system

Abstract

Provide a system. 【Solution means】 Means for collecting data, Means for performing individual credit evaluations based on the data, Means for setting a guarantor based on the credit evaluation, Means for playing the role of a virtual guarantor, Means for generating documents, Means for monitoring the user's situation, Means for performing follow-up when an abnormality is detected A system including.

Description

【Technical Field】 【0001】 The technology of the present 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, and includes 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 in response to the user utterance. 【Prior Art Documents】 【Patent Documents】 【0003】 【Patent Document 1】 Japanese Patent Application Laid-Open No. 2022-180282 【Summary of the Invention】 【Problems to be Solved by the Invention】 【0004】 In modern society, the number of elderly people without relatives is increasing, and it has become particularly difficult to secure a guarantor when being admitted to a medical institution or entering a nursing facility. This situation hinders the elderly from living in peace and increases the risk of social isolation. Furthermore, the necessary document preparation and follow-up procedures are complex, and it is difficult for the elderly themselves to handle them. There is a need for a mechanism to effectively solve such problems. 【Means for Solving the Problems】 【0005】 This invention embodies a system that automates data collection, analysis, and credit assessment, and provides virtual guarantors to the elderly. Specifically, it includes means for evaluating individual credit risk based on collected data and automatically setting up virtual guarantors according to the results. Furthermore, by providing means for generating necessary documents, it simplifies administrative procedures and facility admission procedures, freeing the elderly from the complex procedures they face. It also provides comprehensive support by monitoring the user's lifestyle and health status and providing prompt follow-up in the event of an abnormality. This makes it possible to create an environment in which the elderly can live with peace of mind. 【0006】 "Means for collecting data" refers to a device or program that has the function of acquiring information about a user and storing it in an usable format. 【0007】 "Means for conducting individual credit assessments" refers to a device or program that performs a process of objectively determining an individual's creditworthiness based on collected data. 【0008】 "Means for appointing a guarantor" refers to a device or program that determines an appropriate form of guarantee based on the results of a credit assessment and selects a guarantor accordingly. 【0009】 "Means of acting as a virtual guarantor" refers to a device or program in which a digital agent or similar entity provides the function of a guarantor on behalf of another person, without the involvement of an actual individual. 【0010】 "Means for generating documents" refers to a device or program that automatically creates documents in the appropriate format according to the required procedures. 【0011】 "Means for monitoring the user's situation" refers to a device or program that continuously acquires data about the user's living environment and health status and detects abnormalities. 【0012】 "Means for follow-up when an anomaly is detected" refers to a device or program that executes a process to provide appropriate responses or support when an anomaly is detected through monitoring. 【0013】 "Means for setting credit evaluation criteria" refers to a device or program that defines the criteria for determining creditworthiness that apply to individual users. 【0014】 "Means for determining whether a guarantee is permissible" refers to a device or program that performs a process of determining whether it is appropriate to provide a guarantee based on a credit assessment. 【0015】 "Means for providing the generated documents" refers to a device or program that has the function of presenting or sending the generated documents to the user or related organization. 【0016】 "Means of notifying the user" refers to a device or program that has a communication function for transmitting information to the user. [Brief explanation of the drawing] 【0017】 [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] It 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] It shows an emotion map to which a plurality of emotions are mapped. [Figure 10] It shows an emotion map to which a plurality of emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Example 2 when an emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when an emotion engine is combined. 【Mode for Carrying Out the Invention】 【0018】 Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings. 【0019】 First, the language used in the following description will be explained. 【0020】 In the following embodiments, a processor with a reference number (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of a plurality of arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of a plurality of 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. 【0021】 In the following embodiments, signed RAM (Random Access Memory) is a memory that temporarily stores information and is used as work memory by the processor. 【0022】 In the following embodiments, the signed storage is one or more non-volatile storage devices that store various programs and various parameters. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes. 【0023】 In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark). 【0024】 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." 【0025】 [First Embodiment] 【0026】 Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment. 【0027】 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. 【0028】 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). 【0029】 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. 【0030】 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. 【0031】 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. 【0032】 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. 【0033】 Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14. 【0034】 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. 【0035】 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. 【0036】 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. 【0037】 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". 【0038】 This invention is a system designed to alleviate the difficulties elderly people face in securing guarantors and the complexities of the associated procedures. The system functions based on data collection, credit assessment, virtual guarantor setup, document generation, and user status monitoring. Its overall operation is carried out through the interaction of three parties: the server, the terminal, and the user. 【0039】 The server first collects data provided by the user, including personal information, past transaction history, and health status. This data is managed in a secure environment and forms the basis for evaluating individual credit risk using AI algorithms. The server then uses machine learning models to generate a risk score and evaluate whether risk reduction is applicable. 【0040】 Once the credit assessment is complete, the server automatically creates a virtual guarantor profile. This profile meets the user's required guarantee criteria, and the digital agent fulfills this role, providing a form of guarantee that does not involve a real person. This allows the user to meet the usual guarantor requirements, ensuring smooth procedures such as facility admission and medical treatment. 【0041】 Next, the server automatically creates the necessary administrative documents based on the generated credit information. This process utilizes natural language processing technology to optimize document formatting and quickly provide error-free, accurate documents. The terminal makes these documents available for viewing and sending to the user, who can choose to download or send them directly as needed. 【0042】 The system also includes a mechanism to continuously monitor the user's health and lifestyle and provide follow-up based on this information. For example, if the server detects an anomaly, it quickly notifies the terminal and prompts the user and their support network to take the necessary action. This allows users to respond quickly and appropriately to unexpected problems. 【0043】 As a concrete example, when elderly person A, who has no relatives, enters a nursing home, they would normally be required to have a guarantor. However, by using this system, a virtual guarantor can be set up, and all necessary procedures can be automated. Person A can enter the facility safely and smoothly without having to directly participate in the procedures. 【0044】 Thus, the system of the present invention provides comprehensive support to enable elderly people to live their daily lives with peace of mind by integrating various technologies. 【0045】 The following describes the processing flow. 【0046】 Step 1: 【0047】 The user enters personal information and health data into the device. The device then prepares to send the collected data to the server. 【0048】 Step 2: 【0049】 The server receives user data sent from the terminal and stores it in a secure database. This data includes personal information, past transaction history, and health-related information. 【0050】 Step 3: 【0051】 The server preprocesses the stored data into an analyzable format and uses machine learning algorithms to assess the user's credit risk. Based on this assessment, it generates a risk score to be assigned to the user. 【0052】 Step 4: 【0053】 The server automatically builds a profile for the user that sets up a suitable virtual guarantor based on a credit risk assessment. The virtual guarantor profile includes the terms and scope of the guarantee. 【0054】 Step 5: 【0055】 The server automatically generates the necessary documents for various administrative procedures and facility admission procedures that users require. This process uses natural language processing to ensure accurate document creation. 【0056】 Step 6: 【0057】 The terminal presents the generated document to the user and offers the option to download or send it directly. The user completes the process based on their choice. 【0058】 Step 7: 【0059】 The server continuously monitors the user's health and lifestyle, regularly updating data and promptly sending follow-up notifications to the device if any abnormalities are detected. 【0060】 Step 8: 【0061】 The device receives notifications from the server and provides users with immediate information. It guides users through necessary actions and support, encouraging them to take prompt action. 【0062】 (Example 1) 【0063】 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." 【0064】 For socially vulnerable individuals, such as the elderly, the difficulty of securing a guarantor and the complexity of the procedures involved in managing their lives without one are significant challenges. In particular, the burden of credit assessment, document preparation, and situation monitoring required for these procedures is a major issue. 【0065】 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. 【0066】 In this invention, the server includes means for collecting data, means for performing individual credit assessments using artificial intelligence, and means for setting up virtual agents. This automates procedures that require a guarantor and enables streamlined procedures and rapid problem resolution by creating a virtual guarantor as a digital agent. 【0067】 "Means of data collection" refers to the technical elements for securely receiving and storing information such as personal information, past transaction history, and health status from users. 【0068】 "Means of conducting individual credit assessments" refers to artificial intelligence-related technologies that calculate and evaluate credit risk for each user based on collected data. 【0069】 The "means of setting up a virtual agent" refer to a system that builds a digital agent based on the user's credit information and has it act as a guarantor. 【0070】 "Means of fulfilling the role of a digital agent" refers to technologies that enable a virtual entity to perform functions such as a guarantor without the need for a physical human intermediary. 【0071】 "Methods for generating documents using natural language processing technology" refers to the process of automatically creating necessary procedural documents by utilizing natural language processing, which is a part of artificial intelligence. 【0072】 "Means of monitoring lifestyle indicators" refers to technologies that have the function of continuously observing each user's health status and daily life, and collecting and analyzing data. 【0073】 A "means of rapid notification and follow-up" refers to a system that, upon detecting anomalies or significant changes, immediately communicates information to the relevant parties and prompts them to take any necessary additional action. 【0074】 The present invention will now be described in terms of embodiments. This system is designed to address the problems and procedural complexities faced by elderly individuals in securing guarantors. The system includes functions for data collection, credit assessment, virtual guarantor setup, document generation, and monitoring of health status and lifestyle indicators. 【0075】 First, users use a terminal to enter personal information, past transaction history, health status, etc. The data transmitted from the terminal is securely collected and stored on a server. This data is managed using cloud storage technologies such as AWS® or Azure®. 【0076】 Next, the server uses artificial intelligence to perform a credit assessment based on the collected data. This process utilizes Python and machine learning libraries such as Tensorflow® to evaluate the user's credit risk. Based on this assessment, the server sets up a virtual agent. This virtual agent functions as a digital agent and takes on the role of a guarantor. 【0077】 The system uses natural language processing technology to generate the documents. The server automatically creates the necessary procedural documents using Python's NLTK library and other tools. The terminal provides the generated documents to the user, who can then download or send them to the relevant organization. 【0078】 Furthermore, the server continuously monitors the user's health status and lifestyle indicators, and immediately follows up if any abnormalities are detected. This function enables rapid notification and response to users and related support networks. 【0079】 As a concrete example, when elderly person A enters a nursing home, the guarantor normally required is replaced by a virtual guarantor, allowing A to enter smoothly without being involved in the procedure themselves. An example of an input prompt for the generating AI model is, "Explain the simplification of the guarantor setup and procedures required when elderly people enter nursing homes." 【0080】 In this way, by having the server, terminal, and user each fulfill their respective roles, this system can provide comprehensive support to users, including the elderly. 【0081】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0082】 Step 1: 【0083】 The user uses a terminal to input necessary data such as personal information, past transaction history, and health status. The entered data is sent from the terminal to the server. This allows the server to securely store this data in its database environment and prepare to collect the information necessary for subsequent processing. 【0084】 Step 2: 【0085】 The server uses artificial intelligence based on the collected data to perform individual credit assessments. Specifically, it uses programming libraries such as Python and TensorFlow to calculate a credit risk score for each user. As a result, a risk score is generated, allowing for an objective evaluation of the user's creditworthiness. 【0086】 Step 3: 【0087】 The server sets up a virtual agent based on the calculated credit risk. This involves building a profile in which a digital agent acts as a guarantor. The constructed profile takes on the role of a guarantor without the need for a physical person, helping to ensure the user's procedures proceed smoothly. 【0088】 Step 4: 【0089】 Using natural language processing technology, the server automatically generates the necessary administrative documents. Specifically, it uses the Python NLTK library to create accurate documents in the appropriate format. The generated documents are provided in an electronically accessible format upon user request. 【0090】 Step 5: 【0091】 The terminal displays the generated documents to the user and supports downloading or sending them to the relevant authorities. Users can review the document contents through the terminal and proceed with procedures on the spot if necessary. 【0092】 Step 6: 【0093】 The server continuously monitors the user's health status and lifestyle indicators. It analyzes data collected from sensors such as smart devices and quickly notifies the device if an anomaly is detected. This allows the user and their support organization to take appropriate action quickly. 【0094】 (Application Example 1) 【0095】 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." 【0096】 The goal is to eliminate the cumbersome procedures elderly people face when securing guarantors and to resolve guarantee issues when entering medical and nursing care facilities. Furthermore, there is a need to improve efficiency and peace of mind in health management and lifestyle support. In addition, the aim is to improve the quality of daily life for the elderly through rapid information provision and automated procedures. 【0097】 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. 【0098】 In this invention, the server includes means for collecting data, means for performing individual credit assessments, and means for acting as a virtual guarantor. This enables efficient admission procedures to medical and nursing care facilities without the need for a guarantor. Furthermore, it enables improved health management and lifestyle support for the elderly through analysis based on health information and user-friendly notifications via a digital interface. 【0099】 "Means of data collection" refers to the process of obtaining personal information and health information from users. 【0100】 "Methods for conducting individual credit assessments" refer to the process of evaluating and quantifying the credit risk of each user based on collected data. 【0101】 "Means of fulfilling the role of a virtual guarantor" refers to the process of setting up a digital agent necessary for the system to carry out guarantee activities without the involvement of actual people. 【0102】 "Means of generating documents" refers to the process of automatically creating and preparing necessary administrative documents based on credit ratings and user information. 【0103】 "Means of monitoring user status" refers to the process of continuously tracking changes in the user's health status and lifestyle patterns, and providing necessary follow-up. 【0104】 "Means of follow-up when an anomaly is detected" refers to a process that promptly notifies users and encourages appropriate action when an anomaly is discovered in their health or creditworthiness. 【0105】 "Means for collecting and analyzing health information" refers to the process of taking in and analyzing users' health data and making recommendations regarding health risks and lifestyle habits based on that data. 【0106】 "Means of providing user-friendly notifications through a digital interface" refers to the process of providing information from a system in a way that is easily understandable and usable by the user. 【0107】 "Means for automatically generating and providing permits in accordance with information processing" refers to a process in which the system automatically creates the necessary official permits in response to user requests and provides the results to the user. 【0108】 This invention provides a system that enables elderly people to access care facilities and medical services without the need to secure guarantors or deal with complicated procedures. To achieve this, the server utilizes data collection methods to securely acquire and manage users' personal information and health status data. Python and TensorFlow are used for data analysis, and a machine learning model is run to perform individual credit assessments. This model quantifies and evaluates the user's health risk and credit risk. 【0109】 The server generates a virtual guarantor profile based on the evaluation results and makes it function as a digital agent. The user's required guarantee requirements are automatically met, eliminating the need to provide a physical guarantor. Furthermore, a generation AI model is used to automatically generate the necessary administrative documents using natural language processing technology. These documents are displayed to the user via their terminal and can be downloaded or sent as needed. 【0110】 The device features a user-friendly digital interface that displays the user's status and health data monitoring results in real time, and provides rapid follow-up when an anomaly is detected. This notification function utilizes React Native and is designed to allow users to easily check information and take appropriate action. 【0111】 For example, a user who wants to use a medical facility can proceed smoothly without needing a guarantor. Also, if any abnormality is detected in the user's health condition, a push notification will be sent immediately, enabling a quick response. An example of a prompt sentence for the generated AI model is, "Please explain the procedure for setting up a virtual guarantor so that this elderly person can receive care services safely and smoothly." 【0112】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0113】 Step 1: 【0114】 The server collects personal and health information from users. Inputs include the user's name, address, health status, and medical history. This data is securely stored on the server and undergoes initial processing such as data normalization and cleansing. The output is cleaned data ready for input into machine learning models. 【0115】 Step 2: 【0116】 The server uses TensorFlow to perform a credit assessment based on cleaned data. This process generates a user credit risk score using a machine learning algorithm. The input is the data prepared in step 1, and the output is the credit risk score. Specifically, a pre-trained model analyzes the data and outputs a numerical value indicating the level of risk. 【0117】 Step 3: 【0118】 The server uses a generated AI model to set up virtual guarantors. The input is a credit risk score, and the output is a profile of a virtual guarantor that meets the user's requirements. This profile functions as a digital agent that automatically builds the guarantee the user needs. The role of the generated profile is to relieve the user of the burden of finding a guarantor. 【0119】 Step 4: 【0120】 The server uses natural language processing to automatically generate the necessary documents. The input is a credit risk score and a virtual guarantor profile, and the output is the documents required for formal administrative procedures. Specifically, these documents are generated in formats such as PDF, and error-free documents are provided quickly. 【0121】 Step 5: 【0122】 The device notifies the user of generated documents and status monitoring results. Inputs are generated documents and monitoring data from the server, while outputs are displayed on the user's screen and push notifications. Specifically, the user interface is designed using React Native, playing a role in clearly conveying information to the user. 【0123】 Step 6: 【0124】 The user receives a notification of an anomaly detection and quickly decides on a course of action through their device. The input is the monitoring result from step 5, and the output is the user's decision on the appropriate course of action. Specifically, if a health anomaly is notified, the user can immediately seek medical assistance. 【0125】 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. 【0126】 This invention is a system that, in addition to data collection, credit evaluation, and virtual guarantee construction, integrates an emotion engine to achieve more nuanced responses that take into account the user's emotional state. This creates a comprehensive system to support the stable lives of the elderly. 【0127】 The server receives basic information and health status provided by the user via the device and stores it in secure storage. Furthermore, an emotion engine analyzes the user's voice, facial expressions, and behavioral patterns to estimate their emotional state in real time. This emotional information, along with regular data, is analyzed by AI algorithms on the server and incorporated into the user's credit evaluation process. 【0128】 The server conducts a credit assessment and sets up a virtual guarantor profile based on the assessment results. It is possible to set more detailed guarantee details according to the user's stress and anxiety levels detected by the emotion engine. This ensures that the user's mental well-being is also taken into account in the guarantee assessment. 【0129】 Furthermore, the generation of necessary administrative and medical procedural documents is also promised as an automated process. Document generation is performed using natural language processing and is provided to the user accurately and quickly. The terminal provides an interface that displays the generated documents to the user and instructs them to send them as needed. 【0130】 In its daily monitoring function, the server performs comprehensive data monitoring, including user sentiment data, and issues warnings based on anomalies detected by the sentiment engine. This function also incorporates emotional elements into the follow-up procedures when anomalies are detected, enabling flexible responses tailored to the user and their support network. 【0131】 As a concrete example, if elderly user B is using a system that incorporates an emotion engine, when B exhibits unstable emotional states in daily life, the system will take that information into consideration and provide more appropriate support measures or coordinate with the facility. Through this process, B can continue to live a secure life by receiving flexible support tailored to their emotional state at any given time. 【0132】 This invention aims to provide a user experience that far surpasses conventional guarantee and support systems by integrating an emotion engine, thereby realizing proactive life support. 【0133】 The following describes the processing flow. 【0134】 Step 1: 【0135】 Users enter basic data, including personal information and health status, using their devices. The emotion engine collects the user's emotional data through voice and facial expression analysis. 【0136】 Step 2: 【0137】 The device sends the collected data and sentiment data to the server. The server stores this data in a secure database. 【0138】 Step 3: 【0139】 The server analyzes the accumulated data and performs individual credit assessments. This assessment uses an AI algorithm, and emotional states are reflected in the credit rating. 【0140】 Step 4: 【0141】 The server sets up a virtual guarantor based on the evaluation results. Based on emotional data, if the user is experiencing stress or anxiety, the guarantor's coverage is adjusted to be more comprehensive. 【0142】 Step 5: 【0143】 The server automatically generates the documents the user needs. This process utilizes natural language processing technology to ensure that the necessary information is accurately reflected. 【0144】 Step 6: 【0145】 The terminal presents the generated document to the user and offers options for downloading or sending it. The user can follow the instructions and proceed with the process. 【0146】 Step 7: 【0147】 The server comprehensively monitors the user's health and emotional state. When the emotion engine detects an anomaly, the server considers that information to determine the appropriate follow-up steps. 【0148】 Step 8: 【0149】 The device receives notifications based on anomaly detection and guides the user through the necessary actions. This allows the user to take appropriate action. 【0150】 (Example 2) 【0151】 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 will be referred to as the "terminal." 【0152】 In an increasingly sophisticated social environment, a support system that takes psychological and emotional aspects into account is needed to further stabilize the lives of the elderly and vulnerable. However, conventional systems lack the functionality to analyze changes in users' emotions and utilize that information in support. Therefore, accurately analyzing users' emotional states and providing flexible support based on that analysis is a difficult problem. 【0153】 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. 【0154】 In this invention, the server includes means for aggregating information, means for analyzing emotional states, and means for incorporating the analyzed emotional information into the evaluation. This makes it possible to build a system that can grasp the user's emotions in real time and provide flexible and appropriate support based on that. 【0155】 "Means of aggregating information" refers to a system that collects data from multiple sources, integrates it, and stores it. 【0156】 "Evaluation" is the process of quantifying or ranking a user's creditworthiness or trustworthiness based on aggregated information and specific criteria. 【0157】 A "virtual proxy" is a component that fulfills the role of a proxy without requiring an actual person, and is a function that supports decision-making within a system. 【0158】 "Means of creating documents" refers to a technical system that automatically generates formal documents and reports based on necessary information. 【0159】 "Means of monitoring user status" refers to a system that continuously checks users' daily behavior and condition to detect abnormalities. 【0160】 "Methods for analyzing emotional states" refer to technologies that analyze a user's voice and facial expressions to infer their emotions and psychological state at that moment. 【0161】 "Means for incorporating analyzed emotional information into the evaluation" refers to a function that incorporates the results of emotional analysis into the user's overall evaluation process, thereby achieving a more comprehensive analysis. 【0162】 "Means of providing flexible support" refers to a mechanism for providing timely and optimal support tailored to the individual circumstances and needs of the user. 【0163】 This invention aims to support users' lives through a complex information processing system. It comprises a server, a terminal, and a user, with each component fulfilling its respective role. 【0164】 Hardware and software 【0165】 The server is a high-performance data processing unit equipped with large-capacity storage and high-speed data transfer capabilities. The software used includes a data management system, an emotion analysis engine, and an AI algorithm. The emotion analysis engine analyzes the user's voice and facial expressions to estimate their emotional state in real time. The AI ​​algorithm integrates these analysis results into the user's creditworthiness assessment, enabling flexible support. 【0166】 A terminal is a device used by the user to interact with the interface, and smartphones and tablets are used for this purpose. These terminals play a role in acquiring user data through voice input and cameras and transmitting it to the server. 【0167】 Data processing and computation 【0168】 Data collected from users is integrated and securely stored by the server. The sentiment analysis engine uses a generative AI model to instantly analyze the data and assess the user's emotional state. This information is incorporated into the reliability evaluation process and used as needed for adjusting surrogate roles and creating documentation. Furthermore, the server provides flexible support based on the aforementioned information and responds quickly when anomalies are detected. 【0169】 Examples of specific cases and prompt statements 【0170】 As a concrete example, when an elderly user uses this system to record their daily activity on their smartphone, the emotion analysis engine evaluates their emotional state from the tone of their voice. Based on this information, the server can adjust the appropriate support content and automatically generate and provide the necessary documents. 【0171】 As an example of a prompt, it is possible to instruct the generative AI model in the form of, "If the emotion engine detects that an elderly user has recently been feeling anxious, please tell me what specific support to provide." 【0172】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0173】 Step 1: 【0174】 The device collects data on the user's voice and facial expressions. Input includes the user's daily voice recordings and camera footage. This data is instantly transferred to the server. Specifically, the data is acquired using the smartphone's microphone and camera. 【0175】 Step 2: 【0176】 The server inputs the transmitted audio data into the emotion analysis engine. The emotion analysis engine uses a generative AI model to analyze the tone and pace of the audio and estimate the user's emotional state in real time. The output is an analysis result indicating the user's emotional state. This analysis result is used to evaluate the user's emotional state. 【0177】 Step 3: 【0178】 The server inputs all user information, including the results of sentiment analysis, into the evaluation algorithm. The AI ​​algorithm integrates health status, behavioral history, and sentiment data to assess the user's creditworthiness. The output is a user credit score, and guarantee settings are made based on this score. Specifically, a risk level assessment is performed according to the credit score. 【0179】 Step 4: 【0180】 Based on the evaluation results, the server configures the necessary support and adjusts the virtual guarantee profile. The inputs are the generated credit score and emotional state. Based on this, the necessary support measures and guarantees are individually customized. Specifically, the provision of a particular service is initiated. 【0181】 Step 5: 【0182】 The server inputs pre-processed data into a natural language processing system to generate administrative and medical documents. The output is an accurate document tailored to the user's situation, thereby streamlining document creation tasks. 【0183】 Step 6: 【0184】 The terminal presents documents received from the server to the user and prompts for electronic submission or mailing as needed. The input is the generated document data. Specifically, it provides preview and submission options through the user interface. 【0185】 Step 7: 【0186】 The server continuously monitors the user's status using a routine data monitoring system and issues a warning if an anomaly is detected. Inputs include past emotional states, behavioral patterns, and new emotional analysis results. Outputs include the generation of warning information and any necessary additional inputs. Specifically, the system sends alerts to the user and their support network. 【0187】 (Application Example 2) 【0188】 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". 【0189】 Current care support systems struggle to provide nuanced support that takes into account the emotional state of elderly individuals, resulting in insufficient assistance for users who require emotional stability. Furthermore, the lack of emotional information reflected in credit assessments prevents the provision of appropriate, virtual guarantees for users. 【0190】 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. 【0191】 In this invention, the server includes means for collecting data, means for estimating the user's emotional state in real time using an emotion analysis system, and means for complementing the credit evaluation process based on emotional information. This makes it possible to analyze the user's emotional state in detail and provide flexible support and credit evaluation in accordance with those emotions. 【0192】 "Means of data collection" refers to devices and methods for collecting data such as basic user information, health information, and behavioral patterns. 【0193】 "Means of conducting individual credit assessments" refers to a process or system that determines trustworthiness based on data collected from users. 【0194】 "Means for establishing virtual collateral" refers to a method of establishing a virtual guarantee based on the user's credit rating and adjusting the terms of the guarantee. 【0195】 "A means of estimating a user's emotional state in real time using an emotion analysis system" refers to a technology that analyzes voice, facial expressions, and behavioral data to determine the user's emotional state on the spot. 【0196】 "Means of supplementing the credit evaluation process based on emotional information" refers to a system or method that improves the accuracy of evaluations by reflecting the user's emotional state in the credit evaluation. 【0197】 "Means for processing generated procedural documents" refers to a process that automatically generates and provides documents according to the user's needs. 【0198】 "A means of monitoring the user's status and notifying and taking action when an abnormality is detected" refers to a system that constantly checks the user's status and issues an alert if there is an emotional or health abnormality, and takes necessary action. 【0199】 "Means for implementing emotional follow-up" refers to methods of providing support and communication that are tailored to the user's emotional changes. 【0200】 In the system that implements this application example, the server performs the following steps: First, the server uses a data collection module to collect data on the user's basic information, health status, and voice and behavioral patterns, and stores this data securely. Next, it uses an emotion analysis engine to estimate the emotional state in real time. This analysis uses a mechanism that converts voice data into text data using the Google® Cloud Speech-to-Text API and determines the emotion using Amazon Comprehend. 【0201】 The server then runs a credit rating algorithm, performing individual credit assessments that take emotional information into account. This requires data analysis by an AI model and also reflects the user's mental state. Based on this assessment result, virtual collateral is set. The terminal displays the generated procedural documents to the user and provides an interface to request submission as needed. 【0202】 The user's condition is constantly monitored, and if an anomaly is detected, the server immediately sends an appropriate notification to prompt care staff and family members to take action. In particular, if emotional abnormalities are observed, relaxation methods and appropriate communication are suggested. For example, if the system detects that the user is experiencing stress, a guide message such as "Try taking a deep breath" will be displayed. 【0203】 An example of a prompt message is, "Our suggested relaxation methods are deep breathing exercises, playing classical music, and a warm drink." In this way, the system goes beyond mere data analysis and quickly provides concrete solutions based on emotions. 【0204】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0205】 Step 1: 【0206】 The server collects basic user information, health information, voice and behavioral data using data collection modules and stores it in secure storage. 【0207】 The input consists of various data provided by the user, and the output is digital data stored in storage. In this data collection process, sensor data and user input are integrated and combined into a single dataset. 【0208】 Step 2: 【0209】 The server uses an emotion analysis engine to estimate the user's emotional state in real time. 【0210】 The input consists of audio and behavioral data stored in storage, and the output is an estimate of the user's emotional state. The server utilizes the Google Cloud Speech-to-Text API to convert the audio data into text, and then uses Amazon Comprehend to analyze the emotions from that text. 【0211】 Step 3: 【0212】 The server incorporates the user's emotional state into a credit rating algorithm to perform a credit assessment. 【0213】 The input consists of sentiment analysis results and other collected data, while the output is a sentiment-accepting credit rating score. The AI ​​model analyzes this data and calculates a score for credit evaluation. 【0214】 Step 4: 【0215】 The terminal presents the generated procedural document to the user and prompts them to take appropriate action as needed. 【0216】 The input consists of automatically generated documents based on credit ratings, while the output is information displayed on a user-viewable interface. The documents displayed by the terminal include information related to administrative procedures and medical matters. 【0217】 Step 5: 【0218】 The server continuously monitors the user's status and sends a prompt notification if an anomaly is detected. 【0219】 The input is real-time updated user emotional state and health data, and the output is a warning message corresponding to any anomalies. When the emotional engine detects an anomaly, the server sends an alert to the designated emergency contact. 【0220】 Step 6: 【0221】 The system provides emotional follow-up and suggests relaxation methods and positive actions to the user. 【0222】 The input is the abnormality that occurred and the emotional state that is believed to be its cause, while the output is specific instructions or advice sent to the user. For example, if the user's stress level increases, a prompt message such as "Here are some relaxation methods we suggest: deep breathing exercises, playing classical music, and a warm drink" is provided. 【0223】 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. 【0224】 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. 【0225】 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. 【0226】 [Second Embodiment] 【0227】 Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment. 【0228】 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. 【0229】 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). 【0230】 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. 【0231】 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. 【0232】 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). 【0233】 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. 【0234】 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. 【0235】 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. 【0236】 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. 【0237】 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. 【0238】 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". 【0239】 This invention is a system designed to alleviate the difficulties elderly people face in securing guarantors and the complexities of the associated procedures. The system functions based on data collection, credit assessment, virtual guarantor setup, document generation, and user status monitoring. Its overall operation is carried out through the interaction of three parties: the server, the terminal, and the user. 【0240】 The server first collects data provided by the user, including personal information, past transaction history, and health status. This data is managed in a secure environment and forms the basis for evaluating individual credit risk using AI algorithms. The server then uses machine learning models to generate a risk score and evaluate whether risk reduction is applicable. 【0241】 Once the credit assessment is complete, the server automatically creates a virtual guarantor profile. This profile meets the user's required guarantee criteria, and the digital agent fulfills this role, providing a form of guarantee that does not involve a real person. This allows the user to meet the usual guarantor requirements, ensuring smooth procedures such as facility admission and medical treatment. 【0242】 Next, the server automatically creates the necessary administrative documents based on the generated credit information. This process utilizes natural language processing technology to optimize document formatting and quickly provide error-free, accurate documents. The terminal makes these documents available for viewing and sending to the user, who can choose to download or send them directly as needed. 【0243】 The system also includes a mechanism to continuously monitor the user's health and lifestyle and provide follow-up based on this information. For example, if the server detects an anomaly, it quickly notifies the terminal and prompts the user and their support network to take the necessary action. This allows users to respond quickly and appropriately to unexpected problems. 【0244】 As a concrete example, when elderly person A, who has no relatives, enters a nursing home, they would normally be required to have a guarantor. However, by using this system, a virtual guarantor can be set up, and all necessary procedures can be automated. Person A can enter the facility safely and smoothly without having to directly participate in the procedures. 【0245】 Thus, the system of the present invention provides comprehensive support to enable elderly people to live their daily lives with peace of mind by integrating various technologies. 【0246】 The following describes the processing flow. 【0247】 Step 1: 【0248】 The user enters personal information and health data into the device. The device then prepares to send the collected data to the server. 【0249】 Step 2: 【0250】 The server receives user data sent from the terminal and stores it in a secure database. This data includes personal information, past transaction history, and health-related information. 【0251】 Step 3: 【0252】 The server preprocesses the stored data into an analyzable format and uses machine learning algorithms to assess the user's credit risk. Based on this assessment, it generates a risk score to be assigned to the user. 【0253】 Step 4: 【0254】 The server automatically builds a profile for the user that sets up a suitable virtual guarantor based on a credit risk assessment. The virtual guarantor profile includes the terms and scope of the guarantee. 【0255】 Step 5: 【0256】 The server automatically generates the necessary documents for various administrative procedures and facility admission procedures that users require. This process uses natural language processing to ensure accurate document creation. 【0257】 Step 6: 【0258】 The terminal presents the generated document to the user and offers the option to download or send it directly. The user completes the process based on their choice. 【0259】 Step 7: 【0260】 The server continuously monitors the user's health and lifestyle, regularly updating data and promptly sending follow-up notifications to the device if any abnormalities are detected. 【0261】 Step 8: 【0262】 The device receives notifications from the server and provides users with immediate information. It guides users through necessary actions and support, encouraging them to take prompt action. 【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 socially vulnerable individuals, such as the elderly, the difficulty of securing a guarantor and the complexity of the procedures involved in managing their lives without one are significant challenges. In particular, the burden of credit assessment, document preparation, and situation monitoring required for these procedures is a major issue. 【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 data, means for performing individual credit assessments using artificial intelligence, and means for setting up virtual agents. This automates procedures that require a guarantor and enables streamlined procedures and rapid problem resolution by creating a virtual guarantor as a digital agent. 【0268】 "Means of data collection" refers to the technical elements for securely receiving and storing information such as personal information, past transaction history, and health status from users. 【0269】 "Means of conducting individual credit assessments" refers to artificial intelligence-related technologies that calculate and evaluate credit risk for each user based on collected data. 【0270】 The "means of setting up a virtual agent" refer to a system that builds a digital agent based on the user's credit information and has it act as a guarantor. 【0271】 "Means of fulfilling the role of a digital agent" refers to technologies that enable a virtual entity to perform functions such as a guarantor without the need for a physical human intermediary. 【0272】 "Methods for generating documents using natural language processing technology" refers to the process of automatically creating necessary procedural documents by utilizing natural language processing, which is a part of artificial intelligence. 【0273】 "Means of monitoring lifestyle indicators" refers to technologies that have the function of continuously observing each user's health status and daily life, and collecting and analyzing data. 【0274】 A "means of rapid notification and follow-up" refers to a system that, upon detecting anomalies or significant changes, immediately communicates information to the relevant parties and prompts them to take any necessary additional action. 【0275】 The present invention will now be described in terms of embodiments. This system is designed to address the problems and procedural complexities faced by elderly individuals in securing guarantors. The system includes functions for data collection, credit assessment, virtual guarantor setup, document generation, and monitoring of health status and lifestyle indicators. 【0276】 First, users use a device to enter personal information, past transaction history, health status, etc. The data transmitted from the device is securely collected and stored on a server. This data is managed using cloud storage technologies such as AWS or Azure. 【0277】 Next, the server uses artificial intelligence to perform a credit assessment based on the collected data. This process utilizes machine learning libraries such as Python and TensorFlow to evaluate the user's credit risk. Based on this assessment, the server sets up a virtual proxy. This virtual proxy functions as a digital agent and takes on the role of a guarantor. 【0278】 The system uses natural language processing technology to generate the documents. The server automatically creates the necessary procedural documents using Python's NLTK library and other tools. The terminal provides the generated documents to the user, who can then download or send them to the relevant organization. 【0279】 Furthermore, the server continuously monitors the user's health status and lifestyle indicators, and immediately follows up if any abnormalities are detected. This function enables rapid notification and response to users and related support networks. 【0280】 As a concrete example, when elderly person A enters a nursing home, the guarantor normally required is replaced by a virtual guarantor, allowing A to enter smoothly without being involved in the procedure themselves. An example of an input prompt for the generating AI model is, "Explain the simplification of the guarantor setup and procedures required when elderly people enter nursing homes." 【0281】 In this way, by having the server, terminal, and user each fulfill their respective roles, this system can provide comprehensive support to users, including the elderly. 【0282】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0283】 Step 1: 【0284】 The user uses the terminal to input necessary data such as personal information, past transaction history, health status, etc. The input data is sent from the terminal to the server. As a result, the server safely stores these data in the database environment and prepares to collect the information required for subsequent processing. 【0285】 Step 2: 【0286】 The server uses artificial intelligence based on the collected data to perform individual credit evaluations. Specifically, program libraries such as Python and TensorFlow are used to calculate the credit risk score for each user. As a result, a risk score is generated, enabling an objective evaluation of the user's credit status. 【0287】 Step 3: 【0288】 The server sets up a virtual agent based on the calculated credit risk. This is to build a profile in which the digital agent functions as a guarantor. The constructed profile assumes the role of a guarantor without going through a physical person and assists in the smooth progress of the user's procedures. 【0289】 Step 4: 【0290】 Using natural language processing technology, the server automatically generates the necessary administrative procedure documents. Specifically, the NLTK library of Python is used to create accurate documents in the appropriate format. The generated documents are provided in an electronically accessible form according to the user's requests. 【0291】 Step 5: 【0292】 The terminal displays the generated documents to the user and supports downloading or sending them to relevant institutions. The user can check the content of the documents through the terminal and proceed with the procedures on the spot if necessary. 【0293】 Step 6: 【0294】 The server continuously monitors the user's health status and lifestyle indicators. It analyzes data collected from sensors such as smart devices and quickly notifies the device if an anomaly is detected. This allows the user and their support organization to take appropriate action quickly. 【0295】 (Application Example 1) 【0296】 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." 【0297】 The goal is to eliminate the cumbersome procedures elderly people face when securing guarantors and to resolve guarantee issues when entering medical and nursing care facilities. Furthermore, there is a need to improve efficiency and peace of mind in health management and lifestyle support. In addition, the aim is to improve the quality of daily life for the elderly through rapid information provision and automated procedures. 【0298】 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. 【0299】 In this invention, the server includes means for collecting data, means for performing individual credit assessments, and means for acting as a virtual guarantor. This enables efficient admission procedures to medical and nursing care facilities without the need for a guarantor. Furthermore, it enables improved health management and lifestyle support for the elderly through analysis based on health information and user-friendly notifications via a digital interface. 【0300】 "Means of data collection" refers to the process of obtaining personal information and health information from users. 【0301】 The means for performing individual credit evaluations is a process of evaluating and quantifying the credit risk of each user based on the collected data. 【0302】 The means for playing the role of a virtual guarantor is a process of setting up digital agents necessary for the system to conduct guarantee activities without going through actual persons. 【0303】 The means for generating documents is a process of automatically creating and preparing the documents required for necessary administrative procedures based on credit evaluations and user information. 【0304】 The means for monitoring the user's situation is a process of continuously tracking changes in the user's health status and lifestyle patterns and performing necessary follow-ups. 【0305】 The means for performing follow-ups when detecting abnormalities is a process of promptly notifying and prompting appropriate responses when abnormalities are discovered in the user's health or credit situation. 【0306】 The means for collecting and analyzing health information is a process of capturing and analyzing the user's health data and making recommendations on health risks and lifestyle habits based on that data. 【0307】 The means for providing user-friendly notifications through digital interfaces is a process of providing information from the system in a form that users can easily understand and utilize. 【0308】 The means for automatically generating and providing a certificate of permission according to information processing is a process in which the system automatically creates the official certificate of permission required in response to the user's request and provides the result to the user. 【0309】 This invention provides a system that enables elderly people to access care facilities and medical services without the need to secure guarantors or deal with complicated procedures. To achieve this, the server utilizes data collection methods to securely acquire and manage users' personal information and health status data. Python and TensorFlow are used for data analysis, and a machine learning model is run to perform individual credit assessments. This model quantifies and evaluates the user's health risk and credit risk. 【0310】 The server generates a virtual guarantor profile based on the evaluation results and makes it function as a digital agent. The user's required guarantee requirements are automatically met, eliminating the need to provide a physical guarantor. Furthermore, a generation AI model is used to automatically generate the necessary administrative documents using natural language processing technology. These documents are displayed to the user via their terminal and can be downloaded or sent as needed. 【0311】 The device features a user-friendly digital interface that displays the user's status and health data monitoring results in real time, and provides rapid follow-up when an anomaly is detected. This notification function utilizes React Native and is designed to allow users to easily check information and take appropriate action. 【0312】 For example, a user who wants to use a medical facility can proceed smoothly without needing a guarantor. Also, if any abnormality is detected in the user's health condition, a push notification will be sent immediately, enabling a quick response. An example of a prompt sentence for the generated AI model is, "Please explain the procedure for setting up a virtual guarantor so that this elderly person can receive care services safely and smoothly." 【0313】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0314】 Step 1: 【0315】 The server collects personal and health information from users. Inputs include the user's name, address, health status, and medical history. This data is securely stored on the server and undergoes initial processing such as data normalization and cleansing. The output is cleaned data ready for input into machine learning models. 【0316】 Step 2: 【0317】 The server uses TensorFlow to perform a credit assessment based on cleaned data. This process generates a user credit risk score using a machine learning algorithm. The input is the data prepared in step 1, and the output is the credit risk score. Specifically, a pre-trained model analyzes the data and outputs a numerical value indicating the level of risk. 【0318】 Step 3: 【0319】 The server uses a generated AI model to set up virtual guarantors. The input is a credit risk score, and the output is a profile of a virtual guarantor that meets the user's requirements. This profile functions as a digital agent that automatically builds the guarantee the user needs. The role of the generated profile is to relieve the user of the burden of finding a guarantor. 【0320】 Step 4: 【0321】 The server uses natural language processing to automatically generate the necessary documents. The input is a credit risk score and a virtual guarantor profile, and the output is the documents required for formal administrative procedures. Specifically, these documents are generated in formats such as PDF, and error-free documents are provided quickly. 【0322】 Step 5: 【0323】 The device notifies the user of generated documents and status monitoring results. Inputs are generated documents and monitoring data from the server, while outputs are displayed on the user's screen and push notifications. Specifically, the user interface is designed using React Native, playing a role in clearly conveying information to the user. 【0324】 Step 6: 【0325】 The user receives a notification of an anomaly detection and quickly decides on a course of action through their device. The input is the monitoring result from step 5, and the output is the user's decision on the appropriate course of action. Specifically, if a health anomaly is notified, the user can immediately seek medical assistance. 【0326】 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. 【0327】 This invention is a system that, in addition to data collection, credit evaluation, and virtual guarantee construction, integrates an emotion engine to achieve more nuanced responses that take into account the user's emotional state. This creates a comprehensive system to support the stable lives of the elderly. 【0328】 The server receives basic information and health status provided by the user via the device and stores it in secure storage. Furthermore, an emotion engine analyzes the user's voice, facial expressions, and behavioral patterns to estimate their emotional state in real time. This emotional information, along with regular data, is analyzed by AI algorithms on the server and incorporated into the user's credit evaluation process. 【0329】 The server conducts a credit assessment and sets up a virtual guarantor profile based on the assessment results. It is possible to set more detailed guarantee details according to the user's stress and anxiety levels detected by the emotion engine. This ensures that the user's mental well-being is also taken into account in the guarantee assessment. 【0330】 Furthermore, the generation of necessary administrative and medical procedural documents is also promised as an automated process. Document generation is performed using natural language processing and is provided to the user accurately and quickly. The terminal provides an interface that displays the generated documents to the user and instructs them to send them as needed. 【0331】 In its daily monitoring function, the server performs comprehensive data monitoring, including user sentiment data, and issues warnings based on anomalies detected by the sentiment engine. This function also incorporates emotional elements into the follow-up procedures when anomalies are detected, enabling flexible responses tailored to the user and their support network. 【0332】 As a concrete example, if elderly user B is using a system that incorporates an emotion engine, when B exhibits unstable emotional states in daily life, the system will take that information into consideration and provide more appropriate support measures or coordinate with the facility. Through this process, B can continue to live a secure life by receiving flexible support tailored to their emotional state at any given time. 【0333】 This invention aims to provide a user experience that far surpasses conventional guarantee and support systems by integrating an emotion engine, thereby realizing proactive life support. 【0334】 The following describes the processing flow. 【0335】 Step 1: 【0336】 Users enter basic data, including personal information and health status, using their devices. The emotion engine collects the user's emotional data through voice and facial expression analysis. 【0337】 Step 2: 【0338】 The device sends the collected data and sentiment data to the server. The server stores this data in a secure database. 【0339】 Step 3: 【0340】 The server analyzes the accumulated data and performs individual credit assessments. This assessment uses an AI algorithm, and emotional states are reflected in the credit rating. 【0341】 Step 4: 【0342】 The server sets up a virtual guarantor based on the evaluation results. Based on emotional data, if the user is experiencing stress or anxiety, the guarantor's coverage is adjusted to be more comprehensive. 【0343】 Step 5: 【0344】 The server automatically generates the documents the user needs. This process utilizes natural language processing technology to ensure that the necessary information is accurately reflected. 【0345】 Step 6: 【0346】 The terminal presents the generated document to the user and offers options for downloading or sending it. The user can follow the instructions and proceed with the process. 【0347】 Step 7: 【0348】 The server comprehensively monitors the user's health and emotional state. When the emotion engine detects an anomaly, the server considers that information to determine the appropriate follow-up steps. 【0349】 Step 8: 【0350】 The device receives notifications based on anomaly detection and guides the user through the necessary actions. This allows the user to take appropriate action. 【0351】 (Example 2) 【0352】 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". 【0353】 In an increasingly sophisticated social environment, a support system that takes psychological and emotional aspects into account is needed to further stabilize the lives of the elderly and vulnerable. However, conventional systems lack the functionality to analyze changes in users' emotions and utilize that information in support. Therefore, accurately analyzing users' emotional states and providing flexible support based on that analysis is a difficult problem. 【0354】 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. 【0355】 In this invention, the server includes means for aggregating information, means for analyzing emotional states, and means for incorporating the analyzed emotional information into the evaluation. This makes it possible to build a system that can grasp the user's emotions in real time and provide flexible and appropriate support based on that. 【0356】 "Means of aggregating information" refers to a system that collects data from multiple sources, integrates it, and stores it. 【0357】 "Evaluation" is the process of quantifying or ranking a user's creditworthiness or trustworthiness based on aggregated information and specific criteria. 【0358】 A "virtual proxy" is a component that fulfills the role of a proxy without requiring an actual person, and is a function that supports decision-making within a system. 【0359】 "Means of creating documents" refers to a technical system that automatically generates formal documents and reports based on necessary information. 【0360】 "Means of monitoring user status" refers to a system that continuously checks users' daily behavior and condition to detect abnormalities. 【0361】 "Methods for analyzing emotional states" refer to technologies that analyze a user's voice and facial expressions to infer their emotions and psychological state at that moment. 【0362】 "Means for incorporating analyzed emotional information into the evaluation" refers to a function that incorporates the results of emotional analysis into the user's overall evaluation process, thereby achieving a more comprehensive analysis. 【0363】 "Means of providing flexible support" refers to a mechanism for providing timely and optimal support tailored to the individual circumstances and needs of the user. 【0364】 This invention aims to support users' lives through a complex information processing system. It comprises a server, a terminal, and a user, with each component fulfilling its respective role. 【0365】 Hardware and software 【0366】 The server is a high-performance data processing unit equipped with large-capacity storage and high-speed data transfer capabilities. The software used includes a data management system, an emotion analysis engine, and an AI algorithm. The emotion analysis engine analyzes the user's voice and facial expressions to estimate their emotional state in real time. The AI ​​algorithm integrates these analysis results into the user's creditworthiness assessment, enabling flexible support. 【0367】 A terminal is a device used by the user to interact with the interface, and smartphones and tablets are used for this purpose. These terminals play a role in acquiring user data through voice input and cameras and transmitting it to the server. 【0368】 Data processing and computation 【0369】 Data collected from users is integrated and securely stored by the server. The sentiment analysis engine uses a generative AI model to instantly analyze the data and assess the user's emotional state. This information is incorporated into the reliability evaluation process and used as needed for adjusting surrogate roles and creating documentation. Furthermore, the server provides flexible support based on the aforementioned information and responds quickly when anomalies are detected. 【0370】 Examples of specific cases and prompt statements 【0371】 As a concrete example, when an elderly user uses this system to record their daily activity on their smartphone, the emotion analysis engine evaluates their emotional state from the tone of their voice. Based on this information, the server can adjust the appropriate support content and automatically generate and provide the necessary documents. 【0372】 As an example of a prompt, it is possible to instruct the generative AI model in the form of, "If the emotion engine detects that an elderly user has recently been feeling anxious, please tell me what specific support to provide." 【0373】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0374】 Step 1: 【0375】 The device collects data on the user's voice and facial expressions. Input includes the user's daily voice recordings and camera footage. This data is instantly transferred to the server. Specifically, the data is acquired using the smartphone's microphone and camera. 【0376】 Step 2: 【0377】 The server inputs the transmitted audio data into the emotion analysis engine. The emotion analysis engine uses a generative AI model to analyze the tone and pace of the audio and estimate the user's emotional state in real time. The output is an analysis result indicating the user's emotional state. This analysis result is used to evaluate the user's emotional state. 【0378】 Step 3: 【0379】 The server inputs all user information, including the results of sentiment analysis, into the evaluation algorithm. The AI ​​algorithm integrates health status, behavioral history, and sentiment data to assess the user's creditworthiness. The output is a user credit score, and guarantee settings are made based on this score. Specifically, a risk level assessment is performed according to the credit score. 【0380】 Step 4: 【0381】 Based on the evaluation results, the server configures the necessary support and adjusts the virtual guarantee profile. The inputs are the generated credit score and emotional state. Based on this, the necessary support measures and guarantees are individually customized. Specifically, the provision of a particular service is initiated. 【0382】 Step 5: 【0383】 The server inputs pre-processed data into a natural language processing system to generate administrative and medical documents. The output is an accurate document tailored to the user's situation, thereby streamlining document creation tasks. 【0384】 Step 6: 【0385】 The terminal presents documents received from the server to the user and prompts for electronic submission or mailing as needed. The input is the generated document data. Specifically, it provides preview and submission options through the user interface. 【0386】 Step 7: 【0387】 The server continuously monitors the user's status using a routine data monitoring system and issues a warning if an anomaly is detected. Inputs include past emotional states, behavioral patterns, and new emotional analysis results. Outputs include the generation of warning information and any necessary additional inputs. Specifically, the system sends alerts to the user and their support network. 【0388】 (Application Example 2) 【0389】 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." 【0390】 Current care support systems struggle to provide nuanced support that takes into account the emotional state of elderly individuals, resulting in insufficient assistance for users who require emotional stability. Furthermore, the lack of emotional information reflected in credit assessments prevents the provision of appropriate, virtual guarantees for users. 【0391】 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. 【0392】 In this invention, the server includes means for collecting data, means for estimating the user's emotional state in real time using an emotion analysis system, and means for complementing the credit evaluation process based on emotional information. This makes it possible to analyze the user's emotional state in detail and provide flexible support and credit evaluation in accordance with those emotions. 【0393】 "Means of data collection" refers to devices and methods for collecting data such as basic user information, health information, and behavioral patterns. 【0394】 "Means of conducting individual credit assessments" refers to a process or system that determines trustworthiness based on data collected from users. 【0395】 "Means for establishing virtual collateral" refers to a method of establishing a virtual guarantee based on the user's credit rating and adjusting the terms of the guarantee. 【0396】 "A means of estimating a user's emotional state in real time using an emotion analysis system" refers to a technology that analyzes voice, facial expressions, and behavioral data to determine the user's emotional state on the spot. 【0397】 "Means of supplementing the credit evaluation process based on emotional information" refers to a system or method that improves the accuracy of evaluations by reflecting the user's emotional state in the credit evaluation. 【0398】 "Means for processing generated procedural documents" refers to a process that automatically generates and provides documents according to the user's needs. 【0399】 "A means of monitoring the user's status and notifying and taking action when an abnormality is detected" refers to a system that constantly checks the user's status and issues an alert if there is an emotional or health abnormality, and takes necessary action. 【0400】 "Means for implementing emotional follow-up" refers to methods of providing support and communication that are tailored to the user's emotional changes. 【0401】 In the system that implements this application example, the server performs the following steps: First, the server uses a data collection module to collect data on the user's basic information, health status, and voice and behavioral patterns, and stores this data securely. Next, it uses an emotion analysis engine to estimate the emotional state in real time. This analysis uses the Google Cloud Speech-to-Text API to convert voice data into text data and Amazon Comprehend to determine the emotion. 【0402】 The server then runs a credit rating algorithm, performing individual credit assessments that take emotional information into account. This requires data analysis by an AI model and also reflects the user's mental state. Based on this assessment result, virtual collateral is set. The terminal displays the generated procedural documents to the user and provides an interface to request submission as needed. 【0403】 The user's condition is constantly monitored, and if an anomaly is detected, the server immediately sends an appropriate notification to prompt care staff and family members to take action. In particular, if emotional abnormalities are observed, relaxation methods and appropriate communication are suggested. For example, if the system detects that the user is experiencing stress, a guide message such as "Try taking a deep breath" will be displayed. 【0404】 An example of a prompt message is, "Our suggested relaxation methods are deep breathing exercises, playing classical music, and a warm drink." In this way, the system goes beyond mere data analysis and quickly provides concrete solutions based on emotions. 【0405】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0406】 Step 1: 【0407】 The server collects basic user information, health information, voice and behavioral data using data collection modules and stores it in secure storage. 【0408】 The input consists of various data provided by the user, and the output is digital data stored in storage. In this data collection process, sensor data and user input are integrated and combined into a single dataset. 【0409】 Step 2: 【0410】 The server uses an emotion analysis engine to estimate the user's emotional state in real time. 【0411】 The input consists of audio and behavioral data stored in storage, and the output is an estimate of the user's emotional state. The server utilizes the Google Cloud Speech-to-Text API to convert the audio data into text, and then uses Amazon Comprehend to analyze the emotions from that text. 【0412】 Step 3: 【0413】 The server incorporates the user's emotional state into a credit rating algorithm to perform a credit assessment. 【0414】 The input consists of sentiment analysis results and other collected data, while the output is a sentiment-accepting credit rating score. The AI ​​model analyzes this data and calculates a score for credit evaluation. 【0415】 Step 4: 【0416】 The terminal presents the generated procedural document to the user and prompts them to take appropriate action as needed. 【0417】 The input consists of automatically generated documents based on credit ratings, while the output is information displayed on a user-viewable interface. The documents displayed by the terminal include information related to administrative procedures and medical matters. 【0418】 Step 5: 【0419】 The server continuously monitors the user's status and sends a prompt notification if an anomaly is detected. 【0420】 The input is real-time updated user emotional state and health data, and the output is a warning message corresponding to any anomalies. When the emotional engine detects an anomaly, the server sends an alert to the designated emergency contact. 【0421】 Step 6: 【0422】 The system provides emotional follow-up and suggests relaxation methods and positive actions to the user. 【0423】 The input is the abnormality that occurred and the emotional state that is believed to be its cause, while the output is specific instructions or advice sent to the user. For example, if the user's stress level increases, a prompt message such as "Here are some relaxation methods we suggest: deep breathing exercises, playing classical music, and a warm drink" is provided. 【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 designed to alleviate the difficulties elderly people face in securing guarantors and the complexities of the associated procedures. The system functions based on data collection, credit assessment, virtual guarantor setup, document generation, and user status monitoring. Its overall operation is carried out through the interaction of three parties: the server, the terminal, and the user. 【0441】 The server first collects data provided by the user, including personal information, past transaction history, and health status. This data is managed in a secure environment and forms the basis for evaluating individual credit risk using AI algorithms. The server then uses machine learning models to generate a risk score and evaluate whether risk reduction is applicable. 【0442】 Once the credit assessment is complete, the server automatically creates a virtual guarantor profile. This profile meets the user's required guarantee criteria, and the digital agent fulfills this role, providing a form of guarantee that does not involve a real person. This allows the user to meet the usual guarantor requirements, ensuring smooth procedures such as facility admission and medical treatment. 【0443】 Next, the server automatically creates the necessary administrative documents based on the generated credit information. This process utilizes natural language processing technology to optimize document formatting and quickly provide error-free, accurate documents. The terminal makes these documents available for viewing and sending to the user, who can choose to download or send them directly as needed. 【0444】 The system also includes a mechanism to continuously monitor the user's health and lifestyle and provide follow-up based on this information. For example, if the server detects an anomaly, it quickly notifies the terminal and prompts the user and their support network to take the necessary action. This allows users to respond quickly and appropriately to unexpected problems. 【0445】 As a concrete example, when elderly person A, who has no relatives, enters a nursing home, they would normally be required to have a guarantor. However, by using this system, a virtual guarantor can be set up, and all necessary procedures can be automated. Person A can enter the facility safely and smoothly without having to directly participate in the procedures. 【0446】 Thus, the system of the present invention provides comprehensive support to enable elderly people to live their daily lives with peace of mind by integrating various technologies. 【0447】 The following describes the processing flow. 【0448】 Step 1: 【0449】 The user enters personal information and health data into the device. The device then prepares to send the collected data to the server. 【0450】 Step 2: 【0451】 The server receives user data sent from the terminal and stores it in a secure database. This data includes personal information, past transaction history, and health-related information. 【0452】 Step 3: 【0453】 The server preprocesses the stored data into an analyzable format and uses machine learning algorithms to assess the user's credit risk. Based on this assessment, it generates a risk score to be assigned to the user. 【0454】 Step 4: 【0455】 The server automatically builds a profile for the user that sets up a suitable virtual guarantor based on a credit risk assessment. The virtual guarantor profile includes the terms and scope of the guarantee. 【0456】 Step 5: 【0457】 The server automatically generates the necessary documents for various administrative procedures and facility admission procedures that users require. This process uses natural language processing to ensure accurate document creation. 【0458】 Step 6: 【0459】 The terminal presents the generated document to the user and offers the option to download or send it directly. The user completes the process based on their choice. 【0460】 Step 7: 【0461】 The server continuously monitors the user's health and lifestyle, regularly updating data and promptly sending follow-up notifications to the device if any abnormalities are detected. 【0462】 Step 8: 【0463】 The device receives notifications from the server and provides users with immediate information. It guides users through necessary actions and support, encouraging them to take prompt action. 【0464】 (Example 1) 【0465】 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." 【0466】 For socially vulnerable individuals, such as the elderly, the difficulty of securing a guarantor and the complexity of the procedures involved in managing their lives without one are significant challenges. In particular, the burden of credit assessment, document preparation, and situation monitoring required for these procedures is a major issue. 【0467】 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. 【0468】 In this invention, the server includes means for collecting data, means for performing individual credit assessments using artificial intelligence, and means for setting up virtual agents. This automates procedures that require a guarantor and enables streamlined procedures and rapid problem resolution by creating a virtual guarantor as a digital agent. 【0469】 "Means of data collection" refers to the technical elements for securely receiving and storing information such as personal information, past transaction history, and health status from users. 【0470】 "Means of conducting individual credit assessments" refers to artificial intelligence-related technologies that calculate and evaluate credit risk for each user based on collected data. 【0471】 The "means of setting up a virtual agent" refer to a system that builds a digital agent based on the user's credit information and has it act as a guarantor. 【0472】 "Means of fulfilling the role of a digital agent" refers to technologies that enable a virtual entity to perform functions such as a guarantor without the need for a physical human intermediary. 【0473】 "Methods for generating documents using natural language processing technology" refers to the process of automatically creating necessary procedural documents by utilizing natural language processing, which is a part of artificial intelligence. 【0474】 "Means of monitoring lifestyle indicators" refers to technologies that have the function of continuously observing each user's health status and daily life, and collecting and analyzing data. 【0475】 A "means of rapid notification and follow-up" refers to a system that, upon detecting anomalies or significant changes, immediately communicates information to the relevant parties and prompts them to take any necessary additional action. 【0476】 The present invention will now be described in terms of embodiments. This system is designed to address the problems and procedural complexities faced by elderly individuals in securing guarantors. The system includes functions for data collection, credit assessment, virtual guarantor setup, document generation, and monitoring of health status and lifestyle indicators. 【0477】 First, users use a device to enter personal information, past transaction history, health status, etc. The data transmitted from the device is securely collected and stored on a server. This data is managed using cloud storage technologies such as AWS or Azure. 【0478】 Next, the server uses artificial intelligence to perform a credit assessment based on the collected data. This process utilizes machine learning libraries such as Python and TensorFlow to evaluate the user's credit risk. Based on this assessment, the server sets up a virtual proxy. This virtual proxy functions as a digital agent and takes on the role of a guarantor. 【0479】 The system uses natural language processing technology to generate the documents. The server automatically creates the necessary procedural documents using Python's NLTK library and other tools. The terminal provides the generated documents to the user, who can then download or send them to the relevant organization. 【0480】 Furthermore, the server continuously monitors the user's health status and lifestyle indicators, and immediately follows up if any abnormalities are detected. This function enables rapid notification and response to users and related support networks. 【0481】 As a concrete example, when elderly person A enters a nursing home, the guarantor normally required is replaced by a virtual guarantor, allowing A to enter smoothly without being involved in the procedure themselves. An example of an input prompt for the generating AI model is, "Explain the simplification of the guarantor setup and procedures required when elderly people enter nursing homes." 【0482】 In this way, by having the server, terminal, and user each fulfill their respective roles, this system can provide comprehensive support to users, including the elderly. 【0483】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0484】 Step 1: 【0485】 The user uses a terminal to input necessary data such as personal information, past transaction history, and health status. The entered data is sent from the terminal to the server. This allows the server to securely store this data in its database environment and prepare to collect the information necessary for subsequent processing. 【0486】 Step 2: 【0487】 The server uses artificial intelligence based on the collected data to perform individual credit assessments. Specifically, it uses programming libraries such as Python and TensorFlow to calculate a credit risk score for each user. As a result, a risk score is generated, allowing for an objective evaluation of the user's creditworthiness. 【0488】 Step 3: 【0489】 The server sets up a virtual agent based on the calculated credit risk. This involves building a profile in which a digital agent acts as a guarantor. The constructed profile takes on the role of a guarantor without the need for a physical person, helping to ensure the user's procedures proceed smoothly. 【0490】 Step 4: 【0491】 Using natural language processing technology, the server automatically generates the necessary administrative documents. Specifically, it uses the Python NLTK library to create accurate documents in the appropriate format. The generated documents are provided in an electronically accessible format upon user request. 【0492】 Step 5: 【0493】 The terminal displays the generated documents to the user and supports downloading or sending them to the relevant authorities. Users can review the document contents through the terminal and proceed with procedures on the spot if necessary. 【0494】 Step 6: 【0495】 The server continuously monitors the user's health status and lifestyle indicators. It analyzes data collected from sensors such as smart devices and quickly notifies the device if an anomaly is detected. This allows the user and their support organization to take appropriate action quickly. 【0496】 (Application Example 1) 【0497】 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." 【0498】 The goal is to eliminate the cumbersome procedures elderly people face when securing guarantors and to resolve guarantee issues when entering medical and nursing care facilities. Furthermore, there is a need to improve efficiency and peace of mind in health management and lifestyle support. In addition, the aim is to improve the quality of daily life for the elderly through rapid information provision and automated procedures. 【0499】 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. 【0500】 In this invention, the server includes means for collecting data, means for performing individual credit assessments, and means for acting as a virtual guarantor. This enables efficient admission procedures to medical and nursing care facilities without the need for a guarantor. Furthermore, it enables improved health management and lifestyle support for the elderly through analysis based on health information and user-friendly notifications via a digital interface. 【0501】 "Means of data collection" refers to the process of obtaining personal information and health information from users. 【0502】 "Methods for conducting individual credit assessments" refer to the process of evaluating and quantifying the credit risk of each user based on collected data. 【0503】 "Means of fulfilling the role of a virtual guarantor" refers to the process of setting up a digital agent necessary for the system to carry out guarantee activities without the involvement of actual people. 【0504】 "Means of generating documents" refers to the process of automatically creating and preparing necessary administrative documents based on credit ratings and user information. 【0505】 "Means of monitoring user status" refers to the process of continuously tracking changes in the user's health status and lifestyle patterns, and providing necessary follow-up. 【0506】 "Means of follow-up when an anomaly is detected" refers to a process that promptly notifies users and encourages appropriate action when an anomaly is discovered in their health or creditworthiness. 【0507】 "Means for collecting and analyzing health information" refers to the process of taking in and analyzing users' health data and making recommendations regarding health risks and lifestyle habits based on that data. 【0508】 "Means of providing user-friendly notifications through a digital interface" refers to the process of providing information from a system in a way that is easily understandable and usable by the user. 【0509】 "Means for automatically generating and providing permits in accordance with information processing" refers to a process in which the system automatically creates the necessary official permits in response to user requests and provides the results to the user. 【0510】 This invention provides a system that enables elderly people to access care facilities and medical services without the need to secure guarantors or deal with complicated procedures. To achieve this, the server utilizes data collection methods to securely acquire and manage users' personal information and health status data. Python and TensorFlow are used for data analysis, and a machine learning model is run to perform individual credit assessments. This model quantifies and evaluates the user's health risk and credit risk. 【0511】 The server generates a virtual guarantor profile based on the evaluation results and makes it function as a digital agent. The user's required guarantee requirements are automatically met, eliminating the need to provide a physical guarantor. Furthermore, a generation AI model is used to automatically generate the necessary administrative documents using natural language processing technology. These documents are displayed to the user via their terminal and can be downloaded or sent as needed. 【0512】 The device features a user-friendly digital interface that displays the user's status and health data monitoring results in real time, and provides rapid follow-up when an anomaly is detected. This notification function utilizes React Native and is designed to allow users to easily check information and take appropriate action. 【0513】 For example, a user who wants to use a medical facility can proceed smoothly without needing a guarantor. Also, if any abnormality is detected in the user's health condition, a push notification will be sent immediately, enabling a quick response. An example of a prompt sentence for the generated AI model is, "Please explain the procedure for setting up a virtual guarantor so that this elderly person can receive care services safely and smoothly." 【0514】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0515】 Step 1: 【0516】 The server collects personal and health information from users. Inputs include the user's name, address, health status, and medical history. This data is securely stored on the server and undergoes initial processing such as data normalization and cleansing. The output is cleaned data ready for input into machine learning models. 【0517】 Step 2: 【0518】 The server uses TensorFlow to perform a credit assessment based on cleaned data. This process generates a user credit risk score using a machine learning algorithm. The input is the data prepared in step 1, and the output is the credit risk score. Specifically, a pre-trained model analyzes the data and outputs a numerical value indicating the level of risk. 【0519】 Step 3: 【0520】 The server uses a generated AI model to set up virtual guarantors. The input is a credit risk score, and the output is a profile of a virtual guarantor that meets the user's requirements. This profile functions as a digital agent that automatically builds the guarantee the user needs. The role of the generated profile is to relieve the user of the burden of finding a guarantor. 【0521】 Step 4: 【0522】 The server uses natural language processing to automatically generate the necessary documents. The input is a credit risk score and a virtual guarantor profile, and the output is the documents required for formal administrative procedures. Specifically, these documents are generated in formats such as PDF, and error-free documents are provided quickly. 【0523】 Step 5: 【0524】 The device notifies the user of generated documents and status monitoring results. Inputs are generated documents and monitoring data from the server, while outputs are displayed on the user's screen and push notifications. Specifically, the user interface is designed using React Native, playing a role in clearly conveying information to the user. 【0525】 Step 6: 【0526】 The user receives a notification of an anomaly detection and quickly decides on a course of action through their device. The input is the monitoring result from step 5, and the output is the user's decision on the appropriate course of action. Specifically, if a health anomaly is notified, the user can immediately seek medical assistance. 【0527】 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. 【0528】 This invention is a system that, in addition to data collection, credit evaluation, and virtual guarantee construction, integrates an emotion engine to achieve more nuanced responses that take into account the user's emotional state. This creates a comprehensive system to support the stable lives of the elderly. 【0529】 The server receives basic information and health status provided by the user via the device and stores it in secure storage. Furthermore, an emotion engine analyzes the user's voice, facial expressions, and behavioral patterns to estimate their emotional state in real time. This emotional information, along with regular data, is analyzed by AI algorithms on the server and incorporated into the user's credit evaluation process. 【0530】 The server conducts a credit assessment and sets up a virtual guarantor profile based on the assessment results. It is possible to set more detailed guarantee details according to the user's stress and anxiety levels detected by the emotion engine. This ensures that the user's mental well-being is also taken into account in the guarantee assessment. 【0531】 Furthermore, the generation of necessary administrative and medical procedural documents is also promised as an automated process. Document generation is performed using natural language processing and is provided to the user accurately and quickly. The terminal provides an interface that displays the generated documents to the user and instructs them to send them as needed. 【0532】 In its daily monitoring function, the server performs comprehensive data monitoring, including user sentiment data, and issues warnings based on anomalies detected by the sentiment engine. This function also incorporates emotional elements into the follow-up procedures when anomalies are detected, enabling flexible responses tailored to the user and their support network. 【0533】 As a concrete example, if elderly user B is using a system that incorporates an emotion engine, when B exhibits unstable emotional states in daily life, the system will take that information into consideration and provide more appropriate support measures or coordinate with the facility. Through this process, B can continue to live a secure life by receiving flexible support tailored to their emotional state at any given time. 【0534】 This invention aims to provide a user experience that far surpasses conventional guarantee and support systems by integrating an emotion engine, thereby realizing proactive life support. 【0535】 The following describes the processing flow. 【0536】 Step 1: 【0537】 Users enter basic data, including personal information and health status, using their devices. The emotion engine collects the user's emotional data through voice and facial expression analysis. 【0538】 Step 2: 【0539】 The device sends the collected data and sentiment data to the server. The server stores this data in a secure database. 【0540】 Step 3: 【0541】 The server analyzes the accumulated data and performs individual credit assessments. This assessment uses an AI algorithm, and emotional states are reflected in the credit rating. 【0542】 Step 4: 【0543】 The server sets up a virtual guarantor based on the evaluation results. Based on emotional data, if the user is experiencing stress or anxiety, the guarantor's coverage is adjusted to be more comprehensive. 【0544】 Step 5: 【0545】 The server automatically generates the documents the user needs. This process utilizes natural language processing technology to ensure that the necessary information is accurately reflected. 【0546】 Step 6: 【0547】 The terminal presents the generated document to the user and offers options for downloading or sending it. The user can follow the instructions and proceed with the process. 【0548】 Step 7: 【0549】 The server comprehensively monitors the user's health and emotional state. When the emotion engine detects an anomaly, the server considers that information to determine the appropriate follow-up steps. 【0550】 Step 8: 【0551】 The device receives notifications based on anomaly detection and guides the user through the necessary actions. This allows the user to take appropriate action. 【0552】 (Example 2) 【0553】 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." 【0554】 In an increasingly sophisticated social environment, a support system that takes psychological and emotional aspects into account is needed to further stabilize the lives of the elderly and vulnerable. However, conventional systems lack the functionality to analyze changes in users' emotions and utilize that information in support. Therefore, accurately analyzing users' emotional states and providing flexible support based on that analysis is a difficult problem. 【0555】 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. 【0556】 In this invention, the server includes means for aggregating information, means for analyzing emotional states, and means for incorporating the analyzed emotional information into the evaluation. This makes it possible to build a system that can grasp the user's emotions in real time and provide flexible and appropriate support based on that. 【0557】 "Means of aggregating information" refers to a system that collects data from multiple sources, integrates it, and stores it. 【0558】 "Evaluation" is the process of quantifying or ranking a user's creditworthiness or trustworthiness based on aggregated information and specific criteria. 【0559】 A "virtual proxy" is a component that fulfills the role of a proxy without requiring an actual person, and is a function that supports decision-making within a system. 【0560】 "Means of creating documents" refers to a technical system that automatically generates formal documents and reports based on necessary information. 【0561】 "Means of monitoring user status" refers to a system that continuously checks users' daily behavior and condition to detect abnormalities. 【0562】 "Methods for analyzing emotional states" refer to technologies that analyze a user's voice and facial expressions to infer their emotions and psychological state at that moment. 【0563】 "Means for incorporating analyzed emotional information into the evaluation" refers to a function that incorporates the results of emotional analysis into the user's overall evaluation process, thereby achieving a more comprehensive analysis. 【0564】 "Means of providing flexible support" refers to a mechanism for providing timely and optimal support tailored to the individual circumstances and needs of the user. 【0565】 This invention aims to support users' lives through a complex information processing system. It has a structure consisting of a server, a terminal, and a user, with each component fulfilling its respective role. 【0566】 Hardware and software 【0567】 The server is a high-performance data processing unit equipped with large-capacity storage and high-speed data transfer capabilities. The software used includes a data management system, an emotion analysis engine, and an AI algorithm. The emotion analysis engine analyzes the user's voice and facial expressions to estimate their emotional state in real time. The AI ​​algorithm integrates these analysis results into the user's creditworthiness assessment, enabling flexible support. 【0568】 A terminal is a device used by the user to interact with the interface, and smartphones and tablets are used for this purpose. These terminals play a role in acquiring user data through voice input and cameras and transmitting it to the server. 【0569】 Data processing and computation 【0570】 Data collected from users is integrated and securely stored by the server. The sentiment analysis engine uses a generative AI model to instantly analyze the data and assess the user's emotional state. This information is incorporated into the reliability evaluation process and used as needed for adjusting surrogate roles and creating documentation. Furthermore, the server provides flexible support based on the aforementioned information and responds quickly when anomalies are detected. 【0571】 Examples of specific cases and prompt statements 【0572】 As a concrete example, when an elderly user uses this system to record their daily activity on their smartphone, the emotion analysis engine evaluates their emotional state from the tone of their voice. Based on this information, the server can adjust the appropriate support content and automatically generate and provide the necessary documents. 【0573】 As an example of a prompt, it is possible to instruct the generative AI model in the form of, "If the emotion engine detects that an elderly user has recently been feeling anxious, please tell me what specific support to provide." 【0574】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0575】 Step 1: 【0576】 The device collects data on the user's voice and facial expressions. Input includes the user's daily voice recordings and camera footage. This data is instantly transferred to the server. Specifically, the data is acquired using the smartphone's microphone and camera. 【0577】 Step 2: 【0578】 The server inputs the transmitted audio data into the emotion analysis engine. The emotion analysis engine uses a generative AI model to analyze the tone and pace of the audio and estimate the user's emotional state in real time. The output is an analysis result indicating the user's emotional state. This analysis result is used to evaluate the user's emotional state. 【0579】 Step 3: 【0580】 The server inputs all user information, including the results of sentiment analysis, into the evaluation algorithm. The AI ​​algorithm integrates health status, behavioral history, and sentiment data to assess the user's creditworthiness. The output is a user credit score, and guarantee settings are made based on this score. Specifically, a risk level assessment is performed according to the credit score. 【0581】 Step 4: 【0582】 Based on the evaluation results, the server configures the necessary support and adjusts the virtual guarantee profile. The inputs are the generated credit score and emotional state. Based on this, the necessary support measures and guarantees are individually customized. Specifically, the provision of a particular service is initiated. 【0583】 Step 5: 【0584】 The server inputs pre-processed data into a natural language processing system to generate administrative and medical documents. The output is an accurate document tailored to the user's situation, thereby streamlining document creation tasks. 【0585】 Step 6: 【0586】 The terminal presents documents received from the server to the user and prompts for electronic submission or mailing as needed. The input is the generated document data. Specifically, it provides preview and submission options through the user interface. 【0587】 Step 7: 【0588】 The server continuously monitors the user's status using a routine data monitoring system and issues a warning if an anomaly is detected. Inputs include past emotional states, behavioral patterns, and new emotional analysis results. Outputs include the generation of warning information and any necessary additional inputs. Specifically, the system sends alerts to the user and their support network. 【0589】 (Application Example 2) 【0590】 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." 【0591】 Current care support systems struggle to provide nuanced support that takes into account the emotional state of elderly individuals, resulting in insufficient assistance for users who require emotional stability. Furthermore, the lack of emotional information reflected in credit assessments prevents the provision of appropriate, virtual guarantees for users. 【0592】 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. 【0593】 In this invention, the server includes means for collecting data, means for estimating the user's emotional state in real time using an emotion analysis system, and means for complementing the credit evaluation process based on emotional information. This makes it possible to analyze the user's emotional state in detail and provide flexible support and credit evaluation in accordance with those emotions. 【0594】 "Means of data collection" refers to devices and methods for collecting data such as basic user information, health information, and behavioral patterns. 【0595】 "Means of conducting individual credit assessments" refers to a process or system that determines trustworthiness based on data collected from users. 【0596】 "Means for establishing virtual collateral" refers to a method of establishing a virtual guarantee based on the user's credit rating and adjusting the terms of the guarantee. 【0597】 "A means of estimating a user's emotional state in real time using an emotion analysis system" refers to a technology that analyzes voice, facial expressions, and behavioral data to determine the user's emotional state on the spot. 【0598】 "Means of supplementing the credit evaluation process based on emotional information" refers to a system or method that improves the accuracy of evaluations by reflecting the user's emotional state in the credit evaluation. 【0599】 "Means for processing generated procedural documents" refers to a process that automatically generates and provides documents according to the user's needs. 【0600】 "A means of monitoring the user's status and notifying and taking action when an abnormality is detected" refers to a system that constantly checks the user's status and issues an alert if there is an emotional or health abnormality, and takes necessary action. 【0601】 "Means for implementing emotional follow-up" refers to methods of providing support and communication that are tailored to the user's emotional changes. 【0602】 In the system that implements this application example, the server performs the following steps: First, the server uses a data collection module to collect data on the user's basic information, health status, and voice and behavioral patterns, and stores this data securely. Next, it uses an emotion analysis engine to estimate the emotional state in real time. This analysis uses the Google Cloud Speech-to-Text API to convert voice data into text data and Amazon Comprehend to determine the emotion. 【0603】 The server then runs a credit rating algorithm, performing individual credit assessments that take emotional information into account. This requires data analysis by an AI model and also reflects the user's mental state. Based on this assessment result, virtual collateral is set. The terminal displays the generated procedural documents to the user and provides an interface to request submission as needed. 【0604】 The user's condition is constantly monitored, and if an anomaly is detected, the server immediately sends an appropriate notification to prompt care staff and family members to take action. In particular, if emotional abnormalities are observed, relaxation methods and appropriate communication are suggested. For example, if the system detects that the user is experiencing stress, a guide message such as "Try taking a deep breath" will be displayed. 【0605】 An example of a prompt message is, "Our suggested relaxation methods are deep breathing exercises, playing classical music, and a warm drink." In this way, the system goes beyond mere data analysis and quickly provides concrete solutions based on emotions. 【0606】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0607】 Step 1: 【0608】 The server collects basic user information, health information, voice and behavioral data using data collection modules and stores it in secure storage. 【0609】 The input consists of various data provided by the user, and the output is digital data stored in storage. In this data collection process, sensor data and user input are integrated and combined into a single dataset. 【0610】 Step 2: 【0611】 The server uses an emotion analysis engine to estimate the user's emotional state in real time. 【0612】 The input consists of audio and behavioral data stored in storage, and the output is an estimate of the user's emotional state. The server utilizes the Google Cloud Speech-to-Text API to convert the audio data into text, and then uses Amazon Comprehend to analyze the emotions from that text. 【0613】 Step 3: 【0614】 The server incorporates the user's emotional state into a credit rating algorithm to perform a credit assessment. 【0615】 The input consists of sentiment analysis results and other collected data, while the output is a sentiment-accepting credit rating score. The AI ​​model analyzes this data and calculates a score for credit evaluation. 【0616】 Step 4: 【0617】 The terminal presents the generated procedural document to the user and prompts them to take appropriate action as needed. 【0618】 The input consists of automatically generated documents based on credit ratings, while the output is information displayed on a user-viewable interface. The documents displayed by the terminal include information related to administrative procedures and medical matters. 【0619】 Step 5: 【0620】 The server continuously monitors the user's status and sends a prompt notification if an anomaly is detected. 【0621】 The input is real-time updated user emotional state and health data, and the output is a warning message corresponding to any anomalies. When the emotional engine detects an anomaly, the server sends an alert to the designated emergency contact. 【0622】 Step 6: 【0623】 The system provides emotional follow-up and suggests relaxation methods and positive actions to the user. 【0624】 The input is the abnormality that occurred and the emotional state that is believed to be its cause, while the output is specific instructions or advice sent to the user. For example, if the user's stress level increases, a prompt message such as "Here are some relaxation methods we suggest: deep breathing exercises, playing classical music, and a warm drink" is provided. 【0625】 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. 【0626】 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. 【0627】 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. 【0628】 [Fourth Embodiment] 【0629】 Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment. 【0630】 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. 【0631】 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). 【0632】 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. 【0633】 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. 【0634】 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). 【0635】 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. 【0636】 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. 【0637】 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. 【0638】 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. 【0639】 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. 【0640】 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. 【0641】 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". 【0642】 This invention is a system designed to alleviate the difficulties elderly people face in securing guarantors and the complexities of the associated procedures. The system functions based on data collection, credit assessment, virtual guarantor setup, document generation, and user status monitoring. Its overall operation is carried out through the interaction of three parties: the server, the terminal, and the user. 【0643】 The server first collects data provided by the user, including personal information, past transaction history, and health status. This data is managed in a secure environment and forms the basis for evaluating individual credit risk using AI algorithms. The server then uses machine learning models to generate a risk score and evaluate whether risk reduction is applicable. 【0644】 Once the credit assessment is complete, the server automatically creates a virtual guarantor profile. This profile meets the user's required guarantee criteria, and the digital agent fulfills this role, providing a form of guarantee that does not involve a real person. This allows the user to meet the usual guarantor requirements, ensuring smooth procedures such as facility admission and medical treatment. 【0645】 Next, the server automatically creates the necessary administrative documents based on the generated credit information. This process utilizes natural language processing technology to optimize document formatting and quickly provide error-free, accurate documents. The terminal makes these documents available for viewing and sending to the user, who can choose to download or send them directly as needed. 【0646】 The system also includes a mechanism to continuously monitor the user's health and lifestyle and provide follow-up based on this information. For example, if the server detects an anomaly, it quickly notifies the terminal and prompts the user and their support network to take the necessary action. This allows users to respond quickly and appropriately to unexpected problems. 【0647】 As a concrete example, when elderly person A, who has no relatives, enters a nursing home, they would normally be required to have a guarantor. However, by using this system, a virtual guarantor can be set up, and all necessary procedures can be automated. Person A can enter the facility safely and smoothly without having to directly participate in the procedures. 【0648】 Thus, the system of the present invention provides comprehensive support to enable elderly people to live their daily lives with peace of mind by integrating various technologies. 【0649】 The following describes the processing flow. 【0650】 Step 1: 【0651】 The user enters personal information and health data into the device. The device then prepares to send the collected data to the server. 【0652】 Step 2: 【0653】 The server receives user data sent from the terminal and stores it in a secure database. This data includes personal information, past transaction history, and health-related information. 【0654】 Step 3: 【0655】 The server preprocesses the stored data into an analyzable format and uses machine learning algorithms to assess the user's credit risk. Based on this assessment, it generates a risk score to be assigned to the user. 【0656】 Step 4: 【0657】 The server automatically builds a profile for the user that sets up a suitable virtual guarantor based on a credit risk assessment. The virtual guarantor profile includes the terms and scope of the guarantee. 【0658】 Step 5: 【0659】 The server automatically generates the necessary documents for various administrative procedures and facility admission procedures that users require. This process uses natural language processing to ensure accurate document creation. 【0660】 Step 6: 【0661】 The terminal presents the generated document to the user and offers the option to download or send it directly. The user completes the process based on their choice. 【0662】 Step 7: 【0663】 The server continuously monitors the user's health and lifestyle, regularly updating data and promptly sending follow-up notifications to the device if any abnormalities are detected. 【0664】 Step 8: 【0665】 The device receives notifications from the server and provides users with immediate information. It guides users through necessary actions and support, encouraging them to take prompt action. 【0666】 (Example 1) 【0667】 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". 【0668】 For socially vulnerable individuals, such as the elderly, the difficulty of securing a guarantor and the complexity of the procedures involved in managing their lives without one are significant challenges. In particular, the burden of credit assessment, document preparation, and situation monitoring required for these procedures is a major issue. 【0669】 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. 【0670】 In this invention, the server includes means for collecting data, means for performing individual credit assessments using artificial intelligence, and means for setting up virtual agents. This automates procedures that require a guarantor and enables streamlined procedures and rapid problem resolution by creating a virtual guarantor as a digital agent. 【0671】 "Means of data collection" refers to the technical elements for securely receiving and storing information such as personal information, past transaction history, and health status from users. 【0672】 "Means of conducting individual credit assessments" refers to artificial intelligence-related technologies that calculate and evaluate credit risk for each user based on collected data. 【0673】 The "means of setting up a virtual agent" refer to a system that builds a digital agent based on the user's credit information and has it act as a guarantor. 【0674】 "Means of fulfilling the role of a digital agent" refers to technologies that enable a virtual entity to perform functions such as a guarantor without the need for a physical human intermediary. 【0675】 "Methods for generating documents using natural language processing technology" refers to the process of automatically creating necessary procedural documents by utilizing natural language processing, which is a part of artificial intelligence. 【0676】 "Means of monitoring lifestyle indicators" refers to technologies that have the function of continuously observing each user's health status and daily life, and collecting and analyzing data. 【0677】 A "means of rapid notification and follow-up" refers to a system that, upon detecting anomalies or significant changes, immediately communicates information to the relevant parties and prompts them to take any necessary additional action. 【0678】 The present invention will now be described in terms of embodiments. This system is designed to address the problems and procedural complexities faced by elderly individuals in securing guarantors. The system includes functions for data collection, credit assessment, virtual guarantor setup, document generation, and monitoring of health status and lifestyle indicators. 【0679】 First, users use a device to enter personal information, past transaction history, health status, etc. The data transmitted from the device is securely collected and stored on a server. This data is managed using cloud storage technologies such as AWS or Azure. 【0680】 Next, the server uses artificial intelligence to perform a credit assessment based on the collected data. This process utilizes machine learning libraries such as Python and TensorFlow to evaluate the user's credit risk. Based on this assessment, the server sets up a virtual proxy. This virtual proxy functions as a digital agent and takes on the role of a guarantor. 【0681】 The system uses natural language processing technology to generate the documents. The server automatically creates the necessary procedural documents using Python's NLTK library and other tools. The terminal provides the generated documents to the user, who can then download or send them to the relevant organization. 【0682】 Furthermore, the server continuously monitors the user's health status and lifestyle indicators, and immediately follows up if any abnormalities are detected. This function enables rapid notification and response to users and related support networks. 【0683】 As a concrete example, when elderly person A enters a nursing home, the guarantor normally required is replaced by a virtual guarantor, allowing A to enter smoothly without being involved in the procedure themselves. An example of an input prompt for the generating AI model is, "Explain the simplification of the guarantor setup and procedures required when elderly people enter nursing homes." 【0684】 In this way, by having the server, terminal, and user each fulfill their respective roles, this system can provide comprehensive support to users, including the elderly. 【0685】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0686】 Step 1: 【0687】 The user uses a terminal to input necessary data such as personal information, past transaction history, and health status. The entered data is sent from the terminal to the server. This allows the server to securely store this data in its database environment and prepare to collect the information necessary for subsequent processing. 【0688】 Step 2: 【0689】 The server uses artificial intelligence based on the collected data to perform individual credit assessments. Specifically, it uses programming libraries such as Python and TensorFlow to calculate a credit risk score for each user. As a result, a risk score is generated, allowing for an objective evaluation of the user's creditworthiness. 【0690】 Step 3: 【0691】 The server sets up a virtual agent based on the calculated credit risk. This involves building a profile in which a digital agent acts as a guarantor. The constructed profile takes on the role of a guarantor without the need for a physical person, helping to ensure the user's procedures proceed smoothly. 【0692】 Step 4: 【0693】 Using natural language processing technology, the server automatically generates the necessary administrative documents. Specifically, it uses the Python NLTK library to create accurate documents in the appropriate format. The generated documents are provided in an electronically accessible format upon user request. 【0694】 Step 5: 【0695】 The terminal displays the generated documents to the user and supports downloading or sending them to the relevant authorities. Users can review the document contents through the terminal and proceed with procedures on the spot if necessary. 【0696】 Step 6: 【0697】 The server continuously monitors the user's health status and lifestyle indicators. It analyzes data collected from sensors such as smart devices and quickly notifies the device if an anomaly is detected. This allows the user and their support organization to take appropriate action quickly. 【0698】 (Application Example 1) 【0699】 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". 【0700】 The goal is to eliminate the cumbersome procedures elderly people face when securing guarantors and to resolve guarantee issues when entering medical and nursing care facilities. Furthermore, there is a need to improve efficiency and peace of mind in health management and lifestyle support. In addition, the aim is to improve the quality of daily life for the elderly through rapid information provision and automated procedures. 【0701】 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. 【0702】 In this invention, the server includes means for collecting data, means for performing individual credit assessments, and means for acting as a virtual guarantor. This enables efficient admission procedures to medical and nursing care facilities without the need for a guarantor. Furthermore, it enables improved health management and lifestyle support for the elderly through analysis based on health information and user-friendly notifications via a digital interface. 【0703】 "Means of data collection" refers to the process of obtaining personal information and health information from users. 【0704】 "Methods for conducting individual credit assessments" refer to the process of evaluating and quantifying the credit risk of each user based on collected data. 【0705】 "Means of fulfilling the role of a virtual guarantor" refers to the process of setting up a digital agent necessary for the system to carry out guarantee activities without the involvement of actual people. 【0706】 "Means of generating documents" refers to the process of automatically creating and preparing necessary administrative documents based on credit ratings and user information. 【0707】 "Means of monitoring user status" refers to the process of continuously tracking changes in the user's health status and lifestyle patterns, and providing necessary follow-up. 【0708】 "Means of follow-up when an anomaly is detected" refers to a process that promptly notifies users and encourages appropriate action when an anomaly is discovered in their health or creditworthiness. 【0709】 "Means for collecting and analyzing health information" refers to the process of taking in and analyzing users' health data and making recommendations regarding health risks and lifestyle habits based on that data. 【0710】 "Means of providing user-friendly notifications through a digital interface" refers to the process of providing information from a system in a way that is easily understandable and usable by the user. 【0711】 "Means for automatically generating and providing permits in accordance with information processing" refers to a process in which the system automatically creates the necessary official permits in response to user requests and provides the results to the user. 【0712】 This invention provides a system that enables elderly people to access care facilities and medical services without the need to secure guarantors or deal with complicated procedures. To achieve this, the server utilizes data collection methods to securely acquire and manage users' personal information and health status data. Python and TensorFlow are used for data analysis, and a machine learning model is run to perform individual credit assessments. This model quantifies and evaluates the user's health risk and credit risk. 【0713】 The server generates a virtual guarantor profile based on the evaluation results and makes it function as a digital agent. The user's required guarantee requirements are automatically met, eliminating the need to provide a physical guarantor. Furthermore, a generation AI model is used to automatically generate the necessary administrative documents using natural language processing technology. These documents are displayed to the user via their terminal and can be downloaded or sent as needed. 【0714】 The device features a user-friendly digital interface that displays the user's status and health data monitoring results in real time, and provides rapid follow-up when an anomaly is detected. This notification function utilizes React Native and is designed to allow users to easily check information and take appropriate action. 【0715】 For example, a user who wants to use a medical facility can proceed smoothly without needing a guarantor. Also, if any abnormality is detected in the user's health condition, a push notification will be sent immediately, enabling a quick response. An example of a prompt sentence for the generated AI model is, "Please explain the procedure for setting up a virtual guarantor so that this elderly person can receive care services safely and smoothly." 【0716】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0717】 Step 1: 【0718】 The server collects personal and health information from users. Inputs include the user's name, address, health status, and medical history. This data is securely stored on the server and undergoes initial processing such as data normalization and cleansing. The output is cleaned data ready for input into machine learning models. 【0719】 Step 2: 【0720】 The server uses TensorFlow to perform a credit assessment based on cleaned data. This process generates a user credit risk score using a machine learning algorithm. The input is the data prepared in step 1, and the output is the credit risk score. Specifically, a pre-trained model analyzes the data and outputs a numerical value indicating the level of risk. 【0721】 Step 3: 【0722】 The server uses a generated AI model to set up virtual guarantors. The input is a credit risk score, and the output is a profile of a virtual guarantor that meets the user's requirements. This profile functions as a digital agent that automatically builds the guarantee the user needs. The role of the generated profile is to relieve the user of the burden of finding a guarantor. 【0723】 Step 4: 【0724】 The server uses natural language processing to automatically generate the necessary documents. The input is a credit risk score and a virtual guarantor profile, and the output is the documents required for formal administrative procedures. Specifically, these documents are generated in formats such as PDF, and error-free documents are provided quickly. 【0725】 Step 5: 【0726】 The device notifies the user of generated documents and status monitoring results. Inputs are generated documents and monitoring data from the server, while outputs are displayed on the user's screen and push notifications. Specifically, the user interface is designed using React Native, playing a role in clearly conveying information to the user. 【0727】 Step 6: 【0728】 The user receives a notification of an anomaly detection and quickly decides on a course of action through their device. The input is the monitoring result from step 5, and the output is the user's decision on the appropriate course of action. Specifically, if a health anomaly is notified, the user can immediately seek medical assistance. 【0729】 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. 【0730】 This invention is a system that, in addition to data collection, credit evaluation, and virtual guarantee construction, integrates an emotion engine to achieve more nuanced responses that take into account the user's emotional state. This creates a comprehensive system to support the stable lives of the elderly. 【0731】 The server receives basic information and health status provided by the user via the device and stores it in secure storage. Furthermore, an emotion engine analyzes the user's voice, facial expressions, and behavioral patterns to estimate their emotional state in real time. This emotional information, along with regular data, is analyzed by AI algorithms on the server and incorporated into the user's credit evaluation process. 【0732】 The server conducts a credit assessment and sets up a virtual guarantor profile based on the assessment results. It is possible to set more detailed guarantee details according to the user's stress and anxiety levels detected by the emotion engine. This ensures that the user's mental well-being is also taken into account in the guarantee assessment. 【0733】 Furthermore, the generation of necessary administrative and medical procedural documents is also promised as an automated process. Document generation is performed using natural language processing and is provided to the user accurately and quickly. The terminal provides an interface that displays the generated documents to the user and instructs them to send them as needed. 【0734】 In its daily monitoring function, the server performs comprehensive data monitoring, including user sentiment data, and issues warnings based on anomalies detected by the sentiment engine. This function also incorporates emotional elements into the follow-up procedures when anomalies are detected, enabling flexible responses tailored to the user and their support network. 【0735】 As a concrete example, if elderly user B is using a system that incorporates an emotion engine, when B exhibits unstable emotional states in daily life, the system will take that information into consideration and provide more appropriate support measures or coordinate with the facility. Through this process, B can continue to live a secure life by receiving flexible support tailored to their emotional state at any given time. 【0736】 This invention aims to provide a user experience that far surpasses conventional guarantee and support systems by integrating an emotion engine, thereby realizing proactive life support. 【0737】 The following describes the processing flow. 【0738】 Step 1: 【0739】 Users enter basic data, including personal information and health status, using their devices. The emotion engine collects the user's emotional data through voice and facial expression analysis. 【0740】 Step 2: 【0741】 The device sends the collected data and sentiment data to the server. The server stores this data in a secure database. 【0742】 Step 3: 【0743】 The server analyzes the accumulated data and performs individual credit assessments. This assessment uses an AI algorithm, and emotional states are reflected in the credit rating. 【0744】 Step 4: 【0745】 The server sets up a virtual guarantor based on the evaluation results. Based on emotional data, if the user is experiencing stress or anxiety, the guarantor's coverage is adjusted to be more comprehensive. 【0746】 Step 5: 【0747】 The server automatically generates the documents the user needs. This process utilizes natural language processing technology to ensure that the necessary information is accurately reflected. 【0748】 Step 6: 【0749】 The terminal presents the generated document to the user and offers options for downloading or sending it. The user can follow the instructions and proceed with the process. 【0750】 Step 7: 【0751】 The server comprehensively monitors the user's health and emotional state. When the emotion engine detects an anomaly, the server considers that information to determine the appropriate follow-up steps. 【0752】 Step 8: 【0753】 The device receives notifications based on anomaly detection and guides the user through the necessary actions. This allows the user to take appropriate action. 【0754】 (Example 2) 【0755】 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". 【0756】 In an increasingly sophisticated social environment, a support system that takes psychological and emotional aspects into account is needed to further stabilize the lives of the elderly and vulnerable. However, conventional systems lack the functionality to analyze changes in users' emotions and utilize that information in support. Therefore, accurately analyzing users' emotional states and providing flexible support based on that analysis is a difficult problem. 【0757】 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. 【0758】 In this invention, the server includes means for aggregating information, means for analyzing emotional states, and means for incorporating the analyzed emotional information into the evaluation. This makes it possible to build a system that can grasp the user's emotions in real time and provide flexible and appropriate support based on that. 【0759】 "Means of aggregating information" refers to a system that collects data from multiple sources, integrates it, and stores it. 【0760】 "Evaluation" is the process of quantifying or ranking a user's creditworthiness or trustworthiness based on aggregated information and specific criteria. 【0761】 A "virtual proxy" is a component that fulfills the role of a proxy without requiring an actual person, and is a function that supports decision-making within a system. 【0762】 "Means of creating documents" refers to a technical system that automatically generates formal documents and reports based on necessary information. 【0763】 "Means of monitoring user status" refers to a system that continuously checks users' daily behavior and condition to detect abnormalities. 【0764】 "Methods for analyzing emotional states" refer to technologies that analyze a user's voice and facial expressions to infer their emotions and psychological state at that moment. 【0765】 "Means for incorporating analyzed emotional information into the evaluation" refers to a function that incorporates the results of emotional analysis into the user's overall evaluation process, thereby achieving a more comprehensive analysis. 【0766】 "Means of providing flexible support" refers to a mechanism for providing timely and optimal support tailored to the individual circumstances and needs of the user. 【0767】 This invention aims to support users' lives through a complex information processing system. It has a structure consisting of a server, a terminal, and a user, with each component fulfilling its respective role. 【0768】 Hardware and software 【0769】 The server is a high-performance data processing unit equipped with large-capacity storage and high-speed data transfer capabilities. The software used includes a data management system, an emotion analysis engine, and an AI algorithm. The emotion analysis engine analyzes the user's voice and facial expressions to estimate their emotional state in real time. The AI ​​algorithm integrates these analysis results into the user's creditworthiness assessment, enabling flexible support. 【0770】 A terminal is a device used by the user to interact with the interface, and smartphones and tablets are used for this purpose. These terminals play a role in acquiring user data through voice input and cameras and transmitting it to the server. 【0771】 Data processing and computation 【0772】 Data collected from users is integrated and securely stored by the server. The sentiment analysis engine uses a generative AI model to instantly analyze the data and assess the user's emotional state. This information is incorporated into the reliability evaluation process and used as needed for adjusting surrogate roles and creating documentation. Furthermore, the server provides flexible support based on the aforementioned information and responds quickly when anomalies are detected. 【0773】 Examples of specific cases and prompt statements 【0774】 As a concrete example, when an elderly user uses this system to record their daily activity on their smartphone, the emotion analysis engine evaluates their emotional state from the tone of their voice. Based on this information, the server can adjust the appropriate support content and automatically generate and provide the necessary documents. 【0775】 As an example of a prompt, it is possible to instruct the generative AI model in the form of, "If the emotion engine detects that an elderly user has recently been feeling anxious, please tell me what specific support to provide." 【0776】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0777】 Step 1: 【0778】 The device collects data on the user's voice and facial expressions. Input includes the user's daily voice recordings and camera footage. This data is instantly transferred to the server. Specifically, the data is acquired using the smartphone's microphone and camera. 【0779】 Step 2: 【0780】 The server inputs the transmitted audio data into the emotion analysis engine. The emotion analysis engine uses a generative AI model to analyze the tone and pace of the audio and estimate the user's emotional state in real time. The output is an analysis result indicating the user's emotional state. This analysis result is used to evaluate the user's emotional state. 【0781】 Step 3: 【0782】 The server inputs all user information, including the results of sentiment analysis, into the evaluation algorithm. The AI ​​algorithm integrates health status, behavioral history, and sentiment data to assess the user's creditworthiness. The output is a user credit score, and guarantee settings are made based on this score. Specifically, a risk level assessment is performed according to the credit score. 【0783】 Step 4: 【0784】 Based on the evaluation results, the server configures the necessary support and adjusts the virtual guarantee profile. The inputs are the generated credit score and emotional state. Based on this, the necessary support measures and guarantees are individually customized. Specifically, the provision of a particular service is initiated. 【0785】 Step 5: 【0786】 The server inputs pre-processed data into a natural language processing system to generate administrative and medical documents. The output is an accurate document tailored to the user's situation, thereby streamlining document creation tasks. 【0787】 Step 6: 【0788】 The terminal presents documents received from the server to the user and prompts for electronic submission or mailing as needed. The input is the generated document data. Specifically, it provides preview and submission options through the user interface. 【0789】 Step 7: 【0790】 The server continuously monitors the user's status using a routine data monitoring system and issues a warning if an anomaly is detected. Inputs include past emotional states, behavioral patterns, and new emotional analysis results. Outputs include the generation of warning information and any necessary additional inputs. Specifically, the system sends alerts to the user and their support network. 【0791】 (Application Example 2) 【0792】 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". 【0793】 Current care support systems struggle to provide nuanced support that takes into account the emotional state of elderly individuals, resulting in insufficient assistance for users who require emotional stability. Furthermore, the lack of emotional information reflected in credit assessments prevents the provision of appropriate, virtual guarantees for users. 【0794】 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. 【0795】 In this invention, the server includes means for collecting data, means for estimating the user's emotional state in real time using an emotion analysis system, and means for complementing the credit evaluation process based on emotional information. This makes it possible to analyze the user's emotional state in detail and provide flexible support and credit evaluation in accordance with those emotions. 【0796】 "Means of data collection" refers to devices and methods for collecting data such as basic user information, health information, and behavioral patterns. 【0797】 "Means of conducting individual credit assessments" refers to a process or system that determines trustworthiness based on data collected from users. 【0798】 "Means for establishing virtual collateral" refers to a method of establishing a virtual guarantee based on the user's credit rating and adjusting the terms of the guarantee. 【0799】 "A means of estimating a user's emotional state in real time using an emotion analysis system" refers to a technology that analyzes voice, facial expressions, and behavioral data to determine the user's emotional state on the spot. 【0800】 "Means of supplementing the credit evaluation process based on emotional information" refers to a system or method that improves the accuracy of evaluations by reflecting the user's emotional state in the credit evaluation. 【0801】 "Means for processing generated procedural documents" refers to a process that automatically generates and provides documents according to the user's needs. 【0802】 "A means of monitoring the user's status and notifying and taking action when an abnormality is detected" refers to a system that constantly checks the user's status and issues an alert if there is an emotional or health abnormality, and takes necessary action. 【0803】 "Means for implementing emotional follow-up" refers to methods of providing support and communication that are tailored to the user's emotional changes. 【0804】 In the system that implements this application example, the server performs the following steps: First, the server uses a data collection module to collect data on the user's basic information, health status, and voice and behavioral patterns, and stores this data securely. Next, it uses an emotion analysis engine to estimate the emotional state in real time. This analysis uses the Google Cloud Speech-to-Text API to convert voice data into text data and Amazon Comprehend to determine the emotion. 【0805】 The server then runs a credit rating algorithm, performing individual credit assessments that take emotional information into account. This requires data analysis by an AI model and also reflects the user's mental state. Based on this assessment result, virtual collateral is set. The terminal displays the generated procedural documents to the user and provides an interface to request submission as needed. 【0806】 The user's condition is constantly monitored, and if an anomaly is detected, the server immediately sends an appropriate notification to prompt care staff and family members to take action. In particular, if emotional abnormalities are observed, relaxation methods and appropriate communication are suggested. For example, if the system detects that the user is experiencing stress, a guide message such as "Try taking a deep breath" will be displayed. 【0807】 An example of a prompt message is, "Our suggested relaxation methods are deep breathing exercises, playing classical music, and a warm drink." In this way, the system goes beyond mere data analysis and quickly provides concrete solutions based on emotions. 【0808】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0809】 Step 1: 【0810】 The server collects basic user information, health information, voice and behavioral data using data collection modules and stores it in secure storage. 【0811】 The input consists of various data provided by the user, and the output is digital data stored in storage. In this data collection process, sensor data and user input are integrated and combined into a single dataset. 【0812】 Step 2: 【0813】 The server uses an emotion analysis engine to estimate the user's emotional state in real time. 【0814】 The input consists of audio and behavioral data stored in storage, and the output is an estimate of the user's emotional state. The server utilizes the Google Cloud Speech-to-Text API to convert the audio data into text, and then uses Amazon Comprehend to analyze the emotions from that text. 【0815】 Step 3: 【0816】 The server incorporates the user's emotional state into a credit rating algorithm to perform a credit assessment. 【0817】 The input consists of sentiment analysis results and other collected data, while the output is a sentiment-accepting credit rating score. The AI ​​model analyzes this data and calculates a score for credit evaluation. 【0818】 Step 4: 【0819】 The terminal presents the generated procedural document to the user and prompts them to take appropriate action as needed. 【0820】 The input consists of automatically generated documents based on credit ratings, while the output is information displayed on a user-viewable interface. The documents displayed by the terminal include information related to administrative procedures and medical matters. 【0821】 Step 5: 【0822】 The server continuously monitors the user's status and sends a prompt notification if an anomaly is detected. 【0823】 The input is real-time updated user emotional state and health data, and the output is a warning message corresponding to any anomalies. When the emotional engine detects an anomaly, the server sends an alert to the designated emergency contact. 【0824】 Step 6: 【0825】 The system provides emotional follow-up and suggests relaxation methods and positive actions to the user. 【0826】 The input is the abnormality that occurred and the emotional state that is believed to be its cause, while the output is specific instructions or advice sent to the user. For example, if the user's stress level increases, a prompt message such as "Here are some relaxation methods we suggest: deep breathing exercises, playing classical music, and a warm drink" is provided. 【0827】 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. 【0828】 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. 【0829】 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. 【0830】 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. 【0831】 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. 【0832】 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. 【0833】 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. 【0834】 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. 【0835】 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." 【0836】 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. 【0837】 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. 【0838】 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. 【0839】 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. 【0840】 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. 【0841】 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. 【0842】 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. 【0843】 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. 【0844】 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. 【0845】 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. 【0846】 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. 【0847】 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 as being incorporated by reference. 【0848】 The following is further disclosed regarding the embodiments described above. 【0849】 (Claim 1) 【0850】 Means of collecting data, 【0851】 A means of conducting individual credit assessments based on the aforementioned data, 【0852】 A means of appointing a guarantor based on the aforementioned credit evaluation, 【0853】 Means of fulfilling the role of a virtual guarantor, 【0854】 Means for generating documents, 【0855】 Means for monitoring user status, 【0856】 A means of follow-up when an anomaly is detected. 【0857】 A system that includes this. 【0858】 (Claim 2) 【0859】 Means for setting credit evaluation criteria, 【0860】 A means of determining whether or not a guarantee can be provided based on individual credit assessments. 【0861】 The system according to claim 1, including the following: 【0862】 (Claim 3) 【0863】 Means for providing the generated documents, 【0864】 Means of notifying the user 【0865】 The system according to claim 1, including the following: 【0866】 "Example 1" 【0867】 (Claim 1) 【0868】 Means of collecting data, 【0869】 A means of performing individual credit evaluations using artificial intelligence based on the aforementioned data, 【0870】 Means for establishing a virtual agent based on the aforementioned credit evaluation, 【0871】 Means of fulfilling the role of a digital agent, 【0872】 A means of generating documents using natural language processing technology, 【0873】 A means of monitoring users' lifestyle indicators, 【0874】 A means of quickly notifying and following up when an anomaly is detected. 【0875】 A system that includes this. 【0876】 (Claim 2) 【0877】 Means for setting credit evaluation criteria, 【0878】 A method for determining the feasibility of guarantees based on individual credit assessments and automatically constructing virtual agents. 【0879】 The system according to claim 1, including the following: 【0880】 (Claim 3) 【0881】 A means for displaying and distributing the generated documents, 【0882】 A means of notifying users of anomalies or important information. 【0883】 The system according to claim 1, including the following: 【0884】 "Application Example 1" 【0885】 (Claim 1) 【0886】 Means of collecting data, 【0887】 A means of conducting individual credit assessments based on the aforementioned data, 【0888】 A means of appointing a guarantor based on the aforementioned credit evaluation, 【0889】 Means of fulfilling the role of a virtual guarantor, 【0890】 Means for generating documents, 【0891】 Means for monitoring user status, 【0892】 A means of following up when an anomaly is detected, 【0893】 Means for collecting and analyzing health information, 【0894】 A means of providing user-friendly notifications through a digital interface, 【0895】 A means of automatically generating and providing permits based on information processing. 【0896】 A system that includes this. 【0897】 (Claim 2) 【0898】 Means for setting credit evaluation criteria, 【0899】 A means of determining whether or not a guarantee is possible based on individual credit assessments, 【0900】 A means of evaluating the situation based on health information. 【0901】 The system according to claim 1, including the following: 【0902】 (Claim 3) 【0903】 Means for providing the generated documents, 【0904】 Means of notifying the user, 【0905】 A means of providing an interface to support the necessary procedures when using long-term care services. 【0906】 The system according to claim 1, including the following: 【0907】 "Example 2 of combining an emotion engine" 【0908】 (Claim 1) 【0909】 Means of aggregating information, 【0910】 A means for performing an evaluation based on the aforementioned information, 【0911】 Means for setting up an agent based on the aforementioned evaluation, 【0912】 A means of performing the function of a virtual proxy, 【0913】 The means of creating a document, 【0914】 Means for monitoring the user's status, 【0915】 Means for taking action when an anomaly is detected, 【0916】 A means of analyzing emotional states, 【0917】 Means for incorporating the analyzed emotional information into the evaluation, 【0918】 A means of providing flexible support based on emotional information. 【0919】 A system that includes this. 【0920】 (Claim 2) 【0921】 Means for setting evaluation criteria, 【0922】 A means of determining whether or not a guarantee is available based on individual evaluations. 【0923】 The system according to claim 1, including the following: 【0924】 (Claim 3) 【0925】 Means of providing the created document, 【0926】 Means of informing users 【0927】 The system according to claim 1, including the following: 【0928】 "Application example 2 when combining with an emotional engine" 【0929】 (Claim 1) 【0930】 Means of collecting data, 【0931】 A means of conducting individual credit assessments based on the aforementioned data, 【0932】 A means for establishing a virtual collateral based on the aforementioned credit assessment, 【0933】 A means for estimating the user's emotional state in real time using an emotion analysis system, 【0934】 A means to complement the credit evaluation process based on emotional information, 【0935】 A means for processing the generated procedural document, 【0936】 A means of monitoring the user's status and notifying and taking action when an anomaly is detected, 【0937】 Means for conducting emotional follow-up 【0938】 A system that includes this. 【0939】 (Claim 2) 【0940】 The system according to claim 1, comprising means for setting credit evaluation criteria and performing evaluations that reflect emotional states, and for determining whether or not a guarantee can be provided based on individual credit evaluations. 【0941】 (Claim 3) 【0942】 The system according to claim 1, comprising means for providing the generated procedural document to the user and for providing necessary notifications. [Explanation of symbols] 【0943】 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

[Claim 1] Means of collecting data, A means of conducting individual credit assessments based on the aforementioned data, A means of appointing a guarantor based on the aforementioned credit evaluation, Means of fulfilling the role of a virtual guarantor, Means for generating documents, Means for monitoring user status, A means of follow-up when an anomaly is detected. A system that includes this. [Claim 2] Means for setting credit evaluation criteria, A means of determining whether or not a guarantee can be provided based on individual credit assessments. The system according to claim 1, including the following: [Claim 3] Means for providing the generated documents, Means of notifying the user The system according to claim 1, including the following:

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