system

Abstract

We provide the system. [Solution] Means of collecting grant information for non-profit organizations, A means for analyzing the aforementioned grant information based on user needs, A means of recommending the most suitable grant to the user based on the aforementioned analysis results, A means for generating the documents necessary for applying for the aforementioned grant, A means for managing the progress of the aforementioned application process, A means of notifying users of important updates, A system that includes this.

Description

Technical Field

[0001] The technology of this disclosure relates to a system.

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor, the method including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a character of the chatbot, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance as a response to the user utterance.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] For a non-profit organization to continue its activities sustainably, fundraising is important. However, since the information on grants is vast and complex, there is a problem that it takes a great deal of time and effort to collect information and go through the application procedures. In addition, the lack of specialized knowledge and experience for selecting appropriate grants has become an obstacle to fundraising. As a result, there is a problem that non-profit organizations cannot allocate sufficient resources to their original activities and it becomes difficult to maximize their social value.

Means for Solving the Problems

[0005] This invention solves the above problems by providing a grant information collection system for non-profit organizations. Specifically, it includes a means for automatically collecting grant information from reliable sources on the internet and a means for recommending appropriate grants by analyzing that information with artificial intelligence based on the user's needs. It also includes a means for automatically generating the documents necessary for grant applications based on user input, thereby streamlining the application process. Furthermore, by adding a function to continuously manage the application status and notify the user when there is important update information, the system streamlines the fundraising process and provides an environment where non-profit organizations can concentrate on their core business.

[0006] A "non-profit organization" is an organization that does not pursue specific interests but aims to provide social value.

[0007] "Grant information" refers to information about financial assistance provided by grant-making agencies that non-profit organizations can use to fund their activities.

[0008] "User needs" refer to the specific requests and requirements of non-profit organizations and their representatives that use the system.

[0009] "Artificial intelligence" is a technology in which computer systems imitate human intellectual activity to perform advanced judgments and analyses.

[0010] An "application document" is an official document containing the information necessary to receive a grant.

[0011] The "application process" refers to the series of procedures and actions required to obtain a grant.

[0012] "Notifications" refer to information, updates, and reminders sent from a system to a user. [Brief explanation of the drawing]

[0013] [Figure 1]This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] This is a sequence diagram showing the processing flow of the data processing system in Example 2, which incorporates an emotion engine. [Figure 14] This is a sequence diagram showing the processing flow of the data processing system in Application Example 2, which combines an emotion engine. [Modes for carrying out the invention]

[0014] Hereinafter, an example of an embodiment of the system relating to the technology of this disclosure will be described with reference to the attached drawings.

[0015] First, the terms used in the following description will be explained.

[0016] In the following embodiments, the labeled processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0017] In the following embodiments, the labeled RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0018] In the following embodiments, the labeled storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, etc.

[0019] In the following embodiments, the labeled communication I / F (Interface) is an interface including a communication processor and 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), or Bluetooth (registered trademark), etc.

[0020] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0021] [First Embodiment]

[0022] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0023] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0024] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0025] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0026] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0027] 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 perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0028] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0029] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0030] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0031] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0032] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0033] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0034] This invention is a system that helps non-profit organizations efficiently obtain grants. The system provides users with multiple means to efficiently collect grant information, select the most suitable grants, and simplify the application process.

[0035] The system's program consists of the following main functions. First, to collect grant information from various sources on the internet, the server performs regular web scraping to build a reliable database. This makes it possible to efficiently manage large amounts of complex grant information.

[0036] When a user logs into the system, the terminal sends the user's requests and requirements to the server. The server uses artificial intelligence to analyze grant information that matches the user's needs and presents it to the terminal. This allows the user to easily find the grant that is best suited to them.

[0037] Furthermore, to assist with grant applications, the server creates templates for the necessary application documents and customizes them based on the information entered by the user. This allows users to prepare application documents quickly and accurately.

[0038] After an application is submitted, the server monitors its progress and sends important notifications and reminders to the user via their device as needed. By receiving these notifications, users can stay informed about the status of their application and take necessary actions in a timely manner.

[0039] As a concrete example, consider a non-profit organization using this system to raise funds for operating a children's cafeteria in a poverty-stricken area. The organization's representative logs in via a terminal and enters conditions related to the region and purpose, and the server recommends specific grants and supports the application process. In this way, the organization can efficiently navigate the complex grant application process and focus on its core business.

[0040] Based on the above, this invention aims to streamline fundraising for non-profit organizations and support the maximization of social value.

[0041] The following describes the processing flow.

[0042] Step 1:

[0043] The server periodically scrapes grant information from reliable sources on the internet, organizes the information, and stores it in a database.

[0044] Step 2:

[0045] Users log in to the system on their terminal and enter their grant search criteria and personal needs.

[0046] Step 3:

[0047] The terminal sends the information entered by the user to the server, which then uses artificial intelligence to analyze the database and find grants that match the user's criteria.

[0048] Step 4:

[0049] The server sends a list of grant candidates to the terminal, which the user reviews and selects the appropriate grant.

[0050] Step 5:

[0051] The user initiates the application process for the grant they have selected and enters the necessary information through their device.

[0052] Step 6:

[0053] The terminal sends user input information to the server, which then customizes and generates application form templates based on that information.

[0054] Step 7:

[0055] The server sends the generated application documents to the user's terminal, which the user then downloads, modifies as needed, and submits.

[0056] Step 8:

[0057] The server constantly monitors the progress of the application and notifies the user via their terminal if there are any significant status changes.

[0058] Step 9:

[0059] The user checks the notification on their device and takes additional action as needed.

[0060] (Example 1)

[0061] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0062] For nonprofit organizations, the process of gathering information on grants and submitting applications is complex and time-consuming. In particular, collecting accurate and up-to-date information from diverse sources, finding grants that meet the specific needs of their users, and efficiently preparing applications and managing the process are all challenging. This situation makes it difficult for nonprofit organizations to focus on their core activities.

[0063] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0064] In this invention, the server includes means for collecting financial assistance information from information sources, means for analyzing financial assistance information based on user requests, means for recommending the most suitable financial assistance, means for creating documents, means for managing the progress of the application process, and means for communicating important updates. This enables non-profit organizations to efficiently obtain appropriate grant information and proceed with the application process quickly and accurately.

[0065] "Information sources" refer to information on financial support related to the present invention, provided by government agencies, foundations, etc., that exist on the internet.

[0066] "Financial support information" refers to detailed information about financial support such as grants and subsidies available to non-profit organizations.

[0067] "Users" refers to non-profit organizations or similar entities that use this system to seek and apply for financial assistance.

[0068] "Requests" refer to information that users communicate through the system, indicating specific conditions or desired support.

[0069] "Means of analysis" refers to methods and techniques for analyzing collected financial support information based on the user's requests.

[0070] "Recommended measures" refers to a function that selects and presents appropriate financial support to users based on the analysis results.

[0071] "Document" refers to a structured document containing information that users create and submit, such as forms and documents required for applying for financial assistance.

[0072] "Means of managing the progress of the application process" refers to functions that monitor the progress of the entire financial assistance application process and support its smooth execution.

[0073] "Updates" refer to content that conveys important changes or additions to the application process or financial support information.

[0074] "Means of communication" refers to methods used to notify or inform users of updates.

[0075] This system is designed to help non-profit organizations efficiently obtain grants and requires coordination between servers, terminals, and users.

[0076] First, the server uses web scraping techniques to collect financial support information from various sources on the internet. This process utilizes open-source web scraping tools such as Beautiful Soup and Scrapy. The collected data is then organized and stored using a database system (e.g., MySQL®, PostgreSQL).

[0077] Subsequently, users access the system via their devices and input their organization's requests and requirements. These requirements include the target region, area of ​​activity, and the amount of funding needed.

[0078] The terminal sends the information entered by the user to the server. The server uses a generative AI model (e.g., GPT-4® or BERT) to analyze the information in the database and identify the financial support information that best matches the user's needs. This allows the user to obtain information on the most suitable grants.

[0079] For example, if a non-profit organization is seeking funding for educational support, a user can obtain specific grant information by entering a prompt such as, "I am looking for grants for local education. The activity area is urban, and the focus is on supporting low-income families."

[0080] Furthermore, the server generates templates for the documents required to apply for the identified grants. This process utilizes software such as Word and Google Docs, and the document templates are customized based on the information entered by the user.

[0081] Finally, the server monitors the progress of the application process and notifies users of important updates via smartphones or computer terminals as needed. This allows users to respond in a timely manner.

[0082] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0083] Step 1:

[0084] The server collects financial support information from its sources. Specifically, it uses web scraping tools such as Beautiful Soup and Scrapy to retrieve information from specified URLs. This process involves scheduling regular scraping operations. The input is a list of URLs, and the output is the scraped raw data.

[0085] Step 2:

[0086] The server stores the collected raw data in a database. Using database systems such as MySQL or PostgreSQL, the server converts the acquired data into a structured format. It removes duplicate and invalid data, extracts only the necessary field information, and stores it in the database. The input is the scraped raw data, and the output is an organized database entry.

[0087] Step 3:

[0088] Users log in to the system via their terminal. Users gain access to the system by entering their personal information and organizational details. The input is a user registration form, and the output is an authenticated status indicating the start of a session.

[0089] Step 4:

[0090] The user enters search criteria for support information on the terminal. They specify the target region, activity area, and required funding amount. The terminal formats the entered criteria and prepares to send them to the server. The input is the user's search criteria, and the output is the search query sent to the server.

[0091] Step 5:

[0092] The server searches the database based on the received search query. It then uses a generative AI model (e.g., GPT-4) to analyze the most relevant assistive information that matches the criteria. The input is the query sent to the server, and the output is a list of recommended assistive information.

[0093] Step 6:

[0094] The terminal displays recommended support information received from the server to the user. The user can review the information and click on options of interest to obtain more details. The input is a list of support information sent from the server, and the output is the detailed information displayed to the user.

[0095] Step 7:

[0096] The server generates application documents based on the selected support information. Using Word or Google Docs, it creates customized documents based on the information entered by the user. Input consists of the user-selected support information and prompt text, while output is an application document template.

[0097] Step 8:

[0098] The server monitors the progress of the application process and notifies the user as needed. It uses a progress management system to check submission deadlines and important updates, and sends alerts to the user via their terminal. Input is application status data, and output is notification messages delivered to the user.

[0099] (Application Example 1)

[0100] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0101] For non-profit organizations to secure funding efficiently and securely, they need to quickly navigate a complex process that includes gathering grant information, selecting the most suitable funds, and preparing and managing application documents. Furthermore, while digitalization is advancing, the risk of data security being compromised is also increasing. It is desirable to provide systems that address these challenges and create an environment where non-profit organizations can focus on their core activities.

[0102] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0103] In this invention, the server includes means for collecting financial information for non-profit organizations, means for analyzing the financial information based on user requests, and means for presenting the user with the most suitable funding based on the analysis results. This enables non-profit organizations to raise funds efficiently and securely, allowing them to focus on their core social contribution activities.

[0104] A "non-profit organization" is an organization that does not pursue profit and primarily operates with the aim of contributing to society or the public good.

[0105] "Funding information" refers to detailed information about various sources of funding and grants, including providers, conditions, and available amounts.

[0106] "Analysis" refers to the act of analyzing data to derive information that is optimal for a specific purpose.

[0107] "Application documents" refer to official documents prepared in a specific format for submission to funders.

[0108] A "monitoring mechanism" is a mechanism for constantly checking specific activities or progress within a system and taking action as needed.

[0109] "Means of notification" refers to a function or mechanism for informing users of important information or progress.

[0110] "Encryption technology" is a technology that transforms data to protect it from unauthorized access, and plays a role in maintaining data confidentiality.

[0111] "Biometric authentication technology" is a method of authenticating individuals using human physical characteristics such as fingerprints or facial recognition.

[0112] The system based on this invention is designed to enable non-profit organizations to efficiently and securely raise grants. The server first collects funding information from the internet using web scraping tools (e.g., Beautiful Soup, Scrapy) and API integration. The collected data is securely stored in a cloud database (e.g., Firebase, AWS® RDS) using encryption technology. The server then analyzes this information using AI technology (e.g., TENSORFLOW®, PyTorch) to extract the most suitable funding information for the user's needs.

[0113] The device securely provides the user with analyzed information through biometric authentication (e.g., iOS Face ID, Android® Fingerprint API). This biometric authentication technology protects the user's personal information and prevents unauthorized access to the system. Users can prepare application documents based on the provided financial information in a secure environment.

[0114] As a concrete example, suppose an organization operating a children's cafeteria in a certain region uses this system for fundraising. In this case, the representative uses a smartphone to log in via biometric authentication. The AI ​​then selects the most suitable grant from the fundraising information it provides, and the representative can download application form templates available on the cloud and proceed with the application quickly.

[0115] An example of a prompt might be: "Our non-profit organization runs a local children's cafeteria. Please tell us about the best grants available to efficiently raise operating funds, and also provide us with the necessary documents for the application process." Based on this prompt, the AI ​​will provide appropriate funding information and support the application process.

[0116] As a result, this system enables non-profit organizations to manage their funds more efficiently and concentrate resources on necessary social activities.

[0117] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0118] Step 1:

[0119] The server uses web scraping tools and APIs to collect financial information from the internet. This includes detailed information on various sources of funding. It uses internet URLs and API endpoints as input and obtains structured data (e.g., in JSON format) containing financial information as output. The server sends this data to a cloud database for secure management.

[0120] Step 2:

[0121] The server uses an artificial intelligence model to analyze data based on financial information stored in a cloud database. It receives user requests and conditions as input, and the AI ​​model analyzes this data to select the most suitable financial information for the user. This process yields the optimal financial information to be presented to the user as output.

[0122] Step 3:

[0123] The terminal uses biometric authentication technology to verify the user's identity and provides financial information in a secure manner. It acquires the user's biometric data (facial recognition or fingerprint data) as input, and upon successful authentication, displays the financial information received from the server to the user as output. The terminal then supports the user in taking the next action based on this information.

[0124] Step 4:

[0125] Users can view optimized financial information via their device and begin creating application documents as needed. The system takes the financial information selected by the user as input and generates document templates in the cloud. As output, users receive customized application documents, which they can use to quickly submit their applications.

[0126] Step 5:

[0127] The server monitors the progress of the application process and sends notifications to users via their terminals as needed. It monitors log data and application status trends as input and generates notifications to remind users of important updates (e.g., application approval status and next steps) as output. This allows users to take action at the appropriate time.

[0128] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0129] This invention provides enhanced convenience to a grant support system for non-profit organizations to efficiently raise funds by incorporating an emotion engine that recognizes user emotions. This system analyzes the user's emotional state, recommends optimal grant information based on that analysis, and notifies the user at the appropriate time.

[0130] The system's configuration involves a server that collects grant information from the internet and builds a database. When a user logs in via a terminal and enters search criteria for grants, the terminal collects user sentiment data obtained through voice and text.

[0131] Emotional data is transferred to a server and analyzed by an emotion engine. This engine determines the degree of positive or negative emotion, associates it with information in a database built into the user's needs, and selects appropriate subsidy information. Through this process, the server generates a recommendation list that matches the user's emotions and sends this information to the terminal.

[0132] Furthermore, the emotion engine also has the ability to adjust the timing of alerts and optimize progress notifications according to the user's stress level and level of interest. For example, if a user is feeling anxious about their grant application, the server can reassure them by sending a notification with added detailed explanations.

[0133] For example, if a user is looking for funding for a child's educational project, the system can detect their heightened emotions during their search on their device. Based on this information, the server can provide more helpful details about relevant grants and send notifications recommending expert support if necessary.

[0134] In this way, the present invention can support the support activities of non-profit organizations from an emotional perspective and make the fundraising process smoother and more effective.

[0135] The following describes the processing flow.

[0136] Step 1:

[0137] The server regularly collects the latest grant information from reliable sources on the internet and updates the database.

[0138] Step 2:

[0139] The user logs into the system using their device and enters their search criteria for grants.

[0140] Step 3:

[0141] The device collects user sentiment data from voice and text input and sends it to the server.

[0142] Step 4:

[0143] The server analyzes the received emotional data using an emotion engine to determine the user's emotional state. Based on this analysis, the search criteria for grants corresponding to the user's emotions are fine-tuned.

[0144] Step 5:

[0145] The server uses the output of the emotion engine to select grant information from the database that matches the user's needs and emotional state, and generates a list of recommendations.

[0146] Step 6:

[0147] The server generates a list of recommendations, which is sent to the user's device for display. The user then uses this information to select the appropriate grant.

[0148] Step 7:

[0149] The user begins the application process for the grant they selected and enters the required information on the terminal.

[0150] Step 8:

[0151] The terminal sends the entered information to the server, which automatically generates the application documents. The documents are customized according to the required format.

[0152] Step 9:

[0153] The server continuously monitors the progress of the application and adjusts the content and timing of notifications sent to the terminal based on the stress assessment results from sentiment analysis.

[0154] Step 10:

[0155] The user checks the notification on their device, performs any missing procedures or actions, and completes the application.

[0156] (Example 2)

[0157] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0158] When non-profit organizations seek funding, they often face challenges in efficiently gathering appropriate funding information and smoothly navigating the application process. In particular, optimizing information provision and notifications based on the emotional state of the recipient is crucial, but effective means to achieve this are lacking.

[0159] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0160] In this invention, the server includes means for collecting financial information for non-profit organizations, means for analyzing the financial information based on a user's request, and means for identifying the user's emotional state. This enables the recommendation of optimal financial information tailored to the user's emotional state and notification at an appropriate time.

[0161] A "non-profit organization" is an organization that does not aim to make a profit and pursues social objectives or the public good.

[0162] "Funding information" refers to information about grants, donations, and other sources of funding that provide the necessary funds for a particular project or activity.

[0163] A "user" refers to an individual or organization that uses this system to obtain financial information or receive support for application procedures.

[0164] "Analysis" refers to the process of analyzing collected data to derive useful information.

[0165] "Emotional state" refers to the psychological condition of a user, such as their feelings and mood, and is a state in which their actions and decisions are influenced based on this state.

[0166] A "notification" is a message or alert sent by a system to inform users of information or important updates.

[0167] "Document generation" refers to the process of automatically creating official documents and application forms required for specific activities or purposes.

[0168] "Progress control" refers to management activities that monitor the status of ongoing processes and projects and make adjustments or improvements as needed.

[0169] The grant support system of this invention enables non-profit organizations to effectively raise funds. This system is built on the interaction of servers, terminals, and users.

[0170] The server collects funding information related to non-profit organizations from publicly available resources on the internet and dedicated information services via the network. This collection process utilizes hardware and software such as web scraping techniques and APIs. The collected information is organized and stored in a database, enabling efficient searching and analysis.

[0171] The user accesses the system via a terminal and begins searching for financial information. The terminal accepts voice and text input from the user, and uses natural language processing to detect the user's emotional state. In this process, a generative AI model called an emotion engine is used to evaluate and analyze the user's emotional data.

[0172] The server uses emotional data analyzed by the emotion engine to select financial information from the database that matches the user's needs. Furthermore, it can adjust the presentation method and notification timing according to the user's emotional state to provide optimal recommendations.

[0173] For example, if a user is searching for funding for a child's educational project, and an emotional state indicating anxiety is detected during the search on their device, the server will send additional reassuring information along with more detailed grant information to the device, and, if necessary, provide options to connect with relevant experts.

[0174] An example of a prompt message could be a specific question from a user, such as, "I want to raise funds for a children's education project, but I'm unsure which grant to choose. Could you please provide specific information and support to alleviate my worries and anxieties?"

[0175] In this way, the present invention provides a comprehensive solution to facilitate fundraising for non-profit organizations while taking emotional factors into consideration.

[0176] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0177] Step 1:

[0178] The server collects funding information from the internet. Specifically, it retrieves data from publicly available websites and dedicated APIs. Inputs include URLs and API keys of funding organizations, and output is a list of data such as the name of the funding source, eligibility requirements, and application deadline. This allows the server to form a foundation of funding information available to nonprofit organizations.

[0179] Step 2:

[0180] Users log in to the system via a terminal and enter search criteria for the funding information they are looking for. Specifically, this primarily involves entering details of the purpose and target project in text format. This input includes project name, budget range, and geographical restrictions, which the terminal then transfers as digital data to the server. The output is a list of funding sources that meet the user's criteria.

[0181] Step 3:

[0182] The device performs voice emotion analysis when the user inputs. Emotional data is extracted from the user's voice and text using a generative AI model. The input consists of the user's voice files and text data, and the output is numerical data indicating positivity and stress levels. This allows the user's emotional state to be understood.

[0183] Step 4:

[0184] The server analyzes the user's emotional data and selects the most suitable financial information. Database searches perform data calculations based on the user's emotional state, requirements, and collected financial information. Inputs are the user's emotional score and search criteria, and output is a list of recommended financial information. This allows the server to provide financial information optimized to the user's needs.

[0185] Step 5:

[0186] The server notifies the user of the selected fund list. The notification is configured to include detailed explanations and links to related materials. The input is the selected fund information and its description, and the output is in the form of a notification message. As a result, the user is supported in reviewing the fund information and making appropriate selections.

[0187] Step 6:

[0188] The device will offer options for additional support from experts as needed. For funds the user has expressed interest in, it will display information on consulting services and related events. Inputs include data on the user's selected funds and emotional state, while outputs include guidance on connecting with experts and support information. This allows users to receive deeper, more specific assistance.

[0189] (Application Example 2)

[0190] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0191] For non-profit organizations to raise funds efficiently, it is essential to handle appropriate funding information in a timely and accurate manner. However, when users are in an emotionally unstable state, the funding application process may not proceed smoothly, potentially resulting in lost opportunities. Furthermore, the lack of information provision features that take emotional states into consideration hinders the ability to enhance users' sense of security.

[0192] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0193] In this invention, the server includes means for collecting funding information for non-profit organizations, means for analyzing funding information based on user requests, and means for analyzing the user's emotional state and providing security information based on the emotional state. This enables efficient fundraising while enhancing a sense of security by providing appropriate funding information according to the user's emotional state.

[0194] A "non-profit organization" is an organization that operates for social purposes rather than for profit.

[0195] "Funding information" refers to information about financial resources that support an organization's activities, such as grants and donations.

[0196] "User requirements" refer to the conditions and preferences that a user needs when using the system.

[0197] "Emotional state" refers to the user's psychological and emotional condition, expressed as a degree such as positive or negative.

[0198] "Analysis" is the process of breaking down complex data and information to understand its structure and meaning.

[0199] "Security information" refers to information related to safety, including guidance and instructions to ensure that system users can operate with peace of mind.

[0200] "A sense of security" refers to the feeling of psychological safety that users experience, allowing them to use the system without stress.

[0201] "Efficient fundraising" is the process of obtaining the maximum amount of funds with the minimum amount of time and energy.

[0202] This invention is a system for efficiently processing funding information for non-profit organizations and providing appropriate information according to the user's emotional state. Specifically, the server automatically collects funding information from the internet and builds a database. When performing analysis based on this data, the system uses voice and text data transmitted from the user's terminal to analyze the user's emotional state.

[0203] The analysis uses emotion recognition software to calculate the degree of negative or positive emotions. This analysis result is then utilized by an information recommendation system to select and provide funding information that best matches the user's needs. Furthermore, a notification management system determines the optimal timing for sending information based on the emotional state and notifies the device accordingly.

[0204] In the process of users obtaining information using this system, the system can also provide detailed and security information to offer emotional reassurance. For example, if a user feels anxious while trying to raise funds for an event involving many people, the system can prioritize displaying relevant resources and support information to enhance their sense of security.

[0205] An example of a prompt message is one that shows specific output tailored to the expected usage scenario, such as, "Show how to analyze sentiment data and provide appropriate security guidance for that situation."

[0206] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0207] Step 1:

[0208] The server periodically collects funding information from the internet and updates its database. This collection process uses web scraping techniques to obtain the latest grant and donation information. The input consists of data from various public and private funding portals, and the output is funding information stored in the database in a standardized format.

[0209] Step 2:

[0210] Users log in to the system using a terminal and enter their desired funding conditions. These conditions include the type of project, the required funding amount, and the deadline. The input is text-based requirements provided by the user, and the output is specific request data that the system uses to prepare for analysis.

[0211] Step 3:

[0212] The device extracts emotional data from the user's voice or text and sends it to the server. This process uses speech recognition and text analysis technologies to convert emotional states into numerical data. The input is voice or text indicating the user's emotions, and the output is digital data including an emotional score.

[0213] Step 4:

[0214] The server analyzes the received emotional data using an emotion recognition engine to determine whether the emotion is positive or negative. The input is the emotional score sent from the terminal, and the output is a score report as a result of the emotion analysis.

[0215] Step 5:

[0216] The server uses sentiment analysis results to match the user's request with the most suitable funding information through its information recommendation system. This process uses machine learning algorithms to narrow down the choices to those with the highest degree of match. The input is the sentiment score and user request data, and the output is a list of recommended funding options.

[0217] Step 6:

[0218] The server uses a notification management system to inform the user of information at the optimal time. Based on the results of sentiment analysis, it selects a timing that takes into account the user's stress levels and sense of security. The input is the user's emotional state and recommendation information, and the output is the notification message sent to the user.

[0219] Step 7:

[0220] Users refer to funding information through notifications they receive and initiate the application process if necessary. During this process, the system provides templates for the required documents, assisting users in easily submitting their applications. Inputs are inquiries based on user actions, and outputs are guidance regarding the application process.

[0221] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0222] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0223] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0224] [Second Embodiment]

[0225] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0226] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0227] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0228] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0229] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0230] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0231] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0232] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0233] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0234] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0235] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0236] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. 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".

[0237] This invention is a system that helps non-profit organizations efficiently obtain grants. The system provides users with multiple means to efficiently collect grant information, select the most suitable grants, and simplify the application process.

[0238] The system's program consists of the following main functions. First, to collect grant information from various sources on the internet, the server performs regular web scraping to build a reliable database. This makes it possible to efficiently manage large amounts of complex grant information.

[0239] When a user logs into the system, the terminal sends the user's requests and requirements to the server. The server uses artificial intelligence to analyze grant information that matches the user's needs and presents it to the terminal. This allows the user to easily find the grant that is best suited to them.

[0240] Furthermore, to assist with grant applications, the server creates templates for the necessary application documents and customizes them based on the information entered by the user. This allows users to prepare application documents quickly and accurately.

[0241] After an application is submitted, the server monitors its progress and sends important notifications and reminders to the user via their device as needed. By receiving these notifications, users can stay informed about the status of their application and take necessary actions in a timely manner.

[0242] As a concrete example, consider a non-profit organization using this system to raise funds for operating a children's cafeteria in a poverty-stricken area. The organization's representative logs in via a terminal and enters conditions related to the region and purpose, and the server recommends specific grants and supports the application process. In this way, the organization can efficiently navigate the complex grant application process and focus on its core business.

[0243] Based on the above, this invention aims to streamline fundraising for non-profit organizations and support the maximization of social value.

[0244] The following describes the processing flow.

[0245] Step 1:

[0246] The server periodically scrapes grant information from reliable sources on the internet, organizes the information, and stores it in a database.

[0247] Step 2:

[0248] Users log in to the system on their terminal and enter their grant search criteria and personal needs.

[0249] Step 3:

[0250] The terminal sends the information entered by the user to the server, which then uses artificial intelligence to analyze the database and find grants that match the user's criteria.

[0251] Step 4:

[0252] The server sends a list of grant candidates to the terminal, which the user reviews and selects the appropriate grant.

[0253] Step 5:

[0254] The user initiates the application process for the grant they have selected and enters the necessary information through their device.

[0255] Step 6:

[0256] The terminal sends user input information to the server, which then customizes and generates application form templates based on that information.

[0257] Step 7:

[0258] The server sends the generated application documents to the user's terminal, which the user then downloads, modifies as needed, and submits.

[0259] Step 8:

[0260] The server constantly monitors the progress of the application and notifies the user via their terminal if there are any significant status changes.

[0261] Step 9:

[0262] The user checks the notification on their device and takes additional action as needed.

[0263] (Example 1)

[0264] Next, we will describe Example 1. 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."

[0265] For nonprofit organizations, the process of gathering information on grants and submitting applications is complex and time-consuming. In particular, collecting accurate and up-to-date information from diverse sources, finding grants that meet the specific needs of their users, and efficiently preparing applications and managing the process are all challenging. This situation makes it difficult for nonprofit organizations to focus on their core activities.

[0266] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0267] In this invention, the server includes means for collecting financial assistance information from information sources, means for analyzing financial assistance information based on user requests, means for recommending the most suitable financial assistance, means for creating documents, means for managing the progress of the application process, and means for communicating important updates. This enables non-profit organizations to efficiently obtain appropriate grant information and proceed with the application process quickly and accurately.

[0268] "Information sources" refer to information on financial support related to the present invention, provided by government agencies, foundations, etc., that exist on the internet.

[0269] "Financial support information" refers to detailed information about financial support such as grants and subsidies available to non-profit organizations.

[0270] "Users" refers to non-profit organizations or similar entities that use this system to seek and apply for financial assistance.

[0271] "Requests" refer to information that users communicate through the system, indicating specific conditions or desired support.

[0272] "Means of analysis" refers to methods and techniques for analyzing collected financial support information based on the user's requests.

[0273] "Recommended measures" refers to a function that selects and presents appropriate financial support to users based on the analysis results.

[0274] "Document" refers to a structured document containing information that users create and submit, such as forms and documents required for applying for financial assistance.

[0275] "Means of managing the progress of the application process" refers to functions that monitor the progress of the entire financial assistance application process and support its smooth execution.

[0276] "Updates" refer to content that conveys important changes or additions to the application process or financial support information.

[0277] "Means of communication" refers to methods used to notify or inform users of updates.

[0278] This system is designed to help non-profit organizations efficiently obtain grants and requires coordination between servers, terminals, and users.

[0279] First, the server uses web scraping techniques to collect financial support information from various sources on the internet. This process utilizes open-source web scraping tools such as Beautiful Soup and Scrapy. The collected data is then organized and stored using a database system (e.g., MySQL, PostgreSQL).

[0280] After that, the user accesses the system through the terminal and inputs the requests and conditions of their organization. These conditions include the target area, field of activity, amount of funds required, etc.

[0281] The terminal sends the information input by the user to the server. The server uses a generative AI model (e.g., GPT-4 or BERT) to analyze the information in the database and identify the economic support information that best matches the user's requests. As a result, the user can obtain information on the optimal subsidy.

[0282] As a specific example, when a non-profit organization raises funds for educational support, by inputting a prompt sentence such as "Looking for subsidies for regional education. The activity area is the urban area, and the focus is on supporting low-income families.", it is possible to obtain specific subsidy information.

[0283] Furthermore, the server generates a template for the documents required to apply for the identified subsidy. In this process, software such as Word or Google Docs is utilized, and based on the information input by the user, the document template is customized.

[0284] Finally, the server monitors the progress of the application procedure and notifies the user of important update information through a smartphone or computer terminal as needed. As a result, the user can respond in a timely manner.

[0285] The flow of the specific process in Example 1 will be described using FIG. 11.

[0286] Step 1:

[0287] The server collects financial support information from its sources. Specifically, it uses web scraping tools such as Beautiful Soup and Scrapy to retrieve information from specified URLs. This process involves scheduling regular scraping operations. The input is a list of URLs, and the output is the scraped raw data.

[0288] Step 2:

[0289] The server stores the collected raw data in a database. Using database systems such as MySQL or PostgreSQL, the server converts the acquired data into a structured format. It removes duplicate and invalid data, extracts only the necessary field information, and stores it in the database. The input is the scraped raw data, and the output is an organized database entry.

[0290] Step 3:

[0291] Users log in to the system via their terminal. Users gain access to the system by entering their personal information and organizational details. The input is a user registration form, and the output is an authenticated status indicating the start of a session.

[0292] Step 4:

[0293] The user enters search criteria for support information on the terminal. They specify the target region, activity area, and required funding amount. The terminal formats the entered criteria and prepares to send them to the server. The input is the user's search criteria, and the output is the search query sent to the server.

[0294] Step 5:

[0295] The server searches the database based on the received search query. It then uses a generative AI model (e.g., GPT-4) to analyze the most relevant assistive information that matches the criteria. The input is the query sent to the server, and the output is a list of recommended assistive information.

[0296] Step 6:

[0297] The terminal displays recommended support information received from the server to the user. The user can review the information and click on options of interest to obtain more details. The input is a list of support information sent from the server, and the output is the detailed information displayed to the user.

[0298] Step 7:

[0299] The server generates application documents based on the selected support information. Using Word or Google Docs, it creates customized documents based on the information entered by the user. Input consists of the user-selected support information and prompt text, while output is an application document template.

[0300] Step 8:

[0301] The server monitors the progress of the application process and notifies the user as needed. It uses a progress management system to check submission deadlines and important updates, and sends alerts to the user via their terminal. Input is application status data, and output is notification messages delivered to the user.

[0302] (Application Example 1)

[0303] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0304] In order for non-profit organizations to raise funds efficiently and safely, it is necessary to quickly carry out a complex process that includes collecting subsidy information, selecting the optimal funds, and creating and managing application documents. Also, while digitization is progressing, the risk of data security being threatened is increasing. It is desirable to provide a system that solves these problems and creates an environment in which non-profit organizations can concentrate on their original activities.

[0305] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0306] In this invention, the server includes means for collecting fund information for non-profit organizations, means for analyzing the fund information based on the user's request, and means for presenting the optimal funds to the user based on the analysis result. As a result, non-profit organizations can raise funds efficiently and safely and can focus on their original social contribution activities.

[0307] A "non-profit organization" is an organization that does not pursue profit and mainly conducts activities for social contribution and public benefit.

[0308] "Fund information" refers to detailed information on various funding sources and subsidies, which includes providers, conditions, available amounts, etc.

[0309] "Analysis" refers to an analytical act of deriving information optimal for a specific purpose based on the obtained data.

[0310] "Application documents" refer to official documents created in a certain format for submission to fund providers.

[0311] "Means for monitoring" is a mechanism for constantly checking specific activities and progress within the system and taking corresponding actions as necessary.

[0312] "Means for notifying" refers to a function or mechanism for notifying users of important information and progress status.

[0313] "Encryption technology" is a technology that transforms data to protect it from unauthorized access, and plays a role in maintaining data confidentiality.

[0314] "Biometric authentication technology" is a method of authenticating individuals using human physical characteristics such as fingerprints or facial recognition.

[0315] The system based on this invention is designed to enable non-profit organizations to securely and efficiently raise funds. The server first collects funding information from the internet using web scraping tools (e.g., Beautiful Soup, Scrapy) and API integration. The collected data is securely stored in a cloud database (e.g., Firebase, AWS RDS) using encryption technology. The server then analyzes this information using AI technology (e.g., TensorFlow, PyTorch) to extract the most suitable funding information for the user's needs.

[0316] The device securely provides the user with analyzed information through biometric authentication (e.g., iOS Face ID, Android Fingerprint API). This biometric authentication technology protects the user's personal information and prevents unauthorized access to the system. Users can prepare application documents based on the provided financial information in a secure environment.

[0317] As a concrete example, suppose an organization operating a children's cafeteria in a certain region uses this system for fundraising. In this case, the representative uses a smartphone to log in via biometric authentication. The AI ​​then selects the most suitable grant from the fundraising information it provides, and the representative can download application form templates available on the cloud and proceed with the application quickly.

[0318] An example of a prompt might be: "Our non-profit organization runs a local children's cafeteria. Please tell us about the best grants available to efficiently raise operating funds, and also provide us with the necessary documents for the application process." Based on this prompt, the AI ​​will provide appropriate funding information and support the application process.

[0319] As a result, this system enables non-profit organizations to manage their funds more efficiently and concentrate resources on necessary social activities.

[0320] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0321] Step 1:

[0322] The server uses web scraping tools and APIs to collect financial information from the internet. This includes detailed information on various sources of funding. It uses internet URLs and API endpoints as input and obtains structured data (e.g., in JSON format) containing financial information as output. The server sends this data to a cloud database for secure management.

[0323] Step 2:

[0324] The server uses an artificial intelligence model to analyze data based on financial information stored in a cloud database. It receives user requests and conditions as input, and the AI ​​model analyzes this data to select the most suitable financial information for the user. This process yields the optimal financial information to be presented to the user as output.

[0325] Step 3:

[0326] The terminal uses biometric authentication technology to verify the user's identity and provides financial information in a secure manner. It acquires the user's biometric data (facial recognition or fingerprint data) as input, and upon successful authentication, displays the financial information received from the server to the user as output. The terminal then supports the user in taking the next action based on this information.

[0327] Step 4:

[0328] Users can view optimized financial information via their device and begin creating application documents as needed. The system takes the financial information selected by the user as input and generates document templates in the cloud. As output, users receive customized application documents, which they can use to quickly submit their applications.

[0329] Step 5:

[0330] The server monitors the progress of the application process and sends notifications to users via their terminals as needed. It monitors log data and application status trends as input and generates notifications to remind users of important updates (e.g., application approval status and next steps) as output. This allows users to take action at the appropriate time.

[0331] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0332] This invention provides enhanced convenience to a grant support system for non-profit organizations to efficiently raise funds by incorporating an emotion engine that recognizes user emotions. This system analyzes the user's emotional state, recommends optimal grant information based on that analysis, and notifies the user at the appropriate time.

[0333] The system's configuration involves a server that collects grant information from the internet and builds a database. When a user logs in via a terminal and enters search criteria for grants, the terminal collects user sentiment data obtained through voice and text.

[0334] Emotional data is transferred to a server and analyzed by an emotion engine. This engine determines the degree of positive or negative emotion, associates it with information in a database built into the user's needs, and selects appropriate subsidy information. Through this process, the server generates a recommendation list that matches the user's emotions and sends this information to the terminal.

[0335] Furthermore, the emotion engine also has the ability to adjust the timing of alerts and optimize progress notifications according to the user's stress level and level of interest. For example, if a user is feeling anxious about their grant application, the server can reassure them by sending a notification with added detailed explanations.

[0336] For example, if a user is looking for funding for a child's educational project, the system can detect their heightened emotions during their search on their device. Based on this information, the server can provide more helpful details about relevant grants and send notifications recommending expert support if necessary.

[0337] In this way, the present invention can support the support activities of non-profit organizations from an emotional perspective and make the fundraising process smoother and more effective.

[0338] The following describes the processing flow.

[0339] Step 1:

[0340] The server regularly collects the latest grant information from reliable sources on the internet and updates the database.

[0341] Step 2:

[0342] The user logs into the system using their device and enters their search criteria for grants.

[0343] Step 3:

[0344] The device collects user sentiment data from voice and text input and sends it to the server.

[0345] Step 4:

[0346] The server analyzes the received emotional data using an emotion engine to determine the user's emotional state. Based on this analysis, the search criteria for grants corresponding to the user's emotions are fine-tuned.

[0347] Step 5:

[0348] The server uses the output of the emotion engine to select grant information from the database that matches the user's needs and emotional state, and generates a list of recommendations.

[0349] Step 6:

[0350] The server generates a list of recommendations, which is sent to the user's device for display. The user then uses this information to select the appropriate grant.

[0351] Step 7:

[0352] The user begins the application process for the grant they selected and enters the required information on the terminal.

[0353] Step 8:

[0354] The terminal sends the entered information to the server, which automatically generates the application documents. The documents are customized according to the required format.

[0355] Step 9:

[0356] The server continuously monitors the progress of the application and adjusts the content and timing of notifications sent to the terminal based on the stress assessment results from sentiment analysis.

[0357] Step 10:

[0358] The user checks the notification on their device, performs any missing procedures or actions, and completes the application.

[0359] (Example 2)

[0360] Next, we will describe Example 2. 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".

[0361] When non-profit organizations seek funding, they often face challenges in efficiently gathering appropriate funding information and smoothly navigating the application process. In particular, optimizing information provision and notifications based on the emotional state of the recipient is crucial, but effective means to achieve this are lacking.

[0362] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0363] In this invention, the server includes means for collecting financial information for non-profit organizations, means for analyzing the financial information based on a user's request, and means for identifying the user's emotional state. This enables the recommendation of optimal financial information tailored to the user's emotional state and notification at an appropriate time.

[0364] A "non-profit organization" is an organization that does not aim to make a profit and pursues social objectives or the public good.

[0365] "Funding information" refers to information about grants, donations, and other sources of funding that provide the necessary funds for a particular project or activity.

[0366] A "user" refers to an individual or organization that uses this system to obtain financial information or receive support for application procedures.

[0367] "Analysis" refers to the process of analyzing collected data to derive useful information.

[0368] "Emotional state" refers to the psychological condition of a user, such as their feelings and mood, and is a state in which their actions and decisions are influenced based on this state.

[0369] A "notification" is a message or alert sent by a system to inform users of information or important updates.

[0370] "Document generation" refers to the process of automatically creating official documents and application forms required for specific activities or purposes.

[0371] "Progress control" refers to management activities that monitor the status of ongoing processes and projects and make adjustments or improvements as needed.

[0372] The grant support system of this invention enables non-profit organizations to effectively raise funds. This system is built on the interaction of servers, terminals, and users.

[0373] The server collects funding information related to non-profit organizations from publicly available resources on the internet and dedicated information services via the network. This collection process utilizes hardware and software such as web scraping techniques and APIs. The collected information is organized and stored in a database, enabling efficient searching and analysis.

[0374] The user accesses the system via a terminal and begins searching for financial information. The terminal accepts voice and text input from the user, and uses natural language processing to detect the user's emotional state. In this process, a generative AI model called an emotion engine is used to evaluate and analyze the user's emotional data.

[0375] The server uses emotional data analyzed by the emotion engine to select financial information from the database that matches the user's needs. Furthermore, it can adjust the presentation method and notification timing according to the user's emotional state to provide optimal recommendations.

[0376] For example, if a user is searching for funding for a child's educational project, and an emotional state indicating anxiety is detected during the search on their device, the server will send additional reassuring information along with more detailed grant information to the device, and, if necessary, provide options to connect with relevant experts.

[0377] An example of a prompt message could be a specific question from a user, such as, "I want to raise funds for a children's education project, but I'm unsure which grant to choose. Could you please provide specific information and support to alleviate my worries and anxieties?"

[0378] In this way, the present invention provides a comprehensive solution to facilitate fundraising for non-profit organizations while taking emotional factors into consideration.

[0379] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0380] Step 1:

[0381] The server collects funding information from the internet. Specifically, it retrieves data from publicly available websites and dedicated APIs. Inputs include URLs and API keys of funding organizations, and output is a list of data such as the name of the funding source, eligibility requirements, and application deadline. This allows the server to form a foundation of funding information available to nonprofit organizations.

[0382] Step 2:

[0383] Users log in to the system via a terminal and enter search criteria for the funding information they are looking for. Specifically, this primarily involves entering details of the purpose and target project in text format. This input includes project name, budget range, and geographical restrictions, which the terminal then transfers as digital data to the server. The output is a list of funding sources that meet the user's criteria.

[0384] Step 3:

[0385] The device performs voice emotion analysis when the user inputs. Emotional data is extracted from the user's voice and text using a generative AI model. The input consists of the user's voice files and text data, and the output is numerical data indicating positivity and stress levels. This allows the user's emotional state to be understood.

[0386] Step 4:

[0387] The server analyzes the user's emotional data and selects the most suitable financial information. Database searches perform data calculations based on the user's emotional state, requirements, and collected financial information. Inputs are the user's emotional score and search criteria, and output is a list of recommended financial information. This allows the server to provide financial information optimized to the user's needs.

[0388] Step 5:

[0389] The server notifies the user of the selected fund list. The notification is configured to include detailed explanations and links to related materials. The input is the selected fund information and its description, and the output is in the form of a notification message. As a result, the user is supported in reviewing the fund information and making appropriate selections.

[0390] Step 6:

[0391] The device will offer options for additional support from experts as needed. For funds the user has expressed interest in, it will display information on consulting services and related events. Inputs include data on the user's selected funds and emotional state, while outputs include guidance on connecting with experts and support information. This allows users to receive deeper, more specific assistance.

[0392] (Application Example 2)

[0393] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0394] For non-profit organizations to raise funds efficiently, it is essential to handle appropriate funding information in a timely and accurate manner. However, when users are in an emotionally unstable state, the funding application process may not proceed smoothly, potentially resulting in lost opportunities. Furthermore, the lack of information provision features that take emotional states into consideration hinders the ability to enhance users' sense of security.

[0395] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0396] In this invention, the server includes means for collecting funding information for non-profit organizations, means for analyzing funding information based on user requests, and means for analyzing the user's emotional state and providing security information based on the emotional state. This enables efficient fundraising while enhancing a sense of security by providing appropriate funding information according to the user's emotional state.

[0397] A "non-profit organization" is an organization that operates for social purposes rather than for profit.

[0398] "Funding information" refers to information about financial resources that support an organization's activities, such as grants and donations.

[0399] "User requirements" refer to the conditions and preferences that a user needs when using the system.

[0400] "Emotional state" refers to the user's psychological and emotional condition, expressed as a degree such as positive or negative.

[0401] "Analysis" is the process of breaking down complex data and information to understand its structure and meaning.

[0402] "Security information" refers to information related to safety, including guidance and instructions to ensure that system users can operate with peace of mind.

[0403] "A sense of security" refers to the feeling of psychological safety that users experience, allowing them to use the system without stress.

[0404] "Efficient fundraising" is the process of obtaining the maximum amount of funds with the minimum amount of time and energy.

[0405] This invention is a system for efficiently processing funding information for non-profit organizations and providing appropriate information according to the user's emotional state. Specifically, the server automatically collects funding information from the internet and builds a database. When performing analysis based on this data, the system uses voice and text data transmitted from the user's terminal to analyze the user's emotional state.

[0406] The analysis uses emotion recognition software to calculate the degree of negative or positive emotions. This analysis result is then utilized by an information recommendation system to select and provide funding information that best matches the user's needs. Furthermore, a notification management system determines the optimal timing for sending information based on the emotional state and notifies the device accordingly.

[0407] In the process of users obtaining information using this system, the system can also provide detailed and security information to offer emotional reassurance. For example, if a user feels anxious while trying to raise funds for an event involving many people, the system can prioritize displaying relevant resources and support information to enhance their sense of security.

[0408] An example of a prompt message is one that shows specific output tailored to the expected usage scenario, such as, "Show how to analyze sentiment data and provide appropriate security guidance for that situation."

[0409] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0410] Step 1:

[0411] The server periodically collects funding information from the internet and updates its database. This collection process uses web scraping techniques to obtain the latest grant and donation information. The input consists of data from various public and private funding portals, and the output is funding information stored in the database in a standardized format.

[0412] Step 2:

[0413] Users log in to the system using a terminal and enter their desired funding conditions. These conditions include the type of project, the required funding amount, and the deadline. The input is text-based requirements provided by the user, and the output is specific request data that the system uses to prepare for analysis.

[0414] Step 3:

[0415] The device extracts emotional data from the user's voice or text and sends it to the server. This process uses speech recognition and text analysis technologies to convert emotional states into numerical data. The input is voice or text indicating the user's emotions, and the output is digital data including an emotional score.

[0416] Step 4:

[0417] The server analyzes the received emotional data using an emotion recognition engine to determine whether the emotion is positive or negative. The input is the emotional score sent from the terminal, and the output is a score report as a result of the emotion analysis.

[0418] Step 5:

[0419] The server uses sentiment analysis results to match the user's request with the most suitable funding information through its information recommendation system. This process uses machine learning algorithms to narrow down the choices to those with the highest degree of match. The input is the sentiment score and user request data, and the output is a list of recommended funding options.

[0420] Step 6:

[0421] The server uses a notification management system to inform the user of information at the optimal time. Based on the results of sentiment analysis, it selects a timing that takes into account the user's stress levels and sense of security. The input is the user's emotional state and recommendation information, and the output is the notification message sent to the user.

[0422] Step 7:

[0423] Users refer to funding information through notifications they receive and initiate the application process if necessary. During this process, the system provides templates for the required documents, assisting users in easily submitting their applications. Inputs are inquiries based on user actions, and outputs are guidance regarding the application process.

[0424] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0425] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0426] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0427] [Third Embodiment]

[0428] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0429] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0430] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0431] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0432] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0433] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0434] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0435] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0436] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0437] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0438] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0439] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0440] This invention is a system that helps non-profit organizations efficiently obtain grants. The system provides users with multiple means to efficiently collect grant information, select the most suitable grants, and simplify the application process.

[0441] The system's program consists of the following main functions. First, to collect grant information from various sources on the internet, the server performs regular web scraping to build a reliable database. This makes it possible to efficiently manage large amounts of complex grant information.

[0442] When a user logs into the system, the terminal sends the user's requests and requirements to the server. The server uses artificial intelligence to analyze grant information that matches the user's needs and presents it to the terminal. This allows the user to easily find the grant that is best suited to them.

[0443] Furthermore, to assist with grant applications, the server creates templates for the necessary application documents and customizes them based on the information entered by the user. This allows users to prepare application documents quickly and accurately.

[0444] After an application is submitted, the server monitors its progress and sends important notifications and reminders to the user via their device as needed. By receiving these notifications, users can stay informed about the status of their application and take necessary actions in a timely manner.

[0445] As a concrete example, consider a non-profit organization using this system to raise funds for operating a children's cafeteria in a poverty-stricken area. The organization's representative logs in via a terminal and enters conditions related to the region and purpose, and the server recommends specific grants and supports the application process. In this way, the organization can efficiently navigate the complex grant application process and focus on its core business.

[0446] Based on the above, this invention aims to streamline fundraising for non-profit organizations and support the maximization of social value.

[0447] The following describes the processing flow.

[0448] Step 1:

[0449] The server periodically scrapes grant information from reliable sources on the internet, organizes the information, and stores it in a database.

[0450] Step 2:

[0451] Users log in to the system on their terminal and enter their grant search criteria and personal needs.

[0452] Step 3:

[0453] The terminal sends the information entered by the user to the server, which then uses artificial intelligence to analyze the database and find grants that match the user's criteria.

[0454] Step 4:

[0455] The server sends a list of grant candidates to the terminal, which the user reviews and selects the appropriate grant.

[0456] Step 5:

[0457] The user initiates the application process for the grant they have selected and enters the necessary information through their device.

[0458] Step 6:

[0459] The terminal sends user input information to the server, which then customizes and generates application form templates based on that information.

[0460] Step 7:

[0461] The server sends the generated application documents to the user's terminal, which the user then downloads, modifies as needed, and submits.

[0462] Step 8:

[0463] The server constantly monitors the progress of the application and notifies the user via their terminal if there are any significant status changes.

[0464] Step 9:

[0465] The user checks the notification on their device and takes additional action as needed.

[0466] (Example 1)

[0467] Next, we will describe Example 1. 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."

[0468] For nonprofit organizations, the process of gathering information on grants and submitting applications is complex and time-consuming. In particular, collecting accurate and up-to-date information from diverse sources, finding grants that meet the specific needs of their users, and efficiently preparing applications and managing the process are all challenging. This situation makes it difficult for nonprofit organizations to focus on their core activities.

[0469] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0470] In this invention, the server includes means for collecting financial assistance information from information sources, means for analyzing financial assistance information based on user requests, means for recommending the most suitable financial assistance, means for creating documents, means for managing the progress of the application process, and means for communicating important updates. This enables non-profit organizations to efficiently obtain appropriate grant information and proceed with the application process quickly and accurately.

[0471] "Information sources" refer to information on financial support related to the present invention, provided by government agencies, foundations, etc., that exist on the internet.

[0472] "Financial support information" refers to detailed information about financial support such as grants and subsidies available to non-profit organizations.

[0473] "Users" refers to non-profit organizations or similar entities that use this system to seek and apply for financial assistance.

[0474] "Requests" refer to information that users communicate through the system, indicating specific conditions or desired support.

[0475] "Means of analysis" refers to methods and techniques for analyzing collected financial support information based on the user's requests.

[0476] "Recommended measures" refers to a function that selects and presents appropriate financial support to users based on the analysis results.

[0477] "Document" refers to a structured document containing information that users create and submit, such as forms and documents required for applying for financial assistance.

[0478] "Means of managing the progress of the application process" refers to functions that monitor the progress of the entire financial assistance application process and support its smooth execution.

[0479] "Updates" refer to content that conveys important changes or additions to the application process or financial support information.

[0480] "Means of communication" refers to methods used to notify or inform users of updates.

[0481] This system is designed to help non-profit organizations efficiently obtain grants and requires coordination between servers, terminals, and users.

[0482] First, the server uses web scraping techniques to collect financial support information from various sources on the internet. This process utilizes open-source web scraping tools such as Beautiful Soup and Scrapy. The collected data is then organized and stored using a database system (e.g., MySQL, PostgreSQL).

[0483] Subsequently, users access the system via their devices and input their organization's requests and requirements. These requirements include the target region, area of ​​activity, and the amount of funding needed.

[0484] The terminal sends the information entered by the user to the server. The server uses a generative AI model (e.g., GPT-4 or BERT) to analyze the information in the database and identify the financial support information that best matches the user's needs. This allows the user to obtain information on the most suitable grants.

[0485] For example, if a non-profit organization is seeking funding for educational support, a user can obtain specific grant information by entering a prompt such as, "I am looking for grants for local education. The activity area is urban, and the focus is on supporting low-income families."

[0486] Furthermore, the server generates templates for the documents required to apply for the identified grants. This process utilizes software such as Word and Google Docs, and the document templates are customized based on the information entered by the user.

[0487] Finally, the server monitors the progress of the application process and notifies users of important updates via smartphones or computer terminals as needed. This allows users to respond in a timely manner.

[0488] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0489] Step 1:

[0490] The server collects financial support information from its sources. Specifically, it uses web scraping tools such as Beautiful Soup and Scrapy to retrieve information from specified URLs. This process involves scheduling regular scraping operations. The input is a list of URLs, and the output is the scraped raw data.

[0491] Step 2:

[0492] The server stores the collected raw data in a database. Using database systems such as MySQL or PostgreSQL, the server converts the acquired data into a structured format. It removes duplicate and invalid data, extracts only the necessary field information, and stores it in the database. The input is the scraped raw data, and the output is an organized database entry.

[0493] Step 3:

[0494] Users log in to the system via their terminal. Users gain access to the system by entering their personal information and organizational details. The input is a user registration form, and the output is an authenticated status indicating the start of a session.

[0495] Step 4:

[0496] The user enters search criteria for support information on the terminal. They specify the target region, activity area, and required funding amount. The terminal formats the entered criteria and prepares to send them to the server. The input is the user's search criteria, and the output is the search query sent to the server.

[0497] Step 5:

[0498] The server searches the database based on the received search query. It then uses a generative AI model (e.g., GPT-4) to analyze the most relevant assistive information that matches the criteria. The input is the query sent to the server, and the output is a list of recommended assistive information.

[0499] Step 6:

[0500] The terminal displays recommended support information received from the server to the user. The user can review the information and click on options of interest to obtain more details. The input is a list of support information sent from the server, and the output is the detailed information displayed to the user.

[0501] Step 7:

[0502] The server generates application documents based on the selected support information. Using Word or Google Docs, it creates customized documents based on the information entered by the user. Input consists of the user-selected support information and prompt text, while output is an application document template.

[0503] Step 8:

[0504] The server monitors the progress of the application process and notifies the user as needed. It uses a progress management system to check submission deadlines and important updates, and sends alerts to the user via their terminal. Input is application status data, and output is notification messages delivered to the user.

[0505] (Application Example 1)

[0506] Next, we will explain Application Example 1. In the following explanation, 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."

[0507] For non-profit organizations to secure funding efficiently and securely, they need to quickly navigate a complex process that includes gathering grant information, selecting the most suitable funds, and preparing and managing application documents. Furthermore, while digitalization is advancing, the risk of data security being compromised is also increasing. It is desirable to provide systems that address these challenges and create an environment where non-profit organizations can focus on their core activities.

[0508] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0509] In this invention, the server includes means for collecting financial information for non-profit organizations, means for analyzing the financial information based on user requests, and means for presenting the user with the most suitable funding based on the analysis results. This enables non-profit organizations to raise funds efficiently and securely, allowing them to focus on their core social contribution activities.

[0510] A "non-profit organization" is an organization that does not pursue profit and primarily operates with the aim of contributing to society or the public good.

[0511] "Funding information" refers to detailed information about various sources of funding and grants, including providers, conditions, and available amounts.

[0512] "Analysis" refers to the act of analyzing data to derive information that is optimal for a specific purpose.

[0513] "Application documents" refer to official documents prepared in a specific format for submission to funders.

[0514] A "monitoring mechanism" is a mechanism for constantly checking specific activities or progress within a system and taking action as needed.

[0515] "Means of notification" refers to a function or mechanism for informing users of important information or progress.

[0516] "Encryption technology" is a technology that transforms data to protect it from unauthorized access, and plays a role in maintaining data confidentiality.

[0517] "Biometric authentication technology" is a method of authenticating individuals using human physical characteristics such as fingerprints or facial recognition.

[0518] The system based on this invention is designed to enable non-profit organizations to securely and efficiently raise funds. The server first collects funding information from the internet using web scraping tools (e.g., Beautiful Soup, Scrapy) and API integration. The collected data is securely stored in a cloud database (e.g., Firebase, AWS RDS) using encryption technology. The server then analyzes this information using AI technology (e.g., TensorFlow, PyTorch) to extract the most suitable funding information for the user's needs.

[0519] The device securely provides the user with analyzed information through biometric authentication (e.g., iOS Face ID, Android Fingerprint API). This biometric authentication technology protects the user's personal information and prevents unauthorized access to the system. Users can prepare application documents based on the provided financial information in a secure environment.

[0520] As a concrete example, suppose an organization operating a children's cafeteria in a certain region uses this system for fundraising. In this case, the representative uses a smartphone to log in via biometric authentication. The AI ​​then selects the most suitable grant from the fundraising information it provides, and the representative can download application form templates available on the cloud and proceed with the application quickly.

[0521] An example of a prompt might be: "Our non-profit organization runs a local children's cafeteria. Please tell us about the best grants available to efficiently raise operating funds, and also provide us with the necessary documents for the application process." Based on this prompt, the AI ​​will provide appropriate funding information and support the application process.

[0522] As a result, this system enables non-profit organizations to manage their funds more efficiently and concentrate resources on necessary social activities.

[0523] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0524] Step 1:

[0525] The server uses web scraping tools and APIs to collect financial information from the internet. This includes detailed information on various sources of funding. It uses internet URLs and API endpoints as input and obtains structured data (e.g., in JSON format) containing financial information as output. The server sends this data to a cloud database for secure management.

[0526] Step 2:

[0527] The server uses an artificial intelligence model to analyze data based on financial information stored in a cloud database. It receives user requests and conditions as input, and the AI ​​model analyzes this data to select the most suitable financial information for the user. This process yields the optimal financial information to be presented to the user as output.

[0528] Step 3:

[0529] The terminal uses biometric authentication technology to verify the user's identity and provides financial information in a secure manner. It acquires the user's biometric data (facial recognition or fingerprint data) as input, and upon successful authentication, displays the financial information received from the server to the user as output. The terminal then supports the user in taking the next action based on this information.

[0530] Step 4:

[0531] Users can view optimized financial information via their device and begin creating application documents as needed. The system takes the financial information selected by the user as input and generates document templates in the cloud. As output, users receive customized application documents, which they can use to quickly submit their applications.

[0532] Step 5:

[0533] The server monitors the progress of the application process and sends notifications to users via their terminals as needed. It monitors log data and application status trends as input and generates notifications to remind users of important updates (e.g., application approval status and next steps) as output. This allows users to take action at the appropriate time.

[0534] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0535] This invention provides enhanced convenience to a grant support system for non-profit organizations to efficiently raise funds by incorporating an emotion engine that recognizes user emotions. This system analyzes the user's emotional state, recommends optimal grant information based on that analysis, and notifies the user at the appropriate time.

[0536] The system's configuration involves a server that collects grant information from the internet and builds a database. When a user logs in via a terminal and enters search criteria for grants, the terminal collects user sentiment data obtained through voice and text.

[0537] Emotional data is transferred to a server and analyzed by an emotion engine. This engine determines the degree of positive or negative emotion, associates it with information in a database built into the user's needs, and selects appropriate subsidy information. Through this process, the server generates a recommendation list that matches the user's emotions and sends this information to the terminal.

[0538] Furthermore, the emotion engine also has the ability to adjust the timing of alerts and optimize progress notifications according to the user's stress level and level of interest. For example, if a user is feeling anxious about their grant application, the server can reassure them by sending a notification with added detailed explanations.

[0539] For example, if a user is looking for funding for a child's educational project, the system can detect their heightened emotions during their search on their device. Based on this information, the server can provide more helpful details about relevant grants and send notifications recommending expert support if necessary.

[0540] In this way, the present invention can support the support activities of non-profit organizations from an emotional perspective and make the fundraising process smoother and more effective.

[0541] The following describes the processing flow.

[0542] Step 1:

[0543] The server regularly collects the latest grant information from reliable sources on the internet and updates the database.

[0544] Step 2:

[0545] The user logs into the system using their device and enters their search criteria for grants.

[0546] Step 3:

[0547] The device collects user sentiment data from voice and text input and sends it to the server.

[0548] Step 4:

[0549] The server analyzes the received emotional data using an emotion engine to determine the user's emotional state. Based on this analysis, the search criteria for grants corresponding to the user's emotions are fine-tuned.

[0550] Step 5:

[0551] The server uses the output of the emotion engine to select grant information from the database that matches the user's needs and emotional state, and generates a list of recommendations.

[0552] Step 6:

[0553] The server generates a list of recommendations, which is sent to the user's device for display. The user then uses this information to select the appropriate grant.

[0554] Step 7:

[0555] The user begins the application process for the grant they selected and enters the required information on the terminal.

[0556] Step 8:

[0557] The terminal sends the entered information to the server, which automatically generates the application documents. The documents are customized according to the required format.

[0558] Step 9:

[0559] The server continuously monitors the progress of the application and adjusts the content and timing of notifications sent to the terminal based on the stress assessment results from sentiment analysis.

[0560] Step 10:

[0561] The user checks the notification on their device, performs any missing procedures or actions, and completes the application.

[0562] (Example 2)

[0563] Next, we will describe Example 2. 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."

[0564] When non-profit organizations seek funding, they often face challenges in efficiently gathering appropriate funding information and smoothly navigating the application process. In particular, optimizing information provision and notifications based on the emotional state of the recipient is crucial, but effective means to achieve this are lacking.

[0565] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0566] In this invention, the server includes means for collecting financial information for non-profit organizations, means for analyzing the financial information based on a user's request, and means for identifying the user's emotional state. This enables the recommendation of optimal financial information tailored to the user's emotional state and notification at an appropriate time.

[0567] A "non-profit organization" is an organization that does not aim to make a profit and pursues social objectives or the public good.

[0568] "Funding information" refers to information about grants, donations, and other sources of funding that provide the necessary funds for a particular project or activity.

[0569] A "user" refers to an individual or organization that uses this system to obtain financial information or receive support for application procedures.

[0570] "Analysis" refers to the process of analyzing collected data to derive useful information.

[0571] "Emotional state" refers to the psychological condition of a user, such as their feelings and mood, and is a state in which their actions and decisions are influenced based on this state.

[0572] A "notification" is a message or alert sent by a system to inform users of information or important updates.

[0573] "Document generation" refers to the process of automatically creating official documents and application forms required for specific activities or purposes.

[0574] "Progress control" refers to management activities that monitor the status of ongoing processes and projects and make adjustments or improvements as needed.

[0575] The grant support system of this invention enables non-profit organizations to effectively raise funds. This system is built on the interaction of servers, terminals, and users.

[0576] The server collects funding information related to non-profit organizations from publicly available resources on the internet and dedicated information services via the network. This collection process utilizes hardware and software such as web scraping techniques and APIs. The collected information is organized and stored in a database, enabling efficient searching and analysis.

[0577] The user accesses the system via a terminal and begins searching for financial information. The terminal accepts voice and text input from the user, and uses natural language processing to detect the user's emotional state. In this process, a generative AI model called an emotion engine is used to evaluate and analyze the user's emotional data.

[0578] The server uses emotional data analyzed by the emotion engine to select financial information from the database that matches the user's needs. Furthermore, it can adjust the presentation method and notification timing according to the user's emotional state to provide optimal recommendations.

[0579] For example, if a user is searching for funding for a child's educational project, and an emotional state indicating anxiety is detected during the search on their device, the server will send additional reassuring information along with more detailed grant information to the device, and, if necessary, provide options to connect with relevant experts.

[0580] An example of a prompt message could be a specific question from a user, such as, "I want to raise funds for a children's education project, but I'm unsure which grant to choose. Could you please provide specific information and support to alleviate my worries and anxieties?"

[0581] In this way, the present invention provides a comprehensive solution to facilitate fundraising for non-profit organizations while taking emotional factors into consideration.

[0582] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0583] Step 1:

[0584] The server collects funding information from the internet. Specifically, it retrieves data from publicly available websites and dedicated APIs. Inputs include URLs and API keys of funding organizations, and output is a list of data such as the name of the funding source, eligibility requirements, and application deadline. This allows the server to form a foundation of funding information available to nonprofit organizations.

[0585] Step 2:

[0586] Users log in to the system via a terminal and enter search criteria for the funding information they are looking for. Specifically, this primarily involves entering details of the purpose and target project in text format. This input includes project name, budget range, and geographical restrictions, which the terminal then transfers as digital data to the server. The output is a list of funding sources that meet the user's criteria.

[0587] Step 3:

[0588] The device performs voice emotion analysis when the user inputs. Emotional data is extracted from the user's voice and text using a generative AI model. The input consists of the user's voice files and text data, and the output is numerical data indicating positivity and stress levels. This allows the user's emotional state to be understood.

[0589] Step 4:

[0590] The server analyzes the user's emotional data and selects the most suitable financial information. Database searches perform data calculations based on the user's emotional state, requirements, and collected financial information. Inputs are the user's emotional score and search criteria, and output is a list of recommended financial information. This allows the server to provide financial information optimized to the user's needs.

[0591] Step 5:

[0592] The server notifies the user of the selected fund list. The notification is configured to include detailed explanations and links to related materials. The input is the selected fund information and its description, and the output is in the form of a notification message. As a result, the user is supported in reviewing the fund information and making appropriate selections.

[0593] Step 6:

[0594] The device will offer options for additional support from experts as needed. For funds the user has expressed interest in, it will display information on consulting services and related events. Inputs include data on the user's selected funds and emotional state, while outputs include guidance on connecting with experts and support information. This allows users to receive deeper, more specific assistance.

[0595] (Application Example 2)

[0596] Next, we will explain application example 2. In the following explanation, 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."

[0597] For non-profit organizations to raise funds efficiently, it is essential to handle appropriate funding information in a timely and accurate manner. However, when users are in an emotionally unstable state, the funding application process may not proceed smoothly, potentially resulting in lost opportunities. Furthermore, the lack of information provision features that take emotional states into consideration hinders the ability to enhance users' sense of security.

[0598] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0599] In this invention, the server includes means for collecting funding information for non-profit organizations, means for analyzing funding information based on user requests, and means for analyzing the user's emotional state and providing security information based on the emotional state. This enables efficient fundraising while enhancing a sense of security by providing appropriate funding information according to the user's emotional state.

[0600] A "non-profit organization" is an organization that operates for social purposes rather than for profit.

[0601] "Funding information" refers to information about financial resources that support an organization's activities, such as grants and donations.

[0602] "User requirements" refer to the conditions and preferences that a user needs when using the system.

[0603] "Emotional state" refers to the user's psychological and emotional condition, expressed as a degree such as positive or negative.

[0604] "Analysis" is the process of breaking down complex data and information to understand its structure and meaning.

[0605] "Security information" refers to information related to safety, including guidance and instructions to ensure that system users can operate with peace of mind.

[0606] "A sense of security" refers to the feeling of psychological safety that users experience, allowing them to use the system without stress.

[0607] "Efficient fundraising" is the process of obtaining the maximum amount of funds with the minimum amount of time and energy.

[0608] This invention is a system for efficiently processing funding information for non-profit organizations and providing appropriate information according to the user's emotional state. Specifically, the server automatically collects funding information from the internet and builds a database. When performing analysis based on this data, the system uses voice and text data transmitted from the user's terminal to analyze the user's emotional state.

[0609] The analysis uses emotion recognition software to calculate the degree of negative or positive emotions. This analysis result is then utilized by an information recommendation system to select and provide funding information that best matches the user's needs. Furthermore, a notification management system determines the optimal timing for sending information based on the emotional state and notifies the device accordingly.

[0610] In the process of users obtaining information using this system, the system can also provide detailed and security information to offer emotional reassurance. For example, if a user feels anxious while trying to raise funds for an event involving many people, the system can prioritize displaying relevant resources and support information to enhance their sense of security.

[0611] An example of a prompt message is one that shows specific output tailored to the expected usage scenario, such as, "Show how to analyze sentiment data and provide appropriate security guidance for that situation."

[0612] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0613] Step 1:

[0614] The server periodically collects funding information from the internet and updates its database. This collection process uses web scraping techniques to obtain the latest grant and donation information. The input consists of data from various public and private funding portals, and the output is funding information stored in the database in a standardized format.

[0615] Step 2:

[0616] Users log in to the system using a terminal and enter their desired funding conditions. These conditions include the type of project, the required funding amount, and the deadline. The input is text-based requirements provided by the user, and the output is specific request data that the system uses to prepare for analysis.

[0617] Step 3:

[0618] The device extracts emotional data from the user's voice or text and sends it to the server. This process uses speech recognition and text analysis technologies to convert emotional states into numerical data. The input is voice or text indicating the user's emotions, and the output is digital data including an emotional score.

[0619] Step 4:

[0620] The server analyzes the received emotional data using an emotion recognition engine to determine whether the emotion is positive or negative. The input is the emotional score sent from the terminal, and the output is a score report as a result of the emotion analysis.

[0621] Step 5:

[0622] The server uses sentiment analysis results to match the user's request with the most suitable funding information through its information recommendation system. This process uses machine learning algorithms to narrow down the choices to those with the highest degree of match. The input is the sentiment score and user request data, and the output is a list of recommended funding options.

[0623] Step 6:

[0624] The server uses a notification management system to inform the user of information at the optimal time. Based on the results of sentiment analysis, it selects a timing that takes into account the user's stress levels and sense of security. The input is the user's emotional state and recommendation information, and the output is the notification message sent to the user.

[0625] Step 7:

[0626] Users refer to funding information through notifications they receive and initiate the application process if necessary. During this process, the system provides templates for the required documents, assisting users in easily submitting their applications. Inputs are inquiries based on user actions, and outputs are guidance regarding the application process.

[0627] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0628] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0629] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0630] [Fourth Embodiment]

[0631] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0632] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0633] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0634] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0635] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0636] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0637] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0638] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0639] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0640] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0641] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0642] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0643] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0644] This invention is a system that helps non-profit organizations efficiently obtain grants. The system provides users with multiple means to efficiently collect grant information, select the most suitable grants, and simplify the application process.

[0645] The system's program consists of the following main functions. First, to collect grant information from various sources on the internet, the server performs regular web scraping to build a reliable database. This makes it possible to efficiently manage large amounts of complex grant information.

[0646] When a user logs into the system, the terminal sends the user's requests and requirements to the server. The server uses artificial intelligence to analyze grant information that matches the user's needs and presents it to the terminal. This allows the user to easily find the grant that is best suited to them.

[0647] Furthermore, to assist with grant applications, the server creates templates for the necessary application documents and customizes them based on the information entered by the user. This allows users to prepare application documents quickly and accurately.

[0648] After an application is submitted, the server monitors its progress and sends important notifications and reminders to the user via their device as needed. By receiving these notifications, users can stay informed about the status of their application and take necessary actions in a timely manner.

[0649] As a concrete example, consider a non-profit organization using this system to raise funds for operating a children's cafeteria in a poverty-stricken area. The organization's representative logs in via a terminal and enters conditions related to the region and purpose, and the server recommends specific grants and supports the application process. In this way, the organization can efficiently navigate the complex grant application process and focus on its core business.

[0650] Based on the above, this invention aims to streamline fundraising for non-profit organizations and support the maximization of social value.

[0651] The following describes the processing flow.

[0652] Step 1:

[0653] The server periodically scrapes grant information from reliable sources on the internet, organizes the information, and stores it in a database.

[0654] Step 2:

[0655] Users log in to the system on their terminal and enter their grant search criteria and personal needs.

[0656] Step 3:

[0657] The terminal sends the information entered by the user to the server, which then uses artificial intelligence to analyze the database and find grants that match the user's criteria.

[0658] Step 4:

[0659] The server sends a list of grant candidates to the terminal, which the user reviews and selects the appropriate grant.

[0660] Step 5:

[0661] The user initiates the application process for the grant they have selected and enters the necessary information through their device.

[0662] Step 6:

[0663] The terminal sends user input information to the server, which then customizes and generates application form templates based on that information.

[0664] Step 7:

[0665] The server sends the generated application documents to the user's terminal, which the user then downloads, modifies as needed, and submits.

[0666] Step 8:

[0667] The server constantly monitors the progress of the application and notifies the user via their terminal if there are any significant status changes.

[0668] Step 9:

[0669] The user checks the notification on their device and takes additional action as needed.

[0670] (Example 1)

[0671] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0672] For nonprofit organizations, the process of gathering information on grants and submitting applications is complex and time-consuming. In particular, collecting accurate and up-to-date information from diverse sources, finding grants that meet the specific needs of their users, and efficiently preparing applications and managing the process are all challenging. This situation makes it difficult for nonprofit organizations to focus on their core activities.

[0673] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0674] In this invention, the server includes means for collecting financial assistance information from information sources, means for analyzing financial assistance information based on user requests, means for recommending the most suitable financial assistance, means for creating documents, means for managing the progress of the application process, and means for communicating important updates. This enables non-profit organizations to efficiently obtain appropriate grant information and proceed with the application process quickly and accurately.

[0675] "Information sources" refer to information on financial support related to the present invention, provided by government agencies, foundations, etc., that exist on the internet.

[0676] "Financial support information" refers to detailed information about financial support such as grants and subsidies available to non-profit organizations.

[0677] "Users" refers to non-profit organizations or similar entities that use this system to seek and apply for financial assistance.

[0678] "Requests" refer to information that users communicate through the system, indicating specific conditions or desired support.

[0679] "Means of analysis" refers to methods and techniques for analyzing collected financial support information based on the user's requests.

[0680] "Recommended measures" refers to a function that selects and presents appropriate financial support to users based on the analysis results.

[0681] "Document" refers to a structured document containing information that users create and submit, such as forms and documents required for applying for financial assistance.

[0682] "Means of managing the progress of the application process" refers to functions that monitor the progress of the entire financial assistance application process and support its smooth execution.

[0683] "Updates" refer to content that conveys important changes or additions to the application process or financial support information.

[0684] "Means of communication" refers to methods used to notify or inform users of updates.

[0685] This system is designed to help non-profit organizations efficiently obtain grants and requires coordination between servers, terminals, and users.

[0686] First, the server uses web scraping techniques to collect financial support information from various sources on the internet. This process utilizes open-source web scraping tools such as Beautiful Soup and Scrapy. The collected data is then organized and stored using a database system (e.g., MySQL, PostgreSQL).

[0687] Subsequently, users access the system via their devices and input their organization's requests and requirements. These requirements include the target region, area of ​​activity, and the amount of funding needed.

[0688] The terminal sends the information entered by the user to the server. The server uses a generative AI model (e.g., GPT-4 or BERT) to analyze the information in the database and identify the financial support information that best matches the user's needs. This allows the user to obtain information on the most suitable grants.

[0689] For example, if a non-profit organization is seeking funding for educational support, a user can obtain specific grant information by entering a prompt such as, "I am looking for grants for local education. The activity area is urban, and the focus is on supporting low-income families."

[0690] Furthermore, the server generates templates for the documents required to apply for the identified grants. This process utilizes software such as Word and Google Docs, and the document templates are customized based on the information entered by the user.

[0691] Finally, the server monitors the progress of the application process and notifies users of important updates via smartphones or computer terminals as needed. This allows users to respond in a timely manner.

[0692] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0693] Step 1:

[0694] The server collects financial support information from its sources. Specifically, it uses web scraping tools such as Beautiful Soup and Scrapy to retrieve information from specified URLs. This process involves scheduling regular scraping operations. The input is a list of URLs, and the output is the scraped raw data.

[0695] Step 2:

[0696] The server stores the collected raw data in a database. Using database systems such as MySQL or PostgreSQL, the server converts the acquired data into a structured format. It removes duplicate and invalid data, extracts only the necessary field information, and stores it in the database. The input is the scraped raw data, and the output is an organized database entry.

[0697] Step 3:

[0698] Users log in to the system via their terminal. Users gain access to the system by entering their personal information and organizational details. The input is a user registration form, and the output is an authenticated status indicating the start of a session.

[0699] Step 4:

[0700] The user enters search criteria for support information on the terminal. They specify the target region, activity area, and required funding amount. The terminal formats the entered criteria and prepares to send them to the server. The input is the user's search criteria, and the output is the search query sent to the server.

[0701] Step 5:

[0702] The server searches the database based on the received search query. It then uses a generative AI model (e.g., GPT-4) to analyze the most relevant assistive information that matches the criteria. The input is the query sent to the server, and the output is a list of recommended assistive information.

[0703] Step 6:

[0704] The terminal displays recommended support information received from the server to the user. The user can review the information and click on options of interest to obtain more details. The input is a list of support information sent from the server, and the output is the detailed information displayed to the user.

[0705] Step 7:

[0706] The server generates application documents based on the selected support information. Using Word or Google Docs, it creates customized documents based on the information entered by the user. Input consists of the user-selected support information and prompt text, while output is an application document template.

[0707] Step 8:

[0708] The server monitors the progress of the application process and notifies the user as needed. It uses a progress management system to check submission deadlines and important updates, and sends alerts to the user via their terminal. Input is application status data, and output is notification messages delivered to the user.

[0709] (Application Example 1)

[0710] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0711] For non-profit organizations to secure funding efficiently and securely, they need to quickly navigate a complex process that includes gathering grant information, selecting the most suitable funds, and preparing and managing application documents. Furthermore, while digitalization is advancing, the risk of data security being compromised is also increasing. It is desirable to provide systems that address these challenges and create an environment where non-profit organizations can focus on their core activities.

[0712] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0713] In this invention, the server includes means for collecting financial information for non-profit organizations, means for analyzing the financial information based on user requests, and means for presenting the user with the most suitable funding based on the analysis results. This enables non-profit organizations to raise funds efficiently and securely, allowing them to focus on their core social contribution activities.

[0714] A "non-profit organization" is an organization that does not pursue profit and primarily operates with the aim of contributing to society or the public good.

[0715] "Funding information" refers to detailed information about various sources of funding and grants, including providers, conditions, and available amounts.

[0716] "Analysis" refers to the act of analyzing data to derive information that is optimal for a specific purpose.

[0717] "Application documents" refer to official documents prepared in a specific format for submission to funders.

[0718] A "monitoring mechanism" is a mechanism for constantly checking specific activities or progress within a system and taking action as needed.

[0719] "Means of notification" refers to a function or mechanism for informing users of important information or progress.

[0720] "Encryption technology" is a technology that transforms data to protect it from unauthorized access, and plays a role in maintaining data confidentiality.

[0721] "Biometric authentication technology" is a method of authenticating individuals using human physical characteristics such as fingerprints or facial recognition.

[0722] The system based on this invention is designed to enable non-profit organizations to securely and efficiently raise funds. The server first collects funding information from the internet using web scraping tools (e.g., Beautiful Soup, Scrapy) and API integration. The collected data is securely stored in a cloud database (e.g., Firebase, AWS RDS) using encryption technology. The server then analyzes this information using AI technology (e.g., TensorFlow, PyTorch) to extract the most suitable funding information for the user's needs.

[0723] The device securely provides the user with analyzed information through biometric authentication (e.g., iOS Face ID, Android Fingerprint API). This biometric authentication technology protects the user's personal information and prevents unauthorized access to the system. Users can prepare application documents based on the provided financial information in a secure environment.

[0724] As a concrete example, suppose an organization operating a children's cafeteria in a certain region uses this system for fundraising. In this case, the representative uses a smartphone to log in via biometric authentication. The AI ​​then selects the most suitable grant from the fundraising information it provides, and the representative can download application form templates available on the cloud and proceed with the application quickly.

[0725] An example of a prompt might be: "Our non-profit organization runs a local children's cafeteria. Please tell us about the best grants available to efficiently raise operating funds, and also provide us with the necessary documents for the application process." Based on this prompt, the AI ​​will provide appropriate funding information and support the application process.

[0726] As a result, this system enables non-profit organizations to manage their funds more efficiently and concentrate resources on necessary social activities.

[0727] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0728] Step 1:

[0729] The server uses web scraping tools and APIs to collect financial information from the internet. This includes detailed information on various sources of funding. It uses internet URLs and API endpoints as input and obtains structured data (e.g., in JSON format) containing financial information as output. The server sends this data to a cloud database for secure management.

[0730] Step 2:

[0731] The server uses an artificial intelligence model to analyze data based on financial information stored in a cloud database. It receives user requests and conditions as input, and the AI ​​model analyzes this data to select the most suitable financial information for the user. This process yields the optimal financial information to be presented to the user as output.

[0732] Step 3:

[0733] The terminal uses biometric authentication technology to verify the user's identity and provides financial information in a secure manner. It acquires the user's biometric data (facial recognition or fingerprint data) as input, and upon successful authentication, displays the financial information received from the server to the user as output. The terminal then supports the user in taking the next action based on this information.

[0734] Step 4:

[0735] Users can view optimized financial information via their device and begin creating application documents as needed. The system takes the financial information selected by the user as input and generates document templates in the cloud. As output, users receive customized application documents, which they can use to quickly submit their applications.

[0736] Step 5:

[0737] The server monitors the progress of the application process and sends notifications to users via their terminals as needed. It monitors log data and application status trends as input and generates notifications to remind users of important updates (e.g., application approval status and next steps) as output. This allows users to take action at the appropriate time.

[0738] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0739] This invention provides enhanced convenience to a grant support system for non-profit organizations to efficiently raise funds by incorporating an emotion engine that recognizes user emotions. This system analyzes the user's emotional state, recommends optimal grant information based on that analysis, and notifies the user at the appropriate time.

[0740] The system's configuration involves a server that collects grant information from the internet and builds a database. When a user logs in via a terminal and enters search criteria for grants, the terminal collects user sentiment data obtained through voice and text.

[0741] Emotional data is transferred to a server and analyzed by an emotion engine. This engine determines the degree of positive or negative emotion, associates it with information in a database built into the user's needs, and selects appropriate subsidy information. Through this process, the server generates a recommendation list that matches the user's emotions and sends this information to the terminal.

[0742] Furthermore, the emotion engine also has the ability to adjust the timing of alerts and optimize progress notifications according to the user's stress level and level of interest. For example, if a user is feeling anxious about their grant application, the server can reassure them by sending a notification with added detailed explanations.

[0743] For example, if a user is looking for funding for a child's educational project, the system can detect their heightened emotions during their search on their device. Based on this information, the server can provide more helpful details about relevant grants and send notifications recommending expert support if necessary.

[0744] In this way, the present invention can support the support activities of non-profit organizations from an emotional perspective and make the fundraising process smoother and more effective.

[0745] The following describes the processing flow.

[0746] Step 1:

[0747] The server regularly collects the latest grant information from reliable sources on the internet and updates the database.

[0748] Step 2:

[0749] The user logs into the system using their device and enters their search criteria for grants.

[0750] Step 3:

[0751] The device collects user sentiment data from voice and text input and sends it to the server.

[0752] Step 4:

[0753] The server analyzes the received emotional data using an emotion engine to determine the user's emotional state. Based on this analysis, the search criteria for grants corresponding to the user's emotions are fine-tuned.

[0754] Step 5:

[0755] The server uses the output of the emotion engine to select grant information from the database that matches the user's needs and emotional state, and generates a list of recommendations.

[0756] Step 6:

[0757] The server generates a list of recommendations, which is sent to the user's device for display. The user then uses this information to select the appropriate grant.

[0758] Step 7:

[0759] The user begins the application process for the grant they selected and enters the required information on the terminal.

[0760] Step 8:

[0761] The terminal sends the entered information to the server, which automatically generates the application documents. The documents are customized according to the required format.

[0762] Step 9:

[0763] The server continuously monitors the progress of the application and adjusts the content and timing of notifications sent to the terminal based on the stress assessment results from sentiment analysis.

[0764] Step 10:

[0765] The user checks the notification on their device, performs any missing procedures or actions, and completes the application.

[0766] (Example 2)

[0767] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0768] When non-profit organizations seek funding, they often face challenges in efficiently gathering appropriate funding information and smoothly navigating the application process. In particular, optimizing information provision and notifications based on the emotional state of the recipient is crucial, but effective means to achieve this are lacking.

[0769] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0770] In this invention, the server includes means for collecting financial information for non-profit organizations, means for analyzing the financial information based on a user's request, and means for identifying the user's emotional state. This enables the recommendation of optimal financial information tailored to the user's emotional state and notification at an appropriate time.

[0771] A "non-profit organization" is an organization that does not aim to make a profit and pursues social objectives or the public good.

[0772] "Funding information" refers to information about grants, donations, and other sources of funding that provide the necessary funds for a particular project or activity.

[0773] A "user" refers to an individual or organization that uses this system to obtain financial information or receive support for application procedures.

[0774] "Analysis" refers to the process of analyzing collected data to derive useful information.

[0775] "Emotional state" refers to the psychological condition of a user, such as their feelings and mood, and is a state in which their actions and decisions are influenced based on this state.

[0776] A "notification" is a message or alert sent by a system to inform users of information or important updates.

[0777] "Document generation" refers to the process of automatically creating official documents and application forms required for specific activities or purposes.

[0778] "Progress control" refers to management activities that monitor the status of ongoing processes and projects and make adjustments or improvements as needed.

[0779] The grant support system of this invention enables non-profit organizations to effectively raise funds. This system is built on the interaction of servers, terminals, and users.

[0780] The server collects funding information related to non-profit organizations from publicly available resources on the internet and dedicated information services via the network. This collection process utilizes hardware and software such as web scraping techniques and APIs. The collected information is organized and stored in a database, enabling efficient searching and analysis.

[0781] The user accesses the system via a terminal and begins searching for financial information. The terminal accepts voice and text input from the user, and uses natural language processing to detect the user's emotional state. In this process, a generative AI model called an emotion engine is used to evaluate and analyze the user's emotional data.

[0782] The server uses emotional data analyzed by the emotion engine to select financial information from the database that matches the user's needs. Furthermore, it can adjust the presentation method and notification timing according to the user's emotional state to provide optimal recommendations.

[0783] For example, if a user is searching for funding for a child's educational project, and an emotional state indicating anxiety is detected during the search on their device, the server will send additional reassuring information along with more detailed grant information to the device, and, if necessary, provide options to connect with relevant experts.

[0784] An example of a prompt message could be a specific question from a user, such as, "I want to raise funds for a children's education project, but I'm unsure which grant to choose. Could you please provide specific information and support to alleviate my worries and anxieties?"

[0785] In this way, the present invention provides a comprehensive solution to facilitate fundraising for non-profit organizations while taking emotional factors into consideration.

[0786] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0787] Step 1:

[0788] The server collects funding information from the internet. Specifically, it retrieves data from publicly available websites and dedicated APIs. Inputs include URLs and API keys of funding organizations, and output is a list of data such as the name of the funding source, eligibility requirements, and application deadline. This allows the server to form a foundation of funding information available to nonprofit organizations.

[0789] Step 2:

[0790] Users log in to the system via a terminal and enter search criteria for the funding information they are looking for. Specifically, this primarily involves entering details of the purpose and target project in text format. This input includes project name, budget range, and geographical restrictions, which the terminal then transfers as digital data to the server. The output is a list of funding sources that meet the user's criteria.

[0791] Step 3:

[0792] The device performs voice emotion analysis when the user inputs. Emotional data is extracted from the user's voice and text using a generative AI model. The input consists of the user's voice files and text data, and the output is numerical data indicating positivity and stress levels. This allows the user's emotional state to be understood.

[0793] Step 4:

[0794] The server analyzes the user's emotional data and selects the most suitable financial information. Database searches perform data calculations based on the user's emotional state, requirements, and collected financial information. Inputs are the user's emotional score and search criteria, and output is a list of recommended financial information. This allows the server to provide financial information optimized to the user's needs.

[0795] Step 5:

[0796] The server notifies the user of the selected fund list. The notification is configured to include detailed explanations and links to related materials. The input is the selected fund information and its description, and the output is in the form of a notification message. As a result, the user is supported in reviewing the fund information and making appropriate selections.

[0797] Step 6:

[0798] The device will offer options for additional support from experts as needed. For funds the user has expressed interest in, it will display information on consulting services and related events. Inputs include data on the user's selected funds and emotional state, while outputs include guidance on connecting with experts and support information. This allows users to receive deeper, more specific assistance.

[0799] (Application Example 2)

[0800] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0801] For non-profit organizations to raise funds efficiently, it is essential to handle appropriate funding information in a timely and accurate manner. However, when users are in an emotionally unstable state, the funding application process may not proceed smoothly, potentially resulting in lost opportunities. Furthermore, the lack of information provision features that take emotional states into consideration hinders the ability to enhance users' sense of security.

[0802] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0803] In this invention, the server includes means for collecting funding information for non-profit organizations, means for analyzing funding information based on user requests, and means for analyzing the user's emotional state and providing security information based on the emotional state. This enables efficient fundraising while enhancing a sense of security by providing appropriate funding information according to the user's emotional state.

[0804] A "non-profit organization" is an organization that operates for social purposes rather than for profit.

[0805] "Funding information" refers to information about financial resources that support an organization's activities, such as grants and donations.

[0806] "User requirements" refer to the conditions and preferences that a user needs when using the system.

[0807] "Emotional state" refers to the user's psychological and emotional condition, expressed as a degree such as positive or negative.

[0808] "Analysis" is the process of breaking down complex data and information to understand its structure and meaning.

[0809] "Security information" refers to information related to safety, including guidance and instructions to ensure that system users can operate with peace of mind.

[0810] "A sense of security" refers to the feeling of psychological safety that users experience, allowing them to use the system without stress.

[0811] "Efficient fundraising" is the process of obtaining the maximum amount of funds with the minimum amount of time and energy.

[0812] This invention is a system for efficiently processing funding information for non-profit organizations and providing appropriate information according to the user's emotional state. Specifically, the server automatically collects funding information from the internet and builds a database. When performing analysis based on this data, the system uses voice and text data transmitted from the user's terminal to analyze the user's emotional state.

[0813] The analysis uses emotion recognition software to calculate the degree of negative or positive emotions. This analysis result is then utilized by an information recommendation system to select and provide funding information that best matches the user's needs. Furthermore, a notification management system determines the optimal timing for sending information based on the emotional state and notifies the device accordingly.

[0814] In the process of users obtaining information using this system, the system can also provide detailed and security information to offer emotional reassurance. For example, if a user feels anxious while trying to raise funds for an event involving many people, the system can prioritize displaying relevant resources and support information to enhance their sense of security.

[0815] An example of a prompt message is one that shows specific output tailored to the expected usage scenario, such as, "Show how to analyze sentiment data and provide appropriate security guidance for that situation."

[0816] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0817] Step 1:

[0818] The server periodically collects funding information from the internet and updates its database. This collection process uses web scraping techniques to obtain the latest grant and donation information. The input consists of data from various public and private funding portals, and the output is funding information stored in the database in a standardized format.

[0819] Step 2:

[0820] Users log in to the system using a terminal and enter their desired funding conditions. These conditions include the type of project, the required funding amount, and the deadline. The input is text-based requirements provided by the user, and the output is specific request data that the system uses to prepare for analysis.

[0821] Step 3:

[0822] The device extracts emotional data from the user's voice or text and sends it to the server. This process uses speech recognition and text analysis technologies to convert emotional states into numerical data. The input is voice or text indicating the user's emotions, and the output is digital data including an emotional score.

[0823] Step 4:

[0824] The server analyzes the received emotional data using an emotion recognition engine to determine whether the emotion is positive or negative. The input is the emotional score sent from the terminal, and the output is a score report as a result of the emotion analysis.

[0825] Step 5:

[0826] The server uses sentiment analysis results to match the user's request with the most suitable funding information through its information recommendation system. This process uses machine learning algorithms to narrow down the choices to those with the highest degree of match. The input is the sentiment score and user request data, and the output is a list of recommended funding options.

[0827] Step 6:

[0828] The server uses a notification management system to inform the user of information at the optimal time. Based on the results of sentiment analysis, it selects a timing that takes into account the user's stress levels and sense of security. The input is the user's emotional state and recommendation information, and the output is the notification message sent to the user.

[0829] Step 7:

[0830] Users refer to funding information through notifications they receive and initiate the application process if necessary. During this process, the system provides templates for the required documents, assisting users in easily submitting their applications. Inputs are inquiries based on user actions, and outputs are guidance regarding the application process.

[0831] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0832] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0833] 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 this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0834] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0835] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0836] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0837] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0838] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0839] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0840] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0841] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0842] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0843] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0844] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[0845] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0846] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0847] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0848] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0849] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0850] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0851] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0852] The following is further disclosed regarding the embodiments described above.

[0853] (Claim 1)

[0854] Means of collecting grant information for non-profit organizations,

[0855] A means for analyzing the aforementioned grant information based on user needs,

[0856] A means of recommending the most suitable grant to the user based on the aforementioned analysis results,

[0857] A means for generating the documents necessary for applying for the aforementioned grant,

[0858] A means for managing the progress of the aforementioned application process,

[0859] A means of notifying users of important updates,

[0860] A system that includes this.

[0861] (Claim 2)

[0862] The system according to claim 1, wherein the analysis means uses artificial intelligence to analyze the user's needs.

[0863] (Claim 3)

[0864] The system according to claim 1, wherein the document generation means creates an application document in a specific format based on information entered by the user.

[0865] "Example 1"

[0866] (Claim 1)

[0867] Means of collecting financial support information from information sources,

[0868] A means for analyzing the aforementioned financial support information based on the user's requests,

[0869] A means of recommending the most suitable financial support to the user based on the aforementioned analysis results,

[0870] Means for preparing the documents necessary for applying for the aforementioned financial assistance,

[0871] A means for managing the progress of the aforementioned application procedure,

[0872] A means of communicating important update information to users,

[0873] A system that includes this.

[0874] (Claim 2)

[0875] The system according to claim 1, wherein the analysis means analyzes the user's requests using a learning machine.

[0876] (Claim 3)

[0877] The system according to claim 1, wherein the document creation means creates an application document in a specific format based on information provided by the user.

[0878] "Application Example 1"

[0879] (Claim 1)

[0880] Means of collecting funding information for non-profit organizations,

[0881] A means for analyzing the aforementioned financial information based on the user's request,

[0882] A means of presenting the optimal funds to the user based on the aforementioned analysis results,

[0883] A means for generating the documents necessary for applying for the aforementioned funds,

[0884] Means for monitoring the progress of the aforementioned application process,

[0885] A means of notifying users of important updates,

[0886] A means of providing encryption technology for securely managing data,

[0887] A means of providing access control based on biometric authentication technology,

[0888] A system that includes this.

[0889] (Claim 2)

[0890] The system according to claim 1, wherein the analysis means utilizes machine learning to analyze the user's requests.

[0891] (Claim 3)

[0892] The system according to claim 1, wherein the document generation means creates an application document in a specific format based on information entered by the user and encrypts it to enhance security.

[0893] "Example 2 of combining an emotion engine"

[0894] (Claim 1)

[0895] Means of collecting funding information for non-profit organizations,

[0896] A means for analyzing the aforementioned financial information based on the user's request,

[0897] A means of recommending appropriate funds to users based on the aforementioned analysis results,

[0898] Means for identifying the emotional state of the user,

[0899] Means for adjusting the timing of notification based on the aforementioned emotional state,

[0900] A means for generating the documents necessary for applying for the aforementioned funds,

[0901] Means for controlling the progress of the aforementioned application process,

[0902] A means of notifying users of major updates,

[0903] A system that includes this.

[0904] (Claim 2)

[0905] The system according to claim 1, wherein the analysis means analyzes the user's emotional data using a generative AI model.

[0906] (Claim 3)

[0907] The system according to claim 1, wherein the document generation means creates an application document in a specific format based on information entered by the user.

[0908] "Application example 2 when combining with an emotional engine"

[0909] (Claim 1)

[0910] Means of collecting funding information for non-profit organizations,

[0911] A means for analyzing the aforementioned funding information based on the user's request,

[0912] A means of recommending the most suitable funding to the user based on the aforementioned analysis results,

[0913] A means for generating the documents necessary for the aforementioned funding application,

[0914] A means for managing the progress of the aforementioned application procedure,

[0915] A means of notifying users of important updates,

[0916] A means for analyzing the user's emotional state and providing security information based on the said emotional state,

[0917] A means for adjusting the timing of notifications according to the aforementioned emotional state,

[0918] A system that includes this.

[0919] (Claim 2)

[0920] The system according to claim 1, wherein the analysis means analyzes user requests using machine learning.

[0921] (Claim 3)

[0922] The system according to claim 1, wherein the document generation means creates a document in a general format based on information entered by the user. [Explanation of Symbols]

[0923] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. Means of collecting grant information for non-profit organizations, A means for analyzing the aforementioned grant information based on user needs, A means of recommending the most suitable grant to the user based on the aforementioned analysis results, A means for generating the documents necessary for applying for the aforementioned grant, A means for managing the progress of the aforementioned application process, A means of notifying users of important updates, A system that includes this.

2. The system according to claim 1, wherein the analysis means uses artificial intelligence to analyze the user's needs.

3. The system according to claim 1, wherein the document generation means creates an application document in a specific format based on information entered by the user.

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