system

Abstract

Provide a system. 【Solution means】 Means for analyzing contract data and collecting individual authentication information, credit information, and living environment, Means for evaluating the credit risk of each individual using the collected data, Means for setting a virtual guarantee entity based on the evaluation, Means for providing services by setting a virtual guarantee entity, Means for receiving data necessary for generating submission materials and automatically generating the materials, Means for monitoring the user's living environment and health status and sending notifications, Means for analyzing health data and sending real-time notifications in case of abnormalities, A system including the above.

Description

Technical Field

[0005] , ,

[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

Summary of the Invention

Problems to be Solved by the Invention

[0004] With the progress of an aging society, in modern times where the number of elderly people without relatives is increasing, a guarantor is often required when entering a medical institution or facility. Due to having no relatives, there is a problem that this requirement cannot be met. Furthermore, the document preparation for performing necessary procedures is complicated, and there is also a problem that the system for quickly responding to a sudden change in the health condition in daily life is not established. In order to solve these problems, it is necessary to provide a system in which the elderly can live with confidence and receive necessary services.

Means for Solving the Problems

[0005] This invention provides a means for analyzing personal authentication information, credit information, and living conditions from contract information, and for evaluating individual credit risk based on this analysis. Furthermore, it sets up a virtual guarantor based on the evaluation results, thereby creating a system that allows elderly people without family support to receive the necessary guarantees. In addition, it provides a system that automatically generates documents that users need to submit, monitors their living conditions and health status, and immediately issues an alert if an abnormality is detected. This reduces anxiety among the elderly and supports a safe and comfortable life.

[0006] "Contract information" refers to information about contracts entered into by individuals or corporations in order to use specific services, and includes contract details, identification information of the contractor, and contract period.

[0007] "Authentication information" refers to data used to verify an individual's identity, and includes information such as name, date of birth, address, or social identification number.

[0008] "Credit information" refers to information used to assess the creditworthiness of an individual or corporation, and includes payment history, outstanding loan balances, credit scores, etc.

[0009] A "virtual guarantor" is not a real person, but a non-materialized entity created on a computer system that has the function of providing a specific guarantee.

[0010] "Automatic document generation" is a process in which a program automatically creates the necessary documents based on the information entered, while maintaining consistency in format and content.

[0011] "Monitoring" is the process of continuously observing the state of an individual or subject and collecting and analyzing data to detect anomalies.

[0012] An "alert" is a function that sends a notification based on pre-set conditions when an abnormality or event requiring attention occurs. [Brief explanation of the drawing]

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

[0014] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

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

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

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

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

[0019] 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).

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

[0021] [First Embodiment]

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

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

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

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

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

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

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

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

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

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

[0032] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

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

[0034] This invention is a support system for elderly people without family support in an aging society. The system is designed based on a server analyzing individual contract information and evaluating credit information and living conditions. The server collects contract information using software and a database, and uses this data to assess each individual's credit risk. Based on the evaluation results, it sets up a guarantee in the form of a virtual guarantor and provides necessary support.

[0035] As a concrete example, the server analyzes the contract information of a 70-year-old single male customer. In this process, it focuses on evaluating identity verification information and past payment history, and identifies a non-existent entity generated on the computer as a virtual guarantor. Furthermore, the terminal receives information entered by the customer or their representative and automatically generates documents required for submission to government agencies and nursing homes using AI technology. This utilizes natural language processing to format the information and provide it in the appropriate format.

[0036] Furthermore, this system has the functionality to monitor the user's living situation and health status through the terminal. The server analyzes real-time data acquired from sensors and other sources, and immediately issues an alert if it detects an abnormality in the user's health status. This notification is sent to the terminal, prompting the user to take prompt action. In this way, the system helps ensure the safety and peace of mind of elderly people in their daily lives.

[0037] The following describes the processing flow.

[0038] Step 1:

[0039] The server retrieves customer contract information from the database. This process involves collecting basic data necessary for analysis, including detailed information such as identity verification information, mobile phone usage history, and past payment history.

[0040] Step 2:

[0041] The server analyzes the acquired contract information and formats the data. Here, it uses machine learning algorithms to assess credit risk and performs scoring based on data related to the customer's living situation and health status.

[0042] Step 3:

[0043] The server sets up virtual guarantors based on credit ratings. This ensures that AI entities that meet certain criteria act as guarantees for customers.

[0044] Step 4:

[0045] The terminal receives the information necessary to generate the submission documents from the user. The user logs into the system and completes the provided form.

[0046] Step 5:

[0047] The server executes an automated document generation algorithm based on the received information. Using natural language processing technology, it generates consistent text, formats it, and creates the document.

[0048] Step 6:

[0049] The terminal allows the user to preview the generated document and make any necessary corrections. The user can then submit the document after final review.

[0050] Step 7:

[0051] The server continuously monitors the customer's lifestyle and health status, collecting data in real time. This involves analyzing information from the customer's devices and various sensors.

[0052] Step 8:

[0053] The server immediately issues an alert if it detects an anomaly in the data. The terminal receives this notification and displays a warning to the user or relevant party, enabling a quick response.

[0054] (Example 1)

[0055] 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."

[0056] In an aging society, there is a need to ensure the stability and safety of elderly people who have no family support. However, conventional credit rating systems and health monitoring systems are not fully integrated, making it difficult to provide comprehensive support tailored to the individual needs of each elderly person.

[0057] 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.

[0058] In this invention, the server includes means for collecting and analyzing personal contract information to obtain authentication information, credit information, and living conditions; means for evaluating individual credit risk based on the collected information using a generative AI model; and means for generating a virtual guarantor based on the evaluation results. This enables credit guarantees and health management that allow elderly people to live with peace of mind.

[0059] "Personal contract information" refers to information exchanged when an individual engages in various services or transactions, and includes data such as identity verification and payment history.

[0060] "Authentication information" refers to information used to prove an individual's identity, and includes names, addresses, identification numbers, etc.

[0061] "Credit information" refers to information used to assess an individual's financial reliability, primarily encompassing past payment history and debt status.

[0062] "Living conditions" refers to the circumstances of an individual's daily life, particularly information such as income, housing, and health status.

[0063] A "generative AI model" is a type of artificial intelligence algorithm used to analyze large amounts of data and generate patterns and predictions.

[0064] "Credit risk" is an assessment of the likelihood that an individual will not make the payments they have promised, and it is an indicator of interest to financial institutions and guarantors.

[0065] A "virtual guarantor" is not a real person, but rather an in-program entity that provides a guarantee function generated on a computer.

[0066] A "service guarantee" is a promise to ensure that a service is performed under certain conditions, and is usually intended to mitigate financial risk.

[0067] "Automatic document generation" is a process that automatically creates documents using a specified template based on the entered data.

[0068] "Sensor information" refers to data acquired by various sensors, and in particular includes information about the environment and physical condition.

[0069] An "alert" is a warning message that the system sends to the user when it detects an abnormality or a situation that requires attention.

[0070] This invention provides a comprehensive support system for the elderly. The system mainly consists of a server and terminals, and uses a generative AI model to perform credit risk assessment and health status monitoring.

[0071] The server first collects individual contract information. This process includes a mechanism that uses a database management system to obtain authentication information such as identity verification information and past contract history, as well as information about the individual's living situation. Next, the server uses a generative AI model to assess the individual's credit risk based on the collected data. The AI ​​model calculates a risk score based on past payment history and financial situation. At this time, the server uses prompt messages to the AI ​​model such as "Perform a risk assessment based on payment history over the past 5 years."

[0072] Based on the credit risk assessment results, the server generates a virtual guarantor. This virtual guarantor is a non-physical entity created within the program and provides guarantees to the user as needed. The establishment of this virtual guarantor enables the provision of services to the elderly.

[0073] The terminal plays the role of creating documents that need to be submitted to government agencies and nursing homes, based on information entered by the user. The terminal utilizes natural language processing technology to apply the user's input to a template, format it in the required format, and output it. For example, when a user signs a contract for care services, the terminal automatically generates a complete set of application documents.

[0074] Furthermore, the device monitors the user's lifestyle and health status in real time using sensors. The server analyzes the data sent from the sensors and immediately issues an alert if an anomaly is detected. This alert is displayed on the device, prompting the user and relevant parties to take prompt action. For example, if the user's heart rate suddenly increases, the server generates a notification such as "Rapid change in heart rate detected, action recommended" and sends it to the device.

[0075] This system allows elderly people to live their daily lives with peace of mind and enables early intervention in situations where they need support.

[0076] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0077] Step 1:

[0078] The server collects individual contract information. It receives basic user information as input and retrieves authentication information and past contract history from the database. Specifically, the server sends queries to the database management system, extracts the relevant information, and prepares it for analysis. The output is an individual contract-related dataset.

[0079] Step 2:

[0080] The server uses a generative AI model to assess an individual's credit risk based on the collected information. The input is the contract information dataset obtained in Step 1, and the output is a risk score. Specifically, the server inputs the prompt "Perform a risk assessment based on payment history over the past 5 years" into the generative AI model, and the AI ​​calculates the risk score.

[0081] Step 3:

[0082] The server generates a virtual guarantor based on the results of the credit risk assessment. The input is the risk score from step 2, and the output is the data profile of the virtual guarantor. Specifically, the server analyzes the assessment score, determines the appropriate guarantee level based on the risk, and sets that information for the virtual guarantor within the program.

[0083] Step 4:

[0084] The terminal receives information provided by the user and automatically generates documents. Input is information entered by the user, and output is a formatted document. Specifically, the terminal embeds the data entered by the user into a document template and uses natural language processing to export the document as a PDF in the appropriate format.

[0085] Step 5:

[0086] The device monitors the user's lifestyle and health status through sensors. Input is real-time data from the sensors, and output is monitoring reports and alerts. Specifically, the device periodically receives data from the sensors and sends that information to the server.

[0087] Step 6:

[0088] The server analyzes the monitoring data and issues an alert if an anomaly is detected. The input is the monitoring data from step 5, and the output is the alert notification. Specifically, the server applies an anomaly detection algorithm, and if an anomaly exceeds a threshold, it generates an alert message such as "A sudden change in heart rate has been detected, and action is recommended," and sends it to the terminal.

[0089] (Application Example 1)

[0090] 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."

[0091] In an aging society, seniors without family support face challenges such as credit risk, lack of life support, and difficulty in early detection of health abnormalities. As a result, seniors often face difficulties in accessing the services and support they need. Therefore, there is a growing need for a credit rating system using virtual guarantee entities and a support system that enables real-time monitoring of health status.

[0092] 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.

[0093] In this invention, the server includes means for analyzing contract data and collecting individual authentication information, credit information, and living environment information; means for evaluating the credit risk of each individual using the collected data; and means for analyzing health data and sending real-time notifications in the event of an anomaly. This makes it possible to evaluate and guarantee the creditworthiness of elderly people who have no family support, as well as to quickly detect and notify them of any abnormalities in their health condition.

[0094] "Contract data" refers to a collection of information based on an agreement an individual makes to receive a service.

[0095] "Authentication information" refers to data used to verify an individual's identity and authority.

[0096] "Credit information" refers to financial and payment history information necessary to assess an individual's creditworthiness.

[0097] "Living environment" refers to information about an individual's current living situation and environment.

[0098] "Credit risk" is an indicator that shows the likelihood that an individual may be unable to fulfill their contractual obligations.

[0099] A "virtual guarantee entity" is a digital entity created within a program to complement the creditworthiness of an individual.

[0100] "Providing a service" refers to a series of activities that provide the support and convenience that individuals need.

[0101] "Submitted documents" are documents created by an individual for official presentation to a government agency or corporation.

[0102] "Health data" refers to information about an individual's health status, obtained from sensors and other devices.

[0103] "Real-time notification" refers to an informational message that is sent to an individual immediately when an event occurs.

[0104] To implement this invention, an elderly support system is used. The server analyzes contract data, collects individual authentication information, credit information, and living environment information, and evaluates each individual's credit risk based on this information. Depending on the credit risk, a virtual guarantee entity is generated within the program, and services are provided based on that information. This allows users to receive the support and services they need with peace of mind.

[0105] The server analyzes health data and continuously monitors the individual's health status based on information obtained from sensors and devices. If an abnormality is detected, it sends a real-time notification to prompt the user to take immediate action. For the specific analysis of health data, Python and related data processing libraries (NumPy, Pandas) are used, and the necessary information is formatted and provided using natural language processing technology.

[0106] In one embodiment, a server monitors vital signs such as temperature and heart rate in the user's living environment via internet-connected sensors, and sends notifications via smartphones or other devices when abnormal patterns are detected.

[0107] When using a generative AI model to automatically generate submission documents, the following prompt can be used: "As a generative AI model, please explain how to use this document generation system to analyze a specific contract situation and automatically create the necessary documents." This prompt serves as a guide for the generative AI model to perform the appropriate document creation procedure.

[0108] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0109] Step 1:

[0110] The server receives contract data from users and stores it in a database. Inputs include user authentication information, credit information, and living environment. The server analyzes this information to prepare foundational data for assessing credit risk. A data processing library is used for data analysis.

[0111] Step 2:

[0112] The server assesses each user's credit risk based on the collected contract data. This involves analyzing the user's past payment history and lifestyle to calculate a risk score. This process is used to quantify credit risk from the input data and generate a virtual guarantee entity. The output is the risk score.

[0113] Step 3:

[0114] The server generates a virtual guarantee entity within the program based on the generated credit risk and contract details. This entity complements the user's credit risk and facilitates the use of various services. The input is a credit risk score, and the output is the generation of a virtual guarantee entity.

[0115] Step 4:

[0116] The server receives real-time data from sensors to acquire health information. This allows it to monitor the user's health status and aim for early detection of abnormalities. The input is sensor data, and the output is the result of anomaly detection.

[0117] Step 5:

[0118] The server sends real-time notifications to the user's device when an abnormality in their health status is detected. This notification allows the user to take prompt medical action. The input is the abnormality detection result, and the output is the notification sent to the device.

[0119] Step 6:

[0120] The server uses a generative AI model to process prompts for automatically generating the necessary submission documents. It analyzes the data provided by the user and formats the documents appropriately. The input is the user's contract and health data, and the output is the completed submission document.

[0121] 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.

[0122] This invention is a support system for elderly people without family support in an aging society, and is characterized by its integration of an emotional engine. The system is server-centric and analyzes personal authentication information, credit information, and living conditions from contract information. Based on the data obtained from this analysis, the server evaluates each individual's credit risk, sets up a virtual guarantor, and provides the customer with the necessary services.

[0123] Specifically, the server retrieves data on a 70-year-old single male customer, evaluates his credit information and living situation, and sets up a virtual guarantor. This virtual guarantor's guarantee function allows the customer to meet the requirements for necessary medical care and admission to nursing homes.

[0124] Furthermore, terminals equipped with an emotion engine analyze the user's voice and facial expressions to recognize their emotional state. For example, if a user experiences stress or anxiety in their daily life, the terminal automatically determines their emotional state and provides appropriate alerts and support. In addition, the terminal receives information from the user and runs a document generation program on the server to generate necessary submission documents. Utilizing natural language processing technology, the information is formatted and the automatically generated documents are previewed by the user for final confirmation.

[0125] Furthermore, the server has the function of continuously monitoring the user's living situation and health status. Monitoring is performed based on real-time data acquired from terminals and sensors, and if an abnormality is detected, an alert is immediately issued, taking into account the user's emotional state. In this way, the system of the present invention is effective in supporting seniors to live safe and secure lives.

[0126] The following describes the processing flow.

[0127] Step 1:

[0128] The server retrieves customer contract information from the database. This is a process that collects data on customer identity verification, credit information, and living conditions.

[0129] Step 2:

[0130] The server uses the acquired contract information to assess an individual's credit risk. Using machine learning algorithms, it analyzes payment history and lifestyle to score the customer's trustworthiness.

[0131] Step 3:

[0132] The server sets up a virtual guarantor based on the results of a credit risk assessment. The virtual guarantor is designed as a computer program and fulfills the guarantee conditions required for the customer to use the service.

[0133] Step 4:

[0134] The terminal prompts the user to input information for necessary documents. The user registers the information required for submission to nursing homes and government agencies through the system's interface.

[0135] Step 5:

[0136] The server executes an automated document generation process based on the input information. It uses AI to organize the information and applies natural language processing technology to generate submission documents that conform to the format.

[0137] Step 6:

[0138] The terminal presents the generated document to the user and prompts them to make changes if necessary. Through this review phase, the user makes final approval of the document.

[0139] Step 7:

[0140] The server continuously monitors the user's lifestyle and health status. It utilizes sensors and external data sources to ensure an immediate response in the event of an anomaly.

[0141] Step 8:

[0142] The device uses an emotion engine to analyze the user's emotional state. It captures the user's voice and facial expressions using a camera and microphone, recognizes emotions based on that data, and provides personalized support as needed.

[0143] Step 9:

[0144] The server issues situation-specific alerts based on monitoring and sentiment recognition results. This allows users to be quickly alerted and take appropriate action.

[0145] (Example 2)

[0146] 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."

[0147] In an aging society, it is difficult to assess the credit risk of senior citizens without family support, and they often require guarantors to receive necessary services, but there is a lack of readily available means to secure such guarantors. Furthermore, technologies for emotional analysis to maintain the mental health of seniors, and technologies for effectively monitoring their lifestyles and health status, are not yet sufficiently developed. As a result, there is currently a lack of support systems in place to ensure that seniors can live safe and secure lives.

[0148] 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.

[0149] In this invention, the server includes means for analyzing contract information and collecting personal authentication information, credit information, and living conditions; means for evaluating individual credit risk and setting up a virtual guarantor to provide support functions; means for analyzing voice and video data and recognizing personal emotions; means for automatically generating submission documents using natural language processing technology; and means for monitoring health and living conditions and issuing alerts. This provides an environment in which seniors can receive necessary services with peace of mind and enables appropriate management of their physical and mental health.

[0150] "Contract information" refers to data concerning the conditions and individual agreements that individuals need when using a service.

[0151] "Authentication information" refers to data used to verify an individual's identity and identification, including their name, date of birth, and address.

[0152] "Credit information" refers to data used to evaluate an individual's financial history, ability to pay, and creditworthiness.

[0153] "Living conditions" refers to data related to an individual's lifelong activities and living environment, including housing conditions and lifestyle habits.

[0154] "Credit risk" refers to a numerical value or indicator that assesses the likelihood of an individual defaulting on their debts in the future.

[0155] A "virtual guarantor" refers to an entity that does not actually exist but fulfills the role of a guarantor within a program, and is set up to complement credit risk.

[0156] "Support function" refers to a function provided by a virtual guarantor to enable an individual to receive necessary services.

[0157] "Audio data" refers to information about an individual's voice, including pitch, speed, and volume.

[0158] "Video data" refers to data that includes visual information such as an individual's facial expressions and movements.

[0159] "Recognizing emotions" refers to analyzing audio and video data to estimate an individual's psychological state.

[0160] "Natural language processing technology" refers to the technology used to analyze and generate human language using computers.

[0161] "Automatic generation" refers to a system generating necessary documents and information without human intervention.

[0162] "Health status" refers to an individual's physical or mental health condition.

[0163] "Monitoring" refers to the continuous collection and analysis of data to monitor an individual's health and living conditions.

[0164] "Issuing an alert" refers to the act of notifying a user of a warning when an anomaly is detected.

[0165] This invention is a support system for an aging society, particularly targeting seniors who have no family support. This system is built around a server and aims to provide seniors with a safe and secure living environment by integrating and offering multiple functions.

[0166] The server uses a database management system to collect and analyze contract information, authentication information, credit information, and lifestyle data. Specifically, the database management system (DBMS) is operated using SQL, and a risk assessment algorithm is used for credit information analysis. As a result of the analysis, the individual credit risk is evaluated, and based on this evaluation, a virtual guarantor is set up within the program. This virtual guarantor serves to support the user when they receive specific conditions or services.

[0167] The device is equipped with a microphone and camera for emotion analysis, and uses voice analysis software and facial recognition algorithms to recognize emotions from the user's voice and facial expressions. For example, if a user experiences stress in their daily life, the system will automatically determine that emotion and provide appropriate support.

[0168] In document generation, after the terminal receives the necessary information from the user, the server uses natural language processing technology to format the information and automatically generate the submission document. The user can preview the generated document and use it as the official document after confirming its contents. This improves the efficiency of the procedure and reduces the burden on the user.

[0169] Furthermore, the server has the capability to monitor living conditions and health status in real time, and uses data collected from devices and sensors to immediately issue an alert if an anomaly is detected. This alert is sent to the user or designated contacts via email or app notification.

[0170] As a concrete example, by inputting a prompt message such as, "A 70-year-old single man wants to enter a nursing home. Please set up a virtual guarantor considering his credit information and living situation," into the AI ​​model, it is possible to customize appropriate services according to individual credit risk and living circumstances.

[0171] This system provides comprehensive support to seniors without family, enabling them to continue living with peace of mind.

[0172] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0173] Step 1:

[0174] The server collects contract information.

[0175] The server uses a database management system to retrieve user contract information. This information includes name, age, address, and past contract history. Based on this data, authentication and credit information are collected. It receives information from the database as input and creates a dataset for analysis as output.

[0176] Step 2:

[0177] The server assesses the individual's credit risk.

[0178] The server processes the collected data through an analysis algorithm to assess the individual credit risk. The main inputs are contract information and past credit history, and the output is the user's credit score. A high credit score indicates low risk, while a low score indicates high risk.

[0179] Step 3:

[0180] The server sets up a virtual guarantor.

[0181] The server sets up a virtual guarantor within the program based on the evaluated credit score. The input information is the credit score and the required service conditions, and a virtual guarantor object is generated as output. This ensures that the user is guaranteed when receiving services.

[0182] Step 4:

[0183] The device analyzes the user's voice.

[0184] The device collects voice data using its built-in microphone and recognizes emotions using voice analysis software. The input is the user's voice, and the output is their emotional state (e.g., stress, relief). The tone and tempo of the voice are analyzed to infer the user's emotions.

[0185] Step 5:

[0186] The device analyzes the user's facial expressions.

[0187] The device captures facial data through its camera and analyzes it using a facial recognition algorithm. The input data is real-time video, and the output is analyzed emotional information. For example, it can detect smiles and frown lines to evaluate emotions.

[0188] Step 6:

[0189] The terminal collects information necessary for generating the required documents.

[0190] The user enters the necessary information through the terminal interface. This information includes name, address, and application details, and is sent to the server as input data. The output is a formatted set of information.

[0191] Step 7:

[0192] The server automatically generates the documents.

[0193] The server processes the received information using natural language processing technology and automatically generates documents for submission. The input data is information entered by the user, and the output is in the format of a completed document template. The generated document is previewed by the user for content verification.

[0194] Step 8:

[0195] The server monitors the user's living situation and health status.

[0196] The server continuously monitors the user's status based on data from terminals and external devices. Inputs include sensor data and user activity logs, while outputs include assessments of health status and lifestyle abnormalities. If an abnormality is detected, an alert is quickly issued and the user is notified.

[0197] (Application Example 2)

[0198] 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 device 14 will be referred to as the "terminal."

[0199] In an aging society, there is a growing need for support systems that enable elderly people without family support to live with peace of mind. In particular, difficulties in accessing financial resources, medical facilities, and the lack of emotional support in daily life are significant challenges. Effective solutions to these challenges are essential.

[0200] 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.

[0201] In this invention, the server includes means for analyzing contract information and collecting personal authentication information, credit information, and living conditions; means for providing services by setting up a virtual guarantor; and means for analyzing emotional states and providing support for stress and anxiety. This enables comprehensive support for elderly people to live with peace of mind.

[0202] "Contract information" refers to information that shows the terms of the agreement regarding the use of the service concluded between the user and the service provider.

[0203] "Personal authentication information" refers to information used to verify the user's identity.

[0204] "Credit information" refers to information that indicates a user's financial reliability and ability to pay.

[0205] "Living conditions" refers to information that describes the environment and conditions related to the user's daily life.

[0206] "Credit risk" is the result of an assessment of the potential risks related to the user's creditworthiness.

[0207] A "virtual guarantor" is a non-existent guarantor established for the purpose of providing a service.

[0208] "Service" refers to the various forms of support and benefits provided to users.

[0209] "Submitted documents" are official documents required to use a particular service.

[0210] "Methods for automatically generating documents" refers to a function that automatically creates necessary documents based on information provided by the user.

[0211] "Monitoring" refers to the continuous observation of a user's lifestyle and health status.

[0212] An "alert" is a function that notifies the user when a specific condition or event occurs.

[0213] "Emotional state" refers to the user's psychological state and changes in their emotions.

[0214] "Support for stress and anxiety" refers to providing support to alleviate the psychological burden that users experience.

[0215] "Means of facilitating access to healthcare" refers to functions that help users receive healthcare services smoothly.

[0216] This system connects a server and user terminals to provide multifaceted support to elderly individuals without family support. The server analyzes contract information and obtains personal authentication information, credit information, and living conditions. Based on this, it assesses individual credit risk and, if necessary, generates a virtual guarantor. This virtual guarantor's guarantee function allows elderly individuals to proceed smoothly with procedures at medical institutions and welfare facilities.

[0217] The user terminal is equipped with an emotion engine that analyzes voice input and facial expressions to understand the user's emotional state in real time. If stress or anxiety is detected as a result of the emotion analysis, relaxation guides and mental support are immediately provided. Furthermore, if access to a medical institution is necessary, the terminal sends a request to the server to assist in providing appropriate information.

[0218] This system also incorporates a real-time monitoring function for living conditions and health status. The server analyzes data obtained from devices and sensors, and if an anomaly is detected, it sends an alert to the user. This process also takes emotional states into account, enabling more personalized support than simply receiving notifications based on numerical anomalies.

[0219] For example, if a user reports, "I've been having trouble sleeping lately, and it's making me a little anxious," the system analyzes this and suggests relaxation music and breathing exercises. It also automatically records the user's health status and stores this information on the server for use during future medical visits if necessary.

[0220] Examples of prompts for a generative AI model include the following:

[0221] "Please provide ideas for relaxation activities to offer to users aged 65 and over who are experiencing anxiety."

[0222] "Based on the living conditions information obtained from users, please create a proposal for a reliable monitoring system."

[0223] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0224] Step 1:

[0225] The server analyzes contract information and collects personal authentication information, credit information, and living conditions. In this process, contract information is provided as input, and detailed evaluation data about the user is output using database search and analysis algorithms. Specifically, the server retrieves relevant information from the contract database, analyzes it, and extracts individual attribute information.

[0226] Step 2:

[0227] The server uses the collected data to assess credit risk and set up virtual guarantors. The assessment data extracted in the previous step is used as input, and a credit risk score is output through analysis using a statistical model. Specifically, the server runs the statistical model and generates a digital asset called a virtual guarantor based on the score.

[0228] Step 3:

[0229] The user terminal analyzes the emotional state using an emotion engine. This process receives voice input and facial recognition data, and outputs the emotional state using natural language processing and image processing techniques. The terminal utilizes a microphone and camera to process the data obtained in real time and identify the user's emotional state.

[0230] Step 4:

[0231] If stress or anxiety is detected as a result of the emotional state analysis, the device will provide a relaxation guide. The input is the emotional analysis result, and the output is relaxation content tailored to the user. The device performs audio playback and video guidance through a mobile application.

[0232] Step 5:

[0233] The server monitors living conditions and health status and issues alerts when necessary. This process uses data from sensors as input, which is then analyzed by an anomaly detection algorithm before an alert message is output. The server continuously receives data from the monitoring system and notifies the user and relevant authorities as needed.

[0234] Step 6:

[0235] The server provides the information necessary to facilitate access to healthcare facilities. This process uses user information and a healthcare facility database as input and outputs links to relevant healthcare services. The server then performs a process to suggest accessible healthcare facilities, taking into account the user's location.

[0236] 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.

[0237] 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.

[0238] 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.

[0239] [Second Embodiment]

[0240] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0241] 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.

[0242] 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).

[0243] 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.

[0244] 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.

[0245] 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).

[0246] 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.

[0247] 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.

[0248] 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.

[0249] 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.

[0250] 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.

[0251] 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".

[0252] This invention is a support system for elderly people without family support in an aging society. The system is designed based on a server analyzing individual contract information and evaluating credit information and living conditions. The server collects contract information using software and a database, and uses this data to assess each individual's credit risk. Based on the evaluation results, it sets up a guarantee in the form of a virtual guarantor and provides necessary support.

[0253] As a concrete example, the server analyzes the contract information of a 70-year-old single male customer. In this process, it focuses on evaluating identity verification information and past payment history, and identifies a non-existent entity generated on the computer as a virtual guarantor. Furthermore, the terminal receives information entered by the customer or their representative and automatically generates documents required for submission to government agencies and nursing homes using AI technology. This utilizes natural language processing to format the information and provide it in the appropriate format.

[0254] Furthermore, this system has the functionality to monitor the user's living situation and health status through the terminal. The server analyzes real-time data acquired from sensors and other sources, and immediately issues an alert if it detects an abnormality in the user's health status. This notification is sent to the terminal, prompting the user to take prompt action. In this way, the system helps ensure the safety and peace of mind of elderly people in their daily lives.

[0255] The following describes the processing flow.

[0256] Step 1:

[0257] The server retrieves customer contract information from the database. This process involves collecting basic data necessary for analysis, including detailed information such as identity verification information, mobile phone usage history, and past payment history.

[0258] Step 2:

[0259] The server analyzes the acquired contract information and formats the data. Here, it uses machine learning algorithms to assess credit risk and performs scoring based on data related to the customer's living situation and health status.

[0260] Step 3:

[0261] The server sets up virtual guarantors based on credit ratings. This ensures that AI entities that meet certain criteria act as guarantees for customers.

[0262] Step 4:

[0263] The terminal receives the information necessary to generate the submission documents from the user. The user logs into the system and completes the provided form.

[0264] Step 5:

[0265] The server executes an automated document generation algorithm based on the received information. Using natural language processing technology, it generates consistent text, formats it, and creates the document.

[0266] Step 6:

[0267] The terminal allows the user to preview the generated document and make any necessary corrections. The user can then submit the document after final review.

[0268] Step 7:

[0269] The server continuously monitors the customer's lifestyle and health status, collecting data in real time. This involves analyzing information from the customer's devices and various sensors.

[0270] Step 8:

[0271] The server immediately issues an alert if it detects an anomaly in the data. The terminal receives this notification and displays a warning to the user or relevant party, enabling a quick response.

[0272] (Example 1)

[0273] 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".

[0274] In an aging society, there is a need to ensure the stability and safety of elderly people who have no family support. However, conventional credit rating systems and health monitoring systems are not fully integrated, making it difficult to provide comprehensive support tailored to the individual needs of each elderly person.

[0275] 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.

[0276] In this invention, the server includes means for collecting and analyzing personal contract information to obtain authentication information, credit information, and living conditions; means for evaluating individual credit risk based on the collected information using a generative AI model; and means for generating a virtual guarantor based on the evaluation results. This enables credit guarantees and health management that allow elderly people to live with peace of mind.

[0277] "Personal contract information" refers to information exchanged when an individual engages in various services or transactions, and includes data such as identity verification and payment history.

[0278] "Authentication information" refers to information used to prove an individual's identity, and includes names, addresses, identification numbers, etc.

[0279] "Credit information" refers to information used to assess an individual's financial reliability, primarily encompassing past payment history and debt status.

[0280] "Living conditions" refers to the circumstances of an individual's daily life, particularly information such as income, housing, and health status.

[0281] A "generative AI model" is a type of artificial intelligence algorithm used to analyze large amounts of data and generate patterns and predictions.

[0282] "Credit risk" is an assessment of the likelihood that an individual will not make the payments they have promised, and it is an indicator of interest to financial institutions and guarantors.

[0283] A "virtual guarantor" is not a real entity but an in-program entity that provides a guarantee function generated on a computer.

[0284] "Service guarantee" is a promise to ensure the execution of a service under certain conditions, usually aimed at reducing financial risks.

[0285] "Document automatic generation" is a process of automatically creating documents using a specified template based on the input data.

[0286] "Sensor information" refers to data obtained by various sensors, especially including information related to the environment and physical conditions.

[0287] An "alert" is a warning message that notifies the user when the system detects an abnormal or attention-required situation.

[0288] This invention provides a comprehensive support system for the elderly. The system is mainly composed of a server and a terminal, and uses a generative AI model to conduct credit risk assessment and health status monitoring.

[0289] The server first collects an individual's contract information. This process includes a mechanism for obtaining authentication information such as identity verification information and past contract history, as well as living situation information, using a database management system. Next, the server evaluates the individual's credit risk based on the collected data using a generative AI model. The AI model calculates a risk score based on past payment history and economic situation. At this time, the server uses a prompt sentence such as "Perform a risk assessment based on the payment history of the past five years" for the AI model.

[0290] Based on the credit risk assessment results, the server generates a virtual guarantor. This virtual guarantor is a non-physical entity created within the program and provides guarantees to the user as needed. The establishment of this virtual guarantor enables the provision of services to the elderly.

[0291] The terminal plays the role of creating documents that need to be submitted to government agencies and nursing homes, based on information entered by the user. The terminal utilizes natural language processing technology to apply the user's input to a template, format it in the required format, and output it. For example, when a user signs a contract for care services, the terminal automatically generates a complete set of application documents.

[0292] Furthermore, the device monitors the user's lifestyle and health status in real time using sensors. The server analyzes the data sent from the sensors and immediately issues an alert if an anomaly is detected. This alert is displayed on the device, prompting the user and relevant parties to take prompt action. For example, if the user's heart rate suddenly increases, the server generates a notification such as "Rapid change in heart rate detected, action recommended" and sends it to the device.

[0293] This system allows elderly people to live their daily lives with peace of mind and enables early intervention in situations where they need support.

[0294] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0295] Step 1:

[0296] The server collects individual contract information. It receives basic user information as input and retrieves authentication information and past contract history from the database. Specifically, the server sends queries to the database management system, extracts the relevant information, and prepares it for analysis. The output is an individual contract-related dataset.

[0297] Step 2:

[0298] The server uses a generative AI model to assess an individual's credit risk based on the collected information. The input is the contract information dataset obtained in Step 1, and the output is a risk score. Specifically, the server inputs the prompt "Perform a risk assessment based on payment history over the past 5 years" into the generative AI model, and the AI ​​calculates the risk score.

[0299] Step 3:

[0300] The server generates a virtual guarantor based on the results of the credit risk assessment. The input is the risk score from step 2, and the output is the data profile of the virtual guarantor. Specifically, the server analyzes the assessment score, determines the appropriate guarantee level based on the risk, and sets that information for the virtual guarantor within the program.

[0301] Step 4:

[0302] The terminal receives information provided by the user and automatically generates documents. Input is information entered by the user, and output is a formatted document. Specifically, the terminal embeds the data entered by the user into a document template and uses natural language processing to export the document as a PDF in the appropriate format.

[0303] Step 5:

[0304] The device monitors the user's lifestyle and health status through sensors. Input is real-time data from the sensors, and output is monitoring reports and alerts. Specifically, the device periodically receives data from the sensors and sends that information to the server.

[0305] Step 6:

[0306] The server analyzes the monitoring data and sends an alert when an anomaly is detected. The input is the monitoring data from Step 5, and the output is an alert notification. Specifically, the server applies an anomaly detection algorithm. If there is an anomaly exceeding the threshold, it generates an alert message such as "Detect a sudden change in heart rate and recommend a response" and sends it to the terminal.

[0307] (Application Example 1)

[0308] Next, Application Example 1 will be described. In the following description, the data processing device 12 is referred to as the "server", and the smart glasses 214 are referred to as the "terminal".

[0309] In an aging society, there are problems such as the difficulty of early detection of credit risks, lack of life support, and abnormal health conditions faced by the senior layer without relatives. As a result, situations occur where it is difficult to receive services and support required by the senior layer. Therefore, the need for a credit evaluation system using virtual guarantee entities and a support system enabling real-time monitoring of health conditions is increasing.

[0310] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0311] In this invention, the server includes means for analyzing contract data to collect individual authentication information, credit information, and living environment, means for evaluating the credit risk of each individual using the collected data, and means for analyzing health data and sending a real-time notification in case of an anomaly. This enables the evaluation and guarantee of credit for the senior layer without relatives, and further enables the rapid detection and notification of abnormal health conditions.

[0312] "Contract data" is a set of information based on the agreement made by an individual to receive a service.

[0313] "Authentication information" is data for confirming an individual's identity and authority.

[0314] "Credit information" refers to financial and payment history information necessary to assess an individual's creditworthiness.

[0315] "Living environment" refers to information about an individual's current living situation and environment.

[0316] "Credit risk" is an indicator that shows the likelihood that an individual may be unable to fulfill their contractual obligations.

[0317] A "virtual guarantee entity" is a digital entity created within a program to complement the creditworthiness of an individual.

[0318] "Providing a service" refers to a series of activities that provide the support and convenience that individuals need.

[0319] "Submitted documents" are documents created by an individual for official presentation to a government agency or corporation.

[0320] "Health data" refers to information about an individual's health status, obtained from sensors and other devices.

[0321] "Real-time notification" refers to an informational message that is sent to an individual immediately when an event occurs.

[0322] To implement this invention, an elderly support system is used. The server analyzes contract data, collects individual authentication information, credit information, and living environment information, and evaluates each individual's credit risk based on this information. Depending on the credit risk, a virtual guarantee entity is generated within the program, and services are provided based on that information. This allows users to receive the support and services they need with peace of mind.

[0323] The server analyzes health data and continuously monitors the individual's health status based on information obtained from sensors and devices. If an abnormality is detected, it sends a real-time notification to prompt the user to take immediate action. For the specific analysis of health data, Python and related data processing libraries (NumPy, Pandas) are used, and the necessary information is formatted and provided using natural language processing technology.

[0324] In one embodiment, a server monitors vital signs such as temperature and heart rate in the user's living environment via internet-connected sensors, and sends notifications via smartphones or other devices when abnormal patterns are detected.

[0325] When using a generative AI model to automatically generate submission documents, the following prompt can be used: "As a generative AI model, please explain how to use this document generation system to analyze a specific contract situation and automatically create the necessary documents." This prompt serves as a guide for the generative AI model to perform the appropriate document creation procedure.

[0326] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0327] Step 1:

[0328] The server receives contract data from users and stores it in a database. Inputs include user authentication information, credit information, and living environment. The server analyzes this information to prepare foundational data for assessing credit risk. A data processing library is used for data analysis.

[0329] Step 2:

[0330] The server assesses each user's credit risk based on the collected contract data. This involves analyzing the user's past payment history and lifestyle to calculate a risk score. This process is used to quantify credit risk from the input data and generate a virtual guarantee entity. The output is the risk score.

[0331] Step 3:

[0332] The server generates a virtual guarantee entity within the program based on the generated credit risk and contract details. This entity complements the user's credit risk and facilitates the use of various services. The input is a credit risk score, and the output is the generation of a virtual guarantee entity.

[0333] Step 4:

[0334] The server receives real-time data from sensors to acquire health information. This allows it to monitor the user's health status and aim for early detection of abnormalities. The input is sensor data, and the output is the result of anomaly detection.

[0335] Step 5:

[0336] The server sends real-time notifications to the user's device when an abnormality in their health status is detected. This notification allows the user to take prompt medical action. The input is the abnormality detection result, and the output is the notification sent to the device.

[0337] Step 6:

[0338] The server uses a generative AI model to process prompts for automatically generating the necessary submission documents. It analyzes the data provided by the user and formats the documents appropriately. The input is the user's contract and health data, and the output is the completed submission document.

[0339] 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.

[0340] This invention is a support system for elderly people without family support in an aging society, and is characterized by its integration of an emotional engine. The system is server-centric and analyzes personal authentication information, credit information, and living conditions from contract information. Based on the data obtained from this analysis, the server evaluates each individual's credit risk, sets up a virtual guarantor, and provides the customer with the necessary services.

[0341] Specifically, the server retrieves data on a 70-year-old single male customer, evaluates his credit information and living situation, and sets up a virtual guarantor. This virtual guarantor's guarantee function allows the customer to meet the requirements for necessary medical care and admission to nursing homes.

[0342] Furthermore, terminals equipped with an emotion engine analyze the user's voice and facial expressions to recognize their emotional state. For example, if a user experiences stress or anxiety in their daily life, the terminal automatically determines their emotional state and provides appropriate alerts and support. In addition, the terminal receives information from the user and runs a document generation program on the server to generate necessary submission documents. Utilizing natural language processing technology, the information is formatted and the automatically generated documents are previewed by the user for final confirmation.

[0343] Furthermore, the server has the function of continuously monitoring the user's living situation and health status. Monitoring is performed based on real-time data acquired from terminals and sensors, and if an abnormality is detected, an alert is immediately issued, taking into account the user's emotional state. In this way, the system of the present invention is effective in supporting seniors to live safe and secure lives.

[0344] The following describes the processing flow.

[0345] Step 1:

[0346] The server retrieves customer contract information from the database. This is a process that collects data on customer identity verification, credit information, and living conditions.

[0347] Step 2:

[0348] The server uses the acquired contract information to assess an individual's credit risk. Using machine learning algorithms, it analyzes payment history and lifestyle to score the customer's trustworthiness.

[0349] Step 3:

[0350] The server sets up a virtual guarantor based on the results of a credit risk assessment. The virtual guarantor is designed as a computer program and fulfills the guarantee conditions required for the customer to use the service.

[0351] Step 4:

[0352] The terminal prompts the user to input information for necessary documents. The user registers the information required for submission to nursing homes and government agencies through the system's interface.

[0353] Step 5:

[0354] The server executes an automated document generation process based on the input information. It uses AI to organize the information and applies natural language processing technology to generate submission documents that conform to the format.

[0355] Step 6:

[0356] The terminal presents the generated document to the user and prompts them to make changes if necessary. Through this review phase, the user makes final approval of the document.

[0357] Step 7:

[0358] The server continuously monitors the user's lifestyle and health status. It utilizes sensors and external data sources to ensure an immediate response in the event of an anomaly.

[0359] Step 8:

[0360] The device uses an emotion engine to analyze the user's emotional state. It captures the user's voice and facial expressions using a camera and microphone, recognizes emotions based on that data, and provides personalized support as needed.

[0361] Step 9:

[0362] The server issues situation-specific alerts based on monitoring and sentiment recognition results. This allows users to be quickly alerted and take appropriate action.

[0363] (Example 2)

[0364] 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".

[0365] In an aging society, it is difficult to assess the credit risk of senior citizens without family support, and they often require guarantors to receive necessary services, but there is a lack of readily available means to secure such guarantors. Furthermore, technologies for emotional analysis to maintain the mental health of seniors, and technologies for effectively monitoring their lifestyles and health status, are not yet sufficiently developed. As a result, there is currently a lack of support systems in place to ensure that seniors can live safe and secure lives.

[0366] 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.

[0367] In this invention, the server includes means for analyzing contract information and collecting personal authentication information, credit information, and living conditions; means for evaluating individual credit risk and setting up a virtual guarantor to provide support functions; means for analyzing voice and video data and recognizing personal emotions; means for automatically generating submission documents using natural language processing technology; and means for monitoring health and living conditions and issuing alerts. This provides an environment in which seniors can receive necessary services with peace of mind and enables appropriate management of their physical and mental health.

[0368] "Contract information" refers to data concerning the conditions and individual agreements that individuals need when using a service.

[0369] "Authentication information" refers to data used to verify an individual's identity and identification, including their name, date of birth, and address.

[0370] "Credit information" refers to data used to evaluate an individual's financial history, ability to pay, and creditworthiness.

[0371] "Living conditions" refers to data related to an individual's lifelong activities and living environment, including housing conditions and lifestyle habits.

[0372] "Credit risk" refers to a numerical value or indicator that assesses the likelihood of an individual defaulting on their debts in the future.

[0373] A "virtual guarantor" refers to an entity that does not actually exist but fulfills the role of a guarantor within a program, and is set up to complement credit risk.

[0374] "Support function" refers to a function provided by a virtual guarantor to enable an individual to receive necessary services.

[0375] "Audio data" refers to information about an individual's voice, including pitch, speed, and volume.

[0376] "Video data" refers to data that includes visual information such as an individual's facial expressions and movements.

[0377] "Recognizing emotions" refers to analyzing audio and video data to estimate an individual's psychological state.

[0378] "Natural language processing technology" refers to the technology used to analyze and generate human language using computers.

[0379] "Automatic generation" refers to a system generating necessary documents and information without human intervention.

[0380] "Health status" refers to an individual's physical or mental health condition.

[0381] "Monitoring" refers to the continuous collection and analysis of data to monitor an individual's health and living conditions.

[0382] "Issuing an alert" refers to the act of notifying a user of a warning when an anomaly is detected.

[0383] This invention is a support system for an aging society, particularly targeting seniors who have no family support. This system is built around a server and aims to provide seniors with a safe and secure living environment by integrating and offering multiple functions.

[0384] The server uses a database management system to collect and analyze contract information, authentication information, credit information, and lifestyle data. Specifically, the database management system (DBMS) is operated using SQL, and a risk assessment algorithm is used for credit information analysis. As a result of the analysis, the individual credit risk is evaluated, and based on this evaluation, a virtual guarantor is set up within the program. This virtual guarantor serves to support the user when they receive specific conditions or services.

[0385] The device is equipped with a microphone and camera for emotion analysis, and uses voice analysis software and facial recognition algorithms to recognize emotions from the user's voice and facial expressions. For example, if a user experiences stress in their daily life, the system will automatically determine that emotion and provide appropriate support.

[0386] In document generation, after the terminal receives the necessary information from the user, the server uses natural language processing technology to format the information and automatically generate the submission document. The user can preview the generated document and use it as the official document after confirming its contents. This improves the efficiency of the procedure and reduces the burden on the user.

[0387] Furthermore, the server has the capability to monitor living conditions and health status in real time, and uses data collected from devices and sensors to immediately issue an alert if an anomaly is detected. This alert is sent to the user or designated contacts via email or app notification.

[0388] As a concrete example, by inputting a prompt message such as, "A 70-year-old single man wants to enter a nursing home. Please set up a virtual guarantor considering his credit information and living situation," into the AI ​​model, it is possible to customize appropriate services according to individual credit risk and living circumstances.

[0389] This system provides comprehensive support to seniors without family, enabling them to continue living with peace of mind.

[0390] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0391] Step 1:

[0392] The server collects contract information.

[0393] The server uses a database management system to retrieve user contract information. This information includes name, age, address, and past contract history. Based on this data, authentication and credit information are collected. It receives information from the database as input and creates a dataset for analysis as output.

[0394] Step 2:

[0395] The server assesses the individual's credit risk.

[0396] The server processes the collected data through an analysis algorithm to assess the individual credit risk. The main inputs are contract information and past credit history, and the output is the user's credit score. A high credit score indicates low risk, while a low score indicates high risk.

[0397] Step 3:

[0398] The server sets up a virtual guarantor.

[0399] The server sets up a virtual guarantor within the program based on the evaluated credit score. The input information is the credit score and the required service conditions, and a virtual guarantor object is generated as output. This ensures that the user is guaranteed when receiving services.

[0400] Step 4:

[0401] The device analyzes the user's voice.

[0402] The device collects voice data using its built-in microphone and recognizes emotions using voice analysis software. The input is the user's voice, and the output is their emotional state (e.g., stress, relief). The tone and tempo of the voice are analyzed to infer the user's emotions.

[0403] Step 5:

[0404] The device analyzes the user's facial expressions.

[0405] The device captures facial data through its camera and analyzes it using a facial recognition algorithm. The input data is real-time video, and the output is analyzed emotional information. For example, it can detect smiles and frown lines to evaluate emotions.

[0406] Step 6:

[0407] The terminal collects information necessary for generating the required documents.

[0408] The user enters the necessary information through the terminal interface. This information includes name, address, and application details, and is sent to the server as input data. The output is a formatted set of information.

[0409] Step 7:

[0410] The server automatically generates the documents.

[0411] The server processes the received information using natural language processing technology and automatically generates documents for submission. The input data is information entered by the user, and the output is in the format of a completed document template. The generated document is previewed by the user for content verification.

[0412] Step 8:

[0413] The server monitors the user's living situation and health status.

[0414] The server continuously monitors the user's status based on data from terminals and external devices. Inputs include sensor data and user activity logs, while outputs include assessments of health status and lifestyle abnormalities. If an abnormality is detected, an alert is quickly issued and the user is notified.

[0415] (Application Example 2)

[0416] 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."

[0417] In an aging society, there is a growing need for support systems that enable elderly people without family support to live with peace of mind. In particular, difficulties in accessing financial resources, medical facilities, and the lack of emotional support in daily life are significant challenges. Effective solutions to these challenges are essential.

[0418] 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.

[0419] In this invention, the server includes means for analyzing contract information and collecting personal authentication information, credit information, and living conditions; means for providing services by setting up a virtual guarantor; and means for analyzing emotional states and providing support for stress and anxiety. This enables comprehensive support for elderly people to live with peace of mind.

[0420] "Contract information" refers to information that shows the terms of the agreement regarding the use of the service concluded between the user and the service provider.

[0421] "Personal authentication information" refers to information used to verify the user's identity.

[0422] "Credit information" refers to information that indicates a user's financial reliability and ability to pay.

[0423] "Living conditions" refers to information that describes the environment and conditions related to the user's daily life.

[0424] "Credit risk" is the result of an assessment of the potential risks related to the user's creditworthiness.

[0425] A "virtual guarantor" is a non-existent guarantor established for the purpose of providing a service.

[0426] "Service" refers to the various forms of support and benefits provided to users.

[0427] "Submitted documents" are official documents required to use a particular service.

[0428] "Methods for automatically generating documents" refers to a function that automatically creates necessary documents based on information provided by the user.

[0429] "Monitoring" refers to the continuous observation of a user's lifestyle and health status.

[0430] An "alert" is a function that notifies the user when a specific condition or event occurs.

[0431] "Emotional state" refers to the user's psychological state and changes in their emotions.

[0432] "Support for stress and anxiety" refers to providing support to alleviate the psychological burden that users experience.

[0433] "Means of facilitating access to healthcare" refers to functions that help users receive healthcare services smoothly.

[0434] This system connects a server and user terminals to provide multifaceted support to elderly individuals without family support. The server analyzes contract information and obtains personal authentication information, credit information, and living conditions. Based on this, it assesses individual credit risk and, if necessary, generates a virtual guarantor. This virtual guarantor's guarantee function allows elderly individuals to proceed smoothly with procedures at medical institutions and welfare facilities.

[0435] The user terminal is equipped with an emotion engine that analyzes voice input and facial expressions to understand the user's emotional state in real time. If stress or anxiety is detected as a result of the emotion analysis, relaxation guides and mental support are immediately provided. Furthermore, if access to a medical institution is necessary, the terminal sends a request to the server to assist in providing appropriate information.

[0436] This system also incorporates a real-time monitoring function for living conditions and health status. The server analyzes data obtained from devices and sensors, and if an anomaly is detected, it sends an alert to the user. This process also takes emotional states into account, enabling more personalized support than simply receiving notifications based on numerical anomalies.

[0437] For example, if a user reports, "I've been having trouble sleeping lately, and it's making me a little anxious," the system analyzes this and suggests relaxation music and breathing exercises. It also automatically records the user's health status and stores this information on the server for use during future medical visits if necessary.

[0438] Examples of prompts for a generative AI model include the following:

[0439] "Please provide ideas for relaxation activities to offer to users aged 65 and over who are experiencing anxiety."

[0440] "Based on the living conditions information obtained from users, please create a proposal for a reliable monitoring system."

[0441] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0442] Step 1:

[0443] The server analyzes contract information and collects personal authentication information, credit information, and living conditions. In this process, contract information is provided as input, and detailed evaluation data about the user is output using database search and analysis algorithms. Specifically, the server retrieves relevant information from the contract database, analyzes it, and extracts individual attribute information.

[0444] Step 2:

[0445] The server uses the collected data to assess credit risk and set up virtual guarantors. The assessment data extracted in the previous step is used as input, and a credit risk score is output through analysis using a statistical model. Specifically, the server runs the statistical model and generates a digital asset called a virtual guarantor based on the score.

[0446] Step 3:

[0447] The user terminal analyzes the emotional state using an emotion engine. This process receives voice input and facial recognition data, and outputs the emotional state using natural language processing and image processing techniques. The terminal utilizes a microphone and camera to process the data obtained in real time and identify the user's emotional state.

[0448] Step 4:

[0449] If stress or anxiety is detected as a result of the emotional state analysis, the device will provide a relaxation guide. The input is the emotional analysis result, and the output is relaxation content tailored to the user. The device performs audio playback and video guidance through a mobile application.

[0450] Step 5:

[0451] The server monitors living conditions and health status and issues alerts when necessary. This process uses data from sensors as input, which is then analyzed by an anomaly detection algorithm before an alert message is output. The server continuously receives data from the monitoring system and notifies the user and relevant authorities as needed.

[0452] Step 6:

[0453] The server provides the information necessary to facilitate access to healthcare facilities. This process uses user information and a healthcare facility database as input and outputs links to relevant healthcare services. The server then performs a process to suggest accessible healthcare facilities, taking into account the user's location.

[0454] 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.

[0455] 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.

[0456] 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.

[0457] [Third Embodiment]

[0458] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0459] 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.

[0460] 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).

[0461] 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.

[0462] 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.

[0463] 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).

[0464] 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.

[0465] 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.

[0466] 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.

[0467] 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.

[0468] 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.

[0469] 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".

[0470] This invention is a support system for elderly people without family support in an aging society. The system is designed based on a server analyzing individual contract information and evaluating credit information and living conditions. The server collects contract information using software and a database, and uses this data to assess each individual's credit risk. Based on the evaluation results, it sets up a guarantee in the form of a virtual guarantor and provides necessary support.

[0471] As a concrete example, the server analyzes the contract information of a 70-year-old single male customer. In this process, it focuses on evaluating identity verification information and past payment history, and identifies a non-existent entity generated on the computer as a virtual guarantor. Furthermore, the terminal receives information entered by the customer or their representative and automatically generates documents required for submission to government agencies and nursing homes using AI technology. This utilizes natural language processing to format the information and provide it in the appropriate format.

[0472] Furthermore, this system has the functionality to monitor the user's living situation and health status through the terminal. The server analyzes real-time data acquired from sensors and other sources, and immediately issues an alert if it detects an abnormality in the user's health status. This notification is sent to the terminal, prompting the user to take prompt action. In this way, the system helps ensure the safety and peace of mind of elderly people in their daily lives.

[0473] The following describes the processing flow.

[0474] Step 1:

[0475] The server retrieves customer contract information from the database. This process involves collecting basic data necessary for analysis, including detailed information such as identity verification information, mobile phone usage history, and past payment history.

[0476] Step 2:

[0477] The server analyzes the acquired contract information and formats the data. Here, it uses machine learning algorithms to assess credit risk and performs scoring based on data related to the customer's living situation and health status.

[0478] Step 3:

[0479] The server sets up virtual guarantors based on credit ratings. This ensures that AI entities that meet certain criteria act as guarantees for customers.

[0480] Step 4:

[0481] The terminal receives the information necessary to generate the submission documents from the user. The user logs into the system and completes the provided form.

[0482] Step 5:

[0483] The server executes an automated document generation algorithm based on the received information. Using natural language processing technology, it generates consistent text, formats it, and creates the document.

[0484] Step 6:

[0485] The terminal allows the user to preview the generated document and make any necessary corrections. The user can then submit the document after final review.

[0486] Step 7:

[0487] The server continuously monitors the customer's lifestyle and health status, collecting data in real time. This involves analyzing information from the customer's devices and various sensors.

[0488] Step 8:

[0489] The server immediately issues an alert if it detects an anomaly in the data. The terminal receives this notification and displays a warning to the user or relevant party, enabling a quick response.

[0490] (Example 1)

[0491] 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."

[0492] In an aging society, there is a need to ensure the stability and safety of elderly people who have no family support. However, conventional credit rating systems and health monitoring systems are not fully integrated, making it difficult to provide comprehensive support tailored to the individual needs of each elderly person.

[0493] 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.

[0494] In this invention, the server includes means for collecting and analyzing personal contract information to obtain authentication information, credit information, and living conditions; means for evaluating individual credit risk based on the collected information using a generative AI model; and means for generating a virtual guarantor based on the evaluation results. This enables credit guarantees and health management that allow elderly people to live with peace of mind.

[0495] "Personal contract information" refers to information exchanged when an individual engages in various services or transactions, and includes data such as identity verification and payment history.

[0496] "Authentication information" refers to information used to prove an individual's identity, and includes names, addresses, identification numbers, etc.

[0497] "Credit information" refers to information used to assess an individual's financial reliability, primarily encompassing past payment history and debt status.

[0498] "Living conditions" refers to the circumstances of an individual's daily life, particularly information such as income, housing, and health status.

[0499] A "generative AI model" is a type of artificial intelligence algorithm used to analyze large amounts of data and generate patterns and predictions.

[0500] "Credit risk" is an assessment of the likelihood that an individual will not make the payments they have promised, and it is an indicator of interest to financial institutions and guarantors.

[0501] A "virtual guarantor" is not a real person, but rather an in-program entity that provides a guarantee function generated on a computer.

[0502] A "service guarantee" is a promise to ensure that a service is performed under certain conditions, and is usually intended to mitigate financial risk.

[0503] "Automatic document generation" is a process that automatically creates documents using a specified template based on the entered data.

[0504] "Sensor information" refers to data acquired by various sensors, and in particular includes information about the environment and physical condition.

[0505] An "alert" is a warning message that the system sends to the user when it detects an abnormality or a situation that requires attention.

[0506] This invention provides a comprehensive support system for the elderly. The system mainly consists of a server and terminals, and uses a generative AI model to perform credit risk assessment and health status monitoring.

[0507] The server first collects individual contract information. This process includes a mechanism that uses a database management system to obtain authentication information such as identity verification information and past contract history, as well as information about the individual's living situation. Next, the server uses a generative AI model to assess the individual's credit risk based on the collected data. The AI ​​model calculates a risk score based on past payment history and financial situation. At this time, the server uses prompt messages to the AI ​​model such as "Perform a risk assessment based on payment history over the past 5 years."

[0508] Based on the credit risk assessment results, the server generates a virtual guarantor. This virtual guarantor is a non-physical entity created within the program and provides guarantees to the user as needed. The establishment of this virtual guarantor enables the provision of services to the elderly.

[0509] The terminal plays the role of creating documents that need to be submitted to government agencies and nursing homes, based on information entered by the user. The terminal utilizes natural language processing technology to apply the user's input to a template, format it in the required format, and output it. For example, when a user signs a contract for care services, the terminal automatically generates a complete set of application documents.

[0510] Furthermore, the device monitors the user's lifestyle and health status in real time using sensors. The server analyzes the data sent from the sensors and immediately issues an alert if an anomaly is detected. This alert is displayed on the device, prompting the user and relevant parties to take prompt action. For example, if the user's heart rate suddenly increases, the server generates a notification such as "Rapid change in heart rate detected, action recommended" and sends it to the device.

[0511] This system allows elderly people to live their daily lives with peace of mind and enables early intervention in situations where they need support.

[0512] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0513] Step 1:

[0514] The server collects individual contract information. It receives basic user information as input and retrieves authentication information and past contract history from the database. Specifically, the server sends queries to the database management system, extracts the relevant information, and prepares it for analysis. The output is an individual contract-related dataset.

[0515] Step 2:

[0516] The server uses a generative AI model to assess an individual's credit risk based on the collected information. The input is the contract information dataset obtained in Step 1, and the output is a risk score. Specifically, the server inputs the prompt "Perform a risk assessment based on payment history over the past 5 years" into the generative AI model, and the AI ​​calculates the risk score.

[0517] Step 3:

[0518] The server generates a virtual guarantor based on the results of the credit risk assessment. The input is the risk score from step 2, and the output is the data profile of the virtual guarantor. Specifically, the server analyzes the assessment score, determines the appropriate guarantee level based on the risk, and sets that information for the virtual guarantor within the program.

[0519] Step 4:

[0520] The terminal receives information provided by the user and automatically generates documents. Input is information entered by the user, and output is a formatted document. Specifically, the terminal embeds the data entered by the user into a document template and uses natural language processing to export the document as a PDF in the appropriate format.

[0521] Step 5:

[0522] The device monitors the user's lifestyle and health status through sensors. Input is real-time data from the sensors, and output is monitoring reports and alerts. Specifically, the device periodically receives data from the sensors and sends that information to the server.

[0523] Step 6:

[0524] The server analyzes the monitoring data and issues an alert if an anomaly is detected. The input is the monitoring data from step 5, and the output is the alert notification. Specifically, the server applies an anomaly detection algorithm, and if an anomaly exceeds a threshold, it generates an alert message such as "A sudden change in heart rate has been detected, and action is recommended," and sends it to the terminal.

[0525] (Application Example 1)

[0526] 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."

[0527] In an aging society, seniors without family support face challenges such as credit risk, lack of life support, and difficulty in early detection of health abnormalities. As a result, seniors often face difficulties in accessing the services and support they need. Therefore, there is a growing need for a credit rating system using virtual guarantee entities and a support system that enables real-time monitoring of health status.

[0528] 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.

[0529] In this invention, the server includes means for analyzing contract data and collecting individual authentication information, credit information, and living environment information; means for evaluating the credit risk of each individual using the collected data; and means for analyzing health data and sending real-time notifications in the event of an anomaly. This makes it possible to evaluate and guarantee the creditworthiness of elderly people who have no family support, as well as to quickly detect and notify them of any abnormalities in their health condition.

[0530] "Contract data" refers to a collection of information based on an agreement an individual makes to receive a service.

[0531] "Authentication information" refers to data used to verify an individual's identity and authority.

[0532] "Credit information" refers to financial and payment history information necessary to assess an individual's creditworthiness.

[0533] "Living environment" refers to information about an individual's current living situation and environment.

[0534] "Credit risk" is an indicator that shows the likelihood that an individual may be unable to fulfill their contractual obligations.

[0535] A "virtual guarantee entity" is a digital entity created within a program to complement the creditworthiness of an individual.

[0536] "Providing a service" refers to a series of activities that provide the support and convenience that individuals need.

[0537] "Submitted documents" are documents created by an individual for official presentation to a government agency or corporation.

[0538] "Health data" refers to information about an individual's health status, obtained from sensors and other devices.

[0539] "Real-time notification" refers to an informational message that is sent to an individual immediately when an event occurs.

[0540] To implement this invention, an elderly support system is used. The server analyzes contract data, collects individual authentication information, credit information, and living environment information, and evaluates each individual's credit risk based on this information. Depending on the credit risk, a virtual guarantee entity is generated within the program, and services are provided based on that information. This allows users to receive the support and services they need with peace of mind.

[0541] The server analyzes health data and continuously monitors the individual's health status based on information obtained from sensors and devices. If an abnormality is detected, it sends a real-time notification to prompt the user to take immediate action. For the specific analysis of health data, Python and related data processing libraries (NumPy, Pandas) are used, and the necessary information is formatted and provided using natural language processing technology.

[0542] In one embodiment, a server monitors vital signs such as temperature and heart rate in the user's living environment via internet-connected sensors, and sends notifications via smartphones or other devices when abnormal patterns are detected.

[0543] When using a generative AI model to automatically generate submission documents, the following prompt can be used: "As a generative AI model, please explain how to use this document generation system to analyze a specific contract situation and automatically create the necessary documents." This prompt serves as a guide for the generative AI model to perform the appropriate document creation procedure.

[0544] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0545] Step 1:

[0546] The server receives contract data from users and stores it in a database. Inputs include user authentication information, credit information, and living environment. The server analyzes this information to prepare foundational data for assessing credit risk. A data processing library is used for data analysis.

[0547] Step 2:

[0548] The server assesses each user's credit risk based on the collected contract data. This involves analyzing the user's past payment history and lifestyle to calculate a risk score. This process is used to quantify credit risk from the input data and generate a virtual guarantee entity. The output is the risk score.

[0549] Step 3:

[0550] The server generates a virtual guarantee entity within the program based on the generated credit risk and contract details. This entity complements the user's credit risk and facilitates the use of various services. The input is a credit risk score, and the output is the generation of a virtual guarantee entity.

[0551] Step 4:

[0552] The server receives real-time data from sensors to acquire health information. This allows it to monitor the user's health status and aim for early detection of abnormalities. The input is sensor data, and the output is the result of anomaly detection.

[0553] Step 5:

[0554] The server sends real-time notifications to the user's device when an abnormality in their health status is detected. This notification allows the user to take prompt medical action. The input is the abnormality detection result, and the output is the notification sent to the device.

[0555] Step 6:

[0556] The server uses a generative AI model to process prompts for automatically generating the necessary submission documents. It analyzes the data provided by the user and formats the documents appropriately. The input is the user's contract and health data, and the output is the completed submission document.

[0557] 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.

[0558] This invention is a support system for elderly people without family support in an aging society, and is characterized by its integration of an emotional engine. The system is server-centric and analyzes personal authentication information, credit information, and living conditions from contract information. Based on the data obtained from this analysis, the server evaluates each individual's credit risk, sets up a virtual guarantor, and provides the customer with the necessary services.

[0559] Specifically, the server retrieves data on a 70-year-old single male customer, evaluates his credit information and living situation, and sets up a virtual guarantor. This virtual guarantor's guarantee function allows the customer to meet the requirements for necessary medical care and admission to nursing homes.

[0560] Furthermore, terminals equipped with an emotion engine analyze the user's voice and facial expressions to recognize their emotional state. For example, if a user experiences stress or anxiety in their daily life, the terminal automatically determines their emotional state and provides appropriate alerts and support. In addition, the terminal receives information from the user and runs a document generation program on the server to generate necessary submission documents. Utilizing natural language processing technology, the information is formatted and the automatically generated documents are previewed by the user for final confirmation.

[0561] Furthermore, the server has the function of continuously monitoring the user's living situation and health status. Monitoring is performed based on real-time data acquired from terminals and sensors, and if an abnormality is detected, an alert is immediately issued, taking into account the user's emotional state. In this way, the system of the present invention is effective in supporting seniors to live safe and secure lives.

[0562] The following describes the processing flow.

[0563] Step 1:

[0564] The server retrieves customer contract information from the database. This is a process that collects data on customer identity verification, credit information, and living conditions.

[0565] Step 2:

[0566] The server uses the acquired contract information to assess an individual's credit risk. Using machine learning algorithms, it analyzes payment history and lifestyle to score the customer's trustworthiness.

[0567] Step 3:

[0568] The server sets up a virtual guarantor based on the results of a credit risk assessment. The virtual guarantor is designed as a computer program and fulfills the guarantee conditions required for the customer to use the service.

[0569] Step 4:

[0570] The terminal prompts the user to input information for necessary documents. The user registers the information required for submission to nursing homes and government agencies through the system's interface.

[0571] Step 5:

[0572] The server executes an automated document generation process based on the input information. It uses AI to organize the information and applies natural language processing technology to generate submission documents that conform to the format.

[0573] Step 6:

[0574] The terminal presents the generated document to the user and prompts them to make changes if necessary. Through this review phase, the user makes final approval of the document.

[0575] Step 7:

[0576] The server continuously monitors the user's lifestyle and health status. It utilizes sensors and external data sources to ensure an immediate response in the event of an anomaly.

[0577] Step 8:

[0578] The device uses an emotion engine to analyze the user's emotional state. It captures the user's voice and facial expressions using a camera and microphone, recognizes emotions based on that data, and provides personalized support as needed.

[0579] Step 9:

[0580] The server issues situation-specific alerts based on monitoring and sentiment recognition results. This allows users to be quickly alerted and take appropriate action.

[0581] (Example 2)

[0582] 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."

[0583] In an aging society, it is difficult to assess the credit risk of senior citizens without family support, and they often require guarantors to receive necessary services, but there is a lack of readily available means to secure such guarantors. Furthermore, technologies for emotional analysis to maintain the mental health of seniors, and technologies for effectively monitoring their lifestyles and health status, are not yet sufficiently developed. As a result, there is currently a lack of support systems in place to ensure that seniors can live safe and secure lives.

[0584] 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.

[0585] In this invention, the server includes means for analyzing contract information and collecting personal authentication information, credit information, and living conditions; means for evaluating individual credit risk and setting up a virtual guarantor to provide support functions; means for analyzing voice and video data and recognizing personal emotions; means for automatically generating submission documents using natural language processing technology; and means for monitoring health and living conditions and issuing alerts. This provides an environment in which seniors can receive necessary services with peace of mind and enables appropriate management of their physical and mental health.

[0586] "Contract information" refers to data concerning the conditions and individual agreements that individuals need when using a service.

[0587] "Authentication information" refers to data used to verify an individual's identity and identification, including their name, date of birth, and address.

[0588] "Credit information" refers to data used to evaluate an individual's financial history, ability to pay, and creditworthiness.

[0589] "Living conditions" refers to data related to an individual's lifelong activities and living environment, including housing conditions and lifestyle habits.

[0590] "Credit risk" refers to a numerical value or indicator that assesses the likelihood of an individual defaulting on their debts in the future.

[0591] A "virtual guarantor" refers to an entity that does not actually exist but fulfills the role of a guarantor within a program, and is set up to complement credit risk.

[0592] "Support function" refers to a function provided by a virtual guarantor to enable an individual to receive necessary services.

[0593] "Audio data" refers to information about an individual's voice, including pitch, speed, and volume.

[0594] "Video data" refers to data that includes visual information such as an individual's facial expressions and movements.

[0595] "Recognizing emotions" refers to analyzing audio and video data to estimate an individual's psychological state.

[0596] "Natural language processing technology" refers to the technology used to analyze and generate human language using computers.

[0597] "Automatic generation" refers to a system generating necessary documents and information without human intervention.

[0598] "Health status" refers to an individual's physical or mental health condition.

[0599] "Monitoring" refers to the continuous collection and analysis of data to monitor an individual's health and living conditions.

[0600] "Issuing an alert" refers to the act of notifying a user of a warning when an anomaly is detected.

[0601] This invention is a support system for an aging society, particularly targeting seniors who have no family support. This system is built around a server and aims to provide seniors with a safe and secure living environment by integrating and offering multiple functions.

[0602] The server uses a database management system to collect and analyze contract information, authentication information, credit information, and lifestyle data. Specifically, the database management system (DBMS) is operated using SQL, and a risk assessment algorithm is used for credit information analysis. As a result of the analysis, the individual credit risk is evaluated, and based on this evaluation, a virtual guarantor is set up within the program. This virtual guarantor serves to support the user when they receive specific conditions or services.

[0603] The device is equipped with a microphone and camera for emotion analysis, and uses voice analysis software and facial recognition algorithms to recognize emotions from the user's voice and facial expressions. For example, if a user experiences stress in their daily life, the system will automatically determine that emotion and provide appropriate support.

[0604] In document generation, after the terminal receives the necessary information from the user, the server uses natural language processing technology to format the information and automatically generate the submission document. The user can preview the generated document and use it as the official document after confirming its contents. This improves the efficiency of the procedure and reduces the burden on the user.

[0605] Furthermore, the server has the capability to monitor living conditions and health status in real time, and uses data collected from devices and sensors to immediately issue an alert if an anomaly is detected. This alert is sent to the user or designated contacts via email or app notification.

[0606] As a concrete example, by inputting a prompt message such as, "A 70-year-old single man wants to enter a nursing home. Please set up a virtual guarantor considering his credit information and living situation," into the AI ​​model, it is possible to customize appropriate services according to individual credit risk and living circumstances.

[0607] This system provides comprehensive support to seniors without family, enabling them to continue living with peace of mind.

[0608] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0609] Step 1:

[0610] The server collects contract information.

[0611] The server uses a database management system to retrieve user contract information. This information includes name, age, address, and past contract history. Based on this data, authentication and credit information are collected. It receives information from the database as input and creates a dataset for analysis as output.

[0612] Step 2:

[0613] The server assesses the individual's credit risk.

[0614] The server processes the collected data through an analysis algorithm to assess the individual credit risk. The main inputs are contract information and past credit history, and the output is the user's credit score. A high credit score indicates low risk, while a low score indicates high risk.

[0615] Step 3:

[0616] The server sets up a virtual guarantor.

[0617] The server sets up a virtual guarantor within the program based on the evaluated credit score. The input information is the credit score and the required service conditions, and a virtual guarantor object is generated as output. This ensures that the user is guaranteed when receiving services.

[0618] Step 4:

[0619] The device analyzes the user's voice.

[0620] The device collects voice data using its built-in microphone and recognizes emotions using voice analysis software. The input is the user's voice, and the output is their emotional state (e.g., stress, relief). The tone and tempo of the voice are analyzed to infer the user's emotions.

[0621] Step 5:

[0622] The device analyzes the user's facial expressions.

[0623] The device captures facial data through its camera and analyzes it using a facial recognition algorithm. The input data is real-time video, and the output is analyzed emotional information. For example, it can detect smiles and frown lines to evaluate emotions.

[0624] Step 6:

[0625] The terminal collects information necessary for generating the required documents.

[0626] The user enters the necessary information through the terminal interface. This information includes name, address, and application details, and is sent to the server as input data. The output is a formatted set of information.

[0627] Step 7:

[0628] The server automatically generates the documents.

[0629] The server processes the received information using natural language processing technology and automatically generates documents for submission. The input data is information entered by the user, and the output is in the format of a completed document template. The generated document is previewed by the user for content verification.

[0630] Step 8:

[0631] The server monitors the user's living situation and health status.

[0632] The server continuously monitors the user's status based on data from terminals and external devices. Inputs include sensor data and user activity logs, while outputs include assessments of health status and lifestyle abnormalities. If an abnormality is detected, an alert is quickly issued and the user is notified.

[0633] (Application Example 2)

[0634] 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."

[0635] In an aging society, there is a growing need for support systems that enable elderly people without family support to live with peace of mind. In particular, difficulties in accessing financial resources, medical facilities, and the lack of emotional support in daily life are significant challenges. Effective solutions to these challenges are essential.

[0636] 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.

[0637] In this invention, the server includes means for analyzing contract information and collecting personal authentication information, credit information, and living conditions; means for providing services by setting up a virtual guarantor; and means for analyzing emotional states and providing support for stress and anxiety. This enables comprehensive support for elderly people to live with peace of mind.

[0638] "Contract information" refers to information that shows the terms of the agreement regarding the use of the service concluded between the user and the service provider.

[0639] "Personal authentication information" refers to information used to verify the user's identity.

[0640] "Credit information" refers to information that indicates a user's financial reliability and ability to pay.

[0641] "Living conditions" refers to information that describes the environment and conditions related to the user's daily life.

[0642] "Credit risk" is the result of an assessment of the potential risks related to the user's creditworthiness.

[0643] A "virtual guarantor" is a non-existent guarantor established for the purpose of providing a service.

[0644] "Service" refers to the various forms of support and benefits provided to users.

[0645] "Submitted documents" are official documents required to use a particular service.

[0646] "Methods for automatically generating documents" refers to a function that automatically creates necessary documents based on information provided by the user.

[0647] "Monitoring" refers to the continuous observation of a user's lifestyle and health status.

[0648] An "alert" is a function that notifies the user when a specific condition or event occurs.

[0649] "Emotional state" refers to the user's psychological state and changes in their emotions.

[0650] "Support for stress and anxiety" refers to providing support to alleviate the psychological burden that users experience.

[0651] "Means of facilitating access to healthcare" refers to functions that help users receive healthcare services smoothly.

[0652] This system connects a server and user terminals to provide multifaceted support to elderly individuals without family support. The server analyzes contract information and obtains personal authentication information, credit information, and living conditions. Based on this, it assesses individual credit risk and, if necessary, generates a virtual guarantor. This virtual guarantor's guarantee function allows elderly individuals to proceed smoothly with procedures at medical institutions and welfare facilities.

[0653] The user terminal is equipped with an emotion engine that analyzes voice input and facial expressions to understand the user's emotional state in real time. If stress or anxiety is detected as a result of the emotion analysis, relaxation guides and mental support are immediately provided. Furthermore, if access to a medical institution is necessary, the terminal sends a request to the server to assist in providing appropriate information.

[0654] This system also incorporates a real-time monitoring function for living conditions and health status. The server analyzes data obtained from devices and sensors, and if an anomaly is detected, it sends an alert to the user. This process also takes emotional states into account, enabling more personalized support than simply receiving notifications based on numerical anomalies.

[0655] For example, if a user reports, "I've been having trouble sleeping lately, and it's making me a little anxious," the system analyzes this and suggests relaxation music and breathing exercises. It also automatically records the user's health status and stores this information on the server for use during future medical visits if necessary.

[0656] Examples of prompts for a generative AI model include the following:

[0657] "Please provide ideas for relaxation activities to offer to users aged 65 and over who are experiencing anxiety."

[0658] "Based on the living conditions information obtained from users, please create a proposal for a reliable monitoring system."

[0659] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0660] Step 1:

[0661] The server analyzes contract information and collects personal authentication information, credit information, and living conditions. In this process, contract information is provided as input, and detailed evaluation data about the user is output using database search and analysis algorithms. Specifically, the server retrieves relevant information from the contract database, analyzes it, and extracts individual attribute information.

[0662] Step 2:

[0663] The server uses the collected data to assess credit risk and set up virtual guarantors. The assessment data extracted in the previous step is used as input, and a credit risk score is output through analysis using a statistical model. Specifically, the server runs the statistical model and generates a digital asset called a virtual guarantor based on the score.

[0664] Step 3:

[0665] The user terminal analyzes the emotional state using an emotion engine. This process receives voice input and facial recognition data, and outputs the emotional state using natural language processing and image processing techniques. The terminal utilizes a microphone and camera to process the data obtained in real time and identify the user's emotional state.

[0666] Step 4:

[0667] If stress or anxiety is detected as a result of the emotional state analysis, the device will provide a relaxation guide. The input is the emotional analysis result, and the output is relaxation content tailored to the user. The device performs audio playback and video guidance through a mobile application.

[0668] Step 5:

[0669] The server monitors living conditions and health status and issues alerts when necessary. This process uses data from sensors as input, which is then analyzed by an anomaly detection algorithm before an alert message is output. The server continuously receives data from the monitoring system and notifies the user and relevant authorities as needed.

[0670] Step 6:

[0671] The server provides the information necessary to facilitate access to healthcare facilities. This process uses user information and a healthcare facility database as input and outputs links to relevant healthcare services. The server then performs a process to suggest accessible healthcare facilities, taking into account the user's location.

[0672] 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.

[0673] 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.

[0674] 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.

[0675] [Fourth Embodiment]

[0676] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0677] 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.

[0678] 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).

[0679] 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.

[0680] 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.

[0681] 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).

[0682] 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.

[0683] 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.

[0684] 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.

[0685] 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.

[0686] 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.

[0687] 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.

[0688] 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".

[0689] This invention is a support system for elderly people without family support in an aging society. The system is designed based on a server analyzing individual contract information and evaluating credit information and living conditions. The server collects contract information using software and a database, and uses this data to assess each individual's credit risk. Based on the evaluation results, it sets up a guarantee in the form of a virtual guarantor and provides necessary support.

[0690] As a concrete example, the server analyzes the contract information of a 70-year-old single male customer. In this process, it focuses on evaluating identity verification information and past payment history, and identifies a non-existent entity generated on the computer as a virtual guarantor. Furthermore, the terminal receives information entered by the customer or their representative and automatically generates documents required for submission to government agencies and nursing homes using AI technology. This utilizes natural language processing to format the information and provide it in the appropriate format.

[0691] Furthermore, this system has the functionality to monitor the user's living situation and health status through the terminal. The server analyzes real-time data acquired from sensors and other sources, and immediately issues an alert if it detects an abnormality in the user's health status. This notification is sent to the terminal, prompting the user to take prompt action. In this way, the system helps ensure the safety and peace of mind of elderly people in their daily lives.

[0692] The following describes the processing flow.

[0693] Step 1:

[0694] The server retrieves customer contract information from the database. This process involves collecting basic data necessary for analysis, including detailed information such as identity verification information, mobile phone usage history, and past payment history.

[0695] Step 2:

[0696] The server analyzes the acquired contract information and formats the data. Here, it uses machine learning algorithms to assess credit risk and performs scoring based on data related to the customer's living situation and health status.

[0697] Step 3:

[0698] The server sets up virtual guarantors based on credit ratings. This ensures that AI entities that meet certain criteria act as guarantees for customers.

[0699] Step 4:

[0700] The terminal receives the information necessary to generate the submission documents from the user. The user logs into the system and completes the provided form.

[0701] Step 5:

[0702] The server executes an automated document generation algorithm based on the received information. Using natural language processing technology, it generates consistent text, formats it, and creates the document.

[0703] Step 6:

[0704] The terminal allows the user to preview the generated document and make any necessary corrections. The user can then submit the document after final review.

[0705] Step 7:

[0706] The server continuously monitors the customer's lifestyle and health status, collecting data in real time. This involves analyzing information from the customer's devices and various sensors.

[0707] Step 8:

[0708] The server immediately issues an alert if it detects an anomaly in the data. The terminal receives this notification and displays a warning to the user or relevant party, enabling a quick response.

[0709] (Example 1)

[0710] 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".

[0711] In an aging society, there is a need to ensure the stability and safety of elderly people who have no family support. However, conventional credit rating systems and health monitoring systems are not fully integrated, making it difficult to provide comprehensive support tailored to the individual needs of each elderly person.

[0712] 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.

[0713] In this invention, the server includes means for collecting and analyzing personal contract information to obtain authentication information, credit information, and living conditions; means for evaluating individual credit risk based on the collected information using a generative AI model; and means for generating a virtual guarantor based on the evaluation results. This enables credit guarantees and health management that allow elderly people to live with peace of mind.

[0714] "Personal contract information" refers to information exchanged when an individual engages in various services or transactions, and includes data such as identity verification and payment history.

[0715] "Authentication information" refers to information used to prove an individual's identity, and includes names, addresses, identification numbers, etc.

[0716] "Credit information" refers to information used to assess an individual's financial reliability, primarily encompassing past payment history and debt status.

[0717] "Living conditions" refers to the circumstances of an individual's daily life, particularly information such as income, housing, and health status.

[0718] A "generative AI model" is a type of artificial intelligence algorithm used to analyze large amounts of data and generate patterns and predictions.

[0719] "Credit risk" is an assessment of the likelihood that an individual will not make the payments they have promised, and it is an indicator of interest to financial institutions and guarantors.

[0720] A "virtual guarantor" is not a real person, but rather an in-program entity that provides a guarantee function generated on a computer.

[0721] A "service guarantee" is a promise to ensure that a service is performed under certain conditions, and is usually intended to mitigate financial risk.

[0722] "Automatic document generation" is a process that automatically creates documents using a specified template based on the entered data.

[0723] "Sensor information" refers to data acquired by various sensors, and in particular includes information about the environment and physical condition.

[0724] An "alert" is a warning message that the system sends to the user when it detects an abnormality or a situation that requires attention.

[0725] This invention provides a comprehensive support system for the elderly. The system mainly consists of a server and terminals, and uses a generative AI model to perform credit risk assessment and health status monitoring.

[0726] The server first collects individual contract information. This process includes a mechanism that uses a database management system to obtain authentication information such as identity verification information and past contract history, as well as information about the individual's living situation. Next, the server uses a generative AI model to assess the individual's credit risk based on the collected data. The AI ​​model calculates a risk score based on past payment history and financial situation. At this time, the server uses prompt messages to the AI ​​model such as "Perform a risk assessment based on payment history over the past 5 years."

[0727] Based on the credit risk assessment results, the server generates a virtual guarantor. This virtual guarantor is a non-physical entity created within the program and provides guarantees to the user as needed. The establishment of this virtual guarantor enables the provision of services to the elderly.

[0728] The terminal plays the role of creating documents that need to be submitted to government agencies and nursing homes, based on information entered by the user. The terminal utilizes natural language processing technology to apply the user's input to a template, format it in the required format, and output it. For example, when a user signs a contract for care services, the terminal automatically generates a complete set of application documents.

[0729] Furthermore, the device monitors the user's lifestyle and health status in real time using sensors. The server analyzes the data sent from the sensors and immediately issues an alert if an anomaly is detected. This alert is displayed on the device, prompting the user and relevant parties to take prompt action. For example, if the user's heart rate suddenly increases, the server generates a notification such as "Rapid change in heart rate detected, action recommended" and sends it to the device.

[0730] This system allows elderly people to live their daily lives with peace of mind and enables early intervention in situations where they need support.

[0731] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0732] Step 1:

[0733] The server collects individual contract information. It receives basic user information as input and retrieves authentication information and past contract history from the database. Specifically, the server sends queries to the database management system, extracts the relevant information, and prepares it for analysis. The output is an individual contract-related dataset.

[0734] Step 2:

[0735] The server uses a generative AI model to assess an individual's credit risk based on the collected information. The input is the contract information dataset obtained in Step 1, and the output is a risk score. Specifically, the server inputs the prompt "Perform a risk assessment based on payment history over the past 5 years" into the generative AI model, and the AI ​​calculates the risk score.

[0736] Step 3:

[0737] The server generates a virtual guarantor based on the results of the credit risk assessment. The input is the risk score from step 2, and the output is the data profile of the virtual guarantor. Specifically, the server analyzes the assessment score, determines the appropriate guarantee level based on the risk, and sets that information for the virtual guarantor within the program.

[0738] Step 4:

[0739] The terminal receives information provided by the user and automatically generates documents. Input is information entered by the user, and output is a formatted document. Specifically, the terminal embeds the data entered by the user into a document template and uses natural language processing to export the document as a PDF in the appropriate format.

[0740] Step 5:

[0741] The device monitors the user's lifestyle and health status through sensors. Input is real-time data from the sensors, and output is monitoring reports and alerts. Specifically, the device periodically receives data from the sensors and sends that information to the server.

[0742] Step 6:

[0743] The server analyzes the monitoring data and issues an alert if an anomaly is detected. The input is the monitoring data from step 5, and the output is the alert notification. Specifically, the server applies an anomaly detection algorithm, and if an anomaly exceeds a threshold, it generates an alert message such as "A sudden change in heart rate has been detected, and action is recommended," and sends it to the terminal.

[0744] (Application Example 1)

[0745] 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".

[0746] In an aging society, seniors without family support face challenges such as credit risk, lack of life support, and difficulty in early detection of health abnormalities. As a result, seniors often face difficulties in accessing the services and support they need. Therefore, there is a growing need for a credit rating system using virtual guarantee entities and a support system that enables real-time monitoring of health status.

[0747] 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.

[0748] In this invention, the server includes means for analyzing contract data and collecting individual authentication information, credit information, and living environment information; means for evaluating the credit risk of each individual using the collected data; and means for analyzing health data and sending real-time notifications in the event of an anomaly. This makes it possible to evaluate and guarantee the creditworthiness of elderly people who have no family support, as well as to quickly detect and notify them of any abnormalities in their health condition.

[0749] "Contract data" refers to a collection of information based on an agreement an individual makes to receive a service.

[0750] "Authentication information" refers to data used to verify an individual's identity and authority.

[0751] "Credit information" refers to financial and payment history information necessary to assess an individual's creditworthiness.

[0752] "Living environment" refers to information about an individual's current living situation and environment.

[0753] "Credit risk" is an indicator that shows the likelihood that an individual may be unable to fulfill their contractual obligations.

[0754] A "virtual guarantee entity" is a digital entity created within a program to complement the creditworthiness of an individual.

[0755] "Providing a service" refers to a series of activities that provide the support and convenience that individuals need.

[0756] "Submitted documents" are documents created by an individual for official presentation to a government agency or corporation.

[0757] "Health data" refers to information about an individual's health status, obtained from sensors and other devices.

[0758] "Real-time notification" refers to an informational message that is sent to an individual immediately when an event occurs.

[0759] To implement this invention, an elderly support system is used. The server analyzes contract data, collects individual authentication information, credit information, and living environment information, and evaluates each individual's credit risk based on this information. Depending on the credit risk, a virtual guarantee entity is generated within the program, and services are provided based on that information. This allows users to receive the support and services they need with peace of mind.

[0760] The server analyzes health data and continuously monitors the individual's health status based on information obtained from sensors and devices. If an abnormality is detected, it sends a real-time notification to prompt the user to take immediate action. For the specific analysis of health data, Python and related data processing libraries (NumPy, Pandas) are used, and the necessary information is formatted and provided using natural language processing technology.

[0761] In one embodiment, a server monitors vital signs such as temperature and heart rate in the user's living environment via internet-connected sensors, and sends notifications via smartphones or other devices when abnormal patterns are detected.

[0762] When using a generative AI model to automatically generate submission documents, the following prompt can be used: "As a generative AI model, please explain how to use this document generation system to analyze a specific contract situation and automatically create the necessary documents." This prompt serves as a guide for the generative AI model to perform the appropriate document creation procedure.

[0763] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0764] Step 1:

[0765] The server receives contract data from users and stores it in a database. Inputs include user authentication information, credit information, and living environment. The server analyzes this information to prepare foundational data for assessing credit risk. A data processing library is used for data analysis.

[0766] Step 2:

[0767] The server assesses each user's credit risk based on the collected contract data. This involves analyzing the user's past payment history and lifestyle to calculate a risk score. This process is used to quantify credit risk from the input data and generate a virtual guarantee entity. The output is the risk score.

[0768] Step 3:

[0769] The server generates a virtual guarantee entity within the program based on the generated credit risk and contract details. This entity complements the user's credit risk and facilitates the use of various services. The input is a credit risk score, and the output is the generation of a virtual guarantee entity.

[0770] Step 4:

[0771] The server receives real-time data from sensors to acquire health information. This allows it to monitor the user's health status and aim for early detection of abnormalities. The input is sensor data, and the output is the result of anomaly detection.

[0772] Step 5:

[0773] The server sends real-time notifications to the user's device when an abnormality in their health status is detected. This notification allows the user to take prompt medical action. The input is the abnormality detection result, and the output is the notification sent to the device.

[0774] Step 6:

[0775] The server uses a generative AI model to process prompts for automatically generating the necessary submission documents. It analyzes the data provided by the user and formats the documents appropriately. The input is the user's contract and health data, and the output is the completed submission document.

[0776] 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.

[0777] This invention is a support system for elderly people without family support in an aging society, and is characterized by its integration of an emotional engine. The system is server-centric and analyzes personal authentication information, credit information, and living conditions from contract information. Based on the data obtained from this analysis, the server evaluates each individual's credit risk, sets up a virtual guarantor, and provides the customer with the necessary services.

[0778] Specifically, the server retrieves data on a 70-year-old single male customer, evaluates his credit information and living situation, and sets up a virtual guarantor. This virtual guarantor's guarantee function allows the customer to meet the requirements for necessary medical care and admission to nursing homes.

[0779] Furthermore, terminals equipped with an emotion engine analyze the user's voice and facial expressions to recognize their emotional state. For example, if a user experiences stress or anxiety in their daily life, the terminal automatically determines their emotional state and provides appropriate alerts and support. In addition, the terminal receives information from the user and runs a document generation program on the server to generate necessary submission documents. Utilizing natural language processing technology, the information is formatted and the automatically generated documents are previewed by the user for final confirmation.

[0780] Furthermore, the server has the function of continuously monitoring the user's living situation and health status. Monitoring is performed based on real-time data acquired from terminals and sensors, and if an abnormality is detected, an alert is immediately issued, taking into account the user's emotional state. In this way, the system of the present invention is effective in supporting seniors to live safe and secure lives.

[0781] The following describes the processing flow.

[0782] Step 1:

[0783] The server retrieves customer contract information from the database. This is a process that collects data on customer identity verification, credit information, and living conditions.

[0784] Step 2:

[0785] The server uses the acquired contract information to assess an individual's credit risk. Using machine learning algorithms, it analyzes payment history and lifestyle to score the customer's trustworthiness.

[0786] Step 3:

[0787] The server sets up a virtual guarantor based on the results of a credit risk assessment. The virtual guarantor is designed as a computer program and fulfills the guarantee conditions required for the customer to use the service.

[0788] Step 4:

[0789] The terminal prompts the user to input information for necessary documents. The user registers the information required for submission to nursing homes and government agencies through the system's interface.

[0790] Step 5:

[0791] The server executes an automated document generation process based on the input information. It uses AI to organize the information and applies natural language processing technology to generate submission documents that conform to the format.

[0792] Step 6:

[0793] The terminal presents the generated document to the user and prompts them to make changes if necessary. Through this review phase, the user makes final approval of the document.

[0794] Step 7:

[0795] The server continuously monitors the user's lifestyle and health status. It utilizes sensors and external data sources to ensure an immediate response in the event of an anomaly.

[0796] Step 8:

[0797] The device uses an emotion engine to analyze the user's emotional state. It captures the user's voice and facial expressions using a camera and microphone, recognizes emotions based on that data, and provides personalized support as needed.

[0798] Step 9:

[0799] The server issues situation-specific alerts based on monitoring and sentiment recognition results. This allows users to be quickly alerted and take appropriate action.

[0800] (Example 2)

[0801] 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".

[0802] In an aging society, it is difficult to assess the credit risk of senior citizens without family support, and they often require guarantors to receive necessary services, but there is a lack of readily available means to secure such guarantors. Furthermore, technologies for emotional analysis to maintain the mental health of seniors, and technologies for effectively monitoring their lifestyles and health status, are not yet sufficiently developed. As a result, there is currently a lack of support systems in place to ensure that seniors can live safe and secure lives.

[0803] 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.

[0804] In this invention, the server includes means for analyzing contract information and collecting personal authentication information, credit information, and living conditions; means for evaluating individual credit risk and setting up a virtual guarantor to provide support functions; means for analyzing voice and video data and recognizing personal emotions; means for automatically generating submission documents using natural language processing technology; and means for monitoring health and living conditions and issuing alerts. This provides an environment in which seniors can receive necessary services with peace of mind and enables appropriate management of their physical and mental health.

[0805] "Contract information" refers to data concerning the conditions and individual agreements that individuals need when using a service.

[0806] "Authentication information" refers to data used to verify an individual's identity and identification, including their name, date of birth, and address.

[0807] "Credit information" refers to data used to evaluate an individual's financial history, ability to pay, and creditworthiness.

[0808] "Living conditions" refers to data related to an individual's lifelong activities and living environment, including housing conditions and lifestyle habits.

[0809] "Credit risk" refers to a numerical value or indicator that assesses the likelihood of an individual defaulting on their debts in the future.

[0810] A "virtual guarantor" refers to an entity that does not actually exist but fulfills the role of a guarantor within a program, and is set up to complement credit risk.

[0811] "Support function" refers to a function provided by a virtual guarantor to enable an individual to receive necessary services.

[0812] "Audio data" refers to information about an individual's voice, including pitch, speed, and volume.

[0813] "Video data" refers to data that includes visual information such as an individual's facial expressions and movements.

[0814] "Recognizing emotions" refers to analyzing audio and video data to estimate an individual's psychological state.

[0815] "Natural language processing technology" refers to the technology used to analyze and generate human language using computers.

[0816] "Automatic generation" refers to a system generating necessary documents and information without human intervention.

[0817] "Health status" refers to an individual's physical or mental health condition.

[0818] "Monitoring" refers to the continuous collection and analysis of data to monitor an individual's health and living conditions.

[0819] "Issuing an alert" refers to the act of notifying a user of a warning when an anomaly is detected.

[0820] This invention is a support system for an aging society, particularly targeting seniors who have no family support. This system is built around a server and aims to provide seniors with a safe and secure living environment by integrating and offering multiple functions.

[0821] The server uses a database management system to collect and analyze contract information, authentication information, credit information, and lifestyle data. Specifically, the database management system (DBMS) is operated using SQL, and a risk assessment algorithm is used for credit information analysis. As a result of the analysis, the individual credit risk is evaluated, and based on this evaluation, a virtual guarantor is set up within the program. This virtual guarantor serves to support the user when they receive specific conditions or services.

[0822] The device is equipped with a microphone and camera for emotion analysis, and uses voice analysis software and facial recognition algorithms to recognize emotions from the user's voice and facial expressions. For example, if a user experiences stress in their daily life, the system will automatically determine that emotion and provide appropriate support.

[0823] In document generation, after the terminal receives the necessary information from the user, the server uses natural language processing technology to format the information and automatically generate the submission document. The user can preview the generated document and use it as the official document after confirming its contents. This improves the efficiency of the procedure and reduces the burden on the user.

[0824] Furthermore, the server has the capability to monitor living conditions and health status in real time, and uses data collected from devices and sensors to immediately issue an alert if an anomaly is detected. This alert is sent to the user or designated contacts via email or app notification.

[0825] As a concrete example, by inputting a prompt message such as, "A 70-year-old single man wants to enter a nursing home. Please set up a virtual guarantor considering his credit information and living situation," into the AI ​​model, it is possible to customize appropriate services according to individual credit risk and living circumstances.

[0826] This system provides comprehensive support to seniors without family, enabling them to continue living with peace of mind.

[0827] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0828] Step 1:

[0829] The server collects contract information.

[0830] The server uses a database management system to retrieve user contract information. This information includes name, age, address, and past contract history. Based on this data, authentication and credit information are collected. It receives information from the database as input and creates a dataset for analysis as output.

[0831] Step 2:

[0832] The server assesses the individual's credit risk.

[0833] The server processes the collected data through an analysis algorithm to assess the individual credit risk. The main inputs are contract information and past credit history, and the output is the user's credit score. A high credit score indicates low risk, while a low score indicates high risk.

[0834] Step 3:

[0835] The server sets up a virtual guarantor.

[0836] The server sets up a virtual guarantor within the program based on the evaluated credit score. The input information is the credit score and the required service conditions, and a virtual guarantor object is generated as output. This ensures that the user is guaranteed when receiving services.

[0837] Step 4:

[0838] The device analyzes the user's voice.

[0839] The device collects voice data using its built-in microphone and recognizes emotions using voice analysis software. The input is the user's voice, and the output is their emotional state (e.g., stress, relief). The tone and tempo of the voice are analyzed to infer the user's emotions.

[0840] Step 5:

[0841] The device analyzes the user's facial expressions.

[0842] The device captures facial data through its camera and analyzes it using a facial recognition algorithm. The input data is real-time video, and the output is analyzed emotional information. For example, it can detect smiles and frown lines to evaluate emotions.

[0843] Step 6:

[0844] The terminal collects information necessary for generating the required documents.

[0845] The user enters the necessary information through the terminal interface. This information includes name, address, and application details, and is sent to the server as input data. The output is a formatted set of information.

[0846] Step 7:

[0847] The server automatically generates the documents.

[0848] The server processes the received information using natural language processing technology and automatically generates documents for submission. The input data is information entered by the user, and the output is in the format of a completed document template. The generated document is previewed by the user for content verification.

[0849] Step 8:

[0850] The server monitors the user's living situation and health status.

[0851] The server continuously monitors the user's status based on data from terminals and external devices. Inputs include sensor data and user activity logs, while outputs include assessments of health status and lifestyle abnormalities. If an abnormality is detected, an alert is quickly issued and the user is notified.

[0852] (Application Example 2)

[0853] 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".

[0854] In an aging society, there is a growing need for support systems that enable elderly people without family support to live with peace of mind. In particular, difficulties in accessing financial resources, medical facilities, and the lack of emotional support in daily life are significant challenges. Effective solutions to these challenges are essential.

[0855] 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.

[0856] In this invention, the server includes means for analyzing contract information and collecting personal authentication information, credit information, and living conditions; means for providing services by setting up a virtual guarantor; and means for analyzing emotional states and providing support for stress and anxiety. This enables comprehensive support for elderly people to live with peace of mind.

[0857] "Contract information" refers to information that shows the terms of the agreement regarding the use of the service concluded between the user and the service provider.

[0858] "Personal authentication information" refers to information used to verify the user's identity.

[0859] "Credit information" refers to information that indicates a user's financial reliability and ability to pay.

[0860] "Living conditions" refers to information that describes the environment and conditions related to the user's daily life.

[0861] "Credit risk" is the result of an assessment of the potential risks related to the user's creditworthiness.

[0862] A "virtual guarantor" is a non-existent guarantor established for the purpose of providing a service.

[0863] "Service" refers to the various forms of support and benefits provided to users.

[0864] "Submitted documents" are official documents required to use a particular service.

[0865] "Methods for automatically generating documents" refers to a function that automatically creates necessary documents based on information provided by the user.

[0866] "Monitoring" refers to the continuous observation of a user's lifestyle and health status.

[0867] An "alert" is a function that notifies the user when a specific condition or event occurs.

[0868] "Emotional state" refers to the user's psychological state and changes in their emotions.

[0869] "Support for stress and anxiety" refers to providing support to alleviate the psychological burden that users experience.

[0870] "Means of facilitating access to healthcare" refers to functions that help users receive healthcare services smoothly.

[0871] This system connects a server and user terminals to provide multifaceted support to elderly individuals without family support. The server analyzes contract information and obtains personal authentication information, credit information, and living conditions. Based on this, it assesses individual credit risk and, if necessary, generates a virtual guarantor. This virtual guarantor's guarantee function allows elderly individuals to proceed smoothly with procedures at medical institutions and welfare facilities.

[0872] The user terminal is equipped with an emotion engine that analyzes voice input and facial expressions to understand the user's emotional state in real time. If stress or anxiety is detected as a result of the emotion analysis, relaxation guides and mental support are immediately provided. Furthermore, if access to a medical institution is necessary, the terminal sends a request to the server to assist in providing appropriate information.

[0873] This system also incorporates a real-time monitoring function for living conditions and health status. The server analyzes data obtained from devices and sensors, and if an anomaly is detected, it sends an alert to the user. This process also takes emotional states into account, enabling more personalized support than simply receiving notifications based on numerical anomalies.

[0874] For example, if a user reports, "I've been having trouble sleeping lately, and it's making me a little anxious," the system analyzes this and suggests relaxation music and breathing exercises. It also automatically records the user's health status and stores this information on the server for use during future medical visits if necessary.

[0875] Examples of prompts for a generative AI model include the following:

[0876] "Please provide ideas for relaxation activities to offer to users aged 65 and over who are experiencing anxiety."

[0877] "Based on the living conditions information obtained from users, please create a proposal for a reliable monitoring system."

[0878] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0879] Step 1:

[0880] The server analyzes contract information and collects personal authentication information, credit information, and living conditions. In this process, contract information is provided as input, and detailed evaluation data about the user is output using database search and analysis algorithms. Specifically, the server retrieves relevant information from the contract database, analyzes it, and extracts individual attribute information.

[0881] Step 2:

[0882] The server uses the collected data to assess credit risk and set up virtual guarantors. The assessment data extracted in the previous step is used as input, and a credit risk score is output through analysis using a statistical model. Specifically, the server runs the statistical model and generates a digital asset called a virtual guarantor based on the score.

[0883] Step 3:

[0884] The user terminal analyzes the emotional state using an emotion engine. This process receives voice input and facial recognition data, and outputs the emotional state using natural language processing and image processing techniques. The terminal utilizes a microphone and camera to process the data obtained in real time and identify the user's emotional state.

[0885] Step 4:

[0886] If stress or anxiety is detected as a result of the emotional state analysis, the device will provide a relaxation guide. The input is the emotional analysis result, and the output is relaxation content tailored to the user. The device performs audio playback and video guidance through a mobile application.

[0887] Step 5:

[0888] The server monitors living conditions and health status and issues alerts when necessary. This process uses data from sensors as input, which is then analyzed by an anomaly detection algorithm before an alert message is output. The server continuously receives data from the monitoring system and notifies the user and relevant authorities as needed.

[0889] Step 6:

[0890] The server provides the information necessary to facilitate access to healthcare facilities. This process uses user information and a healthcare facility database as input and outputs links to relevant healthcare services. The server then performs a process to suggest accessible healthcare facilities, taking into account the user's location.

[0891] 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.

[0892] 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.

[0893] 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.

[0894] 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.

[0895] 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.

[0896] 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.

[0897] 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.

[0898] 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.

[0899] 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."

[0900] 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.

[0901] 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.

[0902] 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.

[0903] 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.

[0904] 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.

[0905] 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.

[0906] 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.

[0907] 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.

[0908] 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.

[0909] 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.

[0910] 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.

[0911] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0912] The following is further disclosed regarding the embodiments described above.

[0913] (Claim 1)

[0914] A means of analyzing contract information and collecting personal authentication information, credit information, and living information,

[0915] A means of evaluating individual credit risks using collected data,

[0916] A means of setting up a virtual guarantor based on evaluation,

[0917] A means of providing services by setting up a virtual guarantor,

[0918] A means of receiving the information necessary to generate the submission documents and automatically generating the documents,

[0919] A means of monitoring customers' living conditions and health status and issuing alerts,

[0920] A system that includes this.

[0921] (Claim 2)

[0922] The system according to claim 1, wherein the virtual guarantor is an in-program entity that satisfies the conditions.

[0923] (Claim 3)

[0924] The system according to claim 1, comprising means for detecting abnormalities in health conditions based on sensor information.

[0925] "Example 1"

[0926] (Claim 1)

[0927] A means of collecting and analyzing personal contract information to obtain authentication information, credit information, and living information,

[0928] A means of evaluating individual credit risks based on information collected using a generative AI model,

[0929] A means of generating a virtual guarantor based on the evaluation results,

[0930] A means of providing service guarantees using a virtual guarantor,

[0931] A means of receiving document creation information based on user input and automatically generating documents using AI technology,

[0932] A means of monitoring the user's health status in real time based on sensor information and issuing alerts when an abnormality is detected,

[0933] A system that includes this.

[0934] (Claim 2)

[0935] The system according to claim 1, wherein the virtual guarantor is an in-program entity that satisfies the conditions.

[0936] (Claim 3)

[0937] The system according to claim 1, comprising a process for detecting abnormalities in health status based on sensor information.

[0938] "Application Example 1"

[0939] (Claim 1)

[0940] A means of analyzing contract data and collecting individual authentication information, credit information, and living environment information,

[0941] A means of evaluating the credit risk of each individual using the collected data,

[0942] A means of setting up a virtual guarantee entity based on evaluation,

[0943] A means of providing services by setting up a virtual guarantee entity,

[0944] A means of receiving the data necessary to generate the submission documents and automatically generating the documents,

[0945] A means of monitoring the user's living environment and health status and sending notifications,

[0946] A means of analyzing health data and sending real-time notifications in case of abnormalities,

[0947] A system that includes this.

[0948] (Claim 2)

[0949] The system according to claim 1, wherein the virtual guarantee entity is an in-program entity that satisfies the conditions.

[0950] (Claim 3)

[0951] The system according to claim 1, comprising means for detecting abnormalities in health conditions based on sensor data and issuing an alert.

[0952] "Example 2 of combining an emotion engine"

[0953] (Claim 1)

[0954] A means of analyzing contract information and collecting personal authentication information, credit information, and living information,

[0955] A means of evaluating individual credit risks using collected data,

[0956] A means of setting up a virtual guarantor based on an evaluation and providing support functions to meet the conditions,

[0957] A means of analyzing audio and video data to recognize individual emotions,

[0958] A means of receiving the information necessary to generate submission documents and automatically generating those documents using natural language processing technology,

[0959] A means of continuously monitoring health status and living conditions, and issuing alerts when abnormalities are detected,

[0960] A system that includes this.

[0961] (Claim 2)

[0962] The system according to claim 1, wherein the virtual guarantor is an entity that has a support function to fulfill conditions within the program.

[0963] (Claim 3)

[0964] The system according to claim 1, comprising means for detecting abnormalities in health conditions based on sensing data.

[0965] "Application example 2 when combining with an emotional engine"

[0966] (Claim 1)

[0967] A means of analyzing contract information and collecting personal authentication information, credit information, and living information,

[0968] A means of evaluating individual credit risks using collected data,

[0969] A means of setting up a virtual guarantor based on evaluation,

[0970] A means of providing services by setting up a virtual guarantor,

[0971] A means of receiving the information necessary to generate the submission documents and automatically generating the documents,

[0972] A means of monitoring customers' living conditions and health status and issuing alerts,

[0973] A means of analyzing emotional states and providing support for stress and anxiety,

[0974] Means of providing the information necessary to facilitate access to healthcare facilities,

[0975] A system that includes this.

[0976] (Claim 2)

[0977] The system according to claim 1, wherein the virtual guarantor is an in-program entity that satisfies the conditions.

[0978] (Claim 3)

[0979] The system according to claim 1, comprising means for detecting abnormalities in health conditions based on sensor information. [Explanation of Symbols]

[0980] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A means of analyzing contract data and collecting individual authentication information, credit information, and living environment information, A means of evaluating the credit risk of each individual using the collected data, A means of setting up a virtual guarantee entity based on evaluation, A means of providing services by setting up a virtual guarantee entity, A means of receiving the data necessary to generate the submission documents and automatically generating the documents, A means of monitoring the user's living environment and health status and sending notifications, A means of analyzing health data and sending real-time notifications in case of abnormalities, A system that includes this.

2. The system according to claim 1, wherein the virtual guarantee entity is an in-program entity that satisfies the conditions.

3. The system according to claim 1, comprising means for detecting abnormalities in health conditions based on sensor data and issuing an alert.

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