system

Abstract

We provide the system. [Solution] A means of analyzing the historical data and skill sets provided by elderly individuals and suggesting appropriate tasks based on job characteristics, A means of monitoring the health status and lifestyle data of the elderly and providing advice for improving their health, A means for analyzing conversational data of elderly people and generating activities that support cognitive function improvement, Means of forming communities to promote interaction among the elderly, A system that includes this.

Description

Technical Field

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

Background Art

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

Prior Art Documents

Patent Documents

[0006] "Historical data" refers to structured data representing records of jobs and activities that elderly individuals have experienced in the past.

[0007] A "skill set" is a collection of information that represents the professional abilities, skills, and experience possessed by older adults.

[0008] "Job characteristics" is a concept that refers to the roles, responsibilities, and necessary skills required for a particular job.

[0009] "Health status" refers to information describing the physical and mental health of older adults.

[0010] "Lifestyle data" refers to data that shows the activities and habits of elderly people in their daily lives, and specifically includes things like the number of steps taken and the content of their meals.

[0011] "Advice" refers to information that provides guidance or recommended actions for a specific issue or situation.

[0012] "Conversation data" refers to data that records the content of elderly people's daily conversations in text format.

[0013] "Cognitive function" is a concept that refers to the ability to perform intellectual processing such as thinking, learning, understanding, memory, and judgment.

[0014] An "activity" refers to any undertaking or action undertaken to achieve a specific purpose or goal.

[0015] A "community" is a collective where individuals with common interests or purposes communicate and share information and experiences.

Brief Explanation of Drawings

[0016] [Figure 1] It is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] It is a conceptual diagram showing an example of the main functions of a data processing device and a smart device according to the first embodiment. [Figure 3] It is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] It 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] It is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] It 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] It is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] It is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] It shows an emotion map to which a plurality of emotions are mapped. [Figure 10] It shows an emotion map to which a plurality of emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Example 2 when an emotion engine is combined. [Figure 14]It is a sequence diagram showing the processing flow of a data processing system in Application Example 2 when a sentiment engine is combined.

Embodiments for Carrying Out the Invention

[0017] 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.

[0018] First, the terms used in the following description will be explained.

[0019] In the following embodiments, a 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.

[0020] In the following embodiments, a numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0021] In the following embodiments, a 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, etc.

[0022] 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).

[0023] 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."

[0024] [First Embodiment]

[0025] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0026] 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.

[0027] 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).

[0028] 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.

[0029] 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.

[0030] 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.

[0031] 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.

[0032] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0033] 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.

[0034] 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.

[0035] 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.

[0036] 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".

[0037] This invention efficiently analyzes the historical data and skill sets accumulated by elderly individuals and provides personalized job and health maintenance advice. The system primarily consists of three components: a server, terminals, and users.

[0038] System Configuration

[0039] Users input their past work history, skill set, and health data via their device. This data reflects the user's daily activities and health status, and may also be automatically retrieved from health management applications or wearable devices.

[0040] The terminal transmits the entered data to the server and then presents the user with feedback and advice from the server. The terminal also functions as a user interface, displaying information in an easy-to-understand manner.

[0041] The server receives historical data and skill sets of elderly individuals transmitted from their terminals and performs analysis using AI. Based on the analysis, it presents a list of appropriate tasks and job postings tailored to the user's job characteristics. The generating AI considers the conditions that will best utilize each user's abilities and customizes the job suggestions accordingly.

[0042] Regarding health data, the server analyzes the information and generates advice for maintaining and improving health. Based on the user's health status, it specifically suggests ways to adjust exercise levels and improve diet.

[0043] Furthermore, conversation data is acquired in text format, and the server analyzes it to suggest activities for improving cognitive function. Based on the content of everyday conversations, it recommends training and thinking activities that are effective in preventing dementia.

[0044] Specific example

[0045] For example, if an elderly former teacher registers as a user, the server analyzes their extensive experience in education and suggests suitable employment opportunities, such as local learning support centers or online educational services. If the elderly person also provides pedometer data, the server uses this to create daily exercise suggestions, providing specific instructions such as light stretching during telework or exercises suitable for commuting.

[0046] In this way, the invention is implemented in a manner that balances social participation and health maintenance by utilizing the diverse data possessed by the elderly.

[0047] The following describes the processing flow.

[0048] Step 1:

[0049] Users open an application on their device and enter their work history, skills, and daily health data. This includes past work experience, professional skills, and exercise data obtained from health apps and wearable devices.

[0050] Step 2:

[0051] The terminal converts the entered data into the appropriate format and sends it to the server. During this process, user data is encrypted according to security protocols.

[0052] Step 3:

[0053] The server registers the data received from the terminal into a database and analyzes the skill set using natural language processing (NLP) technology. This generates a skill map tailored to the user's job characteristics.

[0054] Step 4:

[0055] The server uses the analyzed skill set to match it against a job database and identify suitable tasks and roles for the user. Generative AI then edits this information to construct the optimal options.

[0056] Step 5:

[0057] The server analyzes the user's health data and generates improvement advice for maintaining daily health. Specific suggestions include recommended exercise levels and nutritional management advice.

[0058] Step 6:

[0059] The server analyzes conversational data acquired during everyday conversations. Based on the analysis results, it suggests activities to the user that help maintain and improve cognitive function.

[0060] Step 7:

[0061] The terminal notifies the user of business suggestions and health / cognitive function support advice sent from the server, and displays the information in an easy-to-understand format through the interface.

[0062] Step 8:

[0063] Based on the information received through their devices, users can apply for offered jobs or implement health advice in their daily lives. Furthermore, by engaging in the provided cognitive activities, they can maintain continuous health management.

[0064] (Example 1)

[0065] 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."

[0066] In today's aging society, there is a need for older adults to make the most of their work experience and skills and to promote their social participation. However, there is a lack of adequate systems to accurately analyze the experience and skills of individual older adults and provide appropriate job and health advice. This lack can lead to a decline in the quality of life and social isolation among older adults.

[0067] 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.

[0068] In this invention, the server includes means for acquiring work history, skill sets, and health data entered by elderly individuals via an information processing device; means for analyzing the acquired history data and skill sets and presenting appropriate jobs and job postings based on job characteristics; and means for analyzing health data and generating specific advice for improving and maintaining health. This makes it possible to make the most of the individual experiences of elderly people and provide accurate advice and job suggestions that balance social participation and health maintenance.

[0069] An "information processing device" is a device that receives data entered by a user and sends it to a server for analysis.

[0070] "Work history" refers to data that shows the work experience that individual elderly people have engaged in in the past.

[0071] A "skill set" is data that refers to a collection of skills and abilities that older adults have acquired through their past jobs and experiences.

[0072] "Health data" refers to information that indicates the user's health status, and specifically includes information such as body temperature, blood pressure, and step count.

[0073] A "server" is a central processing unit that receives data transmitted from terminals, performs analysis, and generates proposals.

[0074] "Analysis" is the process of examining acquired data in detail and deriving useful information from it.

[0075] "Job characteristics" refer to the conditions and features required for a particular job, and are the criteria used to select appropriate tasks based on them.

[0076] "Job postings" refer to data indicating employment opportunities related to specific jobs, and are provided to users.

[0077] "Improving health status" refers to initiatives and advice aimed at improving one's current level of health.

[0078] A "communication protocol" is a set of procedures and rules for securely sending and receiving data, and includes encryption.

[0079] This invention provides a system that generates individually tailored job suggestions and health advice using the work history data, skill sets, and health data of elderly individuals. The specific implementation methods are described below.

[0080] Users input data related to their work history, skill set, and health status through a terminal. The terminal is an information processing device, such as a smart device or computer, that collects this data. This data may be entered directly through an input interface, or it may be automatically acquired from health management applications or wearable devices.

[0081] The device securely transmits the collected data to the server. This communication uses protected communication protocols such as SSL / TLS, ensuring data confidentiality.

[0082] The server analyzes the received data using an AI model. Based on work history data and skill sets, the server generates and presents a list of suitable jobs and job postings to the user. Specifically, the generating AI model compares job requirements with the user's skill sets to achieve the best possible match. It also provides specific advice for maintaining and improving health based on health data. For example, it may suggest ways to revise exercise habits or improve dietary habits.

[0083] Furthermore, the server analyzes conversational data and suggests training to improve cognitive function. This is achieved by applying AI-powered natural language processing, suggesting activities based on information obtained from everyday conversations.

[0084] For example, if a user has experience as a "culinary school teacher" and wants to aim for walking 8,000 steps a day, the server will use that data to provide job postings for instructors at local cooking classes and suggest a daily exercise plan. For instance, it might suggest an exercise plan that incorporates moderate stretching while cooking and walking to buy groceries.

[0085] An example of a prompt would be: "Based on the user's past education-related experience, please generate suggestions to help older adults find re-employment. Also, based on the provided pedometer data, please provide exercise advice to maintain health." Through such prompts, the system can provide specific and practical advice.

[0086] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0087] Step 1:

[0088] Users input their work history, skill set, and health data into the device. This process involves entering their past experience and acquired skills, and registering health data through input forms. Data may also be automatically retrieved from wearable devices. The input data is stored as structured data on the device.

[0089] Step 2:

[0090] The terminal transmits all entered data to the server using a secure protocol. This process generates an integrated information packet containing work history, skill sets, and health data, while maintaining data confidentiality using SSL / TLS. The output to the server is transmitted data in a secure and encrypted format.

[0091] Step 3:

[0092] The server uses an AI model to analyze the received data. Specifically, work history and skill sets are analyzed, and data is generated to suggest suitable jobs and job postings for that user. Natural language processing and data mining techniques are used in this analysis. The output is a list of job suggestions for each user.

[0093] Step 4:

[0094] The server analyzes the acquired health data and generates customized advice for maintaining and improving the user's health. In this process, a generative AI model is used for data processing, and specific exercise programs and dietary improvements are designed through data analysis. The output is a personalized health plan.

[0095] Step 5:

[0096] The server collects conversational data, analyzes it through natural language processing, and suggests training to improve cognitive function. Text data obtained from everyday conversations is analyzed, and activities that stimulate thinking and language abilities are selected. The output is a list of recommended cognitive activities, which is presented to the user.

[0097] Step 6:

[0098] The terminal receives results sent from the server and presents them to the user in an easy-to-understand manner. Specifically, it displays job suggestion lists, health advice, and cognitive activity lists on the user interface, allowing the user to easily access the information. The output is information presented to the user as a visual display.

[0099] (Application Example 1)

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

[0101] In an aging society, it is important for older adults to continue participating in society. However, they often fail to fully utilize their abundant experience and skills, leading to social isolation and health problems. Furthermore, there is a lack of appropriate guidelines for tasks that older adults face when working in physical stores, making efficient work difficult.

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

[0103] In this invention, the server includes means for analyzing historical data and technical information provided by the elderly and suggesting appropriate tasks based on job characteristics; means for monitoring the elderly's health status and activity data and providing advice for health improvement; and means for suggesting information to provide assistance for work in physical stores. This enables the elderly to engage in appropriate work, maintain their health, and smoothly carry out work in physical stores.

[0104] "Historical data" refers to records of the jobs and activities that elderly people have performed in the past.

[0105] "Technical information" refers to information that specifically details the skills, knowledge, and qualifications possessed by elderly individuals.

[0106] "Job characteristics" refer to the characteristics of a suitable job for an individual elderly person, based on their experience and technical information.

[0107] "Health status" refers to the physical or mental health condition of an elderly person.

[0108] "Activity data" refers to data that records the daily activities and exercise levels of elderly people.

[0109] "Advice" refers to recommendations for maintaining or improving the health of older adults, based on the analysis results.

[0110] "Business assistance" is a function that provides appropriate guidance and support to elderly people when they are working in a physical store.

[0111] "Means of presenting information" refers to methods used by the server to visually or audibly communicate the results of its analysis to the user.

[0112] This invention constitutes a system for efficiently analyzing historical data, technical information, health status, and activity data possessed by elderly individuals, and for providing appropriate job and health maintenance advice.

[0113] System Configuration

[0114] Users input their historical and technical data into the terminal. This data includes past work experience, technical information, health status, and activity data.

[0115] The terminal is responsible for transmitting the entered information to the server. It also visually presents feedback and advice from the server's analysis results to the user. Smartphones are used as the terminal, offering high convenience.

[0116] The server receives data sent from the terminal and performs analysis using a generated AI model. The analysis utilizes the Python TENSORFLOW® library. The AI ​​model suggests appropriate tasks based on the job characteristics of elderly individuals and analyzes health data to generate advice for maintaining health. Information on business assistance in physical stores is also presented based on the analysis results.

[0117] The system is deployed on Amazon Web Services (AWS®) or Google Cloud Platform (GCP), enabling secure data management and highly efficient analysis.

[0118] Specific example

[0119] For example, if a user, Mr. B, an elderly person who was formerly a teacher, enters his work experience into the app, the server analyzes that historical data and suggests employment opportunities at local learning support centers, etc. Conversely, it can also suggest health-maintaining stretching exercises tailored to Mr. B based on his activity data.

[0120] Examples of prompt statements for a generative AI model are as follows:

[0121] Based on the following data, please provide users with advice regarding in-store operations.

[0122] Work experience: 30 years as a teacher in educational institutions.

[0123] Technical information: Educational skills, communication skills.

[0124] Health data: Normal activity steps: 7000 steps / day, blood pressure within the normal range.

[0125] This system allows seniors to maintain their health while contributing to society.

[0126] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0127] Step 1:

[0128] Users input their historical data and technical information into the terminal. This data includes work experience, technical information (skills, qualifications, etc.), health status, and activity data. This creates a dataset that reflects the user's characteristics.

[0129] Step 2:

[0130] The terminal sends the entered information to the server. This communication takes place over the internet. The input dataset is structured in JSON format and sent to the server. This allows the server to receive user characteristic information.

[0131] Step 3:

[0132] The server analyzes the received data. First, the server uses the Python TensorFlow library to input the data into a generated AI model. The purpose of the analysis is to suggest appropriate tasks based on the user's job characteristics. At this stage, the output is information about the most suitable job and work assistance for the user.

[0133] Step 4:

[0134] Simultaneously, the server analyzes health data. This data includes activity levels and health status, and based on this, it generates appropriate health maintenance advice. The output is individually customized health advice, which includes specific exercise suggestions and recommendations for improving dietary habits.

[0135] Step 5:

[0136] The server sends back the business suggestions and health advice it has generated to the terminal. The data is then sent again in JSON format. This allows the terminal to obtain the latest analysis results.

[0137] Step 6:

[0138] The device presents the received information to the user. Here, the suggestions are displayed visually through the device's screen. This presentation helps the user make informed decisions based on comprehensive information.

[0139] Through processing at each step, older adults can appropriately obtain the information they need to make further contributions to society.

[0140] 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.

[0141] This invention combines an emotion engine with a system that comprehensively analyzes the historical data, skill sets, health status, and conversational data of elderly individuals to support the improvement of work, health, and cognitive function in a way that is suitable for them. This system is primarily composed of three components: a server, a terminal, and a user.

[0142] System Configuration

[0143] Users input their work history, skill set, and health data via a device. Furthermore, everyday conversations and feedback are also entered into the device. This allows for the collection of data to understand their emotional state.

[0144] The terminal centralizes this information entered by the user and sends it to the server. The interface is designed to be intuitive for the user to operate.

[0145] The server analyzes the job characteristics, health status, and cognitive function of elderly individuals based on data received from the terminal. Based on these analysis results, the generating AI proposes optimal work, health advice, and cognitive training to the user.

[0146] The newly integrated emotion engine identifies emotional states from user input and conversation data. This allows it to understand the user's mental health and generate personalized stress reduction strategies and relaxation programs. It also analyzes user interactions within the community from an emotional perspective and offers suggestions to promote positive communication.

[0147] Specific example

[0148] For example, suppose an elderly user wants to utilize their existing education-related skills and inputs them into the system. The server analyzes this data and suggests opportunities for volunteer work supporting local education. Also, if the user regularly inputs walking data, the server provides appropriate exercise advice.

[0149] The emotion engine detects signs of stress from the user's daily conversations. Based on this, it suggests relaxation methods and proactive exercise plans to the user. It also provides feedback to help users communicate better with other seniors in the community.

[0150] In this way, the invention is implemented by seamlessly integrating various functions to comprehensively support the physical and psychological health of the elderly.

[0151] The following describes the processing flow.

[0152] Step 1:

[0153] Users input their work history, skill set, health information, and everyday conversations using the device's interface. They can also add emotional feedback and comments during the input process.

[0154] Step 2:

[0155] The terminal organizes user input data and converts it to the appropriate format. The data is then sent to the server using a secure protocol.

[0156] Step 3:

[0157] The server receives the transmitted data and analyzes job characteristics based on historical data and skill sets. Based on these job characteristics, it selects appropriate tasks and matches job postings with user skills.

[0158] Step 4:

[0159] The server analyzes the user's health data and assesses their current health status. Based on this, it generates specific advice and exercise plans for improving their health.

[0160] Step 5:

[0161] The server's emotion engine analyzes user conversation data to identify their current emotional state. It tracks stress levels and emotional changes, and suggests corresponding stress relief methods and relaxation programs.

[0162] Step 6:

[0163] The server sends information generated based on the analysis results to the user's terminal in a format that is easy for the user to understand. This includes business suggestions, health advice, and emotional support.

[0164] Step 7:

[0165] The device receives information from the server and displays it in an easy-to-understand format for the user. If immediate action is required, the user will receive warnings or suggestions via push notifications.

[0166] Step 8:

[0167] Users can utilize the provided support by applying for the tasks offered or by applying health and emotional advice to their daily lives. They can also use the community features to interact with other users and share their feelings.

[0168] (Example 2)

[0169] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0170] As social participation among the elderly increases, there is a need to utilize individual historical data and skills information to find appropriate tasks, to appropriately monitor health conditions and provide effective improvement measures, and to improve cognitive function using conversational information. Furthermore, there is a lack of methods to support mental health based on emotional data, so the development of a new system that comprehensively supports these aspects is necessary.

[0171] 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.

[0172] In this invention, the server includes means for analyzing historical data and skills information provided by the elderly and presenting appropriate tasks based on their work characteristics; means for monitoring the elderly's health status and lifestyle information and providing advice for health improvement; means for analyzing the elderly's conversational information and generating activities to support cognitive function improvement; means for analyzing provided emotional data and generating methods to support mental health; and means for using the generated artificial intelligence model to generate optimal advice and activities as prompts. This enables not only elderly individuals to receive optimal tasks and health improvement measures based on their own data, but also comprehensive support for maintaining their mental health.

[0173] "Historical data" refers to information provided by elderly individuals regarding their past work experience and activity history.

[0174] "Skills information" refers to information about specific abilities and skills possessed by older adults.

[0175] "Job characteristics" refer to the distinctive features and required skills of a particular job or task.

[0176] "Health status" refers to information regarding the physical and mental health of older adults.

[0177] "Lifestyle information" refers to data related to the daily lives of elderly people, including information on diet, exercise, and daily activities.

[0178] "Conversational information" refers to data on the content, tone, and emotions of elderly people's daily conversations.

[0179] "Cognitive function" refers to all the functions that the brain processes, such as memory, attention, and judgment.

[0180] "Emotional data" refers to information about the emotional state and mental responses exhibited by older adults.

[0181] "Mental health" refers to the mental stability and well-being of older adults.

[0182] A "generated artificial intelligence model" is a collection of algorithms that learn from large amounts of data and are used to solve problems and make predictions.

[0183] A "prompt sentence" is an input sentence used to give instructions or questions to artificial intelligence.

[0184] This invention is a system that comprehensively collects and analyzes historical data, skills information, health status, lifestyle information, conversational information, and emotional data of elderly individuals, and provides personalized work suggestions, health improvement measures, and methods to support mental health. This system is primarily composed of a server, terminals, and users.

[0185] First, the user inputs their work history, skills information, health data, and daily conversations and emotional states into the device. The device provides a user-friendly interface, allowing data to be registered through haptic feedback and voice input. For example, the user might input their health checkup results and walking data.

[0186] Next, the device centralizes this data and transmits it to the server while maintaining accuracy and completeness. This communication involves data format conversion and encryption to ensure security. Specific devices that can be used include computer terminals such as tablets and smartphones.

[0187] The server uses data analysis libraries such as Python's Pandas and Scikit-learn to analyze the received data. Based on these analysis results, the generative AI model makes appropriate suggestions. The generative AI model utilizes various algorithms to perform predictions and optimizations. For example, it might suggest volunteer activities at a local education support center to the user. In this case, an example prompt might be, "Please find volunteer activities where you can utilize your education-related skills."

[0188] Furthermore, the emotion engine analyzes the user's emotional state from their everyday conversations using tools such as Hugging Face Transformers and BERT. Based on this, it provides the user with relaxation methods and stress reduction strategies. This system comprehensively supports older adults in maintaining their physical and mental health.

[0189] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0190] Step 1:

[0191] Users input their personal history data, skills information, health data, and daily conversation information into the terminal. The terminal collects and centralizes this data through an interface. Specifically, text and voice data are registered on the input screen of a tablet or smartphone. This input includes work history, recent health check results, and recent conversation content. As a result, all data is aggregated on the terminal and ready to be sent to the server.

[0192] Step 2:

[0193] The terminal sends the collected data to the server. The terminal performs data format conversion and encryption to ensure data accuracy and security. Input is the data entered by the user into the terminal, and output is the data securely transferred to the server. Specific operations include generating and sending data packets.

[0194] Step 3:

[0195] The server analyzes data received from terminals. Data analysis uses Python's Pandas and Scikit-learn libraries, employing statistical methods to evaluate health status and job characteristics. Input is unified data sent from terminals, and output is health assessment and job suitability information as analysis results. Specific operations include data cleaning and statistical evaluation.

[0196] Step 4:

[0197] The server uses a generative AI model to suggest optimal advice and activities to the user based on the analysis results. The AI ​​model learns and optimizes data using various algorithms. The input is the analysis results, and the output is the work options and health improvement measures suggested to the user. Specific operations include pattern recognition and suggestion generation by the AI ​​model.

[0198] Step 5:

[0199] Using an emotion engine, the server analyzes the user's emotional state. It extracts emotions from everyday conversations using Hugging Face Transformers and BERT models. The input is the user's everyday conversation data, and the output is an emotion evaluation and a suggested relaxation method based on it. Specifically, natural language processing and emotion state estimation are performed.

[0200] Step 6:

[0201] The server provides optimal interaction suggestions to facilitate communication between users. It aggregates elderly individuals with shared interests and proposes events and activities. Inputs are past interaction data and shared interests, and output is suggested interaction events. Specific operations include database searching and the use of matching algorithms.

[0202] (Application Example 2)

[0203] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0204] It is important to effectively utilize the wealth of experience and skills that seniors possess and provide them with opportunities to actively contribute to society. However, current support systems for seniors do not adequately address individual health and emotional states, making it difficult to alleviate the stress and health risks they face. Furthermore, there is a lack of appropriate information to improve the experience when visiting physical stores, making it difficult for seniors to find products and services that are suitable for them.

[0205] 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.

[0206] This invention includes a server that includes means for analyzing historical data and abilities provided by elderly individuals and suggesting appropriate tasks based on job characteristics; means for monitoring the health status and biometric data of elderly individuals and providing advice for health improvement; means for analyzing conversational data of elderly individuals and generating activities that support cognitive function improvement; means for analyzing the emotional state of elderly individuals, understanding their mental health status, and suggesting stress reduction measures; means for forming groups to promote interaction among elderly individuals and supporting good communication; and means for visually presenting recommended products and services in a store to elderly individuals using an augmented reality device. This not only facilitates the provision of information to help elderly individuals find the activities and products best suited to them, but also enables individualized support tailored to their health and emotional state.

[0207] "Historical data" refers to information about the work and activities that elderly people have experienced up to that point.

[0208] "Ability" refers to information about specific skills or areas of expertise that older adults possess.

[0209] "Health status" refers to information related to the physical and mental health of older adults.

[0210] "Biometric data" refers to vital signs related to health status and data on physical activity in daily life.

[0211] "Conversation data" refers to information about the words and expressions that elderly people use on a daily basis.

[0212] "Emotional state" refers to information about the mental health and emotional fluctuations of older adults.

[0213] A "group" refers to a group of elderly people who share a particular hobby or interest.

[0214] An "augmented reality device" is a device that overlays digital information onto the real world's field of vision.

[0215] "Recommended products" are products and services selected based on the health condition, hobbies, and interests of elderly individuals.

[0216] To realize this invention, the system consists of three components: a server, a terminal, and a user. The server centrally analyzes the elderly person's historical data, abilities, health status, and conversation data. Based on this, it generates job characteristics, optimal tasks, advice for health improvement, and activities for improving cognitive function. In addition, it utilizes an emotion engine to assess mental health status and propose stress reduction measures on an individual basis.

[0217] The terminal is responsible for collecting data provided by the user and transmitting it to the server. Users input their historical data, abilities, and biometric data through an intuitive interface. The terminal further provides users with visually recommended products based on their health status and interests within the store via augmented reality devices. This process allows users to obtain products and services best suited to their individual health needs.

[0218] For example, when an elderly person with farming experience visits a supermarket, they may receive recommendations for organic foods based on their health condition. In this case, the terminal displays products suitable for the user in real time and provides feedback to support smoother communication.

[0219] As an example of utilizing a generative AI model, the prompt might look like this: "Based on the user's health data and conversational data, suggest the most suitable products and stress relief methods for him. Also, provide advice on how to facilitate communication in stores."

[0220] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0221] Step 1:

[0222] Users input their historical data, abilities, and health status into the terminal via an interface. This input is collected as text or selection-based data. The terminal centralizes this data and sends it to the server in a structured format.

[0223] Step 2:

[0224] The server analyzes received historical data and capabilities, and uses a generative AI model to generate appropriate tasks based on job characteristics. Using prompts, the system queries the AI ​​for optimal tasks and activities, outputting them as job postings and activity suggestions.

[0225] Step 3:

[0226] The server analyzes the user's health status and biometric data to generate specific advice for improving their health. In this process, it analyzes data patterns and suggests exercise and dietary improvements tailored to the user's health condition.

[0227] Step 4:

[0228] The server analyzes conversational data and generates activities to support the user's cognitive function improvement. Using text analysis algorithms, it analyzes cognitive patterns in conversations and outputs specific training programs.

[0229] Step 5:

[0230] Utilizing an emotion engine, the server identifies the user's emotional state from their input data. It detects signs of stress and anxiety and suggests the most appropriate stress relief measures and relaxation methods for each individual user.

[0231] Step 6:

[0232] The terminal visually presents users with recommended products based on their health status and interests within the store via an augmented reality device. It converts recommendation data from the server into a graphical interface and displays it to the user in real time.

[0233] Step 7:

[0234] The server uses a generative AI model to suggest the optimal communication method for the user. An AI assistant, using prompt sentences, outputs advice for better communication and presents it to the user via the terminal.

[0235] 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.

[0236] 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.

[0237] 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.

[0238] [Second Embodiment]

[0239] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0240] 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.

[0241] 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).

[0242] 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.

[0243] 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.

[0244] 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).

[0245] 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.

[0246] 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.

[0247] 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.

[0248] 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.

[0249] 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.

[0250] 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".

[0251] This invention efficiently analyzes the historical data and skill sets accumulated by elderly individuals and provides personalized job and health maintenance advice. The system primarily consists of three components: a server, terminals, and users.

[0252] System Configuration

[0253] Users input their past work history, skill set, and health data via their device. This data reflects the user's daily activities and health status, and may also be automatically retrieved from health management applications or wearable devices.

[0254] The terminal transmits the entered data to the server and then presents the user with feedback and advice from the server. The terminal also functions as a user interface, displaying information in an easy-to-understand manner.

[0255] The server receives historical data and skill sets of elderly individuals transmitted from their terminals and performs analysis using AI. Based on the analysis, it presents a list of appropriate tasks and job postings tailored to the user's job characteristics. The generating AI considers the conditions that will best utilize each user's abilities and customizes the job suggestions accordingly.

[0256] Regarding health data, the server analyzes the information and generates advice for maintaining and improving health. Based on the user's health status, it specifically suggests ways to adjust exercise levels and improve diet.

[0257] Furthermore, conversation data is acquired in text format, and the server analyzes it to suggest activities for improving cognitive function. Based on the content of everyday conversations, it recommends training and thinking activities that are effective in preventing dementia.

[0258] Specific example

[0259] For example, if an elderly former teacher registers as a user, the server analyzes their extensive experience in education and suggests suitable employment opportunities, such as local learning support centers or online educational services. If the elderly person also provides pedometer data, the server uses this to create daily exercise suggestions, providing specific instructions such as light stretching during telework or exercises suitable for commuting.

[0260] In this way, the invention is implemented in a manner that balances social participation and health maintenance by utilizing the diverse data possessed by the elderly.

[0261] The following describes the processing flow.

[0262] Step 1:

[0263] Users open an application on their device and enter their work history, skills, and daily health data. This includes past work experience, professional skills, and exercise data obtained from health apps and wearable devices.

[0264] Step 2:

[0265] The terminal converts the entered data into the appropriate format and sends it to the server. During this process, user data is encrypted according to security protocols.

[0266] Step 3:

[0267] The server registers the data received from the terminal into a database and analyzes the skill set using natural language processing (NLP) technology. This generates a skill map tailored to the user's job characteristics.

[0268] Step 4:

[0269] The server uses the analyzed skill set to match it against a job database and identify suitable tasks and roles for the user. Generative AI then edits this information to construct the optimal options.

[0270] Step 5:

[0271] The server analyzes the user's health data and generates improvement advice for maintaining daily health. Specific suggestions include recommended exercise levels and nutritional management advice.

[0272] Step 6:

[0273] The server analyzes conversational data acquired during everyday conversations. Based on the analysis results, it suggests activities to the user that help maintain and improve cognitive function.

[0274] Step 7:

[0275] The terminal notifies the user of business suggestions and health / cognitive function support advice sent from the server, and displays the information in an easy-to-understand format through the interface.

[0276] Step 8:

[0277] Based on the information received through their devices, users can apply for offered jobs or implement health advice in their daily lives. Furthermore, by engaging in the provided cognitive activities, they can maintain continuous health management.

[0278] (Example 1)

[0279] 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."

[0280] In today's aging society, there is a need for older adults to make the most of their work experience and skills and to promote their social participation. However, there is a lack of adequate systems to accurately analyze the experience and skills of individual older adults and provide appropriate job and health advice. This lack can lead to a decline in the quality of life and social isolation among older adults.

[0281] 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.

[0282] In this invention, the server includes means for acquiring work history, skill sets, and health data entered by elderly individuals via an information processing device; means for analyzing the acquired history data and skill sets and presenting appropriate jobs and job postings based on job characteristics; and means for analyzing health data and generating specific advice for improving and maintaining health. This makes it possible to make the most of the individual experiences of elderly people and provide accurate advice and job suggestions that balance social participation and health maintenance.

[0283] The "information processing device" is a device that receives data input by a user and transmits it to a server for analysis.

[0284] The "work history" is data indicating the work experience that each elderly person has engaged in in the past.

[0285] The "skill set" is data referring to a group of technologies and abilities that an elderly person has acquired through past duties and experiences.

[0286] The "health data" is information indicating the health status of a user, specifically including information such as body temperature, blood pressure, and number of steps.

[0287] The "server" is a central processing device that receives data transmitted from a terminal and performs analysis and proposal generation.

[0288] "Analysis" is a process of examining the acquired data in detail and deriving useful information from it.

[0289] The "job characteristics" refer to the conditions and characteristics required for a specific job, and are the criteria for selecting appropriate work based on them.

[0290] The "job offer information" is data indicating employment opportunities related to jobs and is provided to users.

[0291] "Improvement of health status" refers to efforts and advice aimed at improving the current health level.

[0292] The "communication protocol" defines procedures and rules for safely transmitting and receiving data and includes encryption.

[0293] This invention provides a system that generates job proposals and health advice suitable for individuals using the work history data, skill sets, and health data possessed by the elderly. The specific implementation means will be described below.

[0294] Users input data related to their work history, skill set, and health status through a terminal. The terminal is an information processing device, such as a smart device or computer, that collects this data. This data may be entered directly through an input interface, or it may be automatically acquired from health management applications or wearable devices.

[0295] The device securely transmits the collected data to the server. This communication uses protected communication protocols such as SSL / TLS, ensuring data confidentiality.

[0296] The server analyzes the received data using an AI model. Based on work history data and skill sets, the server generates and presents a list of suitable jobs and job postings to the user. Specifically, the generating AI model compares job requirements with the user's skill sets to achieve the best possible match. It also provides specific advice for maintaining and improving health based on health data. For example, it may suggest ways to revise exercise habits or improve dietary habits.

[0297] Furthermore, the server analyzes conversational data and suggests training to improve cognitive function. This is achieved by applying AI-powered natural language processing, suggesting activities based on information obtained from everyday conversations.

[0298] For example, if a user has experience as a "culinary school teacher" and wants to aim for walking 8,000 steps a day, the server will use that data to provide job postings for instructors at local cooking classes and suggest a daily exercise plan. For instance, it might suggest an exercise plan that incorporates moderate stretching while cooking and walking to buy groceries.

[0299] Examples of prompt texts include "Based on the user's past educational experiences, please generate proposals that are useful for the reemployment of the elderly. Also, based on the provided pedometer data, please provide exercise advice for maintaining health." Through such prompts, the system can provide specific and practical advice.

[0300] The flow of the specific process in Example 1 will be described using FIG. 11.

[0301] Step 1:

[0302] The user inputs job history, skill set, and health data into the terminal. In this process, the user inputs past experiences and acquired skills, and registers health-related data through an input form. Also, data from wearable devices may be automatically acquired. The output of the input data is stored as structured data in the terminal.

[0303] Step 2:

[0304] The terminal transmits all the input data to the server via a secure protocol. In this process, while maintaining the confidentiality of the data using SSL / TLS, an information packet integrating job history, skill set, and health data is generated. The output to the server is transmission data in a secure and encrypted form.

[0305] Step 3:

[0306] The server analyzes the received data using an AI model. Specifically, the job history and skill set are analyzed, and data for presenting suitable jobs and job offers for that user is generated. Natural language processing and data mining techniques are used for this analysis. The output is a job proposal list for each user.

[0307] Step 4:

[0308] The server analyzes the acquired health data and generates customized advice for maintaining and improving the user's health. In this process, a generative AI model is used for data processing, and specific exercise programs and dietary improvements are designed through data analysis. The output is a personalized health plan.

[0309] Step 5:

[0310] The server collects conversational data, analyzes it through natural language processing, and suggests training to improve cognitive function. Text data obtained from everyday conversations is analyzed, and activities that stimulate thinking and language abilities are selected. The output is a list of recommended cognitive activities, which is presented to the user.

[0311] Step 6:

[0312] The terminal receives results sent from the server and presents them to the user in an easy-to-understand manner. Specifically, it displays job suggestion lists, health advice, and cognitive activity lists on the user interface, allowing the user to easily access the information. The output is information presented to the user as a visual display.

[0313] (Application Example 1)

[0314] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0315] In an aging society, it is important for older adults to continue participating in society. However, they often fail to fully utilize their abundant experience and skills, leading to social isolation and health problems. Furthermore, there is a lack of appropriate guidelines for tasks that older adults face when working in physical stores, making efficient work difficult.

[0316] 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.

[0317] In this invention, the server includes means for analyzing historical data and technical information provided by the elderly and suggesting appropriate tasks based on job characteristics; means for monitoring the elderly's health status and activity data and providing advice for health improvement; and means for suggesting information to provide assistance for work in physical stores. This enables the elderly to engage in appropriate work, maintain their health, and smoothly carry out work in physical stores.

[0318] "Historical data" refers to records of the jobs and activities that elderly people have performed in the past.

[0319] "Technical information" refers to information that specifically details the skills, knowledge, and qualifications possessed by elderly individuals.

[0320] "Job characteristics" refer to the characteristics of a suitable job for an individual elderly person, based on their experience and technical information.

[0321] "Health status" refers to the physical or mental health condition of an elderly person.

[0322] "Activity data" refers to data that records the daily activities and exercise levels of elderly people.

[0323] "Advice" refers to recommendations for maintaining or improving the health of older adults, based on the analysis results.

[0324] "Business assistance" is a function that provides appropriate guidance and support to elderly people when they are working in a physical store.

[0325] "Means of presenting information" refers to methods used by the server to visually or audibly communicate the results of its analysis to the user.

[0326] This invention constitutes a system for efficiently analyzing historical data, technical information, health status, and activity data possessed by elderly individuals, and for providing appropriate job and health maintenance advice.

[0327] System Configuration

[0328] Users input their historical and technical data into the terminal. This data includes past work experience, technical information, health status, and activity data.

[0329] The terminal is responsible for transmitting the entered information to the server. It also visually presents feedback and advice from the server's analysis results to the user. Smartphones are used as the terminal, offering high convenience.

[0330] The server receives data sent from the terminal and performs analysis using a generated AI model. The analysis utilizes the Python TensorFlow library. The AI ​​model suggests appropriate tasks based on the job characteristics of elderly individuals and analyzes health data to generate advice for maintaining health. Information on business assistance in physical stores is also presented based on the analysis results.

[0331] The system is deployed on Amazon Web Services (AWS) or Google Cloud Platform (GCP), enabling secure data management and highly efficient analysis.

[0332] Specific example

[0333] For example, if a user, Mr. B, an elderly person who was formerly a teacher, enters his work experience into the app, the server analyzes that historical data and suggests employment opportunities at local learning support centers, etc. Conversely, it can also suggest health-maintaining stretching exercises tailored to Mr. B based on his activity data.

[0334] Examples of prompt statements for a generative AI model are as follows:

[0335] Based on the following data, please provide users with advice regarding in-store operations.

[0336] Work experience: 30 years as a teacher in educational institutions.

[0337] Technical information: Educational skills, communication skills.

[0338] Health data: Normal activity steps: 7000 steps / day, blood pressure within the normal range.

[0339] This system allows seniors to maintain their health while contributing to society.

[0340] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0341] Step 1:

[0342] Users input their historical data and technical information into the terminal. This data includes work experience, technical information (skills, qualifications, etc.), health status, and activity data. This creates a dataset that reflects the user's characteristics.

[0343] Step 2:

[0344] The terminal sends the entered information to the server. This communication takes place over the internet. The input dataset is structured in JSON format and sent to the server. This allows the server to receive user characteristic information.

[0345] Step 3:

[0346] The server analyzes the received data. First, the server uses the Python TensorFlow library to input the data into a generated AI model. The purpose of the analysis is to suggest appropriate tasks based on the user's job characteristics. At this stage, the output is information about the most suitable job and work assistance for the user.

[0347] Step 4:

[0348] Simultaneously, the server analyzes health data. This data includes activity levels and health status, and based on this, it generates appropriate health maintenance advice. The output is individually customized health advice, which includes specific exercise suggestions and recommendations for improving dietary habits.

[0349] Step 5:

[0350] The server sends back the business suggestions and health advice it has generated to the terminal. The data is then sent again in JSON format. This allows the terminal to obtain the latest analysis results.

[0351] Step 6:

[0352] The device presents the received information to the user. Here, the suggestions are displayed visually through the device's screen. This presentation helps the user make informed decisions based on comprehensive information.

[0353] Through processing at each step, older adults can appropriately obtain the information they need to make further contributions to society.

[0354] 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.

[0355] This invention combines an emotion engine with a system that comprehensively analyzes the historical data, skill sets, health status, and conversational data of elderly individuals to support the improvement of work, health, and cognitive function in a way that is suitable for them. This system is primarily composed of three components: a server, a terminal, and a user.

[0356] System Configuration

[0357] Users input their work history, skill set, and health data via a device. Furthermore, everyday conversations and feedback are also entered into the device. This allows for the collection of data to understand their emotional state.

[0358] The terminal centralizes this information entered by the user and sends it to the server. The interface is designed to be intuitive for the user to operate.

[0359] The server analyzes the job characteristics, health status, and cognitive function of elderly individuals based on data received from the terminal. Based on these analysis results, the generating AI proposes optimal work, health advice, and cognitive training to the user.

[0360] The newly integrated emotion engine identifies emotional states from user input and conversation data. This allows it to understand the user's mental health and generate personalized stress reduction strategies and relaxation programs. It also analyzes user interactions within the community from an emotional perspective and offers suggestions to promote positive communication.

[0361] Specific example

[0362] For example, suppose an elderly user wants to utilize their existing education-related skills and inputs them into the system. The server analyzes this data and suggests opportunities for volunteer work supporting local education. Also, if the user regularly inputs walking data, the server provides appropriate exercise advice.

[0363] The emotion engine detects signs of stress from the user's daily conversations. Based on this, it suggests relaxation methods and proactive exercise plans to the user. It also provides feedback to help users communicate better with other seniors in the community.

[0364] In this way, the invention is implemented by seamlessly integrating various functions to comprehensively support the physical and psychological health of the elderly.

[0365] The following describes the processing flow.

[0366] Step 1:

[0367] Users input their work history, skill set, health information, and everyday conversations using the device's interface. They can also add emotional feedback and comments during the input process.

[0368] Step 2:

[0369] The terminal organizes user input data and converts it to the appropriate format. The data is then sent to the server using a secure protocol.

[0370] Step 3:

[0371] The server receives the transmitted data and analyzes job characteristics based on historical data and skill sets. Based on these job characteristics, it selects appropriate tasks and matches job postings with user skills.

[0372] Step 4:

[0373] The server analyzes the user's health data and assesses their current health status. Based on this, it generates specific advice and exercise plans for improving their health.

[0374] Step 5:

[0375] The server's emotion engine analyzes user conversation data to identify their current emotional state. It tracks stress levels and emotional changes, and suggests corresponding stress relief methods and relaxation programs.

[0376] Step 6:

[0377] The server sends information generated based on the analysis results to the user's terminal in a format that is easy for the user to understand. This includes business suggestions, health advice, and emotional support.

[0378] Step 7:

[0379] The device receives information from the server and displays it in an easy-to-understand format for the user. If immediate action is required, the user will receive warnings or suggestions via push notifications.

[0380] Step 8:

[0381] Users can utilize the provided support by applying for the tasks offered or by applying health and emotional advice to their daily lives. They can also use the community features to interact with other users and share their feelings.

[0382] (Example 2)

[0383] 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".

[0384] As social participation among the elderly increases, there is a need to utilize individual historical data and skills information to find appropriate tasks, to appropriately monitor health conditions and provide effective improvement measures, and to improve cognitive function using conversational information. Furthermore, there is a lack of methods to support mental health based on emotional data, so the development of a new system that comprehensively supports these aspects is necessary.

[0385] 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.

[0386] In this invention, the server includes means for analyzing historical data and skills information provided by the elderly and presenting appropriate tasks based on their work characteristics; means for monitoring the elderly's health status and lifestyle information and providing advice for health improvement; means for analyzing the elderly's conversational information and generating activities to support cognitive function improvement; means for analyzing provided emotional data and generating methods to support mental health; and means for using the generated artificial intelligence model to generate optimal advice and activities as prompts. This enables not only elderly individuals to receive optimal tasks and health improvement measures based on their own data, but also comprehensive support for maintaining their mental health.

[0387] "Historical data" refers to information provided by elderly individuals regarding their past work experience and activity history.

[0388] "Skills information" refers to information about specific abilities and skills possessed by older adults.

[0389] "Job characteristics" refer to the distinctive features and required skills of a particular job or task.

[0390] "Health status" refers to information regarding the physical and mental health of older adults.

[0391] "Lifestyle information" refers to data related to the daily lives of elderly people, including information on diet, exercise, and daily activities.

[0392] "Conversational information" refers to data on the content, tone, and emotions of elderly people's daily conversations.

[0393] "Cognitive function" refers to all the functions that the brain processes, such as memory, attention, and judgment.

[0394] "Emotional data" refers to information about the emotional state and mental responses exhibited by older adults.

[0395] "Mental health" refers to the mental stability and well-being of older adults.

[0396] A "generated artificial intelligence model" is a collection of algorithms that learn from large amounts of data and are used to solve problems and make predictions.

[0397] A "prompt sentence" is an input sentence used to give instructions or questions to artificial intelligence.

[0398] This invention is a system that comprehensively collects and analyzes historical data, skills information, health status, lifestyle information, conversational information, and emotional data of elderly individuals, and provides personalized work suggestions, health improvement measures, and methods to support mental health. This system is primarily composed of a server, terminals, and users.

[0399] First, the user inputs their work history, skills information, health data, and daily conversations and emotional states into the device. The device provides a user-friendly interface, allowing data to be registered through haptic feedback and voice input. For example, the user might input their health checkup results and walking data.

[0400] Next, the device centralizes this data and transmits it to the server while maintaining accuracy and completeness. This communication involves data format conversion and encryption to ensure security. Specific devices that can be used include computer terminals such as tablets and smartphones.

[0401] The server uses data analysis libraries such as Python's Pandas and Scikit-learn to analyze the received data. Based on these analysis results, the generative AI model makes appropriate suggestions. The generative AI model utilizes various algorithms to perform predictions and optimizations. For example, it might suggest volunteer activities at a local education support center to the user. In this case, an example prompt might be, "Please find volunteer activities where you can utilize your education-related skills."

[0402] Furthermore, the emotion engine analyzes the user's emotional state from their everyday conversations using tools such as Hugging Face Transformers and BERT. Based on this, it provides the user with relaxation methods and stress reduction strategies. This system comprehensively supports older adults in maintaining their physical and mental health.

[0403] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0404] Step 1:

[0405] Users input their personal history data, skills information, health data, and daily conversation information into the terminal. The terminal collects and centralizes this data through an interface. Specifically, text and voice data are registered on the input screen of a tablet or smartphone. This input includes work history, recent health check results, and recent conversation content. As a result, all data is aggregated on the terminal and ready to be sent to the server.

[0406] Step 2:

[0407] The terminal sends the collected data to the server. The terminal performs data format conversion and encryption to ensure data accuracy and security. Input is the data entered by the user into the terminal, and output is the data securely transferred to the server. Specific operations include generating and sending data packets.

[0408] Step 3:

[0409] The server analyzes data received from terminals. Data analysis uses Python's Pandas and Scikit-learn libraries, employing statistical methods to evaluate health status and job characteristics. Input is unified data sent from terminals, and output is health assessment and job suitability information as analysis results. Specific operations include data cleaning and statistical evaluation.

[0410] Step 4:

[0411] The server uses a generative AI model to suggest optimal advice and activities to the user based on the analysis results. The AI ​​model learns and optimizes data using various algorithms. The input is the analysis results, and the output is the work options and health improvement measures suggested to the user. Specific operations include pattern recognition and suggestion generation by the AI ​​model.

[0412] Step 5:

[0413] Using an emotion engine, the server analyzes the user's emotional state. It extracts emotions from everyday conversations using Hugging Face Transformers and BERT models. The input is the user's everyday conversation data, and the output is an emotion evaluation and a suggested relaxation method based on it. Specifically, natural language processing and emotion state estimation are performed.

[0414] Step 6:

[0415] The server provides optimal interaction suggestions to facilitate communication between users. It aggregates elderly individuals with shared interests and proposes events and activities. Inputs are past interaction data and shared interests, and output is suggested interaction events. Specific operations include database searching and the use of matching algorithms.

[0416] (Application Example 2)

[0417] 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."

[0418] It is important to effectively utilize the wealth of experience and skills that seniors possess and provide them with opportunities to actively contribute to society. However, current support systems for seniors do not adequately address individual health and emotional states, making it difficult to alleviate the stress and health risks they face. Furthermore, there is a lack of appropriate information to improve the experience when visiting physical stores, making it difficult for seniors to find products and services that are suitable for them.

[0419] 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.

[0420] In this invention, the server includes means for analyzing historical data and abilities provided by elderly individuals and suggesting appropriate tasks based on job characteristics; means for monitoring the health status and biometric data of elderly individuals and providing advice for health improvement; means for analyzing conversational data of elderly individuals and generating activities that support cognitive function improvement; means for analyzing the emotional state of elderly individuals, understanding their mental health status, and suggesting stress reduction measures; means for forming groups to promote interaction among elderly individuals and supporting good communication; and means for visually presenting recommended products and services in a store to elderly individuals using an augmented reality device. This not only facilitates the provision of information to help elderly individuals find the activities and products best suited to them, but also enables individualized support tailored to their health and emotional state.

[0421] "Historical data" refers to information about the work and activities that elderly people have experienced up to that point.

[0422] "Ability" refers to information about specific skills or areas of expertise that older adults possess.

[0423] "Health status" refers to information related to the physical and mental health of older adults.

[0424] "Biometric data" refers to vital signs related to health status and data on physical activity in daily life.

[0425] "Conversation data" refers to information about the words and expressions that elderly people use on a daily basis.

[0426] "Emotional state" refers to information about the mental health and emotional fluctuations of older adults.

[0427] A "group" refers to a group of elderly people who share a particular hobby or interest.

[0428] An "augmented reality device" is a device that overlays digital information onto the real world's field of vision.

[0429] "Recommended products" are products and services selected based on the health condition, hobbies, and interests of elderly individuals.

[0430] To realize this invention, the system consists of three components: a server, a terminal, and a user. The server centrally analyzes the elderly person's historical data, abilities, health status, and conversation data. Based on this, it generates job characteristics, optimal tasks, advice for health improvement, and activities for improving cognitive function. In addition, it utilizes an emotion engine to assess mental health status and propose stress reduction measures on an individual basis.

[0431] The terminal is responsible for collecting data provided by the user and transmitting it to the server. Users input their historical data, abilities, and biometric data through an intuitive interface. The terminal further provides users with visually recommended products based on their health status and interests within the store via augmented reality devices. This process allows users to obtain products and services best suited to their individual health needs.

[0432] For example, when an elderly person with farming experience visits a supermarket, they may receive recommendations for organic foods based on their health condition. In this case, the terminal displays products suitable for the user in real time and provides feedback to support smoother communication.

[0433] As an example of utilizing a generative AI model, the prompt might look like this: "Based on the user's health data and conversational data, suggest the most suitable products and stress relief methods for him. Also, provide advice on how to facilitate communication in stores."

[0434] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0435] Step 1:

[0436] Users input their historical data, abilities, and health status into the terminal via an interface. This input is collected as text or selection-based data. The terminal centralizes this data and sends it to the server in a structured format.

[0437] Step 2:

[0438] The server analyzes received historical data and capabilities, and uses a generative AI model to generate appropriate tasks based on job characteristics. Using prompts, the system queries the AI ​​for optimal tasks and activities, outputting them as job postings and activity suggestions.

[0439] Step 3:

[0440] The server analyzes the user's health status and biometric data to generate specific advice for improving their health. In this process, it analyzes data patterns and suggests exercise and dietary improvements tailored to the user's health condition.

[0441] Step 4:

[0442] The server analyzes conversational data and generates activities to support the user's cognitive function improvement. Using text analysis algorithms, it analyzes cognitive patterns in conversations and outputs specific training programs.

[0443] Step 5:

[0444] Utilizing an emotion engine, the server identifies the user's emotional state from their input data. It detects signs of stress and anxiety and suggests the most appropriate stress relief measures and relaxation methods for each individual user.

[0445] Step 6:

[0446] The terminal visually presents users with recommended products based on their health status and interests within the store via an augmented reality device. It converts recommendation data from the server into a graphical interface and displays it to the user in real time.

[0447] Step 7:

[0448] The server uses a generative AI model to suggest the optimal communication method for the user. An AI assistant, using prompt sentences, outputs advice for better communication and presents it to the user via the terminal.

[0449] 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.

[0450] 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.

[0451] 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.

[0452] [Third Embodiment]

[0453] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0454] 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.

[0455] 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).

[0456] 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.

[0457] 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.

[0458] 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).

[0459] 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.

[0460] 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.

[0461] 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.

[0462] 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.

[0463] 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.

[0464] 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".

[0465] This invention efficiently analyzes the historical data and skill sets accumulated by elderly individuals and provides personalized job and health maintenance advice. The system primarily consists of three components: a server, terminals, and users.

[0466] System Configuration

[0467] Users input their past work history, skill set, and health data via their device. This data reflects the user's daily activities and health status, and may also be automatically retrieved from health management applications or wearable devices.

[0468] The terminal transmits the entered data to the server and then presents the user with feedback and advice from the server. The terminal also functions as a user interface, displaying information in an easy-to-understand manner.

[0469] The server receives historical data and skill sets of elderly individuals transmitted from their terminals and performs analysis using AI. Based on the analysis, it presents a list of appropriate tasks and job postings tailored to the user's job characteristics. The generating AI considers the conditions that will best utilize each user's abilities and customizes the job suggestions accordingly.

[0470] Regarding health data, the server analyzes the information and generates advice for maintaining and improving health. Based on the user's health status, it specifically suggests ways to adjust exercise levels and improve diet.

[0471] Furthermore, conversation data is acquired in text format, and the server analyzes it to suggest activities for improving cognitive function. Based on the content of everyday conversations, it recommends training and thinking activities that are effective in preventing dementia.

[0472] Specific example

[0473] For example, if an elderly former teacher registers as a user, the server analyzes their extensive experience in education and suggests suitable employment opportunities, such as local learning support centers or online educational services. If the elderly person also provides pedometer data, the server uses this to create daily exercise suggestions, providing specific instructions such as light stretching during telework or exercises suitable for commuting.

[0474] In this way, the invention is implemented in a manner that balances social participation and health maintenance by utilizing the diverse data possessed by the elderly.

[0475] The following describes the processing flow.

[0476] Step 1:

[0477] Users open an application on their device and enter their work history, skills, and daily health data. This includes past work experience, professional skills, and exercise data obtained from health apps and wearable devices.

[0478] Step 2:

[0479] The terminal converts the entered data into the appropriate format and sends it to the server. During this process, user data is encrypted according to security protocols.

[0480] Step 3:

[0481] The server registers the data received from the terminal into a database and analyzes the skill set using natural language processing (NLP) technology. This generates a skill map tailored to the user's job characteristics.

[0482] Step 4:

[0483] The server uses the analyzed skill set to match it against a job database and identify suitable tasks and roles for the user. Generative AI then edits this information to construct the optimal options.

[0484] Step 5:

[0485] The server analyzes the user's health data and generates improvement advice for maintaining daily health. Specific suggestions include recommended exercise levels and nutritional management advice.

[0486] Step 6:

[0487] The server analyzes conversational data acquired during everyday conversations. Based on the analysis results, it suggests activities to the user that help maintain and improve cognitive function.

[0488] Step 7:

[0489] The terminal notifies the user of business suggestions and health / cognitive function support advice sent from the server, and displays the information in an easy-to-understand format through the interface.

[0490] Step 8:

[0491] Based on the information received through their devices, users can apply for offered jobs or implement health advice in their daily lives. Furthermore, by engaging in the provided cognitive activities, they can maintain continuous health management.

[0492] (Example 1)

[0493] 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."

[0494] In today's aging society, there is a need for older adults to make the most of their work experience and skills and to promote their social participation. However, there is a lack of adequate systems to accurately analyze the experience and skills of individual older adults and provide appropriate job and health advice. This lack can lead to a decline in the quality of life and social isolation among older adults.

[0495] 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.

[0496] In this invention, the server includes means for acquiring work history, skill sets, and health data entered by elderly individuals via an information processing device; means for analyzing the acquired history data and skill sets and presenting appropriate jobs and job postings based on job characteristics; and means for analyzing health data and generating specific advice for improving and maintaining health. This makes it possible to make the most of the individual experiences of elderly people and provide accurate advice and job suggestions that balance social participation and health maintenance.

[0497] An "information processing device" is a device that receives data entered by a user and sends it to a server for analysis.

[0498] "Work history" refers to data that shows the work experience that individual elderly people have engaged in in the past.

[0499] A "skill set" is data that refers to a collection of skills and abilities that older adults have acquired through their past jobs and experiences.

[0500] "Health data" refers to information that indicates the user's health status, and specifically includes information such as body temperature, blood pressure, and step count.

[0501] A "server" is a central processing unit that receives data transmitted from terminals, performs analysis, and generates proposals.

[0502] "Analysis" is the process of examining acquired data in detail and deriving useful information from it.

[0503] "Job characteristics" refer to the conditions and features required for a particular job, and are the criteria used to select appropriate tasks based on them.

[0504] "Job postings" refer to data indicating employment opportunities related to specific jobs, and are provided to users.

[0505] "Improving health status" refers to initiatives and advice aimed at improving one's current level of health.

[0506] A "communication protocol" is a set of procedures and rules for securely sending and receiving data, and includes encryption.

[0507] This invention provides a system that generates individually tailored job suggestions and health advice using the work history data, skill sets, and health data of elderly individuals. The specific implementation methods are described below.

[0508] Users input data related to their work history, skill set, and health status through a terminal. The terminal is an information processing device, such as a smart device or computer, that collects this data. This data may be entered directly through an input interface, or it may be automatically acquired from health management applications or wearable devices.

[0509] The device securely transmits the collected data to the server. This communication uses protected communication protocols such as SSL / TLS, ensuring data confidentiality.

[0510] The server analyzes the received data using an AI model. Based on work history data and skill sets, the server generates and presents a list of suitable jobs and job postings to the user. Specifically, the generating AI model compares job requirements with the user's skill sets to achieve the best possible match. It also provides specific advice for maintaining and improving health based on health data. For example, it may suggest ways to revise exercise habits or improve dietary habits.

[0511] Furthermore, the server analyzes conversational data and suggests training to improve cognitive function. This is achieved by applying AI-powered natural language processing, suggesting activities based on information obtained from everyday conversations.

[0512] For example, if a user has experience as a "culinary school teacher" and wants to aim for walking 8,000 steps a day, the server will use that data to provide job postings for instructors at local cooking classes and suggest a daily exercise plan. For instance, it might suggest an exercise plan that incorporates moderate stretching while cooking and walking to buy groceries.

[0513] An example of a prompt would be: "Based on the user's past education-related experience, please generate suggestions to help older adults find re-employment. Also, based on the provided pedometer data, please provide exercise advice to maintain health." Through such prompts, the system can provide specific and practical advice.

[0514] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0515] Step 1:

[0516] Users input their work history, skill set, and health data into the device. This process involves entering their past experience and acquired skills, and registering health data through input forms. Data may also be automatically retrieved from wearable devices. The input data is stored as structured data on the device.

[0517] Step 2:

[0518] The terminal transmits all entered data to the server using a secure protocol. This process generates an integrated information packet containing work history, skill sets, and health data, while maintaining data confidentiality using SSL / TLS. The output to the server is transmitted data in a secure and encrypted format.

[0519] Step 3:

[0520] The server uses an AI model to analyze the received data. Specifically, work history and skill sets are analyzed, and data is generated to suggest suitable jobs and job postings for that user. Natural language processing and data mining techniques are used in this analysis. The output is a list of job suggestions for each user.

[0521] Step 4:

[0522] The server analyzes the acquired health data and generates customized advice for maintaining and improving the user's health. In this process, a generative AI model is used for data processing, and specific exercise programs and dietary improvements are designed through data analysis. The output is a personalized health plan.

[0523] Step 5:

[0524] The server collects conversational data, analyzes it through natural language processing, and suggests training to improve cognitive function. Text data obtained from everyday conversations is analyzed, and activities that stimulate thinking and language abilities are selected. The output is a list of recommended cognitive activities, which is presented to the user.

[0525] Step 6:

[0526] The terminal receives results sent from the server and presents them to the user in an easy-to-understand manner. Specifically, it displays job suggestion lists, health advice, and cognitive activity lists on the user interface, allowing the user to easily access the information. The output is information presented to the user as a visual display.

[0527] (Application Example 1)

[0528] 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."

[0529] In an aging society, it is important for older adults to continue participating in society. However, they often fail to fully utilize their abundant experience and skills, leading to social isolation and health problems. Furthermore, there is a lack of appropriate guidelines for tasks that older adults face when working in physical stores, making efficient work difficult.

[0530] 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.

[0531] In this invention, the server includes means for analyzing historical data and technical information provided by the elderly and suggesting appropriate tasks based on job characteristics; means for monitoring the elderly's health status and activity data and providing advice for health improvement; and means for suggesting information to provide assistance for work in physical stores. This enables the elderly to engage in appropriate work, maintain their health, and smoothly carry out work in physical stores.

[0532] "Historical data" refers to records of the jobs and activities that elderly people have performed in the past.

[0533] "Technical information" refers to information that specifically details the skills, knowledge, and qualifications possessed by elderly individuals.

[0534] "Job characteristics" refer to the characteristics of a suitable job for an individual elderly person, based on their experience and technical information.

[0535] "Health status" refers to the physical or mental health condition of an elderly person.

[0536] "Activity data" refers to data that records the daily activities and exercise levels of elderly people.

[0537] "Advice" refers to recommendations for maintaining or improving the health of older adults, based on the analysis results.

[0538] "Business assistance" is a function that provides appropriate guidance and support to elderly people when they are working in a physical store.

[0539] "Means of presenting information" refers to methods used by the server to visually or audibly communicate the results of its analysis to the user.

[0540] This invention constitutes a system for efficiently analyzing historical data, technical information, health status, and activity data possessed by elderly individuals, and for providing appropriate job and health maintenance advice.

[0541] System Configuration

[0542] Users input their historical and technical data into the terminal. This data includes past work experience, technical information, health status, and activity data.

[0543] The terminal is responsible for transmitting the entered information to the server. It also visually presents feedback and advice from the server's analysis results to the user. Smartphones are used as the terminal, offering high convenience.

[0544] The server receives data sent from the terminal and performs analysis using a generated AI model. The analysis utilizes the Python TensorFlow library. The AI ​​model suggests appropriate tasks based on the job characteristics of elderly individuals and analyzes health data to generate advice for maintaining health. Information on business assistance in physical stores is also presented based on the analysis results.

[0545] The system is deployed on Amazon Web Services (AWS) or Google Cloud Platform (GCP), enabling secure data management and highly efficient analysis.

[0546] Specific example

[0547] For example, if a user, Mr. B, an elderly person who was formerly a teacher, enters his work experience into the app, the server analyzes that historical data and suggests employment opportunities at local learning support centers, etc. Conversely, it can also suggest health-maintaining stretching exercises tailored to Mr. B based on his activity data.

[0548] Examples of prompt statements for a generative AI model are as follows:

[0549] Based on the following data, please provide users with advice regarding in-store operations.

[0550] Work experience: 30 years as a teacher in educational institutions.

[0551] Technical information: Educational skills, communication skills.

[0552] Health data: Normal activity steps: 7000 steps / day, blood pressure within the normal range.

[0553] This system allows seniors to maintain their health while contributing to society.

[0554] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0555] Step 1:

[0556] Users input their historical data and technical information into the terminal. This data includes work experience, technical information (skills, qualifications, etc.), health status, and activity data. This creates a dataset that reflects the user's characteristics.

[0557] Step 2:

[0558] The terminal sends the entered information to the server. This communication takes place over the internet. The input dataset is structured in JSON format and sent to the server. This allows the server to receive user characteristic information.

[0559] Step 3:

[0560] The server analyzes the received data. First, the server uses the Python TensorFlow library to input the data into a generated AI model. The purpose of the analysis is to suggest appropriate tasks based on the user's job characteristics. At this stage, the output is information about the most suitable job and work assistance for the user.

[0561] Step 4:

[0562] Simultaneously, the server analyzes health data. This data includes activity levels and health status, and based on this, it generates appropriate health maintenance advice. The output is individually customized health advice, which includes specific exercise suggestions and recommendations for improving dietary habits.

[0563] Step 5:

[0564] The server sends back the business suggestions and health advice it has generated to the terminal. The data is then sent again in JSON format. This allows the terminal to obtain the latest analysis results.

[0565] Step 6:

[0566] The device presents the received information to the user. Here, the suggestions are displayed visually through the device's screen. This presentation helps the user make informed decisions based on comprehensive information.

[0567] Through processing at each step, older adults can appropriately obtain the information they need to make further contributions to society.

[0568] 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.

[0569] This invention combines an emotion engine with a system that comprehensively analyzes the historical data, skill sets, health status, and conversational data of elderly individuals to support the improvement of work, health, and cognitive function in a way that is suitable for them. This system is primarily composed of three components: a server, a terminal, and a user.

[0570] System Configuration

[0571] Users input their work history, skill set, and health data via a device. Furthermore, everyday conversations and feedback are also entered into the device. This allows for the collection of data to understand their emotional state.

[0572] The terminal centralizes this information entered by the user and sends it to the server. The interface is designed to be intuitive for the user to operate.

[0573] The server analyzes the job characteristics, health status, and cognitive function of elderly individuals based on data received from the terminal. Based on these analysis results, the generating AI proposes optimal work, health advice, and cognitive training to the user.

[0574] The newly integrated emotion engine identifies emotional states from user input and conversation data. This allows it to understand the user's mental health and generate personalized stress reduction strategies and relaxation programs. It also analyzes user interactions within the community from an emotional perspective and offers suggestions to promote positive communication.

[0575] Specific example

[0576] For example, suppose an elderly user wants to utilize their existing education-related skills and inputs them into the system. The server analyzes this data and suggests opportunities for volunteer work supporting local education. Also, if the user regularly inputs walking data, the server provides appropriate exercise advice.

[0577] The emotion engine detects signs of stress from the user's daily conversations. Based on this, it suggests relaxation methods and proactive exercise plans to the user. It also provides feedback to help users communicate better with other seniors in the community.

[0578] In this way, the invention is implemented by seamlessly integrating various functions to comprehensively support the physical and psychological health of the elderly.

[0579] The following describes the processing flow.

[0580] Step 1:

[0581] Users input their work history, skill set, health information, and everyday conversations using the device's interface. They can also add emotional feedback and comments during the input process.

[0582] Step 2:

[0583] The terminal organizes user input data and converts it to the appropriate format. The data is then sent to the server using a secure protocol.

[0584] Step 3:

[0585] The server receives the transmitted data and analyzes job characteristics based on historical data and skill sets. Based on these job characteristics, it selects appropriate tasks and matches job postings with user skills.

[0586] Step 4:

[0587] The server analyzes the user's health data and assesses their current health status. Based on this, it generates specific advice and exercise plans for improving their health.

[0588] Step 5:

[0589] The server's emotion engine analyzes user conversation data to identify their current emotional state. It tracks stress levels and emotional changes, and suggests corresponding stress relief methods and relaxation programs.

[0590] Step 6:

[0591] The server sends information generated based on the analysis results to the user's terminal in a format that is easy for the user to understand. This includes business suggestions, health advice, and emotional support.

[0592] Step 7:

[0593] The device receives information from the server and displays it in an easy-to-understand format for the user. If immediate action is required, the user will receive warnings or suggestions via push notifications.

[0594] Step 8:

[0595] Users can utilize the provided support by applying for the tasks offered or by applying health and emotional advice to their daily lives. They can also use the community features to interact with other users and share their feelings.

[0596] (Example 2)

[0597] 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."

[0598] As social participation among the elderly increases, there is a need to utilize individual historical data and skills information to find appropriate tasks, to appropriately monitor health conditions and provide effective improvement measures, and to improve cognitive function using conversational information. Furthermore, there is a lack of methods to support mental health based on emotional data, so the development of a new system that comprehensively supports these aspects is necessary.

[0599] 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.

[0600] In this invention, the server includes means for analyzing historical data and skills information provided by the elderly and presenting appropriate tasks based on their work characteristics; means for monitoring the elderly's health status and lifestyle information and providing advice for health improvement; means for analyzing the elderly's conversational information and generating activities to support cognitive function improvement; means for analyzing provided emotional data and generating methods to support mental health; and means for using the generated artificial intelligence model to generate optimal advice and activities as prompts. This enables not only elderly individuals to receive optimal tasks and health improvement measures based on their own data, but also comprehensive support for maintaining their mental health.

[0601] "Historical data" refers to information provided by elderly individuals regarding their past work experience and activity history.

[0602] "Skills information" refers to information about specific abilities and skills possessed by older adults.

[0603] "Job characteristics" refer to the distinctive features and required skills of a particular job or task.

[0604] "Health status" refers to information regarding the physical and mental health of older adults.

[0605] "Lifestyle information" refers to data related to the daily lives of elderly people, including information on diet, exercise, and daily activities.

[0606] "Conversational information" refers to data on the content, tone, and emotions of elderly people's daily conversations.

[0607] "Cognitive function" refers to all the functions that the brain processes, such as memory, attention, and judgment.

[0608] "Emotional data" refers to information about the emotional state and mental responses exhibited by older adults.

[0609] "Mental health" refers to the mental stability and well-being of older adults.

[0610] A "generated artificial intelligence model" is a collection of algorithms that learn from large amounts of data and are used to solve problems and make predictions.

[0611] A "prompt sentence" is an input sentence used to give instructions or questions to artificial intelligence.

[0612] This invention is a system that comprehensively collects and analyzes historical data, skills information, health status, lifestyle information, conversational information, and emotional data of elderly individuals, and provides personalized work suggestions, health improvement measures, and methods to support mental health. This system is primarily composed of a server, terminals, and users.

[0613] First, the user inputs their work history, skills information, health data, and daily conversations and emotional states into the device. The device provides a user-friendly interface, allowing data to be registered through haptic feedback and voice input. For example, the user might input their health checkup results and walking data.

[0614] Next, the device centralizes this data and transmits it to the server while maintaining accuracy and completeness. This communication involves data format conversion and encryption to ensure security. Specific devices that can be used include computer terminals such as tablets and smartphones.

[0615] The server uses data analysis libraries such as Python's Pandas and Scikit-learn to analyze the received data. Based on these analysis results, the generative AI model makes appropriate suggestions. The generative AI model utilizes various algorithms to perform predictions and optimizations. For example, it might suggest volunteer activities at a local education support center to the user. In this case, an example prompt might be, "Please find volunteer activities where you can utilize your education-related skills."

[0616] Furthermore, the emotion engine analyzes the user's emotional state from their everyday conversations using tools such as Hugging Face Transformers and BERT. Based on this, it provides the user with relaxation methods and stress reduction strategies. This system comprehensively supports older adults in maintaining their physical and mental health.

[0617] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0618] Step 1:

[0619] Users input their personal history data, skills information, health data, and daily conversation information into the terminal. The terminal collects and centralizes this data through an interface. Specifically, text and voice data are registered on the input screen of a tablet or smartphone. This input includes work history, recent health check results, and recent conversation content. As a result, all data is aggregated on the terminal and ready to be sent to the server.

[0620] Step 2:

[0621] The terminal sends the collected data to the server. The terminal performs data format conversion and encryption to ensure data accuracy and security. Input is the data entered by the user into the terminal, and output is the data securely transferred to the server. Specific operations include generating and sending data packets.

[0622] Step 3:

[0623] The server analyzes data received from terminals. Data analysis uses Python's Pandas and Scikit-learn libraries, employing statistical methods to evaluate health status and job characteristics. Input is unified data sent from terminals, and output is health assessment and job suitability information as analysis results. Specific operations include data cleaning and statistical evaluation.

[0624] Step 4:

[0625] The server uses a generative AI model to suggest optimal advice and activities to the user based on the analysis results. The AI ​​model learns and optimizes data using various algorithms. The input is the analysis results, and the output is the work options and health improvement measures suggested to the user. Specific operations include pattern recognition and suggestion generation by the AI ​​model.

[0626] Step 5:

[0627] Using an emotion engine, the server analyzes the user's emotional state. It extracts emotions from everyday conversations using Hugging Face Transformers and BERT models. The input is the user's everyday conversation data, and the output is an emotion evaluation and a suggested relaxation method based on it. Specifically, natural language processing and emotion state estimation are performed.

[0628] Step 6:

[0629] The server provides optimal interaction suggestions to facilitate communication between users. It aggregates elderly individuals with shared interests and proposes events and activities. Inputs are past interaction data and shared interests, and output is suggested interaction events. Specific operations include database searching and the use of matching algorithms.

[0630] (Application Example 2)

[0631] 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."

[0632] It is important to effectively utilize the wealth of experience and skills that seniors possess and provide them with opportunities to actively contribute to society. However, current support systems for seniors do not adequately address individual health and emotional states, making it difficult to alleviate the stress and health risks they face. Furthermore, there is a lack of appropriate information to improve the experience when visiting physical stores, making it difficult for seniors to find products and services that are suitable for them.

[0633] 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.

[0634] In this invention, the server includes means for analyzing historical data and abilities provided by elderly individuals and suggesting appropriate tasks based on job characteristics; means for monitoring the health status and biometric data of elderly individuals and providing advice for health improvement; means for analyzing conversational data of elderly individuals and generating activities that support cognitive function improvement; means for analyzing the emotional state of elderly individuals, understanding their mental health status, and suggesting stress reduction measures; means for forming groups to promote interaction among elderly individuals and supporting good communication; and means for visually presenting recommended products and services in a store to elderly individuals using an augmented reality device. This not only facilitates the provision of information to help elderly individuals find the activities and products best suited to them, but also enables individualized support tailored to their health and emotional state.

[0635] "Historical data" refers to information about the work and activities that elderly people have experienced up to that point.

[0636] "Ability" refers to information about specific skills or areas of expertise that older adults possess.

[0637] "Health status" refers to information related to the physical and mental health of older adults.

[0638] "Biometric data" refers to vital signs related to health status and data on physical activity in daily life.

[0639] "Conversation data" refers to information about the words and expressions that elderly people use on a daily basis.

[0640] "Emotional state" refers to information about the mental health and emotional fluctuations of older adults.

[0641] A "group" refers to a group of elderly people who share a particular hobby or interest.

[0642] An "augmented reality device" is a device that overlays digital information onto the real world's field of vision.

[0643] "Recommended products" are products and services selected based on the health condition, hobbies, and interests of elderly individuals.

[0644] To realize this invention, the system consists of three components: a server, a terminal, and a user. The server centrally analyzes the elderly person's historical data, abilities, health status, and conversation data. Based on this, it generates job characteristics, optimal tasks, advice for health improvement, and activities for improving cognitive function. In addition, it utilizes an emotion engine to assess mental health status and propose stress reduction measures on an individual basis.

[0645] The terminal is responsible for collecting data provided by the user and transmitting it to the server. Users input their historical data, abilities, and biometric data through an intuitive interface. The terminal further provides users with visually recommended products based on their health status and interests within the store via augmented reality devices. This process allows users to obtain products and services best suited to their individual health needs.

[0646] For example, when an elderly person with farming experience visits a supermarket, they may receive recommendations for organic foods based on their health condition. In this case, the terminal displays products suitable for the user in real time and provides feedback to support smoother communication.

[0647] As an example of utilizing a generative AI model, the prompt might look like this: "Based on the user's health data and conversational data, suggest the most suitable products and stress relief methods for him. Also, provide advice on how to facilitate communication in stores."

[0648] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0649] Step 1:

[0650] Users input their historical data, abilities, and health status into the terminal via an interface. This input is collected as text or selection-based data. The terminal centralizes this data and sends it to the server in a structured format.

[0651] Step 2:

[0652] The server analyzes received historical data and capabilities, and uses a generative AI model to generate appropriate tasks based on job characteristics. Using prompts, the system queries the AI ​​for optimal tasks and activities, outputting them as job postings and activity suggestions.

[0653] Step 3:

[0654] The server analyzes the user's health status and biometric data to generate specific advice for improving their health. In this process, it analyzes data patterns and suggests exercise and dietary improvements tailored to the user's health condition.

[0655] Step 4:

[0656] The server analyzes conversational data and generates activities to support the user's cognitive function improvement. Using text analysis algorithms, it analyzes cognitive patterns in conversations and outputs specific training programs.

[0657] Step 5:

[0658] Utilizing an emotion engine, the server identifies the user's emotional state from their input data. It detects signs of stress and anxiety and suggests the most appropriate stress relief measures and relaxation methods for each individual user.

[0659] Step 6:

[0660] The terminal visually presents users with recommended products based on their health status and interests within the store via an augmented reality device. It converts recommendation data from the server into a graphical interface and displays it to the user in real time.

[0661] Step 7:

[0662] The server uses a generative AI model to suggest the optimal communication method for the user. An AI assistant, using prompt sentences, outputs advice for better communication and presents it to the user via the terminal.

[0663] 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.

[0664] 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.

[0665] 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.

[0666] [Fourth Embodiment]

[0667] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0668] 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.

[0669] 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).

[0670] 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.

[0671] 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.

[0672] 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).

[0673] 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.

[0674] 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.

[0675] 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.

[0676] 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.

[0677] 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.

[0678] 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.

[0679] 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".

[0680] This invention efficiently analyzes the historical data and skill sets accumulated by elderly individuals and provides personalized job and health maintenance advice. The system primarily consists of three components: a server, terminals, and users.

[0681] System Configuration

[0682] Users input their past work history, skill set, and health data via their device. This data reflects the user's daily activities and health status, and may also be automatically retrieved from health management applications or wearable devices.

[0683] The terminal transmits the entered data to the server and then presents the user with feedback and advice from the server. The terminal also functions as a user interface, displaying information in an easy-to-understand manner.

[0684] The server receives historical data and skill sets of elderly individuals transmitted from their terminals and performs analysis using AI. Based on the analysis, it presents a list of appropriate tasks and job postings tailored to the user's job characteristics. The generating AI considers the conditions that will best utilize each user's abilities and customizes the job suggestions accordingly.

[0685] Regarding health data, the server analyzes the information and generates advice for maintaining and improving health. Based on the user's health status, it specifically suggests ways to adjust exercise levels and improve diet.

[0686] Furthermore, conversation data is acquired in text format, and the server analyzes it to suggest activities for improving cognitive function. Based on the content of everyday conversations, it recommends training and thinking activities that are effective in preventing dementia.

[0687] Specific example

[0688] For example, if an elderly former teacher registers as a user, the server analyzes their extensive experience in education and suggests suitable employment opportunities, such as local learning support centers or online educational services. If the elderly person also provides pedometer data, the server uses this to create daily exercise suggestions, providing specific instructions such as light stretching during telework or exercises suitable for commuting.

[0689] In this way, the invention is implemented in a manner that balances social participation and health maintenance by utilizing the diverse data possessed by the elderly.

[0690] The following describes the processing flow.

[0691] Step 1:

[0692] Users open an application on their device and enter their work history, skills, and daily health data. This includes past work experience, professional skills, and exercise data obtained from health apps and wearable devices.

[0693] Step 2:

[0694] The terminal converts the entered data into the appropriate format and sends it to the server. During this process, user data is encrypted according to security protocols.

[0695] Step 3:

[0696] The server registers the data received from the terminal into a database and analyzes the skill set using natural language processing (NLP) technology. This generates a skill map tailored to the user's job characteristics.

[0697] Step 4:

[0698] The server uses the analyzed skill set to match it against a job database and identify suitable tasks and roles for the user. Generative AI then edits this information to construct the optimal options.

[0699] Step 5:

[0700] The server analyzes the user's health data and generates improvement advice for maintaining daily health. Specific suggestions include recommended exercise levels and nutritional management advice.

[0701] Step 6:

[0702] The server analyzes conversational data acquired during everyday conversations. Based on the analysis results, it suggests activities to the user that help maintain and improve cognitive function.

[0703] Step 7:

[0704] The terminal notifies the user of business suggestions and health / cognitive function support advice sent from the server, and displays the information in an easy-to-understand format through the interface.

[0705] Step 8:

[0706] Based on the information received through their devices, users can apply for offered jobs or implement health advice in their daily lives. Furthermore, by engaging in the provided cognitive activities, they can maintain continuous health management.

[0707] (Example 1)

[0708] 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".

[0709] In today's aging society, there is a need for older adults to make the most of their work experience and skills and to promote their social participation. However, there is a lack of adequate systems to accurately analyze the experience and skills of individual older adults and provide appropriate job and health advice. This lack can lead to a decline in the quality of life and social isolation among older adults.

[0710] 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.

[0711] In this invention, the server includes means for acquiring work history, skill sets, and health data entered by elderly individuals via an information processing device; means for analyzing the acquired history data and skill sets and presenting appropriate jobs and job postings based on job characteristics; and means for analyzing health data and generating specific advice for improving and maintaining health. This makes it possible to make the most of the individual experiences of elderly people and provide accurate advice and job suggestions that balance social participation and health maintenance.

[0712] An "information processing device" is a device that receives data entered by a user and sends it to a server for analysis.

[0713] "Work history" refers to data that shows the work experience that individual elderly people have engaged in in the past.

[0714] A "skill set" is data that refers to a collection of skills and abilities that older adults have acquired through their past jobs and experiences.

[0715] "Health data" refers to information that indicates the user's health status, and specifically includes information such as body temperature, blood pressure, and step count.

[0716] A "server" is a central processing unit that receives data transmitted from terminals, performs analysis, and generates proposals.

[0717] "Analysis" is the process of examining acquired data in detail and deriving useful information from it.

[0718] "Job characteristics" refer to the conditions and features required for a particular job, and are the criteria used to select appropriate tasks based on them.

[0719] "Job postings" refer to data indicating employment opportunities related to specific jobs, and are provided to users.

[0720] "Improving health status" refers to initiatives and advice aimed at improving one's current level of health.

[0721] A "communication protocol" is a set of procedures and rules for securely sending and receiving data, and includes encryption.

[0722] This invention provides a system that generates individually tailored job suggestions and health advice using the work history data, skill sets, and health data of elderly individuals. The specific implementation methods are described below.

[0723] Users input data related to their work history, skill set, and health status through a terminal. The terminal is an information processing device, such as a smart device or computer, that collects this data. This data may be entered directly through an input interface, or it may be automatically acquired from health management applications or wearable devices.

[0724] The device securely transmits the collected data to the server. This communication uses protected communication protocols such as SSL / TLS, ensuring data confidentiality.

[0725] The server analyzes the received data using an AI model. Based on work history data and skill sets, the server generates and presents a list of suitable jobs and job postings to the user. Specifically, the generating AI model compares job requirements with the user's skill sets to achieve the best possible match. It also provides specific advice for maintaining and improving health based on health data. For example, it may suggest ways to revise exercise habits or improve dietary habits.

[0726] Furthermore, the server analyzes conversational data and suggests training to improve cognitive function. This is achieved by applying AI-powered natural language processing, suggesting activities based on information obtained from everyday conversations.

[0727] For example, if a user has experience as a "culinary school teacher" and wants to aim for walking 8,000 steps a day, the server will use that data to provide job postings for instructors at local cooking classes and suggest a daily exercise plan. For instance, it might suggest an exercise plan that incorporates moderate stretching while cooking and walking to buy groceries.

[0728] An example of a prompt would be: "Based on the user's past education-related experience, please generate suggestions to help older adults find re-employment. Also, based on the provided pedometer data, please provide exercise advice to maintain health." Through such prompts, the system can provide specific and practical advice.

[0729] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0730] Step 1:

[0731] Users input their work history, skill set, and health data into the device. This process involves entering their past experience and acquired skills, and registering health data through input forms. Data may also be automatically retrieved from wearable devices. The input data is stored as structured data on the device.

[0732] Step 2:

[0733] The terminal transmits all entered data to the server using a secure protocol. This process generates an integrated information packet containing work history, skill sets, and health data, while maintaining data confidentiality using SSL / TLS. The output to the server is transmitted data in a secure and encrypted format.

[0734] Step 3:

[0735] The server uses an AI model to analyze the received data. Specifically, work history and skill sets are analyzed, and data is generated to suggest suitable jobs and job postings for that user. Natural language processing and data mining techniques are used in this analysis. The output is a list of job suggestions for each user.

[0736] Step 4:

[0737] The server analyzes the acquired health data and generates customized advice for maintaining and improving the user's health. In this process, a generative AI model is used for data processing, and specific exercise programs and dietary improvements are designed through data analysis. The output is a personalized health plan.

[0738] Step 5:

[0739] The server collects conversational data, analyzes it through natural language processing, and suggests training to improve cognitive function. Text data obtained from everyday conversations is analyzed, and activities that stimulate thinking and language abilities are selected. The output is a list of recommended cognitive activities, which is presented to the user.

[0740] Step 6:

[0741] The terminal receives results sent from the server and presents them to the user in an easy-to-understand manner. Specifically, it displays job suggestion lists, health advice, and cognitive activity lists on the user interface, allowing the user to easily access the information. The output is information presented to the user as a visual display.

[0742] (Application Example 1)

[0743] 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".

[0744] In an aging society, it is important for older adults to continue participating in society. However, they often fail to fully utilize their abundant experience and skills, leading to social isolation and health problems. Furthermore, there is a lack of appropriate guidelines for tasks that older adults face when working in physical stores, making efficient work difficult.

[0745] 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.

[0746] In this invention, the server includes means for analyzing historical data and technical information provided by the elderly and suggesting appropriate tasks based on job characteristics; means for monitoring the elderly's health status and activity data and providing advice for health improvement; and means for suggesting information to provide assistance for work in physical stores. This enables the elderly to engage in appropriate work, maintain their health, and smoothly carry out work in physical stores.

[0747] "Historical data" refers to records of the jobs and activities that elderly people have performed in the past.

[0748] "Technical information" refers to information that specifically details the skills, knowledge, and qualifications possessed by elderly individuals.

[0749] "Job characteristics" refer to the characteristics of a suitable job for an individual elderly person, based on their experience and technical information.

[0750] "Health status" refers to the physical or mental health condition of an elderly person.

[0751] "Activity data" refers to data that records the daily activities and exercise levels of elderly people.

[0752] "Advice" refers to recommendations for maintaining or improving the health of older adults, based on the analysis results.

[0753] "Business assistance" is a function that provides appropriate guidance and support to elderly people when they are working in a physical store.

[0754] "Means of presenting information" refers to methods used by the server to visually or audibly communicate the results of its analysis to the user.

[0755] This invention constitutes a system for efficiently analyzing historical data, technical information, health status, and activity data possessed by elderly individuals, and for providing appropriate job and health maintenance advice.

[0756] System Configuration

[0757] Users input their historical and technical data into the terminal. This data includes past work experience, technical information, health status, and activity data.

[0758] The terminal is responsible for transmitting the entered information to the server. It also visually presents feedback and advice from the server's analysis results to the user. Smartphones are used as the terminal, offering high convenience.

[0759] The server receives data sent from the terminal and performs analysis using a generated AI model. The analysis utilizes the Python TensorFlow library. The AI ​​model suggests appropriate tasks based on the job characteristics of elderly individuals and analyzes health data to generate advice for maintaining health. Information on business assistance in physical stores is also presented based on the analysis results.

[0760] The system is deployed on Amazon Web Services (AWS) or Google Cloud Platform (GCP), enabling secure data management and highly efficient analysis.

[0761] Specific example

[0762] For example, if a user, Mr. B, an elderly person who was formerly a teacher, enters his work experience into the app, the server analyzes that historical data and suggests employment opportunities at local learning support centers, etc. Conversely, it can also suggest health-maintaining stretching exercises tailored to Mr. B based on his activity data.

[0763] Examples of prompt statements for a generative AI model are as follows:

[0764] Based on the following data, please provide users with advice regarding in-store operations.

[0765] Work experience: 30 years as a teacher in educational institutions.

[0766] Technical information: Educational skills, communication skills.

[0767] Health data: Normal activity steps: 7000 steps / day, blood pressure within the normal range.

[0768] This system allows seniors to maintain their health while contributing to society.

[0769] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0770] Step 1:

[0771] Users input their historical data and technical information into the terminal. This data includes work experience, technical information (skills, qualifications, etc.), health status, and activity data. This creates a dataset that reflects the user's characteristics.

[0772] Step 2:

[0773] The terminal sends the entered information to the server. This communication takes place over the internet. The input dataset is structured in JSON format and sent to the server. This allows the server to receive user characteristic information.

[0774] Step 3:

[0775] The server analyzes the received data. First, the server uses the Python TensorFlow library to input the data into a generated AI model. The purpose of the analysis is to suggest appropriate tasks based on the user's job characteristics. At this stage, the output is information about the most suitable job and work assistance for the user.

[0776] Step 4:

[0777] Simultaneously, the server analyzes health data. This data includes activity levels and health status, and based on this, it generates appropriate health maintenance advice. The output is individually customized health advice, which includes specific exercise suggestions and recommendations for improving dietary habits.

[0778] Step 5:

[0779] The server sends back the business suggestions and health advice it has generated to the terminal. The data is then sent again in JSON format. This allows the terminal to obtain the latest analysis results.

[0780] Step 6:

[0781] The device presents the received information to the user. Here, the suggestions are displayed visually through the device's screen. This presentation helps the user make informed decisions based on comprehensive information.

[0782] Through processing at each step, older adults can appropriately obtain the information they need to make further contributions to society.

[0783] 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.

[0784] This invention combines an emotion engine with a system that comprehensively analyzes the historical data, skill sets, health status, and conversational data of elderly individuals to support the improvement of work, health, and cognitive function in a way that is suitable for them. This system is primarily composed of three components: a server, a terminal, and a user.

[0785] System Configuration

[0786] Users input their work history, skill set, and health data via a device. Furthermore, everyday conversations and feedback are also entered into the device. This allows for the collection of data to understand their emotional state.

[0787] The terminal centralizes this information entered by the user and sends it to the server. The interface is designed to be intuitive for the user to operate.

[0788] The server analyzes the job characteristics, health status, and cognitive function of elderly individuals based on data received from the terminal. Based on these analysis results, the generating AI proposes optimal work, health advice, and cognitive training to the user.

[0789] The newly integrated emotion engine identifies emotional states from user input and conversation data. This allows it to understand the user's mental health and generate personalized stress reduction strategies and relaxation programs. It also analyzes user interactions within the community from an emotional perspective and offers suggestions to promote positive communication.

[0790] Specific example

[0791] For example, suppose an elderly user wants to utilize their existing education-related skills and inputs them into the system. The server analyzes this data and suggests opportunities for volunteer work supporting local education. Also, if the user regularly inputs walking data, the server provides appropriate exercise advice.

[0792] The emotion engine detects signs of stress from the user's daily conversations. Based on this, it suggests relaxation methods and proactive exercise plans to the user. It also provides feedback to help users communicate better with other seniors in the community.

[0793] In this way, the invention is implemented by seamlessly integrating various functions to comprehensively support the physical and psychological health of the elderly.

[0794] The following describes the processing flow.

[0795] Step 1:

[0796] Users input their work history, skill set, health information, and everyday conversations using the device's interface. They can also add emotional feedback and comments during the input process.

[0797] Step 2:

[0798] The terminal organizes user input data and converts it to the appropriate format. The data is then sent to the server using a secure protocol.

[0799] Step 3:

[0800] The server receives the transmitted data and analyzes job characteristics based on historical data and skill sets. Based on these job characteristics, it selects appropriate tasks and matches job postings with user skills.

[0801] Step 4:

[0802] The server analyzes the user's health data and assesses their current health status. Based on this, it generates specific advice and exercise plans for improving their health.

[0803] Step 5:

[0804] The server's emotion engine analyzes user conversation data to identify their current emotional state. It tracks stress levels and emotional changes, and suggests corresponding stress relief methods and relaxation programs.

[0805] Step 6:

[0806] The server sends information generated based on the analysis results to the user's terminal in a format that is easy for the user to understand. This includes business suggestions, health advice, and emotional support.

[0807] Step 7:

[0808] The device receives information from the server and displays it in an easy-to-understand format for the user. If immediate action is required, the user will receive warnings or suggestions via push notifications.

[0809] Step 8:

[0810] Users can utilize the provided support by applying for the tasks offered or by applying health and emotional advice to their daily lives. They can also use the community features to interact with other users and share their feelings.

[0811] (Example 2)

[0812] 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".

[0813] As social participation among the elderly increases, there is a need to utilize individual historical data and skills information to find appropriate tasks, to appropriately monitor health conditions and provide effective improvement measures, and to improve cognitive function using conversational information. Furthermore, there is a lack of methods to support mental health based on emotional data, so the development of a new system that comprehensively supports these aspects is necessary.

[0814] 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.

[0815] In this invention, the server includes means for analyzing historical data and skills information provided by the elderly and presenting appropriate tasks based on their work characteristics; means for monitoring the elderly's health status and lifestyle information and providing advice for health improvement; means for analyzing the elderly's conversational information and generating activities to support cognitive function improvement; means for analyzing provided emotional data and generating methods to support mental health; and means for using the generated artificial intelligence model to generate optimal advice and activities as prompts. This enables not only elderly individuals to receive optimal tasks and health improvement measures based on their own data, but also comprehensive support for maintaining their mental health.

[0816] "Historical data" refers to information provided by elderly individuals regarding their past work experience and activity history.

[0817] "Skills information" refers to information about specific abilities and skills possessed by older adults.

[0818] "Job characteristics" refer to the distinctive features and required skills of a particular job or task.

[0819] "Health status" refers to information regarding the physical and mental health of older adults.

[0820] "Lifestyle information" refers to data related to the daily lives of elderly people, including information on diet, exercise, and daily activities.

[0821] "Conversational information" refers to data on the content, tone, and emotions of elderly people's daily conversations.

[0822] "Cognitive function" refers to all the functions that the brain processes, such as memory, attention, and judgment.

[0823] "Emotional data" refers to information about the emotional state and mental responses exhibited by older adults.

[0824] "Mental health" refers to the mental stability and well-being of older adults.

[0825] A "generated artificial intelligence model" is a collection of algorithms that learn from large amounts of data and are used to solve problems and make predictions.

[0826] A "prompt sentence" is an input sentence used to give instructions or questions to artificial intelligence.

[0827] This invention is a system that comprehensively collects and analyzes historical data, skills information, health status, lifestyle information, conversational information, and emotional data of elderly individuals, and provides personalized work suggestions, health improvement measures, and methods to support mental health. This system is primarily composed of a server, terminals, and users.

[0828] First, the user inputs their work history, skills information, health data, and daily conversations and emotional states into the device. The device provides a user-friendly interface, allowing data to be registered through haptic feedback and voice input. For example, the user might input their health checkup results and walking data.

[0829] Next, the device centralizes this data and transmits it to the server while maintaining accuracy and completeness. This communication involves data format conversion and encryption to ensure security. Specific devices that can be used include computer terminals such as tablets and smartphones.

[0830] The server uses data analysis libraries such as Python's Pandas and Scikit-learn to analyze the received data. Based on these analysis results, the generative AI model makes appropriate suggestions. The generative AI model utilizes various algorithms to perform predictions and optimizations. For example, it might suggest volunteer activities at a local education support center to the user. In this case, an example prompt might be, "Please find volunteer activities where you can utilize your education-related skills."

[0831] Furthermore, the emotion engine analyzes the user's emotional state from their everyday conversations using tools such as Hugging Face Transformers and BERT. Based on this, it provides the user with relaxation methods and stress reduction strategies. This system comprehensively supports older adults in maintaining their physical and mental health.

[0832] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0833] Step 1:

[0834] Users input their personal history data, skills information, health data, and daily conversation information into the terminal. The terminal collects and centralizes this data through an interface. Specifically, text and voice data are registered on the input screen of a tablet or smartphone. This input includes work history, recent health check results, and recent conversation content. As a result, all data is aggregated on the terminal and ready to be sent to the server.

[0835] Step 2:

[0836] The terminal sends the collected data to the server. The terminal performs data format conversion and encryption to ensure data accuracy and security. Input is the data entered by the user into the terminal, and output is the data securely transferred to the server. Specific operations include generating and sending data packets.

[0837] Step 3:

[0838] The server analyzes data received from terminals. Data analysis uses Python's Pandas and Scikit-learn libraries, employing statistical methods to evaluate health status and job characteristics. Input is unified data sent from terminals, and output is health assessment and job suitability information as analysis results. Specific operations include data cleaning and statistical evaluation.

[0839] Step 4:

[0840] The server uses a generative AI model to suggest optimal advice and activities to the user based on the analysis results. The AI ​​model learns and optimizes data using various algorithms. The input is the analysis results, and the output is the work options and health improvement measures suggested to the user. Specific operations include pattern recognition and suggestion generation by the AI ​​model.

[0841] Step 5:

[0842] Using an emotion engine, the server analyzes the user's emotional state. It extracts emotions from everyday conversations using Hugging Face Transformers and BERT models. The input is the user's everyday conversation data, and the output is an emotion evaluation and a suggested relaxation method based on it. Specifically, natural language processing and emotion state estimation are performed.

[0843] Step 6:

[0844] The server provides optimal interaction suggestions to facilitate communication between users. It aggregates elderly individuals with shared interests and proposes events and activities. Inputs are past interaction data and shared interests, and output is suggested interaction events. Specific operations include database searching and the use of matching algorithms.

[0845] (Application Example 2)

[0846] 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".

[0847] It is important to effectively utilize the wealth of experience and skills that seniors possess and provide them with opportunities to actively contribute to society. However, current support systems for seniors do not adequately address individual health and emotional states, making it difficult to alleviate the stress and health risks they face. Furthermore, there is a lack of appropriate information to improve the experience when visiting physical stores, making it difficult for seniors to find products and services that are suitable for them.

[0848] 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.

[0849] In this invention, the server includes means for analyzing historical data and abilities provided by elderly individuals and suggesting appropriate tasks based on job characteristics; means for monitoring the health status and biometric data of elderly individuals and providing advice for health improvement; means for analyzing conversational data of elderly individuals and generating activities that support cognitive function improvement; means for analyzing the emotional state of elderly individuals, understanding their mental health status, and suggesting stress reduction measures; means for forming groups to promote interaction among elderly individuals and supporting good communication; and means for visually presenting recommended products and services in a store to elderly individuals using an augmented reality device. This not only facilitates the provision of information to help elderly individuals find the activities and products best suited to them, but also enables individualized support tailored to their health and emotional state.

[0850] "Historical data" refers to information about the work and activities that elderly people have experienced up to that point.

[0851] "Ability" refers to information about specific skills or areas of expertise that older adults possess.

[0852] "Health status" refers to information related to the physical and mental health of older adults.

[0853] "Biometric data" refers to vital signs related to health status and data on physical activity in daily life.

[0854] "Conversation data" refers to information about the words and expressions that elderly people use on a daily basis.

[0855] "Emotional state" refers to information about the mental health and emotional fluctuations of older adults.

[0856] A "group" refers to a group of elderly people who share a particular hobby or interest.

[0857] An "augmented reality device" is a device that overlays digital information onto the real world's field of vision.

[0858] "Recommended products" are products and services selected based on the health condition, hobbies, and interests of elderly individuals.

[0859] To realize this invention, the system consists of three components: a server, a terminal, and a user. The server centrally analyzes the elderly person's historical data, abilities, health status, and conversation data. Based on this, it generates job characteristics, optimal tasks, advice for health improvement, and activities for improving cognitive function. In addition, it utilizes an emotion engine to assess mental health status and propose stress reduction measures on an individual basis.

[0860] The terminal is responsible for collecting data provided by the user and transmitting it to the server. Users input their historical data, abilities, and biometric data through an intuitive interface. The terminal further provides users with visually recommended products based on their health status and interests within the store via augmented reality devices. This process allows users to obtain products and services best suited to their individual health needs.

[0861] For example, when an elderly person with farming experience visits a supermarket, they may receive recommendations for organic foods based on their health condition. In this case, the terminal displays products suitable for the user in real time and provides feedback to support smoother communication.

[0862] As an example of utilizing a generative AI model, the prompt might look like this: "Based on the user's health data and conversational data, suggest the most suitable products and stress relief methods for him. Also, provide advice on how to facilitate communication in stores."

[0863] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0864] Step 1:

[0865] Users input their historical data, abilities, and health status into the terminal via an interface. This input is collected as text or selection-based data. The terminal centralizes this data and sends it to the server in a structured format.

[0866] Step 2:

[0867] The server analyzes received historical data and capabilities, and uses a generative AI model to generate appropriate tasks based on job characteristics. Using prompts, the system queries the AI ​​for optimal tasks and activities, outputting them as job postings and activity suggestions.

[0868] Step 3:

[0869] The server analyzes the user's health status and biometric data to generate specific advice for improving their health. In this process, it analyzes data patterns and suggests exercise and dietary improvements tailored to the user's health condition.

[0870] Step 4:

[0871] The server analyzes conversational data and generates activities to support the user's cognitive function improvement. Using text analysis algorithms, it analyzes cognitive patterns in conversations and outputs specific training programs.

[0872] Step 5:

[0873] Utilizing an emotion engine, the server identifies the user's emotional state from their input data. It detects signs of stress and anxiety and suggests the most appropriate stress relief measures and relaxation methods for each individual user.

[0874] Step 6:

[0875] The terminal visually presents users with recommended products based on their health status and interests within the store via an augmented reality device. It converts recommendation data from the server into a graphical interface and displays it to the user in real time.

[0876] Step 7:

[0877] The server uses a generative AI model to suggest the optimal communication method for the user. An AI assistant, using prompt sentences, outputs advice for better communication and presents it to the user via the terminal.

[0878] 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.

[0879] 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.

[0880] 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 robot 414.

[0881] 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.

[0882] 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.

[0883] 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.

[0884] 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.

[0885] 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.

[0886] 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."

[0887] 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.

[0888] 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.

[0889] 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.

[0890] 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.

[0891] 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.

[0892] 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.

[0893] 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.

[0894] 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.

[0895] 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.

[0896] 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.

[0897] 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.

[0898] 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.

[0899] The following is further disclosed regarding the embodiments described above.

[0900] (Claim 1)

[0901] A means of analyzing the historical data and skill sets provided by elderly individuals and suggesting appropriate tasks based on job characteristics,

[0902] A means of monitoring the health status and lifestyle data of the elderly and providing advice for improving their health,

[0903] A means for analyzing conversational data of elderly people and generating activities that support cognitive function improvement,

[0904] Means of forming communities to promote interaction among the elderly,

[0905] A system that includes this.

[0906] (Claim 2)

[0907] The system according to claim 1, wherein appropriate job assignments based on the aforementioned job characteristics are made by matching job information using a generated structured skill set.

[0908] (Claim 3)

[0909] The system according to claim 1, wherein the community formation is carried out by grouping elderly people who have common skills or interests.

[0910] "Example 1"

[0911] (Claim 1)

[0912] A means of acquiring work history, skill sets, and health data entered by elderly individuals via an information processing device,

[0913] A means of analyzing acquired historical data and skill sets to present appropriate jobs and job postings based on job characteristics,

[0914] A means for analyzing health data and generating specific advice for improving and maintaining health status,

[0915] A means of analyzing conversational data to generate activities that support cognitive function improvement,

[0916] Means of using a protected communication protocol to securely communicate the acquired data,

[0917] A system that includes this.

[0918] (Claim 2)

[0919] The system according to claim 1, wherein appropriate job assignments based on the aforementioned job characteristics are performed by comparing job information using the generated skill set structure.

[0920] (Claim 3)

[0921] The system according to claim 1, wherein the generation of advice for improving and maintaining the aforementioned health condition is carried out by utilizing daily activity data.

[0922] "Application Example 1"

[0923] (Claim 1)

[0924] A means of analyzing historical data and technical information provided by elderly individuals and suggesting appropriate tasks based on their job characteristics,

[0925] A means of monitoring the health status and activity data of the elderly and providing advice for improving their health,

[0926] A means for analyzing the conversation content of elderly people and generating activities that support the improvement of cognitive function,

[0927] A means of providing information to elderly people to assist them with tasks at physical stores,

[0928] A system that includes this.

[0929] (Claim 2)

[0930] The system according to claim 1, wherein appropriate work assignments based on the aforementioned job characteristics are made by matching job information using generated structured technical information.

[0931] (Claim 3)

[0932] The system according to claim 1, wherein the business assistance at the physical store is performed by presenting appropriate business guidelines that take into account the user's past experience.

[0933] "Example 2 of combining an emotion engine"

[0934] (Claim 1)

[0935] A means of analyzing historical data and skills information provided by elderly individuals and suggesting appropriate tasks based on their work characteristics,

[0936] A means of monitoring the health status and lifestyle information of the elderly and providing advice for improving their health,

[0937] A means for analyzing conversational information of the elderly and generating activities that support the improvement of cognitive function,

[0938] Means of forming a community to promote interaction among the elderly,

[0939] A means for analyzing provided emotional data and generating methods to support mental health,

[0940] A system that includes means for generating optimal advice and actions as prompts using a generated artificial intelligence model.

[0941] (Claim 2)

[0942] The system according to claim 1, wherein appropriate work assignments based on the aforementioned work characteristics are made by matching job information using generated structured skills information.

[0943] (Claim 3)

[0944] The system according to claim 1, wherein the formation of the community is carried out by bringing together elderly people who have common skills or interests.

[0945] "Application example 2 when combining with an emotional engine"

[0946] (Claim 1)

[0947] A means of analyzing the historical data and abilities provided by elderly individuals and suggesting appropriate tasks based on job characteristics,

[0948] A means of monitoring the health status and biometric data of elderly people and providing advice for improving their health,

[0949] A means for analyzing conversational data of the elderly and generating activities that support cognitive function improvement,

[0950] A method for analyzing the emotional state of elderly people, understanding their mental health, and proposing stress reduction measures,

[0951] Forming groups to promote interaction among the elderly and providing means to support good communication,

[0952] A means of visually presenting recommended products and services to the elderly in a store using augmented reality devices,

[0953] A system that includes this.

[0954] (Claim 2)

[0955] The system according to claim 1, wherein appropriate work assignments based on the aforementioned job characteristics are made by matching job information with a generated structured competency set.

[0956] (Claim 3)

[0957] The system according to claim 1, wherein the group formation is carried out by grouping elderly people who have common abilities or interests. [Explanation of symbols]

[0958] 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 the historical data and skill sets provided by elderly individuals and suggesting appropriate tasks based on job characteristics, A means of monitoring the health status and lifestyle data of the elderly and providing advice for improving their health, A means for analyzing conversational data of elderly people and generating activities that support cognitive function improvement, Means of forming communities to promote interaction among the elderly, A system that includes this.

2. The system according to claim 1, wherein appropriate job assignments based on the aforementioned job characteristics are made by matching job information using a generated structured skill set.

3. The system according to claim 1, wherein the community formation is carried out by grouping elderly people who have common skills or interests.

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