system

Abstract

The system according to this embodiment aims to provide appropriate work and consultation services based on the skills, experience, and health status of elderly individuals, and to propose flexible work arrangements. [Solution] The system according to this embodiment comprises an understanding unit, a provision unit, a proposal unit, and a community unit. The understanding unit understands the skills, experience, and health status of elderly people. The provision unit provides appropriate work and consultation content based on the information understood by the understanding unit. The proposal unit proposes flexible work arrangements that take into account physical limitations and lifestyle rhythms based on the information provided by the provision unit. The community unit provides a community function that allows people to share their experiences and problems with each other.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a persona chatbot control method performed by at least one processor, including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a 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

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In the conventional technology, appropriate jobs and consultation contents based on the skills, experience, and health status of the elderly are not sufficiently provided, and there is room for improvement.

[0005] The system according to the embodiment aims to provide appropriate jobs and consultation contents based on the skills, experience, and health status of the elderly and propose a flexible work form.

Means for Solving the Problems

[0006] ​The system according to this embodiment comprises an understanding unit, a provision unit, a proposal unit, and a community unit. The understanding unit understands the skills, experience, and health status of elderly people. The provision unit provides appropriate work and consultation content based on the information understood by the understanding unit. The proposal unit proposes flexible work arrangements that take into account physical limitations and lifestyle rhythms based on the information provided by the provision unit. The community unit provides a community function that allows people to share their experiences and problems with each other. [Effects of the Invention]

[0007] The system according to this embodiment can provide appropriate work and consultation services based on the skills, experience, and health condition of elderly individuals, and can also propose flexible work arrangements. [Brief explanation of the drawing]

[0008] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10]This shows an emotion map where multiple emotions are mapped. [Modes for carrying out the invention]

[0009] Hereinafter, an example of an embodiment of the system relating to the technology of this disclosure will be described with reference to the attached drawings.

[0010] First, let's explain the terminology used in the following explanation.

[0011] In the following embodiments, the signed processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Furthermore, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include CPU (Central Processing Unit), GPU (Graphics Processing Unit), GPGPU (General-Purpose computing on Graphics Processing Units), APU (Accelerated Processing Unit), or TPU (Tensor Processing Unit).

[0012] In the following embodiments, signed RAM (Random Access Memory) is a memory that temporarily stores information and is used as work memory by the processor.

[0013] In the following embodiments, the signed storage is one or more non-volatile storage devices that store various programs and various parameters. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes.

[0014] In the following embodiments, the labeled communication I / F (Interface) is an interface including a communication processor, an antenna, and the like. The communication I / F controls communication between a plurality of computers. Examples of communication standards applied to the communication I / F include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0015] 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 only A, only B, or a combination of A and B. Also, in this specification, when expressing three or more matters connected by "and / or", the same concept as "A and / or B" is applied.

[0016] [First Embodiment] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0017] As shown in FIG. 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.

[0018] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. Also, the database 24 and the communication I / F 26 are connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0019] 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.

[0020] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, and accepts user input. The touch panel 38A accepts user input via touch by detecting contact with an object (e.g., a pen or finger). The microphone 38B accepts user input via voice 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 unit 12. In the data processing unit 12, the specific processing unit 290 (see Figure 2) acquires the data indicating the user input.

[0021] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user by outputting the data in a form perceptible to the user (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.

[0022] 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.

[0023] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0024] 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.

[0025] 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. The identification processing unit 290 can estimate the user's emotions using the emotion identification model 59 and perform identification processing using the user's emotions. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotions, including but not limited to these examples. Furthermore, emotion estimation and prediction also include, for example, emotion analysis.

[0026] In the smart device 14, specific processing is performed by the processor 46. The storage 50 stores a specific processing program 60. The specific processing program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as a control unit 46A according to the specific processing program 60 executed on the RAM 48. The smart device 14 also has a data generation model 58 and an emotion identification model 59, similar to the data generation model and emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0027] Furthermore, other devices besides the data processing device 12 may also have the data generation model 58. For example, a server device (e.g., a generation server) may have the data generation model 58. In this case, the data processing device 12 obtains processing results (such as prediction results) using the data generation model 58 by communicating with the server device having the data generation model 58. The data processing device 12 may also be a server device or a terminal device owned by a user (e.g., a mobile phone, robot, home appliance, etc.). Next, an example of processing by the data processing system 10 according to the first embodiment will be described.

[0028] (Example of form 1) The integrated AI agent service according to an embodiment of the present invention is a system that provides comprehensive support for seniors, covering their careers, health, learning, and daily lives. This system provides personalized support tailored to the individual needs of seniors, promoting self-realization and social participation. For example, the integrated AI agent service uses a generating AI to understand the skills, experience, and health status of seniors and provide appropriate work and consultation options. It also proposes flexible work arrangements that take into account physical limitations and lifestyle rhythms. Furthermore, it provides a community function that allows seniors to share their experiences and problems, promoting interaction among seniors. This creates an environment where seniors can remain active throughout their lives. For example, the integrated AI agent service uses a generating AI to analyze seniors' past work history and health data, providing support tailored to individual needs. For seniors with specific skills, it proposes jobs that utilize those skills. It also provides appropriate advice based on their health status. Furthermore, the integrated AI agent service proposes flexible work arrangements that take into account physical limitations and lifestyle rhythms. For example, it proposes part-time work or telecommuting for seniors who lack physical strength. It also provides an environment where they can work comfortably by setting work hours that match their lifestyle rhythms. Furthermore, the integrated AI agent service provides a community function that allows seniors to share their experiences and problems. For example, it can provide a space where seniors with similar hobbies can interact and support each other. It can also reduce feelings of loneliness among seniors by creating an environment where they can easily seek advice on health and work-related matters. This creates opportunities for seniors to remain active throughout their lives. Seniors can contribute to society by utilizing their skills and experience. They can also live with peace of mind by receiving appropriate support tailored to their health condition. Furthermore, through community functions, they can lead fulfilling lives while supporting each other. In this way, the integrated AI agent service can broadly support seniors' careers, health, learning, and daily lives, promoting self-realization and social participation.

[0029] The integrated AI agent service according to this embodiment comprises an understanding unit, a provision unit, a proposal unit, and a community unit. The understanding unit understands the skills, experience, and health status of elderly individuals. The understanding unit analyzes, for example, the elderly individual's past work history and health data. The understanding unit uses generative AI to analyze past work history and health data and provides support tailored to individual needs. For example, the understanding unit analyzes the elderly individual's resume and medical records to grasp specific skills and health status. The understanding unit uses generative AI to analyze past work history and health data and proposes jobs that can utilize the skills of elderly individuals with specific skills. The provision unit provides appropriate jobs and consultations based on the information understood by the understanding unit. For example, the provision unit proposes jobs that can utilize the skills of elderly individuals with specific skills. The provision unit uses generative AI to propose jobs that can utilize the skills of elderly individuals with specific skills. For example, the provision unit proposes remote work to elderly individuals with IT skills. The provision unit uses generative AI to provide appropriate advice according to health status. For example, the Provision Department provides exercise recommendations and dietary advice. The Proposal Department, based on the information provided by the Provision Department, proposes flexible work arrangements that take into account physical limitations and lifestyle rhythms. For example, the Proposal Department proposes part-time work or telecommuting for elderly people who are not confident in their physical strength. The Proposal Department uses generative AI to propose part-time work or telecommuting for elderly people who are not confident in their physical strength. For example, the Proposal Department proposes working 4 hours a day or working entirely from home. The Proposal Department uses generative AI to set work hours that match lifestyle rhythms. For example, the Proposal Department proposes morning work or evening work. The Community Department provides community functions where people can share their experiences and problems with each other. For example, the Community Department provides a place where elderly people with the same hobbies can interact with each other. The Community Department uses generative AI to provide a place where elderly people with the same hobbies can interact with each other. For example, the Community Department provides online groups and hobby circles. The Community Department uses generative AI to create an environment where people can easily consult about health and work. For example, the Community Department provides online chat and telephone consultations.As a result, the integrated AI agent service according to this embodiment can provide comprehensive support for the careers, health, learning, and daily lives of elderly people, promoting self-realization and social participation.

[0030] The Understanding Unit understands the skills, experience, and health status of elderly individuals. For example, it analyzes their past work history and health data. Specifically, it collects the elderly's resumes and medical records and analyzes this data using generative AI. The generative AI utilizes natural language processing technology to understand the content of the resumes and extract past work experience and acquired skills. Regarding medical records, the generative AI analyzes electronic medical records and health checkup results to understand their health status and medical history. For example, the Understanding Unit analyzes the resume of an elderly person who previously worked in the IT industry to identify their programming and system administration skills. At the same time, it analyzes medical records to understand their health status, such as diabetes and hypertension. This allows the Understanding Unit to comprehensively understand the elderly's skills and health status and provide support tailored to their individual needs. Furthermore, the Understanding Unit also uses generative AI to analyze the elderly's lifestyle habits and hobbies. For example, it analyzes the content of their social media and blog posts to identify their hobbies and interests. This allows for a deeper understanding of the elderly's overall profile and builds a foundation for providing individualized support. The Understanding Department plays a crucial role in centrally managing this data and collaborating with other departments to provide services that meet the needs of the elderly.

[0031] The service provider department provides appropriate jobs and consultations based on the information understood by the understanding department. Specifically, the service provider department uses generative AI to suggest jobs and advice tailored to the skills and health status of elderly individuals. For example, for elderly individuals with IT skills, remote work jobs are suggested. The generative AI analyzes job postings and identifies jobs that match the skill set of elderly individuals. Furthermore, the service provider department also provides advice tailored to their health status. For example, for elderly individuals who do not get enough exercise, moderate exercise is recommended, and a specific exercise plan is proposed. Dietary advice is also provided to support a healthy lifestyle. The service provider department uses generative AI to personalize this advice and make specific suggestions tailored to the lifestyle of elderly individuals. For example, for elderly individuals with diabetes, a meal plan that helps manage blood sugar levels is proposed, and for elderly individuals who have an exercise habit, more effective exercise methods are suggested. The service provider department provides this information to elderly individuals in an easy-to-understand manner and supports them in an easy-to-implement way. Furthermore, the service provider department uses generative AI to collect feedback from elderly individuals and continuously improve the quality of the services provided. For example, the service provider department analyzes the elderly individuals' reactions to the jobs and advice provided and revises the suggestions as needed. This allows the service provider to offer optimal support to the elderly and improve their quality of life.

[0032] The Proposal Department proposes flexible work arrangements that take into account physical limitations and lifestyles, based on information provided by the Service Provider Department. Specifically, the Proposal Department uses generative AI to propose work arrangements tailored to the physical strength and lifestyle of elderly individuals. For example, for elderly individuals who lack confidence in their physical strength, it proposes part-time work or telecommuting. The generative AI analyzes the health data and lifestyle habits of elderly individuals to identify optimal working hours and work arrangements. For example, it proposes a 4-hour workday or full telecommuting, creating an environment where elderly individuals can work without undue strain. It also sets working hours to match lifestyles. For example, it proposes early morning work for early risers and night shifts for night owls. The Proposal Department uses generative AI to personalize these proposals, providing flexible work arrangements that meet the needs of elderly individuals. Furthermore, the Proposal Department collects feedback from elderly individuals to continuously improve the accuracy of its proposals. For example, it analyzes the elderly individuals' reactions to the proposed work arrangements and revises working hours and arrangements as needed. This allows the Proposal Department to provide elderly individuals with the optimal work arrangements and improve their ease of work. The Proposal Department plays a crucial role in enabling elderly individuals to continue participating in society and achieve self-realization.

[0033] The Community Department provides community features that allow seniors to share their experiences and problems with each other. Specifically, the Community Department uses generative AI to provide a space where seniors with similar hobbies can interact. For example, it provides online groups and hobby circles, allowing seniors to deepen their connections through shared interests. The generative AI analyzes seniors' hobbies and interests and suggests appropriate groups and circles. Furthermore, the Community Department creates an environment where seniors can easily seek advice on health and work-related matters. For example, it provides online chat and telephone consultations, giving seniors a place to easily seek advice. The generative AI analyzes the content of the consultation and provides appropriate advice and information. For example, it provides advice from medical professionals for health-related consultations and advice from career advisors for work-related consultations. Through these functions, the Community Department supports seniors in avoiding isolation and maintaining connections with society. Furthermore, the Community Department collects feedback from seniors and continuously improves the quality of its community features. For example, it analyzes seniors' reactions to the provided groups and circles and adds new groups and circles as needed. In this way, the Community Department can provide seniors with the optimal place for interaction and improve their quality of life. The Community Department plays a crucial role in enabling seniors to achieve self-realization and continue their social participation.

[0034] The understanding unit can analyze the past work history and health data of elderly individuals. For example, the understanding unit can analyze the elderly individual's resume and medical records. The understanding unit uses generative AI to analyze past work history and health data and provide support tailored to individual needs. For example, the understanding unit can analyze the elderly individual's resume to identify specific skills. The understanding unit can also analyze medical records to understand their health status. This allows the understanding unit to provide support tailored to individual needs by analyzing the elderly individual's past work history and health data. Some or all of the above processing in the understanding unit may be performed using generative AI, or it may be performed without generative AI. For example, the understanding unit can input the elderly individual's resume into the generative AI, which can then analyze the resume and extract specific skills.

[0035] The service provider can propose jobs that utilize the skills of elderly individuals who possess specific skills. For example, the service provider can propose remote work to elderly individuals with IT skills. The service provider can use generative AI to propose jobs that utilize the skills of elderly individuals who possess specific skills. For example, the service provider can propose jobs producing and selling handicrafts to elderly individuals with handicraft skills. The service provider can also propose online education jobs to elderly individuals with educational skills. In this way, by proposing jobs that utilize the skills of elderly individuals who possess specific skills, self-realization is promoted. Some or all of the above processing in the service provider may be performed using generative AI, or it may be performed without generative AI. For example, the service provider can input the skills information of elderly individuals into generative AI, and the generative AI can analyze the skills information and propose appropriate jobs.

[0036] The service provider can provide appropriate advice tailored to the individual's health condition. For example, it can recommend exercise and provide dietary advice. The service provider uses generative AI to provide appropriate advice tailored to the individual's health condition. For example, the service provider can suggest an appropriate exercise program to an elderly person who is not getting enough exercise. The service provider can also suggest a nutritionally balanced diet to an elderly person whose diet is unbalanced. By providing appropriate advice tailored to their health condition, the elderly can live with peace of mind. Some or all of the above processing in the service provider may be performed using generative AI, or it may be performed without using generative AI. For example, the service provider can input the elderly person's health data into a generative AI, which can then analyze the health data and provide appropriate advice.

[0037] The proposal department can propose part-time work or telecommuting to elderly people who lack confidence in their physical strength. For example, the proposal department could propose working four hours a day or working entirely from home. The proposal department uses generative AI to propose part-time work or telecommuting to elderly people who lack confidence in their physical strength. For example, the proposal department could propose part-time work three days a week to elderly people who lack confidence in their physical strength. The proposal department can also propose jobs that can be done from home. In this way, by proposing part-time work or telecommuting to elderly people who lack confidence in their physical strength, an environment in which they can work without strain is provided. Some or all of the above processing in the proposal department may be performed using generative AI or not. For example, the proposal department can input the physical strength data of elderly people into the generative AI, and the generative AI can analyze the physical strength data and propose an appropriate work arrangement.

[0038] The proposal unit can set working hours that match the individual's lifestyle. For example, the proposal unit can suggest morning or evening work schedules. The proposal unit uses a generation AI to set working hours that match the individual's lifestyle. For example, the proposal unit can suggest morning work hours for an elderly person who is a morning person. It can also suggest afternoon work hours for an elderly person who is a night owl. This provides an environment in which elderly people can work without strain by setting working hours that match their lifestyle. Some or all of the above processing in the proposal unit may be performed using a generation AI, or it may be performed without a generation AI. For example, the proposal unit can input the elderly person's lifestyle data into a generation AI, and the generation AI can analyze the lifestyle data to set appropriate working hours.

[0039] The Community Department can provide a space where elderly people with similar hobbies can interact with each other. For example, the Community Department can provide online groups or hobby clubs. The Community Department can use generative AI to provide a space where elderly people with similar hobbies can interact with each other. For example, the Community Department can provide online groups where elderly people with hobbies such as handicrafts or gardening can interact with each other. The Community Department can also provide a space where elderly people can interact directly with each other through hobby clubs. By providing a space where elderly people with similar hobbies can interact, they can help each other. Some or all of the above processing in the Community Department may be performed using generative AI or not. For example, the Community Department can input information about the hobbies of elderly people into the generative AI, and the generative AI can analyze the hobby information and suggest appropriate places for interaction.

[0040] The Community Department can create an environment where people can easily seek advice on health and work-related matters. For example, the Community Department can provide online chat and telephone consultations. The Community Department uses generative AI to create an environment where people can easily seek advice on health and work-related matters. For example, the Community Department can accept health-related consultations via online chat. The Community Department can also accept work-related consultations via telephone. By creating an environment where people can easily seek advice on health and work-related matters, the Community Department can reduce feelings of loneliness among the elderly. Some or all of the above-mentioned processes in the Community Department may be performed using generative AI, or they may not be performed using generative AI. For example, the Community Department can input the content of an elderly person's consultation into a generative AI, which can then analyze the content and provide appropriate advice.

[0041] The understanding unit can analyze the hobbies and interests of elderly individuals in addition to their past work history and health data to gain a more comprehensive understanding. For example, the understanding unit can collect information on elderly individuals' hobbies and understand the skills and experience related to those hobbies. The understanding unit uses generative AI to analyze the hobbies and interests of elderly individuals in addition to their past work history and health data to gain a more comprehensive understanding. For example, the understanding unit can analyze the interests of elderly individuals and suggest appropriate jobs and activities based on those interests. The understanding unit can also combine the elderly individual's past work history and hobbies to grasp their overall skill set. This allows for a more comprehensive understanding and the provision of appropriate support by analyzing the hobbies and interests of elderly individuals. Some or all of the above processing in the understanding unit may be performed using generative AI, or it may be performed without generative AI. For example, the understanding unit can input the elderly individual's hobby information into the generative AI, which can then analyze the hobby information and provide appropriate support.

[0042] The understanding unit can deepen its understanding of individual needs by considering the living environment and family structure of elderly individuals. For example, the understanding unit can analyze the living environment of elderly individuals and evaluate their suitability for commuting or working from home. The understanding unit uses generative AI to deepen its understanding of individual needs by considering the living environment and family structure of elderly individuals. For example, the understanding unit considers the family structure of elderly individuals and proposes work arrangements when family support is needed. The understanding unit can also understand the daily rhythm of elderly individuals and propose work arrangements that are not too strenuous. In this way, by considering the living environment and family structure of elderly individuals, it is possible to deepen the understanding of individual needs and provide appropriate support. Some or all of the above processing in the understanding unit may be performed using generative AI, or it may be performed without using generative AI. For example, the understanding unit can input elderly individuals' living environment data into the generative AI, and the generative AI can analyze the living environment data to provide appropriate support.

[0043] The understanding unit can understand region-specific needs by considering the geographical location information of elderly people. For example, the understanding unit can analyze the characteristics of the area where elderly people live and propose region-specific jobs and activities. The understanding unit uses generative AI to understand region-specific needs by considering the geographical location information of elderly people. For example, the understanding unit can provide local health services and support based on the geographical location information of elderly people. The understanding unit can also understand the culture and customs of the area where elderly people live and provide appropriate advice. In this way, by considering the geographical location information of elderly people, region-specific needs can be understood and appropriate support can be provided. Some or all of the above processing in the understanding unit may be performed using generative AI or not. For example, the understanding unit can input the geographical location information of elderly people into the generative AI, and the generative AI can analyze the geographical location information to understand region-specific needs.

[0044] The understanding unit can analyze the social media activities of elderly individuals and understand their online activity status. For example, the understanding unit can analyze the content of elderly individuals' social media posts to grasp their interests and concerns. The understanding unit uses generative AI to analyze the social media activities of elderly individuals and understand their online activity status. For example, the understanding unit can understand the online interactions of elderly individuals and suggest appropriate communities. The understanding unit can also analyze the frequency of elderly individuals' social media activity and provide online support. In this way, by analyzing the social media activities of elderly individuals, their online activity status can be understood and appropriate support can be provided. Some or all of the above processing in the understanding unit may be performed using generative AI or not. For example, the understanding unit can input elderly individuals' social media data into a generative AI, which can then analyze the social media data to understand their online activity status.

[0045] The service provider can incorporate past success stories and feedback from other elderly individuals into the jobs and consultations it offers. For example, the service provider can offer similar jobs and consultations based on past success stories of elderly individuals. The service provider can use generative AI to incorporate past success stories and feedback from other elderly individuals into the jobs and consultations it offers. For example, the service provider can provide appropriate advice by referring to feedback from other elderly individuals. The service provider can also analyze past success stories of elderly individuals and propose the most suitable jobs and consultations. This allows for the provision of more appropriate support by incorporating past success stories and feedback from other elderly individuals. Some or all of the above processes in the service provider may be performed using generative AI, or they may not be performed using generative AI. For example, the service provider can input data on elderly individuals' success stories into a generative AI, which can then analyze the success story data to provide appropriate jobs and consultations.

[0046] The service provider can incorporate the latest market trends and technological trends into the information it provides. For example, the service provider can provide jobs and consultations suitable for the elderly based on the latest market trends. The service provider can use generative AI to incorporate the latest market trends and technological trends into the information it provides. For example, the service provider can incorporate the latest technological trends and provide advice suitable for the elderly. The service provider can also analyze market trends and technological trends and provide information that is optimal for the elderly. This allows for more appropriate support to be provided by incorporating the latest market trends and technological trends. Some or all of the above processing in the service provider may be performed using generative AI, or it may be performed without using generative AI. For example, the service provider can input market trend data into generative AI, and the generative AI can analyze the market trend data and provide appropriate information.

[0047] The service provider can consider local characteristics and culture when determining the types of jobs and consultations offered. For example, the service provider can analyze the characteristics of the area where an elderly person lives and propose jobs and activities specific to that area. The service provider can use generative AI to consider local characteristics and culture when determining the types of jobs and consultations offered. For example, the service provider can understand the culture and customs of the area where an elderly person lives and provide appropriate advice. The service provider can also consider local characteristics and culture to provide jobs and consultations that are best suited to the elderly person. This allows for the provision of more appropriate support by considering local characteristics and culture. Some or all of the above processing in the service provider may be performed using generative AI, or it may be performed without generative AI. For example, the service provider can input local characteristic data into generative AI, which can then analyze the local characteristic data to provide appropriate jobs and consultations.

[0048] The service provider can include the success stories and advice of other elderly individuals in the information it provides. For example, the service provider can provide similar work or consultation content based on the success stories of other elderly individuals. The service provider can use generative AI to include the success stories and advice of other elderly individuals in the information it provides. For example, the service provider can provide appropriate advice by referring to the advice of other elderly individuals. The service provider can also analyze the success stories and advice of elderly individuals to provide optimal information. By including the success stories and advice of other elderly individuals, more appropriate support can be provided. Some or all of the above processing in the service provider may be performed using generative AI, or it may be performed without generative AI. For example, the service provider can input data on elderly individuals' success stories into a generative AI, and the generative AI can analyze the success story data to provide appropriate information.

[0049] The proposal unit can incorporate past work history and performance data into the proposed work arrangements. For example, the proposal unit can propose an optimal work arrangement based on an elderly person's past work history. The proposal unit uses generative AI to incorporate past work history and performance data into the proposed work arrangements. For example, the proposal unit can analyze an elderly person's performance data and propose an appropriate work arrangement. The proposal unit can also combine the elderly person's past work history and performance data to propose a comprehensive work arrangement. This allows for the proposal of a more appropriate work arrangement by incorporating past work history and performance data. Some or all of the above processing in the proposal unit may be performed using generative AI, or it may be performed without using generative AI. For example, the proposal unit can input an elderly person's work history data into a generative AI, which can then analyze the work history data and propose an appropriate work arrangement.

[0050] The proposal department can incorporate the latest labor laws and health guidelines into the proposed work arrangements. For example, the proposal department can propose work arrangements suitable for the elderly based on the latest labor laws. The proposal department uses generative AI to incorporate the latest labor laws and health guidelines into the proposed work arrangements. For example, the proposal department can incorporate the latest health guidelines and provide advice suitable for the elderly. The proposal department can also analyze labor laws and health guidelines and propose the most suitable work arrangements for the elderly. This allows for the proposal of more appropriate work arrangements by incorporating the latest labor laws and health guidelines. Some or all of the above processing in the proposal department may be performed using generative AI, or it may be performed without generative AI. For example, the proposal department can input labor law data into the generative AI, which can then analyze the labor law data and propose appropriate work arrangements.

[0051] The proposal unit can consider the local labor market and employment situation when proposing work arrangements. For example, the proposal unit can analyze the labor market in the area where the elderly person lives and propose a work arrangement specific to that area. The proposal unit uses generative AI to consider the local labor market and employment situation when proposing work arrangements. For example, the proposal unit can understand the employment situation in the area where the elderly person lives and propose an appropriate work arrangement. The proposal unit can also consider the local labor market and employment situation and propose a work arrangement that is optimal for the elderly person. This allows for the proposal of a more appropriate work arrangement by considering the local labor market and employment situation. Some or all of the above processing in the proposal unit may be performed using generative AI, or it may be performed without using generative AI. For example, the proposal unit can input local labor market data into the generative AI, which can then analyze the labor market data and propose an appropriate work arrangement.

[0052] The proposal department can include success stories and advice from other elderly individuals in the proposed work arrangements. For example, the proposal department can propose similar work arrangements based on the success stories of other elderly individuals. The proposal department can use generative AI to include success stories and advice from other elderly individuals in the proposed work arrangements. For example, the proposal department can propose appropriate work arrangements by referring to the advice of other elderly individuals. The proposal department can also analyze success stories and advice from elderly individuals to propose the optimal work arrangement. This allows for the proposal of more appropriate work arrangements by including success stories and advice from other elderly individuals. Some or all of the above processing in the proposal department may be performed using generative AI, or it may be performed without generative AI. For example, the proposal department can input data on success stories from elderly individuals into the generative AI, which can then analyze the success story data to propose appropriate work arrangements.

[0053] The Community Department can incorporate past interaction history and feedback into community functions. For example, the Community Department can propose optimal community functions based on an elderly person's past interaction history. The Community Department uses generative AI to incorporate past interaction history and feedback into community functions. For example, the Community Department provides appropriate community functions by referring to feedback from elderly people. The Community Department can also provide comprehensive community functions by combining the elderly person's past interaction history and feedback. This allows for more appropriate support to be provided by incorporating past interaction history and feedback. Some or all of the above processing in the Community Department may be performed using generative AI or not. For example, the Community Department can input elderly people's interaction history data into a generative AI, which can then analyze the interaction history data to provide appropriate community functions.

[0054] The Community Department can incorporate the latest communication tools and platforms into its community functions. For example, the Community Department can provide community functions suitable for the elderly based on the latest communication tools. The Community Department can use generative AI to incorporate the latest communication tools and platforms into its community functions. For example, the Community Department can incorporate the latest platforms and provide advice suitable for the elderly. The Community Department can also analyze communication tools and platforms and provide community functions that are optimal for the elderly. This allows for the provision of more appropriate support by incorporating the latest communication tools and platforms. Some or all of the above-described processes in the Community Department may be performed using generative AI or not. For example, the Community Department can input communication tool data into a generative AI, which can then analyze the tool data to provide appropriate community functions.

[0055] The Community Department can consider local characteristics and culture when developing community functions. For example, the Community Department can analyze the characteristics of the area where elderly people live and provide community functions specific to that area. The Community Department uses generative AI to consider local characteristics and culture when developing community functions. For example, the Community Department can understand the culture and customs of the area where elderly people live and provide appropriate community functions. The Community Department can also consider local characteristics and culture to provide community functions that are optimal for elderly people. This allows for the provision of more appropriate support by considering local characteristics and culture. Some or all of the above-described processes in the Community Department may be performed using generative AI or not. For example, the Community Department can input local characteristic data into a generative AI, which can then analyze the characteristic data and provide appropriate community functions.

[0056] The Community Department can include the success stories and advice of other elderly people in its community functions. For example, the Community Department can provide similar community functions based on the success stories of other elderly people. The Community Department can use generative AI to include the success stories and advice of other elderly people in its community functions. For example, the Community Department can provide appropriate community functions by referring to the advice of other elderly people. The Community Department can also analyze the success stories and advice of elderly people and provide optimal community functions. This allows for more appropriate support by including the success stories and advice of other elderly people. Some or all of the above processing in the Community Department may be performed using generative AI or not. For example, the Community Department can input elderly people's success story data into generative AI, and the generative AI can analyze the success story data to provide appropriate community functions.

[0057] The system according to the embodiment is not limited to the example described above, and various modifications are possible, for example, as follows.

[0058] The service provider can incorporate past success stories and feedback from other elderly individuals into the work and consultations they offer. For example, they can offer similar work or consultations based on past successes of elderly individuals. They can also provide appropriate advice by referring to feedback from other elderly individuals. Furthermore, they can analyze past success stories of elderly individuals and propose the most suitable work or consultations. In this way, by incorporating past success stories and feedback from other elderly individuals, they can provide more appropriate support.

[0059] The proposal department can incorporate the latest labor laws and health guidelines into the proposed work arrangements. For example, it can propose work arrangements suitable for older workers based on the latest labor laws. It can also incorporate the latest health guidelines and provide advice suitable for older workers. Furthermore, it can analyze labor laws and health guidelines and propose work arrangements that are optimal for older workers. In this way, by incorporating the latest labor laws and health guidelines, it can propose more appropriate work arrangements.

[0060] The Community Department can incorporate the latest communication tools and platforms into its community functions. For example, it can provide community functions tailored to seniors based on the latest communication tools. It can also incorporate the latest platforms to provide advice tailored to seniors. Furthermore, it can analyze communication tools and platforms to provide community functions that are optimal for seniors. In this way, by incorporating the latest communication tools and platforms, more appropriate support can be provided.

[0061] The understanding unit can understand the specific needs of a region by considering the geographical location information of elderly people. For example, it can analyze the characteristics of the area where elderly people live and propose region-specific jobs and activities. It can also provide local health services and support based on the geographical location information of elderly people. Furthermore, it can understand the culture and customs of the area where elderly people live and provide appropriate advice. In this way, by considering the geographical location information of elderly people, it is possible to understand region-specific needs and provide appropriate support.

[0062] The understanding unit can analyze the social media activities of older adults and understand their online activity status. For example, it can analyze the content of older adults' social media posts to understand their interests and concerns. It can also understand their online interactions and suggest appropriate communities. Furthermore, it can analyze the frequency of older adults' social media activity and provide online support. In this way, by analyzing the social media activities of older adults, it is possible to understand their online activity status and provide appropriate support.

[0063] The following briefly describes the processing flow for example form 1.

[0064] Step 1: The Understanding Unit understands the skills, experience, and health status of older adults. For example, it analyzes older adults' past work history and health data, and uses generated AI to provide support tailored to individual needs. Specifically, it analyzes resumes and medical records to understand specific skills and health conditions. Step 2: The provisioning unit provides appropriate work or consultation based on the information understood by the understanding unit. For example, it proposes work that can utilize the skills of elderly people with specific skills and provides appropriate advice tailored to their health condition using generated AI. Specifically, it may propose remote work to elderly people with IT skills and provide recommendations for exercise and dietary advice. Step 3: Based on the information provided by the Provider Department, the Proposal Department proposes flexible work arrangements that take into account physical limitations, lifestyle rhythms, etc. For example, for elderly individuals who are not confident in their physical strength, the Proposal Department proposes short-time work or telecommuting, and uses AI generation to set work hours that match their lifestyle rhythm. Specifically, it proposes 4-hour workdays, full telecommuting, early morning work, or evening work. Step 4: The Community Department will provide community features that allow people to share their experiences and problems. For example, it will provide a space where seniors with the same hobbies can interact, and create an environment where they can easily consult about health and work using AI-generated messages. Specifically, it will provide online groups, hobby circles, online chat, and telephone consultations.

[0065] (Example of form 2) The integrated AI agent service according to an embodiment of the present invention is a system that provides comprehensive support for seniors, covering their careers, health, learning, and daily lives. This system provides personalized support tailored to the individual needs of seniors, promoting self-realization and social participation. For example, the integrated AI agent service uses a generating AI to understand the skills, experience, and health status of seniors and provide appropriate work and consultation options. It also proposes flexible work arrangements that take into account physical limitations and lifestyle rhythms. Furthermore, it provides a community function that allows seniors to share their experiences and problems, promoting interaction among seniors. This creates an environment where seniors can remain active throughout their lives. For example, the integrated AI agent service uses a generating AI to analyze seniors' past work history and health data, providing support tailored to individual needs. For seniors with specific skills, it proposes jobs that utilize those skills. It also provides appropriate advice based on their health status. Furthermore, the integrated AI agent service proposes flexible work arrangements that take into account physical limitations and lifestyle rhythms. For example, it proposes part-time work or telecommuting for seniors who lack physical strength. It also provides an environment where they can work comfortably by setting work hours that match their lifestyle rhythms. Furthermore, the integrated AI agent service provides a community function that allows seniors to share their experiences and problems. For example, it can provide a space where seniors with similar hobbies can interact and support each other. It can also reduce feelings of loneliness among seniors by creating an environment where they can easily seek advice on health and work-related matters. This creates opportunities for seniors to remain active throughout their lives. Seniors can contribute to society by utilizing their skills and experience. They can also live with peace of mind by receiving appropriate support tailored to their health condition. Furthermore, through community functions, they can lead fulfilling lives while supporting each other. In this way, the integrated AI agent service can broadly support seniors' careers, health, learning, and daily lives, promoting self-realization and social participation.

[0066] The integrated AI agent service according to this embodiment comprises an understanding unit, a provision unit, a proposal unit, and a community unit. The understanding unit understands the skills, experience, and health status of elderly individuals. The understanding unit analyzes, for example, the elderly individual's past work history and health data. The understanding unit uses generative AI to analyze past work history and health data and provides support tailored to individual needs. For example, the understanding unit analyzes the elderly individual's resume and medical records to grasp specific skills and health status. The understanding unit uses generative AI to analyze past work history and health data and proposes jobs that can utilize the skills of elderly individuals with specific skills. The provision unit provides appropriate jobs and consultations based on the information understood by the understanding unit. For example, the provision unit proposes jobs that can utilize the skills of elderly individuals with specific skills. The provision unit uses generative AI to propose jobs that can utilize the skills of elderly individuals with specific skills. For example, the provision unit proposes remote work to elderly individuals with IT skills. The provision unit uses generative AI to provide appropriate advice according to health status. For example, the Provision Department provides exercise recommendations and dietary advice. The Proposal Department, based on the information provided by the Provision Department, proposes flexible work arrangements that take into account physical limitations and lifestyle rhythms. For example, the Proposal Department proposes part-time work or telecommuting for elderly people who are not confident in their physical strength. The Proposal Department uses generative AI to propose part-time work or telecommuting for elderly people who are not confident in their physical strength. For example, the Proposal Department proposes working 4 hours a day or working entirely from home. The Proposal Department uses generative AI to set work hours that match lifestyle rhythms. For example, the Proposal Department proposes morning work or evening work. The Community Department provides community functions where people can share their experiences and problems with each other. For example, the Community Department provides a place where elderly people with the same hobbies can interact with each other. The Community Department uses generative AI to provide a place where elderly people with the same hobbies can interact with each other. For example, the Community Department provides online groups and hobby circles. The Community Department uses generative AI to create an environment where people can easily consult about health and work. For example, the Community Department provides online chat and telephone consultations.As a result, the integrated AI agent service according to this embodiment can provide comprehensive support for the careers, health, learning, and daily lives of elderly people, promoting self-realization and social participation.

[0067] The Understanding Unit understands the skills, experience, and health status of elderly individuals. For example, it analyzes their past work history and health data. Specifically, it collects the elderly's resumes and medical records and analyzes this data using generative AI. The generative AI utilizes natural language processing technology to understand the content of the resumes and extract past work experience and acquired skills. Regarding medical records, the generative AI analyzes electronic medical records and health checkup results to understand their health status and medical history. For example, the Understanding Unit analyzes the resume of an elderly person who previously worked in the IT industry to identify their programming and system administration skills. At the same time, it analyzes medical records to understand their health status, such as diabetes and hypertension. This allows the Understanding Unit to comprehensively understand the elderly's skills and health status and provide support tailored to their individual needs. Furthermore, the Understanding Unit also uses generative AI to analyze the elderly's lifestyle habits and hobbies. For example, it analyzes the content of their social media and blog posts to identify their hobbies and interests. This allows for a deeper understanding of the elderly's overall profile and builds a foundation for providing individualized support. The Understanding Department plays a crucial role in centrally managing this data and collaborating with other departments to provide services that meet the needs of the elderly.

[0068] The service provider department provides appropriate jobs and consultations based on the information understood by the understanding department. Specifically, the service provider department uses generative AI to suggest jobs and advice tailored to the skills and health status of elderly individuals. For example, for elderly individuals with IT skills, remote work jobs are suggested. The generative AI analyzes job postings and identifies jobs that match the skill set of elderly individuals. Furthermore, the service provider department also provides advice tailored to their health status. For example, for elderly individuals who do not get enough exercise, moderate exercise is recommended, and a specific exercise plan is proposed. Dietary advice is also provided to support a healthy lifestyle. The service provider department uses generative AI to personalize this advice and make specific suggestions tailored to the lifestyle of elderly individuals. For example, for elderly individuals with diabetes, a meal plan that helps manage blood sugar levels is proposed, and for elderly individuals who have an exercise habit, more effective exercise methods are suggested. The service provider department provides this information to elderly individuals in an easy-to-understand manner and supports them in an easy-to-implement way. Furthermore, the service provider department uses generative AI to collect feedback from elderly individuals and continuously improve the quality of the services provided. For example, the service provider department analyzes the elderly individuals' reactions to the jobs and advice provided and revises the suggestions as needed. This allows the service provider to offer optimal support to the elderly and improve their quality of life.

[0069] The Proposal Department proposes flexible work arrangements that take into account physical limitations and lifestyles, based on information provided by the Service Provider Department. Specifically, the Proposal Department uses generative AI to propose work arrangements tailored to the physical strength and lifestyle of elderly individuals. For example, for elderly individuals who lack confidence in their physical strength, it proposes part-time work or telecommuting. The generative AI analyzes the health data and lifestyle habits of elderly individuals to identify optimal working hours and work arrangements. For example, it proposes a 4-hour workday or full telecommuting, creating an environment where elderly individuals can work without undue strain. It also sets working hours to match lifestyles. For example, it proposes early morning work for early risers and night shifts for night owls. The Proposal Department uses generative AI to personalize these proposals, providing flexible work arrangements that meet the needs of elderly individuals. Furthermore, the Proposal Department collects feedback from elderly individuals to continuously improve the accuracy of its proposals. For example, it analyzes the elderly individuals' reactions to the proposed work arrangements and revises working hours and arrangements as needed. This allows the Proposal Department to provide elderly individuals with the optimal work arrangements and improve their ease of work. The Proposal Department plays a crucial role in enabling elderly individuals to continue participating in society and achieve self-realization.

[0070] The Community Department provides community features that allow seniors to share their experiences and problems with each other. Specifically, the Community Department uses generative AI to provide a space where seniors with similar hobbies can interact. For example, it provides online groups and hobby circles, allowing seniors to deepen their connections through shared interests. The generative AI analyzes seniors' hobbies and interests and suggests appropriate groups and circles. Furthermore, the Community Department creates an environment where seniors can easily seek advice on health and work-related matters. For example, it provides online chat and telephone consultations, giving seniors a place to easily seek advice. The generative AI analyzes the content of the consultation and provides appropriate advice and information. For example, it provides advice from medical professionals for health-related consultations and advice from career advisors for work-related consultations. Through these functions, the Community Department supports seniors in avoiding isolation and maintaining connections with society. Furthermore, the Community Department collects feedback from seniors and continuously improves the quality of its community features. For example, it analyzes seniors' reactions to the provided groups and circles and adds new groups and circles as needed. In this way, the Community Department can provide seniors with the optimal place for interaction and improve their quality of life. The Community Department plays a crucial role in enabling seniors to achieve self-realization and continue their social participation.

[0071] The understanding unit can analyze the past work history and health data of elderly individuals. For example, the understanding unit can analyze the elderly individual's resume and medical records. The understanding unit uses generative AI to analyze past work history and health data and provide support tailored to individual needs. For example, the understanding unit can analyze the elderly individual's resume to identify specific skills. The understanding unit can also analyze medical records to understand their health status. This allows the understanding unit to provide support tailored to individual needs by analyzing the elderly individual's past work history and health data. Some or all of the above processing in the understanding unit may be performed using generative AI, or it may be performed without generative AI. For example, the understanding unit can input the elderly individual's resume into the generative AI, which can then analyze the resume and extract specific skills.

[0072] The service provider can propose jobs that utilize the skills of elderly individuals who possess specific skills. For example, the service provider can propose remote work to elderly individuals with IT skills. The service provider can use generative AI to propose jobs that utilize the skills of elderly individuals who possess specific skills. For example, the service provider can propose jobs producing and selling handicrafts to elderly individuals with handicraft skills. The service provider can also propose online education jobs to elderly individuals with educational skills. In this way, by proposing jobs that utilize the skills of elderly individuals who possess specific skills, self-realization is promoted. Some or all of the above processing in the service provider may be performed using generative AI, or it may be performed without generative AI. For example, the service provider can input the skills information of elderly individuals into generative AI, and the generative AI can analyze the skills information and propose appropriate jobs.

[0073] The service provider can provide appropriate advice tailored to the individual's health condition. For example, it can recommend exercise and provide dietary advice. The service provider uses generative AI to provide appropriate advice tailored to the individual's health condition. For example, the service provider can suggest an appropriate exercise program to an elderly person who is not getting enough exercise. The service provider can also suggest a nutritionally balanced diet to an elderly person whose diet is unbalanced. By providing appropriate advice tailored to their health condition, the elderly can live with peace of mind. Some or all of the above processing in the service provider may be performed using generative AI, or it may be performed without using generative AI. For example, the service provider can input the elderly person's health data into a generative AI, which can then analyze the health data and provide appropriate advice.

[0074] The proposal department can propose part-time work or telecommuting to elderly people who lack confidence in their physical strength. For example, the proposal department could propose working four hours a day or working entirely from home. The proposal department uses generative AI to propose part-time work or telecommuting to elderly people who lack confidence in their physical strength. For example, the proposal department could propose part-time work three days a week to elderly people who lack confidence in their physical strength. The proposal department can also propose jobs that can be done from home. In this way, by proposing part-time work or telecommuting to elderly people who lack confidence in their physical strength, an environment in which they can work without strain is provided. Some or all of the above processing in the proposal department may be performed using generative AI or not. For example, the proposal department can input the physical strength data of elderly people into the generative AI, and the generative AI can analyze the physical strength data and propose an appropriate work arrangement.

[0075] The proposal unit can set working hours that match the individual's lifestyle. For example, the proposal unit can suggest morning or evening work schedules. The proposal unit uses a generation AI to set working hours that match the individual's lifestyle. For example, the proposal unit can suggest morning work hours for an elderly person who is a morning person. It can also suggest afternoon work hours for an elderly person who is a night owl. This provides an environment in which elderly people can work without strain by setting working hours that match their lifestyle. Some or all of the above processing in the proposal unit may be performed using a generation AI, or it may be performed without a generation AI. For example, the proposal unit can input the elderly person's lifestyle data into a generation AI, and the generation AI can analyze the lifestyle data to set appropriate working hours.

[0076] The Community Department can provide a space where elderly people with similar hobbies can interact with each other. For example, the Community Department can provide online groups or hobby clubs. The Community Department can use generative AI to provide a space where elderly people with similar hobbies can interact with each other. For example, the Community Department can provide online groups where elderly people with hobbies such as handicrafts or gardening can interact with each other. The Community Department can also provide a space where elderly people can interact directly with each other through hobby clubs. By providing a space where elderly people with similar hobbies can interact, they can help each other. Some or all of the above processing in the Community Department may be performed using generative AI or not. For example, the Community Department can input information about the hobbies of elderly people into the generative AI, and the generative AI can analyze the hobby information and suggest appropriate places for interaction.

[0077] The Community Department can create an environment where people can easily seek advice on health and work-related matters. For example, the Community Department can provide online chat and telephone consultations. The Community Department uses generative AI to create an environment where people can easily seek advice on health and work-related matters. For example, the Community Department can accept health-related consultations via online chat. The Community Department can also accept work-related consultations via telephone. By creating an environment where people can easily seek advice on health and work-related matters, the Community Department can reduce feelings of loneliness among the elderly. Some or all of the above-mentioned processes in the Community Department may be performed using generative AI, or they may not be performed using generative AI. For example, the Community Department can input the content of an elderly person's consultation into a generative AI, which can then analyze the content and provide appropriate advice.

[0078] The understanding unit can estimate the emotions of older adults and adjust its understanding of skills and experiences based on the estimated emotions. For example, if an older adult is feeling anxious, the understanding unit's generative AI will ask questions in a gentle tone, allowing them to talk about their skills and experiences in a relaxed state. The understanding unit uses generative AI to estimate the emotions of older adults and adjusts its understanding of skills and experiences based on the estimated emotions. For example, if an older adult is confident, the understanding unit's generative AI will ask detailed questions to delve deeper into specific skills and experiences. Also, if an older adult is tired, the understanding unit's generative AI will ask concise questions to gather necessary information in a short time. This allows for more appropriate support by adjusting the understanding of skills and experiences based on the emotions of older adults. Emotion estimation is achieved using an emotion estimation function, for example, an emotion engine or generative AI. Generative AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the understanding unit may be performed using or without generative AI. For example, the understanding unit can input emotional data from elderly individuals into a generating AI, which can then analyze the emotional data and adjust its approach to understanding skills and experience.

[0079] The understanding unit can analyze the hobbies and interests of elderly individuals in addition to their past work history and health data to gain a more comprehensive understanding. For example, the understanding unit can collect information on elderly individuals' hobbies and understand the skills and experience related to those hobbies. The understanding unit uses generative AI to analyze the hobbies and interests of elderly individuals in addition to their past work history and health data to gain a more comprehensive understanding. For example, the understanding unit can analyze the interests of elderly individuals and suggest appropriate jobs and activities based on those interests. The understanding unit can also combine the elderly individual's past work history and hobbies to grasp their overall skill set. This allows for a more comprehensive understanding and the provision of appropriate support by analyzing the hobbies and interests of elderly individuals. Some or all of the above processing in the understanding unit may be performed using generative AI, or it may be performed without generative AI. For example, the understanding unit can input the elderly individual's hobby information into the generative AI, which can then analyze the hobby information and provide appropriate support.

[0080] The understanding unit can deepen its understanding of individual needs by considering the living environment and family structure of elderly individuals. For example, the understanding unit can analyze the living environment of elderly individuals and evaluate their suitability for commuting or working from home. The understanding unit uses generative AI to deepen its understanding of individual needs by considering the living environment and family structure of elderly individuals. For example, the understanding unit considers the family structure of elderly individuals and proposes work arrangements when family support is needed. The understanding unit can also understand the daily rhythm of elderly individuals and propose work arrangements that are not too strenuous. In this way, by considering the living environment and family structure of elderly individuals, it is possible to deepen the understanding of individual needs and provide appropriate support. Some or all of the above processing in the understanding unit may be performed using generative AI, or it may be performed without using generative AI. For example, the understanding unit can input elderly individuals' living environment data into the generative AI, and the generative AI can analyze the living environment data to provide appropriate support.

[0081] The understanding unit can estimate the emotions of elderly individuals and determine the priority of information to be understood based on the estimated emotions. For example, if an elderly individual is stressed, the understanding unit will prioritize providing information that promotes relaxation through the generative AI. The understanding unit uses the generative AI to estimate the emotions of elderly individuals and determines the priority of information to be understood based on the estimated emotions. For example, if an elderly individual is agitated, the understanding unit will prioritize providing detailed information through the generative AI. The understanding unit can also prioritize providing concise information through the generative AI if an elderly individual is tired. This allows for the provision of more appropriate information by prioritizing information based on the emotions of elderly individuals. Emotion estimation is achieved using an emotion estimation function, for example, with an emotion engine or generative AI. The generative AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above-described processes in the understanding unit may be performed using the generative AI or not. For example, the understanding unit can input elderly individuals' emotion data into the generative AI, which can then analyze the emotion data to determine the priority of information.

[0082] The understanding unit can understand region-specific needs by considering the geographical location information of elderly people. For example, the understanding unit can analyze the characteristics of the area where elderly people live and propose region-specific jobs and activities. The understanding unit uses generative AI to understand region-specific needs by considering the geographical location information of elderly people. For example, the understanding unit can provide local health services and support based on the geographical location information of elderly people. The understanding unit can also understand the culture and customs of the area where elderly people live and provide appropriate advice. In this way, by considering the geographical location information of elderly people, region-specific needs can be understood and appropriate support can be provided. Some or all of the above processing in the understanding unit may be performed using generative AI or not. For example, the understanding unit can input the geographical location information of elderly people into the generative AI, and the generative AI can analyze the geographical location information to understand region-specific needs.

[0083] The understanding unit can analyze the social media activities of elderly individuals and understand their online activity status. For example, the understanding unit can analyze the content of elderly individuals' social media posts to grasp their interests and concerns. The understanding unit uses generative AI to analyze the social media activities of elderly individuals and understand their online activity status. For example, the understanding unit can understand the online interactions of elderly individuals and suggest appropriate communities. The understanding unit can also analyze the frequency of elderly individuals' social media activity and provide online support. In this way, by analyzing the social media activities of elderly individuals, their online activity status can be understood and appropriate support can be provided. Some or all of the above processing in the understanding unit may be performed using generative AI or not. For example, the understanding unit can input elderly individuals' social media data into a generative AI, which can then analyze the social media data to understand their online activity status.

[0084] The service provider can estimate the emotions of elderly individuals and adjust the way the work or consultation content is presented based on the estimated emotions. For example, if an elderly individual is feeling anxious, the service provider's generating AI will present the work or consultation content in a gentle tone. The service provider uses the generating AI to estimate the emotions of elderly individuals and adjust the way the work or consultation content is presented based on the estimated emotions. For example, if an elderly individual is confident, the service provider's generating AI will provide detailed information and specific advice. Also, if an elderly individual is tired, the service provider's generating AI can provide concise information and necessary support in a short amount of time. In this way, by adjusting the way the work or consultation content is presented based on the emotions of elderly individuals, more appropriate support can be provided. Emotion estimation is achieved using an emotion estimation function, for example, using an emotion engine or a generating AI. The generating AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the service provider may be performed using a generating AI or not. For example, the service provider can input emotional data from elderly individuals into a generating AI, which can then analyze the data and adjust the way work-related or consultation topics are expressed.

[0085] The service provider can incorporate past success stories and feedback from other elderly individuals into the jobs and consultations it offers. For example, the service provider can offer similar jobs and consultations based on past success stories of elderly individuals. The service provider can use generative AI to incorporate past success stories and feedback from other elderly individuals into the jobs and consultations it offers. For example, the service provider can provide appropriate advice by referring to feedback from other elderly individuals. The service provider can also analyze past success stories of elderly individuals and propose the most suitable jobs and consultations. This allows for the provision of more appropriate support by incorporating past success stories and feedback from other elderly individuals. Some or all of the above processes in the service provider may be performed using generative AI, or they may not be performed using generative AI. For example, the service provider can input data on elderly individuals' success stories into a generative AI, which can then analyze the success story data to provide appropriate jobs and consultations.

[0086] The service provider can incorporate the latest market trends and technological trends into the information it provides. For example, the service provider can provide jobs and consultations suitable for the elderly based on the latest market trends. The service provider can use generative AI to incorporate the latest market trends and technological trends into the information it provides. For example, the service provider can incorporate the latest technological trends and provide advice suitable for the elderly. The service provider can also analyze market trends and technological trends and provide information that is optimal for the elderly. This allows for more appropriate support to be provided by incorporating the latest market trends and technological trends. Some or all of the above processing in the service provider may be performed using generative AI, or it may be performed without using generative AI. For example, the service provider can input market trend data into generative AI, and the generative AI can analyze the market trend data and provide appropriate information.

[0087] The information provider can estimate the emotions of elderly individuals and prioritize the information to be provided based on the estimated emotions. For example, if an elderly individual is stressed, the generating AI will prioritize providing information that promotes relaxation. The information provider uses the generating AI to estimate the emotions of elderly individuals and prioritize the information to be provided based on the estimated emotions. For example, if an elderly individual is agitated, the generating AI will prioritize providing detailed information. Alternatively, if an elderly individual is tired, the generating AI can prioritize providing concise information. By prioritizing the information to be provided based on the emotions of elderly individuals, more appropriate information can be provided. Emotion estimation is achieved using an emotion estimation function, such as an emotion engine or a generating AI. The generating AI is, but is not limited to, a text generation AI (e.g., LLM) or a multimodal generation AI. Some or all of the above-described processes in the information provider may be performed using the generating AI or not. For example, the information provider can input elderly individuals' emotion data into the generating AI, which can then analyze the emotion data to determine the priority of the information.

[0088] The service provider can consider local characteristics and culture when determining the types of jobs and consultations offered. For example, the service provider can analyze the characteristics of the area where an elderly person lives and propose jobs and activities specific to that area. The service provider can use generative AI to consider local characteristics and culture when determining the types of jobs and consultations offered. For example, the service provider can understand the culture and customs of the area where an elderly person lives and provide appropriate advice. The service provider can also consider local characteristics and culture to provide jobs and consultations that are best suited to the elderly person. This allows for the provision of more appropriate support by considering local characteristics and culture. Some or all of the above processing in the service provider may be performed using generative AI, or it may be performed without generative AI. For example, the service provider can input local characteristic data into generative AI, which can then analyze the local characteristic data to provide appropriate jobs and consultations.

[0089] The service provider can include the success stories and advice of other elderly individuals in the information it provides. For example, the service provider can provide similar work or consultation content based on the success stories of other elderly individuals. The service provider can use generative AI to include the success stories and advice of other elderly individuals in the information it provides. For example, the service provider can provide appropriate advice by referring to the advice of other elderly individuals. The service provider can also analyze the success stories and advice of elderly individuals to provide optimal information. By including the success stories and advice of other elderly individuals, more appropriate support can be provided. Some or all of the above processing in the service provider may be performed using generative AI, or it may be performed without generative AI. For example, the service provider can input data on elderly individuals' success stories into a generative AI, and the generative AI can analyze the success story data to provide appropriate information.

[0090] The suggestion unit can estimate the emotions of elderly individuals and adjust the way it presents suggested work arrangements based on those estimated emotions. For example, if an elderly individual is feeling anxious, the suggestion unit's generating AI will suggest work arrangements in a gentle tone. The suggestion unit uses the generating AI to estimate the emotions of elderly individuals and adjust the way it presents suggested work arrangements based on those estimated emotions. For example, if an elderly individual is confident, the suggestion unit's generating AI will provide detailed information and suggest specific work arrangements. Also, if an elderly individual is tired, the suggestion unit's generating AI can provide concise information and offer necessary support in a short amount of time. This allows for more appropriate support to be provided by adjusting the way suggested work arrangements are presented based on the emotions of elderly individuals. Emotion estimation is achieved using an emotion estimation function, such as an emotion engine or a generating AI. The generating AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above-described processes in the suggestion unit may be performed using or without a generating AI. For example, the proposal department can input emotional data of elderly people into a generating AI, which can then analyze the emotional data and adjust how work patterns are expressed.

[0091] The proposal unit can incorporate past work history and performance data into the proposed work arrangements. For example, the proposal unit can propose an optimal work arrangement based on an elderly person's past work history. The proposal unit uses generative AI to incorporate past work history and performance data into the proposed work arrangements. For example, the proposal unit can analyze an elderly person's performance data and propose an appropriate work arrangement. The proposal unit can also combine the elderly person's past work history and performance data to propose a comprehensive work arrangement. This allows for the proposal of a more appropriate work arrangement by incorporating past work history and performance data. Some or all of the above processing in the proposal unit may be performed using generative AI, or it may be performed without using generative AI. For example, the proposal unit can input an elderly person's work history data into a generative AI, which can then analyze the work history data and propose an appropriate work arrangement.

[0092] The proposal department can incorporate the latest labor laws and health guidelines into the proposed work arrangements. For example, the proposal department can propose work arrangements suitable for the elderly based on the latest labor laws. The proposal department uses generative AI to incorporate the latest labor laws and health guidelines into the proposed work arrangements. For example, the proposal department can incorporate the latest health guidelines and provide advice suitable for the elderly. The proposal department can also analyze labor laws and health guidelines and propose the most suitable work arrangements for the elderly. This allows for the proposal of more appropriate work arrangements by incorporating the latest labor laws and health guidelines. Some or all of the above processing in the proposal department may be performed using generative AI, or it may be performed without generative AI. For example, the proposal department can input labor law data into the generative AI, which can then analyze the labor law data and propose appropriate work arrangements.

[0093] The suggestion unit can estimate the emotions of elderly individuals and determine the priority of suggested work arrangements based on those estimated emotions. For example, if an elderly individual is feeling stressed, the suggestion unit's generating AI will prioritize suggesting work arrangements that promote relaxation. The suggestion unit uses the generating AI to estimate the emotions of elderly individuals and determine the priority of suggested work arrangements based on those estimated emotions. For example, if an elderly individual is agitated, the suggestion unit's generating AI will prioritize suggesting detailed work arrangements. Alternatively, if an elderly individual is tired, the suggestion unit's generating AI can prioritize suggesting concise work arrangements. This allows for more appropriate support by prioritizing suggested work arrangements based on the emotions of elderly individuals. Emotion estimation is achieved using an emotion estimation function, such as an emotion engine or a generating AI. The generating AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the processing described above in the suggestion unit may be performed using or without a generating AI. For example, the proposal department can input emotional data of elderly people into a generating AI, which can then analyze the emotional data to determine the priority of work arrangements.

[0094] The proposal unit can consider the local labor market and employment situation when proposing work arrangements. For example, the proposal unit can analyze the labor market in the area where the elderly person lives and propose a work arrangement specific to that area. The proposal unit uses generative AI to consider the local labor market and employment situation when proposing work arrangements. For example, the proposal unit can understand the employment situation in the area where the elderly person lives and propose an appropriate work arrangement. The proposal unit can also consider the local labor market and employment situation and propose a work arrangement that is optimal for the elderly person. This allows for the proposal of a more appropriate work arrangement by considering the local labor market and employment situation. Some or all of the above processing in the proposal unit may be performed using generative AI, or it may be performed without using generative AI. For example, the proposal unit can input local labor market data into the generative AI, which can then analyze the labor market data and propose an appropriate work arrangement.

[0095] The proposal department can include success stories and advice from other elderly individuals in the proposed work arrangements. For example, the proposal department can propose similar work arrangements based on the success stories of other elderly individuals. The proposal department can use generative AI to include success stories and advice from other elderly individuals in the proposed work arrangements. For example, the proposal department can propose appropriate work arrangements by referring to the advice of other elderly individuals. The proposal department can also analyze success stories and advice from elderly individuals to propose the optimal work arrangement. This allows for the proposal of more appropriate work arrangements by including success stories and advice from other elderly individuals. Some or all of the above processing in the proposal department may be performed using generative AI, or it may be performed without generative AI. For example, the proposal department can input data on success stories from elderly individuals into the generative AI, which can then analyze the success story data to propose appropriate work arrangements.

[0096] The community unit can estimate the emotions of elderly individuals and adjust how community functions are displayed based on the estimated emotions. For example, if an elderly individual is feeling anxious, the community unit's generating AI will display community functions in a gentle tone. The community unit uses the generating AI to estimate the emotions of elderly individuals and adjust how community functions are displayed based on the estimated emotions. For example, if an elderly individual is confident, the community unit's generating AI will display detailed information and suggest specific ways to interact. Also, if an elderly individual is tired, the community unit's generating AI can display concise information and provide necessary support in a short time. This allows for more appropriate support to be provided by adjusting how community functions are displayed based on the emotions of elderly individuals. Emotion estimation is achieved using an emotion estimation function, for example, an emotion engine or a generating AI. The generating AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above-described processes in the community unit may be performed using or without a generating AI. For example, the community department can input emotional data from elderly people into a generating AI, which can then analyze the emotional data and adjust how community functions are displayed.

[0097] The Community Department can incorporate past interaction history and feedback into community functions. For example, the Community Department can propose optimal community functions based on an elderly person's past interaction history. The Community Department uses generative AI to incorporate past interaction history and feedback into community functions. For example, the Community Department provides appropriate community functions by referring to feedback from elderly people. The Community Department can also provide comprehensive community functions by combining the elderly person's past interaction history and feedback. This allows for more appropriate support to be provided by incorporating past interaction history and feedback. Some or all of the above processing in the Community Department may be performed using generative AI or not. For example, the Community Department can input elderly people's interaction history data into a generative AI, which can then analyze the interaction history data to provide appropriate community functions.

[0098] The Community Department can incorporate the latest communication tools and platforms into its community functions. For example, the Community Department can provide community functions suitable for the elderly based on the latest communication tools. The Community Department can use generative AI to incorporate the latest communication tools and platforms into its community functions. For example, the Community Department can incorporate the latest platforms and provide advice suitable for the elderly. The Community Department can also analyze communication tools and platforms and provide community functions that are optimal for the elderly. This allows for the provision of more appropriate support by incorporating the latest communication tools and platforms. Some or all of the above-described processes in the Community Department may be performed using generative AI or not. For example, the Community Department can input communication tool data into a generative AI, which can then analyze the tool data to provide appropriate community functions.

[0099] The community unit can estimate the emotions of elderly individuals and prioritize community functions based on those estimated emotions. For example, if an elderly individual is stressed, the community unit's generative AI will prioritize providing relaxing community functions. The community unit uses generative AI to estimate the emotions of elderly individuals and prioritize community functions based on those estimated emotions. For example, if an elderly individual is agitated, the community unit's generative AI will prioritize providing detailed community functions. Alternatively, if an elderly individual is tired, the community unit's generative AI can prioritize providing concise community functions. This allows for more appropriate support by prioritizing community functions based on the emotions of elderly individuals. Emotion estimation is achieved using an emotion estimation function, such as an emotion engine or generative AI. Generative AI may be, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above-described processes in the community unit may be performed using or without generative AI. For example, the community unit can input elderly individuals' emotion data into a generative AI, which can then analyze the emotion data to determine the priority of community functions.

[0100] The Community Department can consider local characteristics and culture when developing community functions. For example, the Community Department can analyze the characteristics of the area where elderly people live and provide community functions specific to that area. The Community Department uses generative AI to consider local characteristics and culture when developing community functions. For example, the Community Department can understand the culture and customs of the area where elderly people live and provide appropriate community functions. The Community Department can also consider local characteristics and culture to provide community functions that are optimal for elderly people. This allows for the provision of more appropriate support by considering local characteristics and culture. Some or all of the above-described processes in the Community Department may be performed using generative AI or not. For example, the Community Department can input local characteristic data into a generative AI, which can then analyze the characteristic data and provide appropriate community functions.

[0101] The Community Department can include the success stories and advice of other elderly people in its community functions. For example, the Community Department can provide similar community functions based on the success stories of other elderly people. The Community Department can use generative AI to include the success stories and advice of other elderly people in its community functions. For example, the Community Department can provide appropriate community functions by referring to the advice of other elderly people. The Community Department can also analyze the success stories and advice of elderly people and provide optimal community functions. This allows for more appropriate support by including the success stories and advice of other elderly people. Some or all of the above processing in the Community Department may be performed using generative AI or not. For example, the Community Department can input elderly people's success story data into generative AI, and the generative AI can analyze the success story data to provide appropriate community functions.

[0102] The system according to the embodiment is not limited to the example described above, and various modifications are possible, for example, as follows.

[0103] The understanding unit can estimate the emotions of elderly individuals and adjust how it understands their skills and experiences based on those estimated emotions. For example, if an elderly person is feeling anxious, the generating AI will ask questions in a gentle tone, encouraging them to talk about their skills and experiences in a relaxed state. If the elderly person is confident, the generating AI will ask more detailed questions, allowing it to delve deeper into specific skills and experiences. Furthermore, if the elderly person is tired, the generating AI can ask concise questions, allowing it to gather necessary information quickly. By adjusting how it understands skills and experiences based on the elderly person's emotions, it can provide more appropriate support.

[0104] The service provider can incorporate past success stories and feedback from other elderly individuals into the work and consultations they offer. For example, they can offer similar work or consultations based on past successes of elderly individuals. They can also provide appropriate advice by referring to feedback from other elderly individuals. Furthermore, they can analyze past success stories of elderly individuals and propose the most suitable work or consultations. In this way, by incorporating past success stories and feedback from other elderly individuals, they can provide more appropriate support.

[0105] The proposal department can incorporate the latest labor laws and health guidelines into the proposed work arrangements. For example, it can propose work arrangements suitable for older workers based on the latest labor laws. It can also incorporate the latest health guidelines and provide advice suitable for older workers. Furthermore, it can analyze labor laws and health guidelines and propose work arrangements that are optimal for older workers. In this way, by incorporating the latest labor laws and health guidelines, it can propose more appropriate work arrangements.

[0106] The Community Department can incorporate the latest communication tools and platforms into its community functions. For example, it can provide community functions tailored to seniors based on the latest communication tools. It can also incorporate the latest platforms to provide advice tailored to seniors. Furthermore, it can analyze communication tools and platforms to provide community functions that are optimal for seniors. In this way, by incorporating the latest communication tools and platforms, more appropriate support can be provided.

[0107] The understanding unit can understand the specific needs of a region by considering the geographical location information of elderly people. For example, it can analyze the characteristics of the area where elderly people live and propose region-specific jobs and activities. It can also provide local health services and support based on the geographical location information of elderly people. Furthermore, it can understand the culture and customs of the area where elderly people live and provide appropriate advice. In this way, by considering the geographical location information of elderly people, it is possible to understand region-specific needs and provide appropriate support.

[0108] The understanding unit can estimate the emotions of elderly individuals and prioritize the information to be understood based on those estimated emotions. For example, if an elderly person is stressed, the generating AI will prioritize providing information that promotes relaxation. Similarly, if an elderly person is agitated, the generating AI can prioritize providing detailed information. Furthermore, if an elderly person is tired, the generating AI can prioritize providing concise information. This allows for the provision of more appropriate information by prioritizing information based on the elderly person's emotions.

[0109] The information provider can estimate the emotions of elderly individuals and prioritize the information to be provided based on those estimated emotions. For example, if an elderly person is stressed, the generating AI will prioritize providing information that promotes relaxation. If an elderly person is agitated, the generating AI can prioritize providing detailed information. Furthermore, if an elderly person is tired, the generating AI can prioritize providing concise information. This allows for the provision of more appropriate information by prioritizing information based on the emotions of the elderly person.

[0110] The proposal function can estimate the emotions of elderly individuals and adjust the way suggested work arrangements are presented based on those estimated emotions. For example, if an elderly person is feeling anxious, the generating AI will suggest work arrangements in a gentle tone. If the elderly person is confident, the generating AI can provide detailed information and suggest specific work arrangements. Furthermore, if the elderly person is tired, the generating AI can provide concise information and offer necessary support in a short amount of time. In this way, by adjusting the way suggested work arrangements are presented based on the emotions of elderly individuals, more appropriate support can be provided.

[0111] The community function can estimate the emotions of elderly individuals and adjust how community features are displayed based on those estimates. For example, if an elderly person is feeling anxious, the generating AI will display community features in a gentle tone. If the elderly person is confident, the generating AI can display detailed information and suggest specific ways to interact. Furthermore, if the elderly person is tired, the generating AI can display concise information and provide necessary support in a short amount of time. In this way, by adjusting how community features are displayed based on the emotions of elderly individuals, more appropriate support can be provided.

[0112] The understanding unit can analyze the social media activities of older adults and understand their online activity status. For example, it can analyze the content of older adults' social media posts to understand their interests and concerns. It can also understand their online interactions and suggest appropriate communities. Furthermore, it can analyze the frequency of older adults' social media activity and provide online support. In this way, by analyzing the social media activities of older adults, it is possible to understand their online activity status and provide appropriate support.

[0113] The following briefly describes the processing flow for example form 2.

[0114] Step 1: The Understanding Unit understands the skills, experience, and health status of older adults. For example, it analyzes older adults' past work history and health data, and uses generated AI to provide support tailored to individual needs. Specifically, it analyzes resumes and medical records to understand specific skills and health conditions. Step 2: The provisioning unit provides appropriate work or consultation based on the information understood by the understanding unit. For example, it proposes work that can utilize the skills of elderly people with specific skills and provides appropriate advice tailored to their health condition using generated AI. Specifically, it may propose remote work to elderly people with IT skills and provide recommendations for exercise and dietary advice. Step 3: Based on the information provided by the Provider Department, the Proposal Department proposes flexible work arrangements that take into account physical limitations, lifestyle rhythms, etc. For example, for elderly individuals who are not confident in their physical strength, the Proposal Department proposes short-time work or telecommuting, and uses AI generation to set work hours that match their lifestyle rhythm. Specifically, it proposes 4-hour workdays, full telecommuting, early morning work, or evening work. Step 4: The Community Department will provide community features that allow people to share their experiences and problems. For example, it will provide a space where seniors with the same hobbies can interact, and create an environment where they can easily consult about health and work using AI-generated messages. Specifically, it will provide online groups, hobby circles, online chat, and telephone consultations.

[0115] 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.

[0116] Data generation model 58 is a form of 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> Examples of generative AI include text generation AI, image generation AI, and multimodal generation AI. 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 (e.g., still image data or video data). The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference result in one or more data formats from audio data, text data, and image data. The data generation model 58 includes, for example, text generation AI, image generation AI, and multimodal generation AI. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specific processing unit 290 performs the specific processing described above using the data generation model 58. The data generation model 58 may be a fine-tuned model that outputs inference results from prompts that do not contain instructions, in which case the data generation model 58 can output inference results from prompts that do not contain instructions. In the data processing device 12, etc., there are multiple types of data generation models 58, and the data generation model 58 includes AI other than generative AI. AI other than generative AI includes, for example, linear regression, logistic regression, decision trees, random forests, support vector machines (SVMs), k-means clustering, convolutional neural networks (CNNs), recurrent neural networks (RNNs), generative adversarial networks (GANs), or naive Bayes, and can perform various processes, but is not limited to these examples. Also, the AI ​​may be an AI agent. Furthermore, when the processing of each of the above parts is performed by the AI, the processing may be performed by the AI ​​in part or in whole, but is not limited to this example.Furthermore, processing performed by AI, including generative AI, may be replaced with rule-based processing, and rule-based processing may be replaced with processing performed by AI, including generative AI.

[0117] Furthermore, the processing performed by the data processing system 10 described above is carried out by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart device 14, but it may also be carried out by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart device 14. In addition, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the smart device 14 or an external device, and the smart device 14 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0118] Each of the multiple elements described above, including the understanding unit, provision unit, proposal unit, and community unit, is implemented, for example, by at least one of the smart device 14 and the data processing unit 12. For example, the understanding unit uses the camera 42 and microphone 38B of the smart device 14 to understand the skills, experience, and health status of elderly people, and the control unit 46A analyzes this information. The provision unit is implemented, for example, by the specific processing unit 290 of the data processing unit 12, and provides appropriate work and consultation content based on the information obtained by the understanding unit. The proposal unit is implemented, for example, by the specific processing unit 290 of the data processing unit 12, and proposes flexible work arrangements that take into account physical limitations and lifestyle rhythms. The community unit is implemented, for example, by the control unit 46A of the smart device 14, and provides a community function that allows people to share their experiences and problems with each other. The correspondence between each unit and the device or control unit is not limited to the examples described above, and various changes are possible.

[0119] [Second Embodiment] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0120] 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.

[0121] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. 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 and / or LAN.

[0122] 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.

[0123] The microphone 238 receives voice signals from the user and accepts instructions from the user. The microphone 238 captures the voice signals from the user, 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.

[0124] 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, which captures images of the area around the user (for example, an imaging range defined by a field of view equivalent to the field of vision of a typical healthy person).

[0125] 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.

[0126] 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 by the processor 28. The storage 32 stores the specific processing program 56.

[0127] The processor 28 reads a 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 acting as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0128] 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. The identification processing unit 290 can estimate the user's emotions using the emotion identification model 59 and perform identification processing using the user's emotions. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotions, including but not limited to these examples. Furthermore, emotion estimation and prediction also include, for example, emotion analysis.

[0129] In the smart glasses 214, specific processing is performed by the processor 46. The storage 50 stores a specific processing program 60. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 acting as a control unit 46A according to the specific processing program 60 executed on the RAM 48. The smart glasses 214 also have a data generation model 58 and an emotion identification model 59, similar to the data generation model and emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0130] Furthermore, other devices besides the data processing device 12 may also have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 obtains processing results (such as prediction results) using the data generation model 58 by communicating with the server device that has the data generation model 58. Also, the data processing device 12 may be a server device or a terminal device owned by the user (for example, a mobile phone, robot, home appliance, etc.).

[0131] 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.

[0132] The data generation model 58 is a so-called generative AI. An example of a data generation model 58 is a generative AI such as ChatGPT. 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 inference data such as audio data representing speech, text data representing text, and image data representing images (e.g., still image data or video data). The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference result in one or more data formats such as audio data, text data, and image data. The data generation model 58 includes, for example, text generation AI, image generation AI, and multimodal generation AI. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specific processing unit 290 performs the specific processing described above using the data generation model 58. The data generation model 58 may be a fine-tuned model that outputs inference results from prompts that do not contain instructions, in which case the data generation model 58 can output inference results from prompts that do not contain instructions. In the data processing device 12, etc., there are multiple types of data generation models 58, and the data generation model 58 includes AI other than generative AI. AI other than generative AI includes, for example, linear regression, logistic regression, decision trees, random forests, support vector machines (SVM), k-means clustering, convolutional neural networks (CNN), recurrent neural networks (RNN), generative adversarial networks (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. Also, the AI ​​may be an AI agent. Furthermore, when the processing of each part described above is performed by the AI, the processing may be performed by the AI ​​in part or in whole, but is not limited to this example. Also, processing performed by an AI including a generative AI may be replaced by rule-based processing, and rule-based processing may be replaced by processing performed by an AI including a generative AI.

[0133] The data processing system 210 according to the second embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 210 is performed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart glasses 214, but it may also be performed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart glasses 214. In addition, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the smart glasses 214 or an external device, and the smart glasses 214 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0134] Each of the multiple elements described above, including the understanding unit, provision unit, proposal unit, and community unit, is implemented, for example, in at least one of the smart glasses 214 and the data processing unit 12. For example, the understanding unit uses the camera 42 and microphone 238 of the smart glasses 214 to understand the skills, experience, and health status of elderly people, and the control unit 46A analyzes this information. The provision unit is implemented, for example, in the specific processing unit 290 of the data processing unit 12, and provides appropriate work or consultation content based on the information obtained by the understanding unit. The proposal unit is implemented, for example, in the specific processing unit 290 of the data processing unit 12, and proposes flexible work arrangements that take into account physical limitations and lifestyle rhythms. The community unit is implemented, for example, in the control unit 46A of the smart glasses 214, and provides a community function that allows people to share their experiences and problems with each other. The correspondence between each unit and the device or control unit is not limited to the examples described above, and various changes are possible.

[0135] [Third Embodiment] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0136] 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.

[0137] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. 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 and / or LAN.

[0138] 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.

[0139] The microphone 238 receives voice signals from the user and accepts instructions from the user. The microphone 238 captures the voice signals from the user, 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.

[0140] 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, which captures images of the area around the user (for example, an imaging range defined by a field of view equivalent to the field of vision of a typical healthy person).

[0141] 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.

[0142] 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.

[0143] The processor 28 reads a 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 acting as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0144] 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. The identification processing unit 290 can estimate the user's emotions using the emotion identification model 59 and perform identification processing using the user's emotions. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotions, including but not limited to these examples. Furthermore, emotion estimation and prediction also include, for example, emotion analysis.

[0145] In the headset terminal 314, specific processing is performed by the processor 46. The storage 50 stores a specific program 60. The processor 46 reads the specific program 60 from the storage 50 and executes the read specific program 60 on the RAM 48. The specific processing is realized by the processor 46 acting as a control unit 46A according to the specific program 60 executed on the RAM 48. The headset terminal 314 also has a data generation model 58 and an emotion identification model 59, similar to the data generation model and emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0146] Furthermore, other devices besides the data processing device 12 may also have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 obtains processing results (such as prediction results) using the data generation model 58 by communicating with the server device that has the data generation model 58. Also, the data processing device 12 may be a server device or a terminal device owned by the user (for example, a mobile phone, robot, home appliance, etc.).

[0147] 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.

[0148] The data generation model 58 is a so-called generative AI. An example of a data generation model 58 is a generative AI such as ChatGPT. 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 inference data such as audio data representing speech, text data representing text, and image data representing images (e.g., still image data or video data). The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference result in one or more data formats such as audio data, text data, and image data. The data generation model 58 includes, for example, text generation AI, image generation AI, and multimodal generation AI. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specific processing unit 290 performs the specific processing described above using the data generation model 58. The data generation model 58 may be a fine-tuned model that outputs inference results from prompts that do not contain instructions, in which case the data generation model 58 can output inference results from prompts that do not contain instructions. In the data processing device 12, etc., there are multiple types of data generation models 58, and the data generation model 58 includes AI other than generative AI. AI other than generative AI includes, for example, linear regression, logistic regression, decision trees, random forests, support vector machines (SVM), k-means clustering, convolutional neural networks (CNN), recurrent neural networks (RNN), generative adversarial networks (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. Also, the AI ​​may be an AI agent. Furthermore, when the processing of each part described above is performed by the AI, the processing may be performed by the AI ​​in part or in whole, but is not limited to this example. Also, processing performed by an AI including a generative AI may be replaced by rule-based processing, and rule-based processing may be replaced by processing performed by an AI including a generative AI.

[0149] The data processing system 310 according to the third embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 310 is performed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the headset terminal 314, but may also be performed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the headset terminal 314. In addition, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the headset terminal 314 or an external device, and the headset terminal 314 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0150] Each of the multiple elements described above, including the understanding unit, provision unit, proposal unit, and community unit, is implemented by, for example, at least one of the headset terminal 314 and the data processing unit 12. For example, the understanding unit uses the camera 42 and microphone 238 of the headset terminal 314 to understand the skills, experience, and health status of elderly people, and the control unit 46A analyzes this information. The provision unit is implemented by, for example, the specific processing unit 290 of the data processing unit 12, and provides appropriate work and consultation content based on the information obtained by the understanding unit. The proposal unit is implemented by, for example, the specific processing unit 290 of the data processing unit 12, and proposes flexible work arrangements that take into account physical limitations and lifestyle rhythms. The community unit is implemented by, for example, the control unit 46A of the headset terminal 314, and provides a community function that allows people to share their experiences and problems with each other. The correspondence between each unit and the device or control unit is not limited to the examples described above, and various changes are possible.

[0151] [Fourth Embodiment] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0152] 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.

[0153] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. 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 and / or LAN.

[0154] 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.

[0155] The microphone 238 receives voice signals from the user and accepts instructions from the user. The microphone 238 captures the voice signals from the user, 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.

[0156] 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 image sensor or CCD image sensor, which captures images of the area around the user (for example, an imaging range defined by a field of view equivalent to the field of vision of a typical healthy person).

[0157] 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.

[0158] 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. The robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0159] 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.

[0160] The processor 28 reads a 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 acting as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0161] 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. The identification processing unit 290 can estimate the user's emotions using the emotion identification model 59 and perform identification processing using the user's emotions. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotions, including but not limited to these examples. Furthermore, emotion estimation and prediction also include, for example, emotion analysis.

[0162] In robot 414, specific processing is performed by processor 46. A specific program 60 is stored in storage 50. Processor 46 reads the specific program 60 from storage 50 and executes it on RAM 48. The specific processing is achieved by processor 46 acting as a control unit 46A according to the specific program 60 executed on RAM 48. Robot 414 also has data generation model 58 and emotion identification model 59, similar to those of the robot, and can perform processing similar to that of the specific processing unit 290 using these models.

[0163] Furthermore, other devices besides the data processing device 12 may also have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 obtains processing results (such as prediction results) using the data generation model 58 by communicating with the server device that has the data generation model 58. Also, the data processing device 12 may be a server device or a terminal device owned by the user (for example, a mobile phone, robot, home appliance, etc.).

[0164] 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.

[0165] The data generation model 58 is a so-called generative AI. An example of a data generation model 58 is a generative AI such as ChatGPT. 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 inference data such as audio data representing speech, text data representing text, and image data representing images (e.g., still image data or video data). The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference result in one or more data formats such as audio data, text data, and image data. The data generation model 58 includes, for example, text generation AI, image generation AI, and multimodal generation AI. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specific processing unit 290 performs the specific processing described above using the data generation model 58. The data generation model 58 may be a fine-tuned model that outputs inference results from prompts that do not contain instructions, in which case the data generation model 58 can output inference results from prompts that do not contain instructions. In the data processing device 12, etc., there are multiple types of data generation models 58, and the data generation model 58 includes AI other than generative AI. AI other than generative AI includes, for example, linear regression, logistic regression, decision trees, random forests, support vector machines (SVM), k-means clustering, convolutional neural networks (CNN), recurrent neural networks (RNN), generative adversarial networks (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. Also, the AI ​​may be an AI agent. Furthermore, when the processing of each part described above is performed by the AI, the processing may be performed by the AI ​​in part or in whole, but is not limited to this example. Also, processing performed by an AI including a generative AI may be replaced by rule-based processing, and rule-based processing may be replaced by processing performed by an AI including a generative AI.

[0166] The data processing system 410 according to the fourth embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 410 is performed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the robot 414, but it may also be performed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the robot 414. In addition, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the robot 414 or an external device, and the robot 414 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0167] Each of the multiple elements described above, including the understanding unit, provision unit, proposal unit, and community unit, is implemented in at least one of the following: the robot 414 and the data processing unit 12. For example, the understanding unit uses the camera 42 and microphone 238 of the robot 414 to understand the skills, experience, and health status of elderly people, and the control unit 46A analyzes this information. The provision unit is implemented in the specific processing unit 290 of the data processing unit 12 and provides appropriate work and consultation content based on the information obtained by the understanding unit. The proposal unit is implemented in the specific processing unit 290 of the data processing unit 12 and proposes flexible work arrangements that take into account physical limitations and lifestyle rhythms. The community unit is implemented in the control unit 46A of the robot 414 and provides a community function that allows people to share their experiences and problems with each other. The correspondence between each unit and the device or control unit is not limited to the examples described above and can be modified in various ways.

[0168] 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.

[0169] Figure 9 shows the 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.

[0170] 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.

[0171] 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.

[0172] 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, and motorcycles, 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 based, for example, 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.

[0173] 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."

[0174] 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.

[0175] 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 method for the specific process may be used, which includes computer 22 and multiple other computers.

[0176] 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.

[0177] 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.

[0178] 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.

[0179] 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.

[0180] 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.

[0181] 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.

[0182] 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.

[0183] Furthermore, although the above-described examples were divided into four embodiments, some or all of these embodiments may be combined. Also, the smart device 14, smart glasses 214, headset terminal 314, and robot 414 are just examples, and they may be combined, or other devices may be used. Also, although the above-described examples were divided into two embodiments, Embodiment 1 and Embodiment 2, these may be combined.

[0184] 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 other things 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.

[0185] 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.

[0186] (Note 1) Understanding section to understand the skills, experience, and health status of elderly people, Based on the information understood by the aforementioned understanding unit, the provision unit provides appropriate work and consultation content. Based on the information provided by the aforementioned provisioning department, the proposal department proposes flexible work arrangements that take into account physical limitations, lifestyle rhythms, etc. It includes a community section that provides community functions for sharing each other's experiences and problems. A system characterized by the following features. (Note 2) The aforementioned understanding unit is, Analyzing the past work history and health data of elderly people. The system described in Appendix 1, characterized by the features described herein. (Note 3) The aforementioned supply unit is, Proposing jobs that utilize specific skills to elderly individuals who possess those skills. The system described in Appendix 1, characterized by the features described herein. (Note 4) The aforementioned supply unit is, We provide appropriate advice tailored to your health condition. The system described in Appendix 1, characterized by the features described herein. (Note 5) The aforementioned proposal section is, We propose part-time work or telecommuting to elderly people who lack confidence in their physical strength. The system described in Appendix 1, characterized by the features described herein. (Note 6) The aforementioned proposal section is, Set working hours to match your lifestyle. The system described in Appendix 1, characterized by the features described herein. (Note 7) The aforementioned community section, To provide a place where elderly people with the same hobbies can interact with each other. The system described in Appendix 1, characterized by the features described herein. (Note 8) The aforementioned community department, To create an environment where people can easily seek advice on health and work-related matters. The system described in Appendix 1, characterized by the features described herein. (Note 9) The aforementioned understanding unit is, We estimate the emotions of older adults and adjust our understanding of skills and experiences based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 10) The aforementioned understanding unit is, In addition to analyzing the past work history and health data of elderly individuals, we will analyze their hobbies and interests to gain a more comprehensive understanding. The system described in Appendix 1, characterized by the features described herein. (Note 11) The aforementioned understanding unit is, Taking into account the living environment and family structure of elderly people, we aim to deepen our understanding of their individual needs. The system described in Appendix 1, characterized by the features described herein. (Note 12) The aforementioned understanding unit is, The system estimates the emotions of older adults and prioritizes information to understand based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 13) The aforementioned understanding unit is, Understanding region-specific needs by considering the geographical location of elderly people The system described in Appendix 1, characterized by the features described herein. (Note 14) The aforementioned understanding unit is, Analyzing the social media activities of older adults to understand their online activity patterns. The system described in Appendix 1, characterized by the features described herein. (Note 15) The aforementioned supply unit is, We estimate the emotions of elderly people and adjust the way we express the work and consultations we provide based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 16) The aforementioned supply unit is, The services and consultations offered will incorporate past success stories and feedback from other elderly individuals. The system described in Appendix 1, characterized by the features described herein. (Note 17) The aforementioned supply unit is, The information we provide will incorporate the latest market trends and technological developments. The system described in Appendix 1, characterized by the features described herein. (Note 18) The aforementioned supply unit is, The system estimates the emotions of older adults and prioritizes the information provided based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 19) The aforementioned supply unit is, We take into consideration the characteristics and culture of the region when providing services and consultations. The system described in Appendix 1, characterized by the features described herein. (Note 20) The aforementioned supply unit is, The information provided should include success stories and advice from other seniors. The system described in Appendix 1, characterized by the features described herein. (Note 21) The aforementioned proposal section is, We estimate the emotions of elderly people and adjust the way we express proposed work arrangements based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 22) The aforementioned proposal section is, The proposed work arrangement will reflect past work history and performance data. The system described in Appendix 1, characterized by the features described herein. (Note 23) The aforementioned proposal section is, The proposed work arrangements will incorporate the latest labor laws and health guidelines. The system described in Appendix 1, characterized by the features described herein. (Note 24) The aforementioned proposal section is, The system estimates the emotions of elderly individuals and prioritizes proposed work arrangements based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 25) The aforementioned proposal section is, The proposed work arrangement will take into consideration the local labor market and employment situation. The system described in Appendix 1, characterized by the features described herein. (Note 26) The aforementioned proposal section is, The proposed work arrangement will include success stories and advice from other senior citizens. The system described in Appendix 1, characterized by the features described herein. (Note 27) The aforementioned community department, The system estimates the emotions of older adults and adjusts how community features are displayed based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 28) The aforementioned community department, The community features will reflect past interaction history and feedback. The system described in Appendix 1, characterized by the features described herein. (Note 29) The aforementioned community department, Incorporate the latest communication tools and platforms into community features. The system described in Appendix 1, characterized by the features described herein. (Note 30) The aforementioned community department, The system estimates the emotions of older adults and prioritizes community functions based on these estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 31) The aforementioned community department, Community functions should take local characteristics and culture into consideration. The system described in Appendix 1, characterized by the features described herein. (Note 32) The aforementioned community department, Include other seniors' success stories and advice in the community features. The system described in Appendix 1, characterized by the features described herein. [Explanation of Symbols]

[0187] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots

Claims

1. Understanding the skills, experience, and health status of elderly people, Based on the information understood by the aforementioned understanding unit, the provision unit provides appropriate work and consultation content. Based on the information provided by the aforementioned provisioning department, the proposal department proposes flexible work arrangements that take into account physical limitations, lifestyle rhythms, etc. It includes a community section that provides community functions for sharing each other's experiences and problems. A system characterized by the following features.

2. The aforementioned understanding unit is, Analyzing the past work history and health data of elderly people. The system according to feature 1.

3. The aforementioned supply unit is, Proposing jobs that utilize specific skills to elderly individuals who possess those skills. The system according to feature 1.

4. The aforementioned supply unit is, We provide appropriate advice tailored to your health condition. The system according to feature 1.

5. The aforementioned proposal section is, We propose part-time work or telecommuting to elderly people who lack confidence in their physical strength. The system according to feature 1.

6. The aforementioned proposal section is, Set working hours to match your lifestyle. The system according to feature 1.

7. The aforementioned community department, To provide a place where elderly people with the same hobbies can interact with each other. The system according to feature 1.

8. The aforementioned community department, To create an environment where people can easily seek advice on health and work-related matters. The system according to feature 1.

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