment (SIA), adding explanatory notes to the assessment based on feedback from the emotion engine.

[0843] Step 13:

[0844] The server sends the generated SIA report to the terminal, which displays it to the user. The emotion engine displays a support message to help the user smoothly receive and understand the evaluation results.

[0845] Cloud-based data sharing process

[0846] Step 14:

[0847] The user inputs permission to share data into the device, and the emotion engine monitors the user's stress level and displays appropriate feedback messages.

[0848] Step 15:

[0849] The terminal transmits the authority setting information to the server.

[0850] Step 16:

[0851] The server manages data access on the cloud platform based on the received permission settings.

[0852] Step 17:

[0853] When a user requests data access, the server verifies the user's authorization and provides the appropriate data to the user's device. The server adjusts the display format of the data and supplementary information according to the user's emotional state.

[0854] Open data API provision process

[0855] Step 18:

[0856] The user (developer) inputs information to request the issuance of an API key into the device. The emotion engine also recognizes the user's emotional state during this process.

[0857] Step 19:

[0858] The terminal transmits the request information and the emotional state to the server.

[0859] Step 20:

[0860] The server generates an API key and sends it to the device, along with supplementary explanations that take into account the user's emotional state.

[0861] Step 21:

[0862] The user (developer) inputs a data request into the terminal using the API key.

[0863] Step 22:

[0864] The server retrieves the relevant data from the database and sends it back to the user's device, where the emotion engine provides feedback according to the emotion.

[0865] Through these steps, a system incorporating an emotion engine will efficiently promote digitalization in local governments, data-driven policy making, and improve user experience.

[0866] Example 2

[0867] 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."

[0868] The traditional process for applying for local government subsidies and grants, as well as for social impact assessments, required a lot of time and effort and was inefficient. Furthermore, there was a lack of ingenuity to reduce the stress and anxiety users felt while applying and creating assessments. This resulted in a poor user experience and sometimes led to processes that did not proceed smoothly. Furthermore, there was a need for flexible responses, such as cleaning data inconsistencies and missing values, and emotion recognition.

[0869] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0870] In this invention, the server includes: means for acquiring open data from local governments and private data; means for integrating the acquired data and cleaning inconsistencies and missing values; means for analyzing the integrated data using an AI algorithm; means for generating a list of optimal subsidies and grants and creating a report based on the analysis results; means for sending the generated report to a user terminal and displaying it; means for recognizing the user's emotional state; and means for displaying supplementary information and advice if the user is feeling stressed or anxious. This improves the user experience and enables efficient, data-driven policy planning and application processes. It also enables flexible responses based on the user's emotional state, reducing stress and anxiety.

[0871] "Municipal open data" refers to public data such as demographic, economic, and environmental data made public by local governments.

[0872] "Private data" refers to data on consumer behavior, economic activity, marketing research, etc. provided by commercial companies and non-profit organizations.

[0873] "Data integration" is the process of bringing together data from different sources into a single unified format.

[0874] "Inconsistent data" is data that is inconsistent and contradictory and requires correction before it can be used in data analysis.

[0875] "Missing value cleaning" is the process of properly handling missing values ​​in a dataset to improve data quality.

[0876] An "AI algorithm" is a series of processes and methods that use artificial intelligence technology to analyze data, make predictions, and perform optimization.

[0877] "Grants and grants" are funds provided by governments or local governments to support specific projects or activities.

[0878] "Report generation" refers to the automatic creation of reports tailored to specific purposes based on the analysis results.

[0879] A "user terminal" is a device operated by a user, such as a personal computer, smartphone, or tablet.

[0880] An "emotional state" is the emotional state a user is feeling at a particular moment, and is detected through facial recognition and voice analysis.

[0881] "Supporting information and advice" is any additional information or suggestions that can help users navigate the application or evaluation process.

[0882] "Automatic application generation" refers to the automatic creation of grant and subsidy applications based on user-provided information and related data.

[0883] A "social impact assessment" is the process of assessing the impact that a particular project will have on society or a community.

[0884] An "action plan" is a specific plan or proposal to be implemented to achieve a specific goal.

[0885] The present invention relates to a system that combines open data from local governments with private data and recognizes user emotions. The system includes a server, a terminal, an emotion engine, and multiple processing steps that are user-driven.

[0886] Data Acquisition and Integration

[0887] The server uses the Autonomous Data acquisition module to retrieve demographic, economic, and environmental data from the local government's open data API. This is done using the Python requests library. The retrieved data is stored in an internal database such as MySQL. The server also retrieves data from private data providers and stores this in the internal database. For this purpose, the Pandas library is used to integrate, clean, and resolve inconsistencies in the data.

[0888] Emotion engine and application generation

[0889] The user inputs the information needed to complete a grant or subsidy application into the device. The endpoint uses Azure Cognitive Services or a similar emotion engine to recognize emotions in real time through facial recognition and voice analysis. The device then transmits the input data and emotional state to a server.

[0890] The server retrieves relevant data from the database and automatically generates an application form using an AI algorithm (e.g., a natural language processing model) powered by TensorFlow. It also provides supplementary information and advice depending on the user's emotional state.

[0891] Generating a Social Impact Assessment (SIA)

[0892] Users input information about a specific project into the device. The device then uses an emotion engine to recognize the user's emotional state. The device then sends the input data and emotional state to a server. The server then collects relevant data from open and private sources and automatically generates a social impact assessment (SIA) using a Python AI algorithm. The generated report is then displayed to the user, providing feedback and an action plan based on the user's emotions.

[0893] Cloud-based data sharing

[0894] The user inputs information into the device that sets permissions for data sharing. The emotion engine recognizes the user's emotional state and sends that information to the server. The server manages data access permissions on a cloud platform and provides data according to the user's request.

[0895] Open data API provision

[0896] A user as a developer inputs information to request the issuance of an API key into the device, and the emotional state is recognized by the emotion engine. The device sends this information to the server, which generates and returns an API key. The user makes a data request using the API key, and the server provides the data.

[0897] Prompt Sentence Examples

[0898] For example, consider the following prompt:

[0899] "Auto-generate a child care grant application. Enter your project summary, goals, and required budget."

[0900] "Conduct a social impact assessment of this project. Enter the project objectives, target area, and stakeholders."

[0901] "Give specific users access to specific data."

[0902] This will enable the invention to promote the digitalization of local governments and improve user experience. Furthermore, by incorporating an emotion engine, it will reduce stress and anxiety felt by users and realize efficient data-driven policy planning and application processes.

[0903] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0904] Step 1:

[0905] The server periodically calls the local government's open data API to obtain demographic, economic, and environmental data. The input is the API endpoint, and the output is JSON-formatted data. Specifically, it uses Python's requests library to obtain data using response = requests.get('https: / / api.example.com / data'). This data is stored in an internal database (such as MySQL). It is written to the database using session.add(data_object) and session.commit().

[0906] Step 2:

[0907] The server also retrieves data from private data providers and stores it in its internal database. The input is a request including an activated API key, and the output is JSON-formatted data. For example, set authentication information as headers = {'Authorization': 'Bearer YOUR_API_KEY'} and retrieve data as follows: response = requests.get('https: / / privateapi.example.com / data', headers=headers). This data is also converted to a data frame using the Pandas library and stored in the database.

[0908] Step 3:

[0909] The server combines the acquired open data and private data. The input is multiple datasets, and the output is a unified dataset. Specifically, the Pandas library is used to combine data frames and concatenate the data using combined_data = pd.concat([open_data, private_data], axis=0). Furthermore, operations such as combined_data.dropna() and combined_data.fillna(method='ffill') are performed to clean inconsistencies and missing values. The combined dataset is then saved back to the database.

[0910] Step 4:

[0911] A user enters information into a device to complete a grant or subsidy application. The input is information provided through a web form or application fields, and the output is JSON-formatted data sent to a server. Specifically, the data is collected using an HTML form, validated in real time with JavaScript, and then submitted using fetch('https: / / server.example.com / submit', {method: 'POST', body: JSON.stringify(formData)}).

[0912] Step 5:

[0913] The device recognizes the user's input data and emotional state. The input is data including the user's facial recognition and voice analysis, and the output is JSON data containing emotional state information. The emotion engine uses Azure Cognitive Services and uses the camera and microphone with navigator.mediaDevices.getUserMedia({ video: true, audio: true}). The data obtained from this is sent to the API to obtain the emotional state.

[0914] Step 6:

[0915] The device sends input data and emotional state to the server. The input is JSON format data containing user information and emotional data, and the output is data sent to the server. Specifically, data is sent as follows: fetch('https: / / server.example.com / emotion', {method: 'POST', body: JSON.stringify(emotionData)}).

[0916] Step 7:

[0917] The server retrieves relevant data from the database based on the input information and uses an AI algorithm to automatically generate an application form. The input is user information, emotion data, and an integrated dataset, and the output is an automatically generated application form. Specifically, it uses a TensorFlow model to automatically generate a draft application form as follows: model.predict(input_data).

[0918] Step 8:

[0919] The server sends the generated application form to the terminal, which displays it to the user. The input is the automatically generated application form data, and the output is the information displayed on the user's terminal. Specifically, the DOM is manipulated as follows: document.getElementById('generated_document').innerHTML = generated_content, and the generated content is inserted into the HTML element.

[0920] Step 9:

[0921] Users input information into their device to request a social impact assessment of a specific project. The input is detailed information about the project, and the output is JSON-formatted data that is sent to the server. Specifically, similar to the application creation process described above, data is collected using a web form and sent to the server.

[0922] Step 10:

[0923] The device sends input data and the user's emotional state to the server. The input is project information and emotional data from the user, and the output is data sent to the server. Specifically, data is sent as follows: fetch('https: / / server.example.com / project', {method: 'POST', body: JSON.stringify(projectData)}).

[0924] Step 11:

[0925] The server collects data related to the project and automatically generates a Social Impact Assessment (SIA) using an AI algorithm. The input is user information, sentiment data, and an integrated dataset, and the output is an automatically generated SIA report. Specifically, the model is used to generate the assessment: siaevaluation_model.evaluate(project_data).

[0926] Step 12:

[0927] The server sends the generated SIA report to the terminal, which displays it to the user. The input is the automatically generated SIA report data, and the output is the information displayed on the user's terminal. Specifically, the DOM is manipulated as follows: document.getElementById('sia_report').innerHTML = sia_content to insert the generated content into the HTML element.

[0928] Step 13:

[0929] The user inputs information into the device to set data sharing permissions. The input is detailed information about data sharing, and the output is JSON-formatted data that is sent to the server. Specifically, the setting information is entered into a form and sent to the server.

[0930] Step 14:

[0931] The device sends setting information and emotional state to the server. The input is setting information and emotional data, and the output is data sent to the server. Specifically, data is sent as follows: fetch('https: / / server.example.com / settings', {method: 'POST', body: JSON.stringify(settingsData)}).

[0932] Step 15:

[0933] The server uses AWS IAM and other cloud services to set sharing permissions and manage data access. The input is configuration information and emotion data, and the output is the completion of permission settings. Specifically, permission settings are performed using iam.createUser({UserName: 'username'}) and iam.attachUserPolicy.

[0934] Step 16:

[0935] When a user requests data access, the server checks the authorization and provides the appropriate data to the user's device. The input is the data access request, and the output is the requested data. Specifically, the data is retrieved using an AJAX request and displayed through the aforementioned DOM manipulation.

[0936] Step 17:

[0937] The user (developer) enters information into the terminal to request the issuance of an API key. The input is detailed information about the API key request, and the output is JSON format data that is sent to the server. Specifically, the user fills in the form and sends it as follows: fetch('https: / / server.example.com / apikey', {method: 'POST', body: JSON.stringify(apikeyRequest)}).

[0938] Step 18:

[0939] The device sends request information and emotional state to the server. The input is the request information and emotional data, and the output is data transmission to the server. Specifically, it sends an API request as described above.

[0940] Step 19:

[0941] The server generates an API key and sends it to the user's device. The input is the request information and emotional state, and the output is the generated API key. Specifically, it runs a script that generates an API key and sends it as fetch('https: / / server.example.com / apikey', {method: 'POST', body: JSON.stringify(apikeyResponse)}).

[0942] Step 20:

[0943] The user (developer) uses an API key to input a data request into their device, and the server retrieves the relevant data from the database and sends it back to the user's device. The input is the API key and data request, and the output is the requested data. Specifically, an AJAX request is used to retrieve the data and perform the appropriate processing.

[0944] (Application example 2)

[0945] 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."

[0946] Conventional systems that combine open data from local governments with private data can integrate and analyze data, but they are unable to provide appropriate feedback based on the user's emotional state, and therefore do not adequately improve the user experience or support efficient work.Furthermore, in the security field, there was no system that could recognize user emotions in real time and take appropriate action based on that, making it difficult to fully ensure users' sense of security.

[0947] 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 acquiring open data from local governments and private data, means for integrating the acquired data and cleaning inconsistencies and missing values, means for analyzing the integrated data using an AI algorithm, means for generating a list of optimal subsidies and grants and creating a report based on the analysis results, means for sending the generated report to a user terminal and displaying it, and means for using an emotion engine to recognize the user's emotions and provide corresponding feedback. This makes it possible to provide appropriate feedback according to the user's emotional state, thereby improving work efficiency and security.

[0948] "Municipal open data" refers to diverse datasets on the economy, environment, population, etc. provided by public institutions, and is generally accessible through APIs.

[0949] "Private data" refers to data obtained from private organizations such as companies and non-profit organizations, and includes information on consumer behavior and economic activity.

[0950] "Integration" is the process of combining data from multiple different data sources into a single dataset, including the process of correcting inconsistencies and missing values ​​to ensure consistency.

[0951] "AI algorithm" is a general term for mathematical models and methods that use artificial intelligence technology to analyze data and extract patterns and insights.

[0952] The "emotion engine" is a system that recognizes the user's emotional state from their facial expressions and voice and analyzes their emotions in real time.

[0953] A "security alarm system" is a system that detects security risks based on specified conditions and issues an alarm, and in this case, it also analyzes emotional state data.

[0954] A "user terminal" is a device that allows a user to access the system, input information, and receive analysis results and feedback, and includes smartphones, PCs, smart glasses, etc.

[0955] "Subsidies and grants" are financial assistance provided by the government or local governments for specific purposes, and are funds that are granted upon application.

[0956] A "social impact assessment" is the process of assessing the social impact of a particular project or policy, and in this case it is carried out automatically using AI algorithms.

[0957] "Real-time" refers to the extremely short time between data acquisition and the provision of analysis results, and the processing being carried out in accordance with real-time.

[0958] These definitions clarify each element of the invention.

[0959] System Overview

[0960] This invention is a system that realizes more effective subsidy and grant application preparation and social impact assessment by combining open data from local governments with private data and adding an emotion engine that recognizes user emotions. This system includes multiple processing steps, mainly consisting of a server, user terminals, and the emotion engine.

[0961] Data Acquisition and Integration

[0962] The server periodically accesses the local government's open data API to obtain demographic, economic, and environmental data. The obtained data is stored in an internal database. The server also obtains data on consumer behavior and economic activity from private data providers and stores this data in an internal database. This data is then integrated for later data analysis.

[0963] Emotion Recognition and Feedback

[0964] The user device provides an interface for inputting the information necessary to complete applications for subsidies and grants. At this time, the emotion engine uses facial recognition and voice analysis to recognize the user's emotional state in real time. The input data and the user's emotional state are sent to the server, which then analyzes them.

[0965] Automatic generation of application forms

[0966] The server retrieves relevant data from a database based on the input information and uses an AI algorithm to automatically generate an application form. Based on information from an emotion engine, the server displays supplementary information and advice if the user is feeling stressed or anxious. The generated application form is sent to the user's device, and if the user is relaxed, they are given the option to confirm the application contents through a short confirmation process.

[0967] Automatic generation of social impact assessments

[0968] When a user inputs information into their device to request a social impact assessment of a specific project, the emotion engine also recognizes the user's emotions during this process. The user's device then sends the input data and emotional state to the server, which then collects project-related data from open and private sources and uses AI algorithms to automatically generate a social impact assessment (SIA). The generated SIA report containing the assessment results is then sent to the user's device, and if the user's stress level is high, additional information is added suggesting a specific action plan.

[0969] Cloud-based data sharing

[0970] The server manages permission settings and data access for data sharing. When a user accesses the data, an emotion engine recognizes the user's emotional state and adjusts the way the data is displayed and supplementary information is provided. This functionality allows data visualization and presentation methods to be flexibly adapted to the user's needs.

[0971] The specific hardware and software used

[0972] Hardware: Smart glasses, PC, server

[0973] Software: Python, OpenCV (image processing library), EmotionEngine (emotion analysis module), SecurityAlertSystem (security system module)

[0974] Prompt Sentence Examples

[0975] As a concrete example, we will show an example of a prompt sentence to be input to the generative AI model used by the emotion engine.

[0976] Generate safety alerts based on climate data

[0977] Prompt: "If the user's facial expression indicates stress, suggest additional security alerts due to severe weather based on the last 30 minutes of weather data."

[0978] Input data:

[0979] Expression: "Stressed"

[0980] Weather: "Thunderstorm"

[0981] Sample output: "Current stress state detected. Thunderstorms expected. Additional sheltering and lock checks recommended."

[0982] This allows users to intuitively understand how protected they are in real time.

[0983] effect

[0984] This system integrates and analyzes open data from local governments and private sector data, and uses an emotion engine to research users' emotional states, enabling efficient preparation of subsidy and grant applications and social impact assessments. It also provides appropriate feedback in real time based on users' emotions in the field of security services, improving users' sense of security and convenience.

[0985] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0986] Step 1:

[0987] The server periodically calls the local government's open data API to obtain demographic, economic, and environmental data. The input is the open data API, and the output is the obtained data. This data is stored in the server's internal database. The server then obtains data on consumer behavior and economic activity from private data providers and stores that data in its internal database.

[0988] Step 2:

[0989] The server integrates the acquired open data and private data, cleaning up inconsistencies and missing values. The input is the acquired diverse data, and the output is an integrated, clean dataset. Data cleaning and consistency checks are performed to ensure the data is integrated accurately.

[0990] Step 3:

[0991] The server analyzes the integrated dataset using AI algorithms. The input is the integrated dataset and the output is the analysis results. The AI ​​algorithms extract patterns and trends from the data and provide useful insights relevant to grants and other funding.

[0992] Step 4:

[0993] The user inputs the information required to create a grant or subsidy application into the device. The input is information from the user, and the output is data stored locally on the device. At this time, the emotion engine recognizes the user's emotions in real time, which are also stored on the device.

[0994] Step 5:

[0995] The terminal transmits the information input by the user and the emotional state obtained from the emotion engine to the server. The input is the locally stored data and the emotional state, and the output is the data transmitted to the server.

[0996] Step 6:

[0997] The server retrieves relevant data from the database based on the information submitted by the user and uses an AI algorithm to automatically generate an application form. The input is user information, emotional state, and the integrated dataset, and the output is the generated application form. Information from the emotion engine is also included in the analysis, and supplementary advice is added if the user feels anxious.

[0998] Step 7:

[0999] The server sends the generated application to the terminal, which displays it to the user. The input is the generated application, and the output is the application displayed on the user's terminal. If the user is relaxed, a simple confirmation procedure and options are provided.

[1000] Step 8:

[1001] When a user inputs information to request a social impact assessment (SIA) into the terminal, the terminal transmits this information and the user's emotional state to the server. The input is the project information and the emotional state, and the output is the data transmitted to the server.

[1002] Step 9:

[1003] The server collects project-related data from open and private sources and uses AI algorithms to automatically generate a social impact assessment. The inputs are project information, sentiment state, and the integrated dataset, and the output is a social impact assessment report, which may also include feedback from the sentiment engine.

[1004] Step 10:

[1005] The server sends the generated evaluation report to the terminal, which displays it to the user. The input is the generated report, and the output is the report displayed on the user terminal. If the user's stress level is high, a specific action plan is proposed.

[1006] 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.

[1007] 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.

[1008] 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.

[1009] [Third embodiment]

[1010] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1011] 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.

[1012] 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).

[1013] 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.

[1014] 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.

[1015] 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).

[1016] 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.

[1017] 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.

[1018] 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.

[1019] 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.

[1020] 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.

[1021] 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."

[1022] The present invention relates to a system that combines open data from local governments with private data to automatically generate applications for subsidies and grants, and also to create detailed reports including social impact assessments. This system includes multiple processing steps that are mainly performed by servers, terminals, and users.

[1023] Utilizing local government open data and private data

[1024] Data Acquisition and Integration

[1025] 1. The server periodically calls the local government's open data API to obtain demographic, economic, and environmental data. The obtained data is stored in an internal database.

[1026] 2. The server also collects data on consumer behavior and economic activity from private data providers and stores it in an internal database. This data is then integrated for later data analysis.

[1027] Data Analysis and Report Generation

[1028] 1. The server applies AI algorithms to the integrated data to analyze the specific needs and challenges of the region. This analysis makes it possible to identify the most appropriate subsidies and grants.

[1029] 2. The server automatically generates a personalized report based on the analysis results, including details of the analysis, related grant information, and recommended actions.

[1030] User Interface

[1031] Automatic generation of application forms

[1032] 1. The user enters the information required to create a grant or subsidy application into the terminal, such as the project name, purpose, and estimated costs.

[1033] 2. The terminal sends the input data to the server.

[1034] 3. The server automatically generates an application form based on the input information, which meets the requirements for the grant or subsidy. This application form contains all the necessary data.

[1035] 4. The server sends the generated application form to the terminal, which displays it to the user. The user can check the application form and make corrections or additions as necessary.

[1036] Automated generation of Social Impact Assessments (SIAs)

[1037] 1. A user inputs information into a terminal to request a social impact assessment of a specific project, such as the project's goals, intended impact area, and target communities.

[1038] 2. The terminal sends the input data to the server.

[1039] 3. The server collects relevant open data and private data based on the input information.

[1040] 4. The server uses AI algorithms to automatically generate a Social Impact Assessment (SIA) for the project, which details the project's potential impact on the local community.

[1041] 5. The server sends the generated SIA report to the terminal, which displays it to the user, who can review the report and make corrections or additions as necessary.

[1042] Cloud-based data sharing

[1043] Permissions and Data Access

[1044] 1. Users set permissions for data sharing on their devices, which determines who can access what data.

[1045] 2. The terminal sends the setting information to the server.

[1046] 3. The server manages data access on the cloud platform based on the received permission settings.

[1047] 4. When the user makes a request to access the required data, the server checks the authorization and provides the appropriate data.

[1048] Open data API provision

[1049] Issuing API keys and providing data

[1050] 1. The user (developer) requests an API key from their device.

[1051] 2. The device sends a request to the server.

[1052] 3. The server generates an API key and sends it to the device.

[1053] 4. The user (developer) uses the acquired API key to make a request to access the open data from their device.

[1054] 5. The server provides the requested data and sends it back to the device.

[1055] Examples:

[1056] When an administrative official (user) from local city A applies for a subsidy for a new child-rearing support program, the server collects child-rearing-related data from the region and uses AI to automatically generate the optimal application form. The application form is displayed on the terminal, and the administrative official can check its contents and prepare to submit it.

[1057] When another municipality B starts a local park development project and needs to evaluate its social impact, the server analyzes the relevant data and automatically generates an SIA report, which can be displayed on the terminals to help stakeholders effectively implement the project.

[1058] As described above, this system provides a wide range of functions to promote the digitalization of local governments and support efficient, data-driven policymaking.

[1059] The processing flow will be explained below.

[1060] Data Acquisition and Integration

[1061] Data Acquisition Steps

[1062] Step 1:

[1063] The server periodically calls the local government's open data API to obtain demographic, economic, and environmental data.

[1064] Step 2:

[1065] The server obtains data on consumer behavior and economic activity from private data providers and stores it in an internal database.

[1066] Step 3:

[1067] The server checks for inconsistencies in the various data stored in the database and performs data cleaning as necessary.

[1068] Data Analysis and Report Generation

[1069] Data Analysis Steps

[1070] Step 4:

[1071] The server analyzes the integrated data using AI algorithms (such as regression analysis and clustering) to identify local needs and challenges.

[1072] Step 5:

[1073] The server generates graphs and charts to visualize the analysis results.

[1074] Report Generation Steps

[1075] Step 6:

[1076] The server creates a list of optimal subsidies and grants based on the analysis results and automatically generates a personalized report.

[1077] Step 7:

[1078] The server outputs the generated report in PDF or Excel format and sends it to the user's device.

[1079] User Interface

[1080] Automatic generation of application forms

[1081] Step 8:

[1082] The user inputs the information required to complete an application for a subsidy or grant into the terminal.

[1083] Step 9:

[1084] The terminal transmits the input information to the server.

[1085] Step 10:

[1086] The server retrieves relevant data from a database based on the input information.

[1087] Step 11:

[1088] The server automatically generates the application form using an AI algorithm.

[1089] Step 12:

[1090] The server sends the generated application to the user terminal, which displays it to the user.

[1091] Automated generation of Social Impact Assessments (SIAs)

[1092] Step 13:

[1093] The user inputs information into the terminal to request a social impact assessment of the project.

[1094] Step 14:

[1095] The terminal transmits the input information to the server.

[1096] Step 15:

[1097] The server collects data related to the project from open and private sources.

[1098] Step 16:

[1099] The server automatically generates a social impact assessment (SIA) using an AI algorithm.

[1100] Step 17:

[1101] The server sends an SIA report containing the generated evaluation results to the user's terminal, which displays it to the user.

[1102] Cloud-based data sharing

[1103] Permissions and Data Access

[1104] Step 18:

[1105] The user inputs information for setting the data sharing authority into the terminal.

[1106] Step 19:

[1107] The terminal transmits the setting information to the server.

[1108] Step 20:

[1109] The server manages data access on the cloud platform based on the received permission settings.

[1110] Step 21:

[1111] When a user requests data access, the server verifies the authorization and provides the appropriate data to the user terminal.

[1112] Open data API provision

[1113] Issuing API keys and providing data

[1114] Step 22:

[1115] The user (developer) enters information into the terminal to request the issuance of an API key.

[1116] Step 23:

[1117] The terminal transmits the request information to the server.

[1118] Step 24:

[1119] The server generates an API key and sends it to the user's device.

[1120] Step 25:

[1121] The user (developer) inputs a data request into the terminal using the API key.

[1122] Step 26:

[1123] The server retrieves the relevant data from the database and returns it to the user's terminal.

[1124] Through these steps, this system will promote the digitalization of local governments and support efficient, data-driven policymaking.

[1125] Example 1

[1126] 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."

[1127] Currently, many local governments and private organizations publish various types of data, but there are only a limited number of systems that can effectively link and utilize this data. In particular, there is a lack of systems that automate the creation of subsidy and grant applications and the associated social impact assessments (SIA). As a result, the creation of applications and evaluations takes a huge amount of time and effort, making it difficult to respond quickly. There is a need for a system that solves these problems.

[1128] 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.

[1129] In this invention, the server includes a means for acquiring public information from local governments and private information, a means for integrating the acquired information and cleaning inconsistencies and missing values, and a means for analyzing the integrated information using an AI model. This enables the efficient generation of optimal lists of subsidies and grants and the efficient performance of social impact assessments (SIAs) by integrating and analyzing data from local governments and private sectors. The server also includes a means for transmitting and displaying generated reports and application forms to a user's terminal, allowing users to quickly and easily create and review necessary documents.

[1130] "Public information from local governments" refers to statistical information, administrative data, economic data, environmental data, etc. that are made public by local governments.

[1131] "Private information" refers to data provided by companies and private organizations, and includes consumer behavior, economic activity, marketing data, etc.

[1132] "Data cleaning" is the process of filling in or removing inconsistencies and missing values ​​from acquired data.

[1133] An "AI model" is an algorithm or framework that uses machine learning and deep learning techniques to analyze data and discover specific patterns and trends.

[1134] "Subsidies and grants" are funds provided by governments, local governments, and private organizations for specific purposes or activities.

[1135] A "report" is a document that summarizes data analysis results, recommended actions, subsidy information, etc.

[1136] "User terminal" means the device or computer that a user uses to access the system, enter information, and view results.

[1137] An "application form" is an official document that contains the information required to receive a grant or assistance fund.

[1138] A "Social Impact Assessment (SIA)" is a process that involves detailed analysis and evaluation of the potential impacts of a particular project on local communities.

[1139] The present invention is a system that combines public information from local governments with private information to automatically generate applications for financial aid and grants, and also prepares detailed reports including social impact assessments (SIAs). The following details explain the procedures and configurations for specifically implementing the present invention.

[1140] Utilizing public information from local governments and private information

[1141] Data Acquisition and Integration

[1142] The server periodically calls the local government's public information API to obtain demographic, economic, and environmental data. The obtained data is stored in an internal database (e.g., PostgreSQL). The server also calls the API of private data providers (e.g., Google Analytics and other marketing data providers) to obtain data on consumer behavior and economic activity. This data is also stored in a database, and a process is performed to clean inconsistencies and missing values ​​(data cleansing).

[1143] Data Analysis and Report Generation

[1144] The server runs AI models (e.g., TensorFlow and Scikit-learn) on the integrated data to analyze the specific needs and challenges of the region. Based on this analysis, it generates a list of optimal grants and support programs and automatically generates a personalized report. The report includes details of the analysis, relevant support program information, and recommended actions. The generated report is then sent from the server to the device and can be accessed by the user.

[1145] User Interface

[1146] Automatic generation of application forms

[1147] The user inputs the information required to create an application for a grant or subsidy into the terminal. Specifically, the user inputs the project name, purpose, estimated costs, etc. The terminal then sends this input data to the server. The server then automatically generates an application form based on the input information that meets the requirements of the subsidy or grant. This application form is created based on a template and reflects all necessary information. The generated application form is then sent from the server to the terminal, where the user can review it and make corrections or additions.

[1148] Automated generation of Social Impact Assessments (SIAs)

[1149] Users input information into their device to request a social impact assessment for a specific project. Specifically, they input the project's goals, expected impact area, and target communities. The device then sends this input data to a server. The server then collects relevant public and private information based on the input information and uses an AI model to automatically generate a social impact assessment. This assessment details the project's potential impact on the local community. The generated SIA report is then sent from the server to the device, where the user can review, modify, or add to it.

[1150] Specific examples

[1151] Example 1: Grant application

[1152] When an administrative official (user) from local city A applies for a subsidy for a new child-rearing support program, the server collects child-rearing-related data from the region and uses AI to automatically generate the optimal application form. The application form is displayed on the user's device, and the administrative official can review its contents and prepare for submission.

[1153] Prompt Sentence Examples

[1154] Provide the information you need to create a grant application for a new child care program. Automatically generate the application using historical data to select the optimal format.

[1155] Project name: "City Childcare Support Program"

[1156] Objective: "Enhancing family support"

[1157] Estimated cost: 5 million yen

[1158] Example 2: Social Impact Assessment

[1159] When Municipality B starts a local park development project, the server analyzes the relevant data and automatically generates an SIA report, which can be displayed on the terminals to help stakeholders effectively implement the project.

[1160] Prompt Sentence Examples

[1161] Conduct a social impact assessment of a regional park development project. Provide information such as project goals, intended impact area, and target communities. Generate an SIA report using historical data and AI models.

[1162] Project name: "Citizens' Park Development Project"

[1163] Goal: "Expanding green space and revitalizing the community"

[1164] Affected area: "Residential area surrounding the park"

[1165] Target community: "Local residents"

[1166] The above is a specific embodiment of the present invention. This system collects information from various data sources and uses advanced AI models to analyze and automatically generate data, enabling effective subsidy applications and social impact assessments.

[1167] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1168] Step 1:

[1169] Data Acquisition

[1170] The server runs a scheduled job every day at 2:00 AM to call the local government's public information API, using the API endpoint and authentication information as input.

[1171] The server retrieves public information such as demographic, economic, environmental data, etc. The output is the retrieved dataset.

[1172] The server also calls the APIs of private data providers to obtain data on consumer behavior and economic activity. The API endpoints and authentication information are used as input, and the obtained dataset is output.

[1173] Step 2:

[1174] Data integration and cleaning

[1175] The server stores the retrieved public and private information in a database (e.g., PostgreSQL). It uses the retrieved dataset as input and the output is the stored database.

[1176] The server performs data cleaning, imputing or removing inconsistencies and missing values ​​(for example, using the mean or median for imputation). The input is the stored database, and the output is the cleaned data.

[1177] Step 3:

[1178] Data analysis

[1179] The server runs an AI model (e.g., TensorFlow, Scikit-learn) based on the cleaned data, using the cleaned data and the AI ​​model as input.

[1180] The server analyzes the specific needs and issues of the region, temporarily stores the analysis results in a table, and outputs the analysis result data.

[1181] Step 4:

[1182] Automatic report generation

[1183] The server automatically generates personalized reports based on the analysis results, taking the analysis result data and report template as input.

[1184] The server includes a report with details of the analysis, relevant funding information, and recommended actions. The output is the generated report.

[1185] Step 5:

[1186] Sending and viewing reports

[1187] The server sends the generated report to the terminal. The input is the generated report and the output is the report sent to the terminal.

[1188] The terminal displays the report to the user. The input is the report sent from the server and the output is the report displayed to the user.

[1189] Step 6:

[1190] Enter application information

[1191] Users input the information necessary to complete a grant or support application, such as the project name, purpose, and estimated costs, into the terminal.

[1192] The terminal sends input data to the server, and the output is the data sent to the server.

[1193] Step 7:

[1194] Automatic generation of application forms

[1195] The server receives the input information and automatically generates an application form that meets the requirements of the grant or subsidy. The input is the user's input information and the application form template.

[1196] The server sends the generated application form to the terminal and allows the user to confirm it. The output is the application form sent to the terminal.

[1197] Step 8:

[1198] Check and correct the application form

[1199] The user checks the application form displayed on the terminal and makes corrections or additions as necessary. The input is the application form displayed on the terminal.

[1200] The terminal sends the amended application form back to the server, and the output is the amended application form sent to the server.

[1201] Step 9:

[1202] Entering social impact assessment information

[1203] Users input information into the terminal to request a social impact assessment, such as the project's goals, the expected scope of impact, and the target community.

[1204] The terminal sends the input data to the server, and the output is the data sent to the server.

[1205] Step 10:

[1206] Automatic generation of social impact assessments

[1207] The server collects relevant data based on the input information and automatically generates a social impact assessment using an AI model. The input is user information and related data.

[1208] The server sends the generated social impact assessment report to the terminal for display by the user. The output is the assessment report sent to the terminal.

[1209] Step 11:

[1210] Checking and correcting SIA reports

[1211] The user checks the SIA report displayed on the terminal and makes corrections or additions as necessary. The input is the SIA report displayed on the terminal.

[1212] The terminal sends the modified SIA report back to the server, and the output is the modified assessment report sent to the server.

[1213] The above are the specific steps of the program processing of this system.

[1214] (Application example 1)

[1215] 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."

[1216] The conventional application process for subsidies and grants involves a lot of manual work and insufficient data integration and analysis, making it difficult to obtain subsidies efficiently and effectively. Furthermore, social impact assessments (SIAs) require specialized knowledge, making them difficult for local governments and shopping districts to easily perform. The present invention aims to solve these problems and provide a data-driven, efficient subsidy application and evaluation process.

[1217] 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.

[1218] In this invention, the server includes means for acquiring open data from local governments and private data, means for integrating the acquired data and cleaning inconsistencies and missing values, means for analyzing the integrated data using an AI algorithm, means for generating a list of optimal subsidies and grants and creating a report based on the analysis results, means for sending the generated report to a user terminal and displaying it, means for collecting data provided by each store in a physical store, means for supporting subsidy applications for each store in a shopping district or shopping mall, and means for conducting social impact assessments of shopping districts and shopping malls. This enables local governments and shopping district managers to efficiently and effectively apply for appropriate subsidies and conduct social impact assessments.

[1219] "Municipal open data" refers to information such as demographic, economic, and environmental data made public by local governments.

[1220] "Private data" refers to information on consumer behavior and economic activity provided by companies and private institutions.

[1221] "Data integration methods" refers to methods for combining data from different sources into a single data set, ensuring consistency and uniformity.

[1222] "Measures for cleaning inconsistencies and missing values" refers to methods for correcting or completing errors or gaps in a dataset.

[1223] "Means of analysis using AI algorithms" refers to methods that use artificial intelligence techniques to analyze integrated data and derive specific patterns and insights.

[1224] "Means for generating a list of grants and subsidies" refers to a method for creating a list of appropriate grants and subsidies based on the analysis results.

[1225] "Means for creating a report" refers to a method for organizing the analysis results and generating a report in an easy-to-understand format.

[1226] The "means for transmitting the generated report to the user terminal and displaying it" refers to a method for transmitting the automatically generated report to the user terminal and displaying it so that the user can check it.

[1227] "Means of collecting data provided by each store within a physical store" refers to methods of collecting information on sales and services from each store within a shopping district or shopping mall.

[1228] "Measures to support each store in a shopping district or shopping mall in applying for subsidies" refers to methods to support each store in applying for subsidies effectively.

[1229] "Methods for conducting social impact assessments of shopping districts and shopping malls" refers to methods for assessing the impact that shopping districts and shopping malls have on local communities and compiling the results into a report.

[1230] MODE FOR CARRYING OUT THE INVENTION

[1231] This invention relates to a system that enables each store in a brick-and-mortar store to efficiently apply for subsidies and conduct social impact assessments (SIAs). This system is realized by combining a server and smart glasses or mobile devices as user terminals.

[1232] System Overview

[1233] The system consists of the following main components:

[1234] 1. Server:

[1235] Hardware: High-performance server

[1236] Software: MySQL (database management system), requests (API call library), pandas (data analysis library), Scikit-learn (AI analysis library), TensorFlow (AI algorithms)

[1237] The server periodically acquires open data from local governments and private data, and integrates and cleans this data. It then analyzes the integrated data using AI algorithms to generate optimal subsidy and grant lists and prepare reports. It also collects data from each store within the physical store, and uses this data to support subsidy applications and conduct social impact assessments (SIA).

[1238] 2. User device (smart glasses or mobile device):

[1239] Hardware: Smart glasses (VR device), smartphone

[1240] Software: Form generation tool (Flask), LaTeX (report generation tool), AWS (cloud platform), OAuth (access control library)

[1241] Users can input the information required for grant applications using smart glasses or a mobile device. The input information is sent to a server, where it is analyzed by AI and the appropriate application form is automatically generated. Users can also input information to request a social impact assessment of a project, and the results of the AI ​​analysis can be visually confirmed as a report.

[1242] Specific examples

[1243] For example, each store in a shopping district can use smart glasses to input its own sales data and service information. Based on this, the server automatically generates an optimal subsidy application form and displays it on the smart glasses. The system can also conduct a social impact assessment (SIA) on the impact the entire shopping district has on the local community and generate a detailed report. Shopping district managers and store owners can use these reports to develop effective management strategies.

[1244] Prompt Sentence Examples

[1245] We would like to use smart glasses to streamline the process of applying for subsidies for the entire shopping district. Please develop a system that automatically generates optimal subsidy application forms based on the sales data and services offered by each store in the shopping district. Also, please automatically generate social impact assessments of shopping district projects and provide the results as a report.

[1246] In the above-described manner, the present invention makes it possible to efficiently and effectively carry out subsidy applications and social impact assessments within physical stores.

[1247] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1248] Step 1:

[1249] The server periodically accesses the local government's open data API to obtain demographic, economic, and environmental data. The data is then stored in an internal database. This data includes the local population structure and economic situation.

[1250] Step 2:

[1251] The server obtains data on consumer behavior and economic activity from private data providers. This data is also stored in the internal database. The private data includes sales data for each store and customer purchasing information.

[1252] Step 3:

[1253] The server integrates the acquired municipal and private data and cleans it up for inconsistencies and missing values. Data cleaning includes correcting inconsistent data and filling in missing values.

[1254] Step 4:

[1255] The server applies AI algorithms (such as Scikit-learn and TensorFlow) to the integrated data to analyze the specific needs and challenges of the region. This analysis makes it possible to identify optimal subsidies and grants. The input data includes integrated open data and private data, and the analysis results are obtained as the output.

[1256] Step 5:

[1257] The server automatically generates a personalized report based on the analysis results, including details of the analysis, related grant information, and recommended actions. The generated report uses LaTeX formatting.

[1258] Step 6:

[1259] Users use smart glasses or a mobile device to input information required for grant applications, such as the project name, purpose, and estimated costs. The input data is then sent from the device to the server.

[1260] Step 7:

[1261] The server automatically generates an application form based on the input data, meeting the requirements for the subsidy or grant. The application form reflects the information entered by the user and recommended subsidy information based on the analysis results. The generated application form is sent to the terminal.

[1262] Step 8:

[1263] The terminal displays the generated application form to the user, who can then check it and make corrections or additions as necessary.

[1264] Step 9:

[1265] To request a Social Impact Assessment (SIA), users input project information, such as the project's goals, the intended impact area, and the target community. The input data is sent from the device to the server.

[1266] Step 10:

[1267] The server collects and analyzes relevant open data and private data based on project information provided by users, and uses AI algorithms to automatically generate a social impact assessment (SIA) for the project.

[1268] Step 11:

[1269] The server then sends the generated SIA report to the device, which details the project's potential impact on the local community.

[1270] Step 12:

[1271] The terminal displays the generated SIA report to the user, who can then review the report and make corrections or additions as necessary.

[1272] 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.

[1273] This invention adds an emotion engine that recognizes user emotions to a system that combines open data from local governments and private data, enabling more effective preparation of applications for subsidies and grants and social impact assessments. This system includes a server, a terminal, an emotion engine, and multiple processing steps that are user-driven.

[1274] Utilizing local government open data and private data

[1275] Data Acquisition and Integration

[1276] 1. The server periodically calls the local government's open data API to obtain demographic, economic, and environmental data, which is then stored in an internal database.

[1277] 2. The server also acquires data on consumer behavior and economic activity from private data providers and stores it in an internal database. This data is then integrated for later data analysis.

[1278] User Interface and Emotion Engine

[1279] Automatic generation of application forms

[1280] 1. The user enters the information needed to complete a grant or subsidy application into the device. The emotion engine uses facial recognition and voice analysis to recognize the user's emotional state in real time.

[1281] 2. The device sends the input data and the user's emotional state to the server.

[1282] 3. The server retrieves relevant data from the database based on the input information and automatically generates an application form using an AI algorithm. Based on information from the emotion engine, it displays supplementary information and advice if the user is feeling stressed or anxious.

[1283] 4. The server sends the generated application to the terminal, which displays it to the user. If the user is relaxed, they are given the option to confirm the application contents with a short confirmation procedure.

[1284] Automated generation of Social Impact Assessments (SIAs)

[1285] 1. A user inputs information into a terminal to request a social impact assessment of a specific project. The emotion engine also recognizes the user's emotions during this process.

[1286] 2. The device sends the input data and emotional state to the server.

[1287] 3. The server collects project-related data from open and private sources, automatically generates a Social Impact Assessment (SIA) using AI algorithms, and provides feedback based on an emotion engine.

[1288] 4. The server sends the generated SIA report containing the evaluation results to the device, which displays it to the user. If the user's stress level is high, the device adds information suggesting a specific action plan.

[1289] Cloud-based data sharing and emotion engine

[1290] Permissions and Data Access

[1291] 1. The user inputs information into the device to set up permissions for data sharing. The emotion engine recognizes the user's emotional state during this process.

[1292] 2. The device sends the setting information and emotional state to the server.

[1293] 3. The server manages data access on the cloud platform based on the received permission settings.

[1294] 4. When a user requests data access, the server verifies the user's authorization and provides the appropriate data to the user's device. The server also adjusts the data display method and supplementary information according to the user's emotional state.

[1295] Open data API provision and emotion engine

[1296] Issuing API keys and providing data

[1297] 1. The user (developer) inputs information to request the issuance of an API key into the device. The emotion engine also recognizes the emotional state during this process.

[1298] 2. The device sends the request information and emotional state to the server.

[1299] 3. The server generates an API key and sends it to the user's device. Emotional state may affect how applicable information is provided.

[1300] 4. The user (developer) enters a data request into the device using the API key, and the server retrieves the relevant data from the database and returns it to the user's device.

[1301] Examples:

[1302] When a local city A's administrative official (user) applies for a subsidy for a new child-rearing support program, the server collects data related to child-rearing in the area and uses AI to automatically generate the optimal application form. If the emotion engine detects a state of stress, the device provides additional information and advice, and adjusts the platform for reviewing the final application form taking into account the user's state of relaxation.

[1303] When another local government B starts a local park development project, it uses an emotion engine to recognize the emotional state of the project manager and automatically generates a social impact assessment (SIA) through AI analysis. When displaying the assessment results, the device provides feedback according to the user's emotions.

[1304] In this way, by incorporating an emotion engine, the present invention aims to promote the digitalization of local governments, improve user experience, and support efficient, data-driven policymaking.

[1305] The processing flow will be explained below.

[1306] Specific processing steps for creating an application form incorporating an emotion engine

[1307] Data Acquisition and Integration

[1308] Step 1:

[1309] The server periodically calls the local government's open data API to obtain demographic, economic, and environmental data.

[1310] Step 2:

[1311] The server obtains data on consumer behavior and economic activity from private data providers and stores it in an internal database.

[1312] Step 3:

[1313] The server checks for inconsistencies in the various data stored in the database and performs data cleaning as necessary.

[1314] Application Form Creation Process

[1315] Step 4:

[1316] Users input the information necessary to complete a grant or subsidy application into the device, and the emotion engine analyzes the user's facial expressions and tone of voice in real time to recognize their emotional state.

[1317] Step 5:

[1318] The terminal transmits the input data and emotional state to the server.

[1319] Step 6:

[1320] The server retrieves relevant open and private data from a database based on the input information. If the emotion engine determines that the user's stress level is high, it provides supplementary information and input assistance.

[1321] Step 7:

[1322] The server uses AI algorithms to analyze the acquired data and automatically generate the optimal application form, including supplementary information and confirmation messages that take the user's emotional state into account.

[1323] Step 8:

[1324] The server sends the generated application form to the terminal, which displays it to the user. The emotion engine checks the user's stress level and displays an appropriate feedback message.

[1325] Automated generation process for Social Impact Assessments (SIA)

[1326] Step 9:

[1327] Users input information into the terminal to request a social impact assessment of their project, and the emotion engine monitors the user's psychological state in real time.

[1328] Step 10:

[1329] The terminal transmits the input data and emotional state to the server.

[1330] Step 11:

[1331] The server collects data related to the project from open and private sources. If the emotion engine detects negative emotions, it displays supplemental information offering advice to the user on how to relax.

[1332] Step 12:

[1333] The server uses an AI algorithm to automatically generate a social impact assessment (SIA), adding explanatory notes to the assessment based on feedback from the emotion engine.

[1334] Step 13:

[1335] The server sends the generated SIA report to the terminal, which displays it to the user. The emotion engine displays a support message to help the user smoothly receive and understand the evaluation results.

[1336] Cloud-based data sharing process

[1337] Step 14:

[1338] The user inputs permission to share data into the device, and the emotion engine monitors the user's stress level and displays appropriate feedback messages.

[1339] Step 15:

[1340] The terminal transmits the authority setting information to the server.

[1341] Step 16:

[1342] The server manages data access on the cloud platform based on the received permission settings.

[1343] Step 17:

[1344] When a user requests data access, the server verifies the user's authorization and provides the appropriate data to the user's device. The server adjusts the display format of the data and supplementary information according to the user's emotional state.

[1345] Open data API provision process

[1346] Step 18:

[1347] The user (developer) inputs information to request the issuance of an API key into the device. The emotion engine also recognizes the user's emotional state during this process.

[1348] Step 19:

[1349] The terminal transmits the request information and the emotional state to the server.

[1350] Step 20:

[1351] The server generates an API key and sends it to the device, along with supplementary explanations that take into account the user's emotional state.

[1352] Step 21:

[1353] The user (developer) inputs a data request into the terminal using the API key.

[1354] Step 22:

[1355] The server retrieves the relevant data from the database and sends it back to the user's device, where the emotion engine provides feedback according to the emotion.

[1356] Through these steps, a system incorporating an emotion engine will efficiently promote digitalization in local governments, data-driven policy making, and improve user experience.

[1357] Example 2

[1358] 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."

[1359] The traditional process for applying for local government subsidies and grants, as well as for social impact assessments, required a lot of time and effort and was inefficient. Furthermore, there was a lack of ingenuity to reduce the stress and anxiety users felt while applying and creating assessments. This resulted in a poor user experience and sometimes led to processes that did not proceed smoothly. Furthermore, there was a need for flexible responses, such as cleaning data inconsistencies and missing values, and emotion recognition.

[1360] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1361] In this invention, the server includes: means for acquiring open data from local governments and private data; means for integrating the acquired data and cleaning inconsistencies and missing values; means for analyzing the integrated data using an AI algorithm; means for generating a list of optimal subsidies and grants and creating a report based on the analysis results; means for sending the generated report to a user terminal and displaying it; means for recognizing the user's emotional state; and means for displaying supplementary information and advice if the user is feeling stressed or anxious. This improves the user experience and enables efficient, data-driven policy planning and application processes. It also enables flexible responses based on the user's emotional state, reducing stress and anxiety.

[1362] "Municipal open data" refers to public data such as demographic, economic, and environmental data made public by local governments.

[1363] "Private data" refers to data on consumer behavior, economic activity, marketing research, etc. provided by commercial companies and non-profit organizations.

[1364] "Data integration" is the process of bringing together data from different sources into a single unified format.

[1365] "Inconsistent data" is data that is inconsistent and contradictory and requires correction before it can be used in data analysis.

[1366] "Missing value cleaning" is the process of properly handling missing values ​​in a dataset to improve data quality.

[1367] An "AI algorithm" is a series of processes and methods that use artificial intelligence technology to analyze data, make predictions, and perform optimization.

[1368] "Grants and grants" are funds provided by governments or local governments to support specific projects or activities.

[1369] "Report generation" refers to the automatic creation of reports tailored to specific purposes based on the analysis results.

[1370] A "user terminal" is a device operated by a user, such as a personal computer, smartphone, or tablet.

[1371] An "emotional state" is the emotional state a user is feeling at a particular moment, and is detected through facial recognition and voice analysis.

[1372] "Supporting information and advice" is any additional information or suggestions that can help users navigate the application or evaluation process.

[1373] "Automatic application generation" refers to the automatic creation of grant and subsidy applications based on user-provided information and related data.

[1374] A "social impact assessment" is the process of assessing the impact that a particular project will have on society or a community.

[1375] An "action plan" is a specific plan or proposal to be implemented to achieve a specific goal.

[1376] The present invention relates to a system that combines open data from local governments with private data and recognizes user emotions. The system includes a server, a terminal, an emotion engine, and multiple processing steps that are user-driven.

[1377] Data Acquisition and Integration

[1378] The server uses the Autonomous Data acquisition module to retrieve demographic, economic, and environmental data from the local government's open data API. This is done using the Python requests library. The retrieved data is stored in an internal database such as MySQL. The server also retrieves data from private data providers and stores this in the internal database. For this purpose, the Pandas library is used to integrate, clean, and resolve inconsistencies in the data.

[1379] Emotion engine and application generation

[1380] The user inputs the information needed to complete a grant or subsidy application into the device. The endpoint uses Azure Cognitive Services or a similar emotion engine to recognize emotions in real time through facial recognition and voice analysis. The device then transmits the input data and emotional state to a server.

[1381] The server retrieves relevant data from the database and automatically generates an application form using an AI algorithm (e.g., a natural language processing model) powered by TensorFlow. It also provides supplementary information and advice depending on the user's emotional state.

[1382] Generating a Social Impact Assessment (SIA)

[1383] Users input information about a specific project into the device. The device then uses an emotion engine to recognize the user's emotional state. The device then sends the input data and emotional state to a server. The server then collects relevant data from open and private sources and automatically generates a social impact assessment (SIA) using a Python AI algorithm. The generated report is then displayed to the user, providing feedback and an action plan based on the user's emotions.

[1384] Cloud-based data sharing

[1385] The user inputs information into the device that sets permissions for data sharing. The emotion engine recognizes the user's emotional state and sends that information to the server. The server manages data access permissions on a cloud platform and provides data according to the user's request.

[1386] Open data API provision

[1387] A user as a developer inputs information to request the issuance of an API key into the device, and the emotional state is recognized by the emotion engine. The device sends this information to the server, which generates and returns an API key. The user makes a data request using the API key, and the server provides the data.

[1388] Prompt Sentence Examples

[1389] For example, consider the following prompt:

[1390] "Auto-generate a child care grant application. Enter your project summary, goals, and required budget."

[1391] "Conduct a social impact assessment of this project. Enter the project objectives, target area, and stakeholders."

[1392] "Give specific users access to specific data."

[1393] This will enable the invention to promote the digitalization of local governments and improve user experience. Furthermore, by incorporating an emotion engine, it will reduce stress and anxiety felt by users and realize efficient data-driven policy planning and application processes.

[1394] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1395] Step 1:

[1396] The server periodically calls the local government's open data API to obtain demographic, economic, and environmental data. The input is the API endpoint, and the output is JSON-formatted data. Specifically, it uses Python's requests library to obtain data using response = requests.get('https: / / api.example.com / data'). This data is stored in an internal database (such as MySQL). It is written to the database using session.add(data_object) and session.commit().

[1397] Step 2:

[1398] The server also retrieves data from private data providers and stores it in its internal database. The input is a request including an activated API key, and the output is JSON-formatted data. For example, set authentication information as headers = {'Authorization': 'Bearer YOUR_API_KEY'} and retrieve data as follows: response = requests.get('https: / / privateapi.example.com / data', headers=headers). This data is also converted to a data frame using the Pandas library and stored in the database.

[1399] Step 3:

[1400] The server combines the acquired open data and private data. The input is multiple datasets, and the output is a unified dataset. Specifically, the Pandas library is used to combine data frames and concatenate the data using combined_data = pd.concat([open_data, private_data], axis=0). Furthermore, operations such as combined_data.dropna() and combined_data.fillna(method='ffill') are performed to clean inconsistencies and missing values. The combined dataset is then saved back to the database.

[1401] Step 4:

[1402] A user enters information into a device to complete a grant or subsidy application. The input is information provided through a web form or application fields, and the output is JSON-formatted data sent to a server. Specifically, the data is collected using an HTML form, validated in real time with JavaScript, and then submitted using fetch('https: / / server.example.com / submit', {method: 'POST', body: JSON.stringify(formData)}).

[1403] Step 5:

[1404] The device recognizes the user's input data and emotional state. The input is data including the user's facial recognition and voice analysis, and the output is JSON data containing emotional state information. The emotion engine uses Azure Cognitive Services and uses the camera and microphone with navigator.mediaDevices.getUserMedia({ video: true, audio: true}). The data obtained from this is sent to the API to obtain the emotional state.

[1405] Step 6:

[1406] The device sends input data and emotional state to the server. The input is JSON format data containing user information and emotional data, and the output is data sent to the server. Specifically, data is sent as follows: fetch('https: / / server.example.com / emotion', {method: 'POST', body: JSON.stringify(emotionData)}).

[1407] Step 7:

[1408] The server retrieves relevant data from the database based on the input information and uses an AI algorithm to automatically generate an application form. The input is user information, emotion data, and an integrated dataset, and the output is an automatically generated application form. Specifically, it uses a TensorFlow model to automatically generate a draft application form as follows: model.predict(input_data).

[1409] Step 8:

[1410] The server sends the generated application form to the terminal, which displays it to the user. The input is the automatically generated application form data, and the output is the information displayed on the user's terminal. Specifically, the DOM is manipulated as follows: document.getElementById('generated_document').innerHTML = generated_content, and the generated content is inserted into the HTML element.

[1411] Step 9:

[1412] Users input information into their device to request a social impact assessment of a specific project. The input is detailed information about the project, and the output is JSON-formatted data that is sent to the server. Specifically, similar to the application creation process described above, data is collected using a web form and sent to the server.

[1413] Step 10:

[1414] The device sends input data and the user's emotional state to the server. The input is project information and emotional data from the user, and the output is data sent to the server. Specifically, data is sent as follows: fetch('https: / / server.example.com / project', {method: 'POST', body: JSON.stringify(projectData)}).

[1415] Step 11:

[1416] The server collects data related to the project and automatically generates a Social Impact Assessment (SIA) using an AI algorithm. The input is user information, sentiment data, and an integrated dataset, and the output is an automatically generated SIA report. Specifically, the model is used to generate the assessment: siaevaluation_model.evaluate(project_data).

[1417] Step 12:

[1418] The server sends the generated SIA report to the terminal, which displays it to the user. The input is the automatically generated SIA report data, and the output is the information displayed on the user's terminal. Specifically, the DOM is manipulated as follows: document.getElementById('sia_report').innerHTML = sia_content to insert the generated content into the HTML element.

[1419] Step 13:

[1420] The user inputs information into the device to set data sharing permissions. The input is detailed information about data sharing, and the output is JSON-formatted data that is sent to the server. Specifically, the setting information is entered into a form and sent to the server.

[1421] Step 14:

[1422] The device sends setting information and emotional state to the server. The input is setting information and emotional data, and the output is data sent to the server. Specifically, data is sent as follows: fetch('https: / / server.example.com / settings', {method: 'POST', body: JSON.stringify(settingsData)}).

[1423] Step 15:

[1424] The server uses AWS IAM and other cloud services to set sharing permissions and manage data access. The input is configuration information and emotion data, and the output is the completion of permission settings. Specifically, permission settings are performed using iam.createUser({UserName: 'username'}) and iam.attachUserPolicy.

[1425] Step 16:

[1426] When a user requests data access, the server checks the authorization and provides the appropriate data to the user's device. The input is the data access request, and the output is the requested data. Specifically, the data is retrieved using an AJAX request and displayed through the aforementioned DOM manipulation.

[1427] Step 17:

[1428] The user (developer) enters information into the terminal to request the issuance of an API key. The input is detailed information about the API key request, and the output is JSON format data that is sent to the server. Specifically, the user fills in the form and sends it as follows: fetch('https: / / server.example.com / apikey', {method: 'POST', body: JSON.stringify(apikeyRequest)}).

[1429] Step 18:

[1430] The device sends request information and emotional state to the server. The input is the request information and emotional data, and the output is data transmission to the server. Specifically, it sends an API request as described above.

[1431] Step 19:

[1432] The server generates an API key and sends it to the user's device. The input is the request information and emotional state, and the output is the generated API key. Specifically, it runs a script that generates an API key and sends it as fetch('https: / / server.example.com / apikey', {method: 'POST', body: JSON.stringify(apikeyResponse)}).

[1433] Step 20:

[1434] The user (developer) uses an API key to input a data request into their device, and the server retrieves the relevant data from the database and sends it back to the user's device. The input is the API key and data request, and the output is the requested data. Specifically, an AJAX request is used to retrieve the data and perform the appropriate processing.

[1435] (Application example 2)

[1436] 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."

[1437] Conventional systems that combine open data from local governments with private data can integrate and analyze data, but they are unable to provide appropriate feedback based on the user's emotional state, and therefore do not adequately improve the user experience or support efficient work.Furthermore, in the security field, there was no system that could recognize user emotions in real time and take appropriate action based on that, making it difficult to fully ensure users' sense of security.

[1438] 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 acquiring open data from local governments and private data, means for integrating the acquired data and cleaning inconsistencies and missing values, means for analyzing the integrated data using an AI algorithm, means for generating a list of optimal subsidies and grants and creating a report based on the analysis results, means for sending the generated report to a user terminal and displaying it, and means for using an emotion engine to recognize the user's emotions and provide corresponding feedback. This makes it possible to provide appropriate feedback according to the user's emotional state, thereby improving work efficiency and security.

[1439] "Municipal open data" refers to diverse datasets on the economy, environment, population, etc. provided by public institutions, and is generally accessible through APIs.

[1440] "Private data" refers to data obtained from private organizations such as companies and non-profit organizations, and includes information on consumer behavior and economic activity.

[1441] "Integration" is the process of combining data from multiple different data sources into a single dataset, including the process of correcting inconsistencies and missing values ​​to ensure consistency.

[1442] "AI algorithm" is a general term for mathematical models and methods that use artificial intelligence technology to analyze data and extract patterns and insights.

[1443] The "emotion engine" is a system that recognizes the user's emotional state from their facial expressions and voice and analyzes their emotions in real time.

[1444] A "security alarm system" is a system that detects security risks based on specified conditions and issues an alarm, and in this case, it also analyzes emotional state data.

[1445] A "user terminal" is a device that allows a user to access the system, input information, and receive analysis results and feedback, and includes smartphones, PCs, smart glasses, etc.

[1446] "Subsidies and grants" are financial assistance provided by the government or local governments for specific purposes, and are funds that are granted upon application.

[1447] A "social impact assessment" is the process of assessing the social impact of a particular project or policy, and in this case it is carried out automatically using AI algorithms.

[1448] "Real-time" refers to the extremely short time between data acquisition and the provision of analysis results, and the processing being carried out in accordance with real-time.

[1449] These definitions clarify each element of the invention.

[1450] System Overview

[1451] This invention is a system that realizes more effective subsidy and grant application preparation and social impact assessment by combining open data from local governments with private data and adding an emotion engine that recognizes user emotions. This system includes multiple processing steps, mainly consisting of a server, user terminals, and the emotion engine.

[1452] Data Acquisition and Integration

[1453] The server periodically accesses the local government's open data API to obtain demographic, economic, and environmental data. The obtained data is stored in an internal database. The server also obtains data on consumer behavior and economic activity from private data providers and stores this data in an internal database. This data is then integrated for later data analysis.

[1454] Emotion Recognition and Feedback

[1455] The user device provides an interface for inputting the information necessary to complete applications for subsidies and grants. At this time, the emotion engine uses facial recognition and voice analysis to recognize the user's emotional state in real time. The input data and the user's emotional state are sent to the server, which then analyzes them.

[1456] Automatic generation of application forms

[1457] The server retrieves relevant data from a database based on the input information and uses an AI algorithm to automatically generate an application form. Based on information from an emotion engine, the server displays supplementary information and advice if the user is feeling stressed or anxious. The generated application form is sent to the user's device, and if the user is relaxed, they are given the option to confirm the application contents through a short confirmation process.

[1458] Automatic generation of social impact assessments

[1459] When a user inputs information into their device to request a social impact assessment of a specific project, the emotion engine also recognizes the user's emotions during this process. The user's device then sends the input data and emotional state to the server, which then collects project-related data from open and private sources and uses AI algorithms to automatically generate a social impact assessment (SIA). The generated SIA report containing the assessment results is then sent to the user's device, and if the user's stress level is high, additional information is added suggesting a specific action plan.

[1460] Cloud-based data sharing

[1461] The server manages permission settings and data access for data sharing. When a user accesses the data, an emotion engine recognizes the user's emotional state and adjusts the way the data is displayed and supplementary information is provided. This functionality allows data visualization and presentation methods to be flexibly adapted to the user's needs.

[1462] The specific hardware and software used

[1463] Hardware: Smart glasses, PC, server

[1464] Software: Python, OpenCV (image processing library), EmotionEngine (emotion analysis module), SecurityAlertSystem (security system module)

[1465] Prompt Sentence Examples

[1466] As a concrete example, we will show an example of a prompt sentence to be input to the generative AI model used by the emotion engine.

[1467] Generate safety alerts based on climate data

[1468] Prompt: "If the user's facial expression indicates stress, suggest additional security alerts due to severe weather based on the last 30 minutes of weather data."

[1469] Input data:

[1470] Expression: "Stressed"

[1471] Weather: "Thunderstorm"

[1472] Sample output: "Current stress state detected. Thunderstorms expected. Additional sheltering and lock checks recommended."

[1473] This allows users to intuitively understand how protected they are in real time.

[1474] effect

[1475] This system integrates and analyzes open data from local governments and private sector data, and uses an emotion engine to research users' emotional states, enabling efficient preparation of subsidy and grant applications and social impact assessments. It also provides appropriate feedback in real time based on users' emotions in the field of security services, improving users' sense of security and convenience.

[1476] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1477] Step 1:

[1478] The server periodically calls the local government's open data API to obtain demographic, economic, and environmental data. The input is the open data API, and the output is the obtained data. This data is stored in the server's internal database. The server then obtains data on consumer behavior and economic activity from private data providers and stores that data in its internal database.

[1479] Step 2:

[1480] The server integrates the acquired open data and private data, cleaning up inconsistencies and missing values. The input is the acquired diverse data, and the output is an integrated, clean dataset. Data cleaning and consistency checks are performed to ensure the data is integrated accurately.

[1481] Step 3:

[1482] The server analyzes the integrated dataset using AI algorithms. The input is the integrated dataset and the output is the analysis results. The AI ​​algorithms extract patterns and trends from the data and provide useful insights relevant to grants and other funding.

[1483] Step 4:

[1484] The user inputs the information required to create a grant or subsidy application into the device. The input is information from the user, and the output is data stored locally on the device. At this time, the emotion engine recognizes the user's emotions in real time, which are also stored on the device.

[1485] Step 5:

[1486] The terminal transmits the information input by the user and the emotional state obtained from the emotion engine to the server. The input is the locally stored data and the emotional state, and the output is the data transmitted to the server.

[1487] Step 6:

[1488] The server retrieves relevant data from the database based on the information submitted by the user and uses an AI algorithm to automatically generate an application form. The input is user information, emotional state, and the integrated dataset, and the output is the generated application form. Information from the emotion engine is also included in the analysis, and supplementary advice is added if the user feels anxious.

[1489] Step 7:

[1490] The server sends the generated application to the terminal, which displays it to the user. The input is the generated application, and the output is the application displayed on the user's terminal. If the user is relaxed, a simple confirmation procedure and options are provided.

[1491] Step 8:

[1492] When a user inputs information to request a social impact assessment (SIA) into the terminal, the terminal transmits this information and the user's emotional state to the server. The input is the project information and the emotional state, and the output is the data transmitted to the server.

[1493] Step 9:

[1494] The server collects project-related data from open and private sources and uses AI algorithms to automatically generate a social impact assessment. The inputs are project information, sentiment state, and the integrated dataset, and the output is a social impact assessment report, which may also include feedback from the sentiment engine.

[1495] Step 10:

[1496] The server sends the generated evaluation report to the terminal, which displays it to the user. The input is the generated report, and the output is the report displayed on the user terminal. If the user's stress level is high, a specific action plan is proposed.

[1497] 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.

[1498] 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.

[1499] 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.

[1500] [Fourth embodiment]

[1501] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1502] 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.

[1503] 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).

[1504] 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.

[1505] 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.

[1506] 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).

[1507] 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.

[1508] 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.

[1509] 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.

[1510] 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.

[1511] 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.

[1512] 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.

[1513] 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."

[1514] The present invention relates to a system that combines open data from local governments with private data to automatically generate applications for subsidies and grants, and also to create detailed reports including social impact assessments. This system includes multiple processing steps that are mainly performed by servers, terminals, and users.

[1515] Utilizing local government open data and private data

[1516] Data Acquisition and Integration

[1517] 1. The server periodically calls the local government's open data API to obtain demographic, economic, and environmental data. The obtained data is stored in an internal database.

[1518] 2. The server also collects data on consumer behavior and economic activity from private data providers and stores it in an internal database. This data is then integrated for later data analysis.

[1519] Data Analysis and Report Generation

[1520] 1. The server applies AI algorithms to the integrated data to analyze the specific needs and challenges of the region. This analysis makes it possible to identify the most appropriate subsidies and grants.

[1521] 2. The server automatically generates a personalized report based on the analysis results, including details of the analysis, related grant information, and recommended actions.

[1522] User Interface

[1523] Automatic generation of application forms

[1524] 1. The user enters the information required to create a grant or subsidy application into the terminal, such as the project name, purpose, and estimated costs.

[1525] 2. The terminal sends the input data to the server.

[1526] 3. The server automatically generates an application form based on the input information, which meets the requirements for the grant or subsidy. This application form contains all the necessary data.

[1527] 4. The server sends the generated application form to the terminal, which displays it to the user. The user can check the application form and make corrections or additions as necessary.

[1528] Automated generation of Social Impact Assessments (SIAs)

[1529] 1. A user inputs information into a terminal to request a social impact assessment of a specific project, such as the project's goals, intended impact area, and target communities.

[1530] 2. The terminal sends the input data to the server.

[1531] 3. The server collects relevant open data and private data based on the input information.

[1532] 4. The server uses AI algorithms to automatically generate a Social Impact Assessment (SIA) for the project, which details the project's potential impact on the local community.

[1533] 5. The server sends the generated SIA report to the terminal, which displays it to the user, who can review the report and make corrections or additions as necessary.

[1534] Cloud-based data sharing

[1535] Permissions and Data Access

[1536] 1. Users set permissions for data sharing on their devices, which determines who can access what data.

[1537] 2. The terminal sends the setting information to the server.

[1538] 3. The server manages data access on the cloud platform based on the received permission settings.

[1539] 4. When the user makes a request to access the required data, the server checks the authorization and provides the appropriate data.

[1540] Open data API provision

[1541] Issuing API keys and providing data

[1542] 1. The user (developer) requests an API key from their device.

[1543] 2. The device sends a request to the server.

[1544] 3. The server generates an API key and sends it to the device.

[1545] 4. The user (developer) uses the acquired API key to make a request to access the open data from their device.

[1546] 5. The server provides the requested data and sends it back to the device.

[1547] Examples:

[1548] When an administrative official (user) from local city A applies for a subsidy for a new child-rearing support program, the server collects child-rearing-related data from the region and uses AI to automatically generate the optimal application form. The application form is displayed on the terminal, and the administrative official can check its contents and prepare to submit it.

[1549] When another municipality B starts a local park development project and needs to evaluate its social impact, the server analyzes the relevant data and automatically generates an SIA report, which can be displayed on the terminals to help stakeholders effectively implement the project.

[1550] As described above, this system provides a wide range of functions to promote the digitalization of local governments and support efficient, data-driven policymaking.

[1551] The processing flow will be explained below.

[1552] Data Acquisition and Integration

[1553] Data Acquisition Steps

[1554] Step 1:

[1555] The server periodically calls the local government's open data API to obtain demographic, economic, and environmental data.

[1556] Step 2:

[1557] The server obtains data on consumer behavior and economic activity from private data providers and stores it in an internal database.

[1558] Step 3:

[1559] The server checks for inconsistencies in the various data stored in the database and performs data cleaning as necessary.

[1560] Data Analysis and Report Generation

[1561] Data Analysis Steps

[1562] Step 4:

[1563] The server analyzes the integrated data using AI algorithms (such as regression analysis and clustering) to identify local needs and challenges.

[1564] Step 5:

[1565] The server generates graphs and charts to visualize the analysis results.

[1566] Report Generation Steps

[1567] Step 6:

[1568] The server creates a list of optimal subsidies and grants based on the analysis results and automatically generates a personalized report.

[1569] Step 7:

[1570] The server outputs the generated report in PDF or Excel format and sends it to the user's device.

[1571] User Interface

[1572] Automatic generation of application forms

[1573] Step 8:

[1574] The user inputs the information required to complete an application for a subsidy or grant into the terminal.

[1575] Step 9:

[1576] The terminal transmits the input information to the server.

[1577] Step 10:

[1578] The server retrieves relevant data from a database based on the input information.

[1579] Step 11:

[1580] The server automatically generates the application form using an AI algorithm.

[1581] Step 12:

[1582] The server sends the generated application to the user terminal, which displays it to the user.

[1583] Automated generation of Social Impact Assessments (SIAs)

[1584] Step 13:

[1585] The user inputs information into the terminal to request a social impact assessment of the project.

[1586] Step 14:

[1587] The terminal transmits the input information to the server.

[1588] Step 15:

[1589] The server collects data related to the project from open and private sources.

[1590] Step 16:

[1591] The server automatically generates a social impact assessment (SIA) using an AI algorithm.

[1592] Step 17:

[1593] The server sends an SIA report containing the generated evaluation results to the user's terminal, which displays it to the user.

[1594] Cloud-based data sharing

[1595] Permissions and Data Access

[1596] Step 18:

[1597] The user inputs information for setting the data sharing authority into the terminal.

[1598] Step 19:

[1599] The terminal transmits the setting information to the server.

[1600] Step 20:

[1601] The server manages data access on the cloud platform based on the received permission settings.

[1602] Step 21:

[1603] When a user requests data access, the server verifies the authorization and provides the appropriate data to the user terminal.

[1604] Open data API provision

[1605] Issuing API keys and providing data

[1606] Step 22:

[1607] The user (developer) enters information into the terminal to request the issuance of an API key.

[1608] Step 23:

[1609] The terminal transmits the request information to the server.

[1610] Step 24:

[1611] The server generates an API key and sends it to the user's device.

[1612] Step 25:

[1613] The user (developer) inputs a data request into the terminal using the API key.

[1614] Step 26:

[1615] The server retrieves the relevant data from the database and returns it to the user's terminal.

[1616] Through these steps, this system will promote the digitalization of local governments and support efficient, data-driven policymaking.

[1617] Example 1

[1618] 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."

[1619] Currently, many local governments and private organizations publish various types of data, but there are only a limited number of systems that can effectively link and utilize this data. In particular, there is a lack of systems that automate the creation of subsidy and grant applications and the associated social impact assessments (SIA). As a result, the creation of applications and evaluations takes a huge amount of time and effort, making it difficult to respond quickly. There is a need for a system that solves these problems.

[1620] 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.

[1621] In this invention, the server includes a means for acquiring public information from local governments and private information, a means for integrating the acquired information and cleaning inconsistencies and missing values, and a means for analyzing the integrated information using an AI model. This enables the efficient generation of optimal lists of subsidies and grants and the efficient performance of social impact assessments (SIAs) by integrating and analyzing data from local governments and private sectors. The server also includes a means for transmitting and displaying generated reports and application forms to a user's terminal, allowing users to quickly and easily create and review necessary documents.

[1622] "Public information from local governments" refers to statistical information, administrative data, economic data, environmental data, etc. that are made public by local governments.

[1623] "Private information" refers to data provided by companies and private organizations, and includes consumer behavior, economic activity, marketing data, etc.

[1624] "Data cleaning" is the process of filling in or removing inconsistencies and missing values ​​from acquired data.

[1625] An "AI model" is an algorithm or framework that uses machine learning and deep learning techniques to analyze data and discover specific patterns and trends.

[1626] "Subsidies and grants" are funds provided by governments, local governments, and private organizations for specific purposes or activities.

[1627] A "report" is a document that summarizes data analysis results, recommended actions, subsidy information, etc.

[1628] "User terminal" means the device or computer that a user uses to access the system, enter information, and view results.

[1629] An "application form" is an official document that contains the information required to receive a grant or assistance fund.

[1630] A "Social Impact Assessment (SIA)" is a process that involves detailed analysis and evaluation of the potential impacts of a particular project on local communities.

[1631] The present invention is a system that combines public information from local governments with private information to automatically generate applications for financial aid and grants, and also prepares detailed reports including social impact assessments (SIAs). The following details explain the procedures and configurations for specifically implementing the present invention.

[1632] Utilizing public information from local governments and private information

[1633] Data Acquisition and Integration

[1634] The server periodically calls the local government's public information API to obtain demographic, economic, and environmental data. The obtained data is stored in an internal database (e.g., PostgreSQL). The server also calls the API of private data providers (e.g., Google Analytics and other marketing data providers) to obtain data on consumer behavior and economic activity. This data is also stored in a database, and a process is performed to clean inconsistencies and missing values ​​(data cleansing).

[1635] Data Analysis and Report Generation

[1636] The server runs AI models (e.g., TensorFlow and Scikit-learn) on the integrated data to analyze the specific needs and challenges of the region. Based on this analysis, it generates a list of optimal grants and support programs and automatically generates a personalized report. The report includes details of the analysis, relevant support program information, and recommended actions. The generated report is then sent from the server to the device and can be accessed by the user.

[1637] User Interface

[1638] Automatic generation of application forms

[1639] The user inputs the information required to create an application for a grant or subsidy into the terminal. Specifically, the user inputs the project name, purpose, estimated costs, etc. The terminal then sends this input data to the server. The server then automatically generates an application form based on the input information that meets the requirements of the subsidy or grant. This application form is created based on a template and reflects all necessary information. The generated application form is then sent from the server to the terminal, where the user can review it and make corrections or additions.

[1640] Automated generation of Social Impact Assessments (SIAs)

[1641] Users input information into their device to request a social impact assessment for a specific project. Specifically, they input the project's goals, expected impact area, and target communities. The device then sends this input data to a server. The server then collects relevant public and private information based on the input information and uses an AI model to automatically generate a social impact assessment. This assessment details the project's potential impact on the local community. The generated SIA report is then sent from the server to the device, where the user can review, modify, or add to it.

[1642] Specific examples

[1643] Example 1: Grant application

[1644] When an administrative official (user) from local city A applies for a subsidy for a new child-rearing support program, the server collects child-rearing-related data from the region and uses AI to automatically generate the optimal application form. The application form is displayed on the user's device, and the administrative official can review its contents and prepare for submission.

[1645] Prompt Sentence Examples

[1646] Provide the information you need to create a grant application for a new child care program. Automatically generate the application using historical data to select the optimal format.

[1647] Project name: "City Childcare Support Program"

[1648] Objective: "Enhancing family support"

[1649] Estimated cost: 5 million yen

[1650] Example 2: Social Impact Assessment

[1651] When Municipality B starts a local park development project, the server analyzes the relevant data and automatically generates an SIA report, which can be displayed on the terminals to help stakeholders effectively implement the project.

[1652] Prompt Sentence Examples

[1653] Conduct a social impact assessment of a regional park development project. Provide information such as project goals, intended impact area, and target communities. Generate an SIA report using historical data and AI models.

[1654] Project name: "Citizens' Park Development Project"

[1655] Goal: "Expanding green space and revitalizing the community"

[1656] Affected area: "Residential area surrounding the park"

[1657] Target community: "Local residents"

[1658] The above is a specific embodiment of the present invention. This system collects information from various data sources and uses advanced AI models to analyze and automatically generate data, enabling effective subsidy applications and social impact assessments.

[1659] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1660] Step 1:

[1661] Data Acquisition

[1662] The server runs a scheduled job every day at 2:00 AM to call the local government's public information API, using the API endpoint and authentication information as input.

[1663] The server retrieves public information such as demographic, economic, environmental data, etc. The output is the retrieved dataset.

[1664] The server also calls the APIs of private data providers to obtain data on consumer behavior and economic activity. The API endpoints and authentication information are used as input, and the obtained dataset is output.

[1665] Step 2:

[1666] Data integration and cleaning

[1667] The server stores the retrieved public and private information in a database (e.g., PostgreSQL). It uses the retrieved dataset as input and the output is the stored database.

[1668] The server performs data cleaning, imputing or removing inconsistencies and missing values ​​(for example, using the mean or median for imputation). The input is the stored database, and the output is the cleaned data.

[1669] Step 3:

[1670] Data analysis

[1671] The server runs an AI model (e.g., TensorFlow, Scikit-learn) based on the cleaned data, using the cleaned data and the AI ​​model as input.

[1672] The server analyzes the specific needs and issues of the region, temporarily stores the analysis results in a table, and outputs the analysis result data.

[1673] Step 4:

[1674] Automatic report generation

[1675] The server automatically generates personalized reports based on the analysis results, taking the analysis result data and report template as input.

[1676] The server includes a report with details of the analysis, relevant funding information, and recommended actions. The output is the generated report.

[1677] Step 5:

[1678] Sending and viewing reports

[1679] The server sends the generated report to the terminal. The input is the generated report and the output is the report sent to the terminal.

[1680] The terminal displays the report to the user. The input is the report sent from the server and the output is the report displayed to the user.

[1681] Step 6:

[1682] Enter application information

[1683] Users input the information necessary to complete a grant or support application, such as the project name, purpose, and estimated costs, into the terminal.

[1684] The terminal sends input data to the server, and the output is the data sent to the server.

[1685] Step 7:

[1686] Automatic generation of application forms

[1687] The server receives the input information and automatically generates an application form that meets the requirements of the grant or subsidy. The input is the user's input information and the application form template.

[1688] The server sends the generated application form to the terminal and allows the user to confirm it. The output is the application form sent to the terminal.

[1689] Step 8:

[1690] Check and correct the application form

[1691] The user checks the application form displayed on the terminal and makes corrections or additions as necessary. The input is the application form displayed on the terminal.

[1692] The terminal sends the amended application form back to the server, and the output is the amended application form sent to the server.

[1693] Step 9:

[1694] Entering social impact assessment information

[1695] Users input information into the terminal to request a social impact assessment, such as the project's goals, the expected scope of impact, and the target community.

[1696] The terminal sends the input data to the server, and the output is the data sent to the server.

[1697] Step 10:

[1698] Automatic generation of social impact assessments

[1699] The server collects relevant data based on the input information and automatically generates a social impact assessment using an AI model. The input is user information and related data.

[1700] The server sends the generated social impact assessment report to the terminal for display by the user. The output is the assessment report sent to the terminal.

[1701] Step 11:

[1702] Checking and correcting SIA reports

[1703] The user checks the SIA report displayed on the terminal and makes corrections or additions as necessary. The input is the SIA report displayed on the terminal.

[1704] The terminal sends the modified SIA report back to the server, and the output is the modified assessment report sent to the server.

[1705] The above are the specific steps of the program processing of this system.

[1706] (Application example 1)

[1707] 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."

[1708] The conventional application process for subsidies and grants involves a lot of manual work and insufficient data integration and analysis, making it difficult to obtain subsidies efficiently and effectively. Furthermore, social impact assessments (SIAs) require specialized knowledge, making them difficult for local governments and shopping districts to easily perform. The present invention aims to solve these problems and provide a data-driven, efficient subsidy application and evaluation process.

[1709] 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.

[1710] In this invention, the server includes means for acquiring open data from local governments and private data, means for integrating the acquired data and cleaning inconsistencies and missing values, means for analyzing the integrated data using an AI algorithm, means for generating a list of optimal subsidies and grants and creating a report based on the analysis results, means for sending the generated report to a user terminal and displaying it, means for collecting data provided by each store in a physical store, means for supporting subsidy applications for each store in a shopping district or shopping mall, and means for conducting social impact assessments of shopping districts and shopping malls. This enables local governments and shopping district managers to efficiently and effectively apply for appropriate subsidies and conduct social impact assessments.

[1711] "Municipal open data" refers to information such as demographic, economic, and environmental data made public by local governments.

[1712] "Private data" refers to information on consumer behavior and economic activity provided by companies and private institutions.

[1713] "Data integration methods" refers to methods for combining data from different sources into a single data set, ensuring consistency and uniformity.

[1714] "Measures for cleaning inconsistencies and missing values" refers to methods for correcting or completing errors or gaps in a dataset.

[1715] "Means of analysis using AI algorithms" refers to methods that use artificial intelligence techniques to analyze integrated data and derive specific patterns and insights.

[1716] "Means for generating a list of grants and subsidies" refers to a method for creating a list of appropriate grants and subsidies based on the analysis results.

[1717] "Means for creating a report" refers to a method for organizing the analysis results and generating a report in an easy-to-understand format.

[1718] The "means for transmitting the generated report to the user terminal and displaying it" refers to a method for transmitting the automatically generated report to the user terminal and displaying it so that the user can check it.

[1719] "Means of collecting data provided by each store within a physical store" refers to methods of collecting information on sales and services from each store within a shopping district or shopping mall.

[1720] "Measures to support each store in a shopping district or shopping mall in applying for subsidies" refers to methods to support each store in applying for subsidies effectively.

[1721] "Methods for conducting social impact assessments of shopping districts and shopping malls" refers to methods for assessing the impact that shopping districts and shopping malls have on local communities and compiling the results into a report.

[1722] MODE FOR CARRYING OUT THE INVENTION

[1723] This invention relates to a system that enables each store in a brick-and-mortar store to efficiently apply for subsidies and conduct social impact assessments (SIAs). This system is realized by combining a server and smart glasses or mobile devices as user terminals.

[1724] System Overview

[1725] The system consists of the following main components:

[1726] 1. Server:

[1727] Hardware: High-performance server

[1728] Software: MySQL (database management system), requests (API call library), pandas (data analysis library), Scikit-learn (AI analysis library), TensorFlow (AI algorithms)

[1729] The server periodically acquires open data from local governments and private data, and integrates and cleans this data. It then analyzes the integrated data using AI algorithms to generate optimal subsidy and grant lists and prepare reports. It also collects data from each store within the physical store, and uses this data to support subsidy applications and conduct social impact assessments (SIA).

[1730] 2. User device (smart glasses or mobile device):

[1731] Hardware: Smart glasses (VR device), smartphone

[1732] Software: Form generation tool (Flask), LaTeX (report generation tool), AWS (cloud platform), OAuth (access control library)

[1733] Users can input the information required for grant applications using smart glasses or a mobile device. The input information is sent to a server, where it is analyzed by AI and the appropriate application form is automatically generated. Users can also input information to request a social impact assessment of a project, and the results of the AI ​​analysis can be visually confirmed as a report.

[1734] Specific examples

[1735] For example, each store in a shopping district can use smart glasses to input its own sales data and service information. Based on this, the server automatically generates an optimal subsidy application form and displays it on the smart glasses. The system can also conduct a social impact assessment (SIA) on the impact the entire shopping district has on the local community and generate a detailed report. Shopping district managers and store owners can use these reports to develop effective management strategies.

[1736] Prompt Sentence Examples

[1737] We would like to use smart glasses to streamline the process of applying for subsidies for the entire shopping district. Please develop a system that automatically generates optimal subsidy application forms based on the sales data and services offered by each store in the shopping district. Also, please automatically generate social impact assessments of shopping district projects and provide the results as a report.

[1738] In the above-described manner, the present invention makes it possible to efficiently and effectively carry out subsidy applications and social impact assessments within physical stores.

[1739] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1740] Step 1:

[1741] The server periodically accesses the local government's open data API to obtain demographic, economic, and environmental data. The data is then stored in an internal database. This data includes the local population structure and economic situation.

[1742] Step 2:

[1743] The server obtains data on consumer behavior and economic activity from private data providers. This data is also stored in the internal database. The private data includes sales data for each store and customer purchasing information.

[1744] Step 3:

[1745] The server integrates the acquired municipal and private data and cleans it up for inconsistencies and missing values. Data cleaning includes correcting inconsistent data and filling in missing values.

[1746] Step 4:

[1747] The server applies AI algorithms (such as Scikit-learn and TensorFlow) to the integrated data to analyze the specific needs and challenges of the region. This analysis makes it possible to identify optimal subsidies and grants. The input data includes integrated open data and private data, and the analysis results are obtained as the output.

[1748] Step 5:

[1749] The server automatically generates a personalized report based on the analysis results, including details of the analysis, related grant information, and recommended actions. The generated report uses LaTeX formatting.

[1750] Step 6:

[1751] Users use smart glasses or a mobile device to input information required for grant applications, such as the project name, purpose, and estimated costs. The input data is then sent from the device to the server.

[1752] Step 7:

[1753] The server automatically generates an application form based on the input data, meeting the requirements for the subsidy or grant. The application form reflects the information entered by the user and recommended subsidy information based on the analysis results. The generated application form is sent to the terminal.

[1754] Step 8:

[1755] The terminal displays the generated application form to the user, who can then check it and make corrections or additions as necessary.

[1756] Step 9:

[1757] To request a Social Impact Assessment (SIA), users input project information, such as the project's goals, the intended impact area, and the target community. The input data is sent from the device to the server.

[1758] Step 10:

[1759] The server collects and analyzes relevant open data and private data based on project information provided by users, and uses AI algorithms to automatically generate a social impact assessment (SIA) for the project.

[1760] Step 11:

[1761] The server then sends the generated SIA report to the device, which details the project's potential impact on the local community.

[1762] Step 12:

[1763] The terminal displays the generated SIA report to the user, who can then review the report and make corrections or additions as necessary.

[1764] 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.

[1765] This invention adds an emotion engine that recognizes user emotions to a system that combines open data from local governments and private data, enabling more effective preparation of applications for subsidies and grants and social impact assessments. This system includes a server, a terminal, an emotion engine, and multiple processing steps that are user-driven.

[1766] Utilizing local government open data and private data

[1767] Data Acquisition and Integration

[1768] 1. The server periodically calls the local government's open data API to obtain demographic, economic, and environmental data, which is then stored in an internal database.

[1769] 2. The server also acquires data on consumer behavior and economic activity from private data providers and stores it in an internal database. This data is then integrated for later data analysis.

[1770] User Interface and Emotion Engine

[1771] Automatic generation of application forms

[1772] 1. The user enters the information needed to complete a grant or subsidy application into the device. The emotion engine uses facial recognition and voice analysis to recognize the user's emotional state in real time.

[1773] 2. The device sends the input data and the user's emotional state to the server.

[1774] 3. The server retrieves relevant data from the database based on the input information and automatically generates an application form using an AI algorithm. Based on information from the emotion engine, it displays supplementary information and advice if the user is feeling stressed or anxious.

[1775] 4. The server sends the generated application to the terminal, which displays it to the user. If the user is relaxed, they are given the option to confirm the application contents with a short confirmation procedure.

[1776] Automated generation of Social Impact Assessments (SIAs)

[1777] 1. A user inputs information into a terminal to request a social impact assessment of a specific project. The emotion engine also recognizes the user's emotions during this process.

[1778] 2. The device sends the input data and emotional state to the server.

[1779] 3. The server collects project-related data from open and private sources, automatically generates a Social Impact Assessment (SIA) using AI algorithms, and provides feedback based on an emotion engine.

[1780] 4. The server sends the generated SIA report containing the evaluation results to the device, which displays it to the user. If the user's stress level is high, the device adds information suggesting a specific action plan.

[1781] Cloud-based data sharing and emotion engine

[1782] Permissions and Data Access

[1783] 1. The user inputs information into the device to set up permissions for data sharing. The emotion engine recognizes the user's emotional state during this process.

[1784] 2. The device sends the setting information and emotional state to the server.

[1785] 3. The server manages data access on the cloud platform based on the received permission settings.

[1786] 4. When a user requests data access, the server verifies the user's authorization and provides the appropriate data to the user's device. The server also adjusts the data display method and supplementary information according to the user's emotional state.

[1787] Open data API provision and emotion engine

[1788] Issuing API keys and providing data

[1789] 1. The user (developer) inputs information to request the issuance of an API key into the device. The emotion engine also recognizes the emotional state during this process.

[1790] 2. The device sends the request information and emotional state to the server.

[1791] 3. The server generates an API key and sends it to the user's device. Emotional state may affect how applicable information is provided.

[1792] 4. The user (developer) enters a data request into the device using the API key, and the server retrieves the relevant data from the database and returns it to the user's device.

[1793] Examples:

[1794] When a local city A's administrative official (user) applies for a subsidy for a new child-rearing support program, the server collects data related to child-rearing in the area and uses AI to automatically generate the optimal application form. If the emotion engine detects a state of stress, the device provides additional information and advice, and adjusts the platform for reviewing the final application form taking into account the user's state of relaxation.

[1795] When another local government B starts a local park development project, it uses an emotion engine to recognize the emotional state of the project manager and automatically generates a social impact assessment (SIA) through AI analysis. When displaying the assessment results, the device provides feedback according to the user's emotions.

[1796] In this way, by incorporating an emotion engine, the present invention aims to promote the digitalization of local governments, improve user experience, and support efficient, data-driven policymaking.

[1797] The processing flow will be explained below.

[1798] Specific processing steps for creating an application form incorporating an emotion engine

[1799] Data Acquisition and Integration

[1800] Step 1:

[1801] The server periodically calls the local government's open data API to obtain demographic, economic, and environmental data.

[1802] Step 2:

[1803] The server obtains data on consumer behavior and economic activity from private data providers and stores it in an internal database.

[1804] Step 3:

[1805] The server checks for inconsistencies in the various data stored in the database and performs data cleaning as necessary.

[1806] Application Form Creation Process

[1807] Step 4:

[1808] Users input the information necessary to complete a grant or subsidy application into the device, and the emotion engine analyzes the user's facial expressions and tone of voice in real time to recognize their emotional state.

[1809] Step 5:

[1810] The terminal transmits the input data and emotional state to the server.

[1811] Step 6:

[1812] The server retrieves relevant open and private data from a database based on the input information. If the emotion engine determines that the user's stress level is high, it provides supplementary information and input assistance.

[1813] Step 7:

[1814] The server uses AI algorithms to analyze the acquired data and automatically generate the optimal application form, including supplementary information and confirmation messages that take the user's emotional state into account.

[1815] Step 8:

[1816] The server sends the generated application form to the terminal, which displays it to the user. The emotion engine checks the user's stress level and displays an appropriate feedback message.

[1817] Automated generation process for Social Impact Assessments (SIA)

[1818] Step 9:

[1819] Users input information into the terminal to request a social impact assessment of their project, and the emotion engine monitors the user's psychological state in real time.

[1820] Step 10:

[1821] The terminal transmits the input data and emotional state to the server.

[1822] Step 11:

[1823] The server collects data related to the project from open and private sources. If the emotion engine detects negative emotions, it displays supplemental information offering advice to the user on how to relax.

[1824] Step 12:

[1825] The server uses an AI algorithm to automatically generate a social impact assessment (SIA), adding explanatory notes to the assessment based on feedback from the emotion engine.

[1826] Step 13:

[1827] The server sends the generated SIA report to the terminal, which displays it to the user. The emotion engine displays a support message to help the user smoothly receive and understand the evaluation results.

[1828] Cloud-based data sharing process

[1829] Step 14:

[1830] The user inputs permission to share data into the device, and the emotion engine monitors the user's stress level and displays appropriate feedback messages.

[1831] Step 15:

[1832] The terminal transmits the authority setting information to the server.

[1833] Step 16:

[1834] The server manages data access on the cloud platform based on the received permission settings.

[1835] Step 17:

[1836] When a user requests data access, the server verifies the user's authorization and provides the appropriate data to the user's device. The server adjusts the display format of the data and supplementary information according to the user's emotional state.

[1837] Open data API provision process

[1838] Step 18:

[1839] The user (developer) inputs information to request the issuance of an API key into the device. The emotion engine also recognizes the user's emotional state during this process.

[1840] Step 19:

[1841] The terminal transmits the request information and the emotional state to the server.

[1842] Step 20:

[1843] The server generates an API key and sends it to the device, along with supplementary explanations that take into account the user's emotional state.

[1844] Step 21:

[1845] The user (developer) inputs a data request into the terminal using the API key.

[1846] Step 22:

[1847] The server retrieves the relevant data from the database and sends it back to the user's device, where the emotion engine provides feedback according to the emotion.

[1848] Through these steps, a system incorporating an emotion engine will efficiently promote digitalization in local governments, data-driven policy making, and improve user experience.

[1849] Example 2

[1850] 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."

[1851] The traditional process for applying for local government subsidies and grants, as well as for social impact assessments, required a lot of time and effort and was inefficient. Furthermore, there was a lack of ingenuity to reduce the stress and anxiety users felt while applying and creating assessments. This resulted in a poor user experience and sometimes led to processes that did not proceed smoothly. Furthermore, there was a need for flexible responses, such as cleaning data inconsistencies and missing values, and emotion recognition.

[1852] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1853] In this invention, the server includes: means for acquiring open data from local governments and private data; means for integrating the acquired data and cleaning inconsistencies and missing values; means for analyzing the integrated data using an AI algorithm; means for generating a list of optimal subsidies and grants and creating a report based on the analysis results; means for sending the generated report to a user terminal and displaying it; means for recognizing the user's emotional state; and means for displaying supplementary information and advice if the user is feeling stressed or anxious. This improves the user experience and enables efficient, data-driven policy planning and application processes. It also enables flexible responses based on the user's emotional state, reducing stress and anxiety.

[1854] "Municipal open data" refers to public data such as demographic, economic, and environmental data made public by local governments.

[1855] "Private data" refers to data on consumer behavior, economic activity, marketing research, etc. provided by commercial companies and non-profit organizations.

[1856] "Data integration" is the process of bringing together data from different sources into a single unified format.

[1857] "Inconsistent data" is data that is inconsistent and contradictory and requires correction before it can be used in data analysis.

[1858] "Missing value cleaning" is the process of properly handling missing values ​​in a dataset to improve data quality.

[1859] An "AI algorithm" is a series of processes and methods that use artificial intelligence technology to analyze data, make predictions, and perform optimization.

[1860] "Grants and grants" are funds provided by governments or local governments to support specific projects or activities.

[1861] "Report generation" refers to the automatic creation of reports tailored to specific purposes based on the analysis results.

[1862] A "user terminal" is a device operated by a user, such as a personal computer, smartphone, or tablet.

[1863] An "emotional state" is the emotional state a user is feeling at a particular moment, and is detected through facial recognition and voice analysis.

[1864] "Supporting information and advice" is any additional information or suggestions that can help users navigate the application or evaluation process.

[1865] "Automatic application generation" refers to the automatic creation of grant and subsidy applications based on user-provided information and related data.

[1866] A "social impact assessment" is the process of assessing the impact that a particular project will have on society or a community.

[1867] An "action plan" is a specific plan or proposal to be implemented to achieve a specific goal.

[1868] The present invention relates to a system that combines open data from local governments with private data and recognizes user emotions. The system includes a server, a terminal, an emotion engine, and multiple processing steps that are user-driven.

[1869] Data Acquisition and Integration

[1870] The server uses the Autonomous Data acquisition module to retrieve demographic, economic, and environmental data from the local government's open data API. This is done using the Python requests library. The retrieved data is stored in an internal database such as MySQL. The server also retrieves data from private data providers and stores this in the internal database. For this purpose, the Pandas library is used to integrate, clean, and resolve inconsistencies in the data.

[1871] Emotion engine and application generation

[1872] The user inputs the information needed to complete a grant or subsidy application into the device. The endpoint uses Azure Cognitive Services or a similar emotion engine to recognize emotions in real time through facial recognition and voice analysis. The device then transmits the input data and emotional state to a server.

[1873] The server retrieves relevant data from the database and automatically generates an application form using an AI algorithm (e.g., a natural language processing model) powered by TensorFlow. It also provides supplementary information and advice depending on the user's emotional state.

[1874] Generating a Social Impact Assessment (SIA)

[1875] Users input information about a specific project into the device. The device then uses an emotion engine to recognize the user's emotional state. The device then sends the input data and emotional state to a server. The server then collects relevant data from open and private sources and automatically generates a social impact assessment (SIA) using a Python AI algorithm. The generated report is then displayed to the user, providing feedback and an action plan based on the user's emotions.

[1876] Cloud-based data sharing

[1877] The user inputs information into the device that sets permissions for data sharing. The emotion engine recognizes the user's emotional state and sends that information to the server. The server manages data access permissions on a cloud platform and provides data according to the user's request.

[1878] Open data API provision

[1879] A user as a developer inputs information to request the issuance of an API key into the device, and the emotional state is recognized by the emotion engine. The device sends this information to the server, which generates and returns an API key. The user makes a data request using the API key, and the server provides the data.

[1880] Prompt Sentence Examples

[1881] For example, consider the following prompt:

[1882] "Auto-generate a child care grant application. Enter your project summary, goals, and required budget."

[1883] "Conduct a social impact assessment of this project. Enter the project objectives, target area, and stakeholders."

[1884] "Give specific users access to specific data."

[1885] This will enable the invention to promote the digitalization of local governments and improve user experience. Furthermore, by incorporating an emotion engine, it will reduce stress and anxiety felt by users and realize efficient data-driven policy planning and application processes.

[1886] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1887] Step 1:

[1888] The server periodically calls the local government's open data API to obtain demographic, economic, and environmental data. The input is the API endpoint, and the output is JSON-formatted data. Specifically, it uses Python's requests library to obtain data using response = requests.get('https: / / api.example.com / data'). This data is stored in an internal database (such as MySQL). It is written to the database using session.add(data_object) and session.commit().

[1889] Step 2:

[1890] The server also retrieves data from private data providers and stores it in its internal database. The input is a request including an activated API key, and the output is JSON-formatted data. For example, set authentication information as headers = {'Authorization': 'Bearer YOUR_API_KEY'} and retrieve data as follows: response = requests.get('https: / / privateapi.example.com / data', headers=headers). This data is also converted to a data frame using the Pandas library and stored in the database.

[1891] Step 3:

[1892] The server combines the acquired open data and private data. The input is multiple datasets, and the output is a unified dataset. Specifically, the Pandas library is used to combine data frames and concatenate the data using combined_data = pd.concat([open_data, private_data], axis=0). Furthermore, operations such as combined_data.dropna() and combined_data.fillna(method='ffill') are performed to clean inconsistencies and missing values. The combined dataset is then saved back to the database.

[1893] Step 4:

[1894] A user enters information into a device to complete a grant or subsidy application. The input is information provided through a web form or application fields, and the output is JSON-formatted data sent to a server. Specifically, the data is collected using an HTML form, validated in real time with JavaScript, and then submitted using fetch('https: / / server.example.com / submit', {method: 'POST', body: JSON.stringify(formData)}).

[1895] Step 5:

[1896] The device recognizes the user's input data and emotional state. The input is data including the user's facial recognition and voice analysis, and the output is JSON data containing emotional state information. The emotion engine uses Azure Cognitive Services and uses the camera and microphone with navigator.mediaDevices.getUserMedia({ video: true, audio: true}). The data obtained from this is sent to the API to obtain the emotional state.

[1897] Step 6:

[1898] The device sends input data and emotional state to the server. The input is JSON format data containing user information and emotional data, and the output is data sent to the server. Specifically, data is sent as follows: fetch('https: / / server.example.com / emotion', {method: 'POST', body: JSON.stringify(emotionData)}).

[1899] Step 7:

[1900] The server retrieves relevant data from the database based on the input information and uses an AI algorithm to automatically generate an application form. The input is user information, emotion data, and an integrated dataset, and the output is an automatically generated application form. Specifically, it uses a TensorFlow model to automatically generate a draft application form as follows: model.predict(input_data).

[1901] Step 8:

[1902] The server sends the generated application form to the terminal, which displays it to the user. The input is the automatically generated application form data, and the output is the information displayed on the user's terminal. Specifically, the DOM is manipulated as follows: document.getElementById('generated_document').innerHTML = generated_content, and the generated content is inserted into the HTML element.

[1903] Step 9:

[1904] Users input information into their device to request a social impact assessment of a specific project. The input is detailed information about the project, and the output is JSON-formatted data that is sent to the server. Specifically, similar to the application creation process described above, data is collected using a web form and sent to the server.

[1905] Step 10:

[1906] The device sends input data and the user's emotional state to the server. The input is project information and emotional data from the user, and the output is data sent to the server. Specifically, data is sent as follows: fetch('https: / / server.example.com / project', {method: 'POST', body: JSON.stringify(projectData)}).

[1907] Step 11:

[1908] The server collects data related to the project and automatically generates a Social Impact Assessment (SIA) using an AI algorithm. The input is user information, sentiment data, and an integrated dataset, and the output is an automatically generated SIA report. Specifically, the model is used to generate the assessment: siaevaluation_model.evaluate(project_data).

[1909] Step 12:

[1910] The server sends the generated SIA report to the terminal, which displays it to the user. The input is the automatically generated SIA report data, and the output is the information displayed on the user's terminal. Specifically, the DOM is manipulated as follows: document.getElementById('sia_report').innerHTML = sia_content to insert the generated content into the HTML element.

[1911] Step 13:

[1912] The user inputs information into the device to set data sharing permissions. The input is detailed information about data sharing, and the output is JSON-formatted data that is sent to the server. Specifically, the setting information is entered into a form and sent to the server.

[1913] Step 14:

[1914] The device sends setting information and emotional state to the server. The input is setting information and emotional data, and the output is data sent to the server. Specifically, data is sent as follows: fetch('https: / / server.example.com / settings', {method: 'POST', body: JSON.stringify(settingsData)}).

[1915] Step 15:

[1916] The server uses AWS IAM and other cloud services to set sharing permissions and manage data access. The input is configuration information and emotion data, and the output is the completion of permission settings. Specifically, permission settings are performed using iam.createUser({UserName: 'username'}) and iam.attachUserPolicy.

[1917] Step 16:

[1918] When a user requests data access, the server checks the authorization and provides the appropriate data to the user's device. The input is the data access request, and the output is the requested data. Specifically, the data is retrieved using an AJAX request and displayed through the aforementioned DOM manipulation.

[1919] Step 17:

[1920] The user (developer) enters information into the terminal to request the issuance of an API key. The input is detailed information about the API key request, and the output is JSON format data that is sent to the server. Specifically, the user fills in the form and sends it as follows: fetch('https: / / server.example.com / apikey', {method: 'POST', body: JSON.stringify(apikeyRequest)}).

[1921] Step 18:

[1922] The device sends request information and emotional state to the server. The input is the request information and emotional data, and the output is data transmission to the server. Specifically, it sends an API request as described above.

[1923] Step 19:

[1924] The server generates an API key and sends it to the user's device. The input is the request information and emotional state, and the output is the generated API key. Specifically, it runs a script that generates an API key and sends it as fetch('https: / / server.example.com / apikey', {method: 'POST', body: JSON.stringify(apikeyResponse)}).

[1925] Step 20:

[1926] The user (developer) uses an API key to input a data request into their device, and the server retrieves the relevant data from the database and sends it back to the user's device. The input is...

Claims

1. Means of obtaining open data from local governments and private data, A means of integrating the acquired data and cleaning it for inconsistencies and missing values; A means of analyzing the integrated data using AI algorithms; A means to generate a list of optimal grants and subsidies and create reports based on the analysis results; means for transmitting the generated report to a user terminal and displaying it; A system including:

2. A means for users to input information necessary to complete a grant or subsidy application; A means for retrieving related data from a database based on the input information and automatically generating an application form; means for transmitting the generated application form to a user terminal and displaying it; The system of claim 1 , comprising:

3. a means for a user to input information to request a social impact assessment of a project; A means of collecting relevant data based on input information and automatically generating a social impact assessment using an AI algorithm; means for transmitting the generated social impact assessment report to a terminal and displaying the report; The system of claim 1 , comprising:

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