System

Abstract

A system is provided.SOLUTION: A means in which a user inputs a question or concern related to a household, a means in which a server receives input information of the user and passes the input information to a generative artificial intelligence, a means in which the generative artificial intelligence analyzes the input information and generates advice, a means in which the server returns the generated advice to the user, a means in which the server selects an optimal senior mentor based on a skill set of the senior mentor and user evaluation based on the advice, and a means in which the server coordinates schedules of the user and the senior mentor, A system comprising: means for establishing a date and time of assistance; means for a senior mentor to visit a user's home at the established date and time and provide assistance; and means for receiving feedback from the user and reflecting the feedback in the senior mentor's rating system.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

[0002] Patent document 1 discloses a persona chatbot control method performed by at least one processor, the method including the steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to a description of the chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Publication No. 2022-180282 Summary of the Invention [Problem to be solved by the invention]

[0004] In today's family environment, there are problems such as an increase in dual-income households and single-parent households, a lack of advice from grandparents due to the trend toward nuclear families, and a weakening of local communication. These problems increase the burden within the family and further weaken the connection between the family and the local community. Furthermore, the elderly have fewer social roles and opportunities to interact, and are losing their sense of purpose in life. Therefore, a system is needed to reduce worries and burdens within the family and strengthen ties with the local community. [Means for solving the problem]

[0005] The home support platform provided here is a system in which a generative artificial intelligence (AI) provides advice in response to household questions and concerns, and matches senior mentors to provide actual support to households. Specifically, the system includes a means for users to input their household questions and concerns, a means for a server to receive the user's input information and pass it on to the generative AI, a means for the generative AI to analyze the input information and generate advice, a means for the server to return the generated advice to the user, a means for the server to select the most suitable senior mentor based on the senior mentor's skill set and user ratings, a means for the server to coordinate schedules between the user and the senior mentor and confirm the date and time of support, a means for the senior mentor to visit the user's home at the confirmed date and time to provide support, and a means for receiving user feedback and reflecting it in the senior mentor rating system. This system can reduce the burden on households, strengthen community ties, and promote the social roles and opportunities for older adults to interact.

[0006] "User" refers to an individual who uses the system to input questions or concerns about their home and receive support.

[0007] "Server" refers to a computer system that receives user input information, passes it on to the generative AI, and manages and operates the entire system, including generating advice, managing schedules, and selecting senior mentors.

[0008] "Generative AI" refers to AI technology that analyzes input questions and concerns and generates expert advice.

[0009] A "senior mentor" is an older person in their 50s or older who has a wealth of experience and knowledge and provides support for questions and concerns at home.

[0010] "Skill set" refers to information that compiles the skills, knowledge, experience, etc. that a senior mentor possesses.

[0011] "User Evaluation" refers to the feedback or evaluation given by a user regarding the support provided by a senior mentor.

[0012] "Matching algorithm" refers to a calculation method for selecting the senior mentor best suited to a user's question or concern.

[0013] "Schedule management" refers to the process of coordinating the free time of the user and senior mentor and determining the date and time of support.

[0014] "Feedback" refers to the act of a user who has received assistance providing the system with their opinion or evaluation of the assistance. [Brief explanation of the drawings]

[0015] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0016] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0017] First, the terms used in the following description will be explained.

[0018] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0019] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0020] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0021] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0022] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0023] [First embodiment]

[0024] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0025] 1, a 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.

[0026] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. 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. The database 24 and the communication I / F 26 are also 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).

[0027] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0028] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0029] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0030] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0031] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0032] 2, in the data processing device 12, a specific process 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" according to the technology of the present 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 process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0033] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0034] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0035] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0036] The present invention relates to a family support platform, which is a system that provides advice and support for family questions and concerns through the cooperation of generative artificial intelligence (AI) and senior mentors. Specific embodiments for implementing the present invention will be described below.

[0037] Program processing and system configuration

[0038] 1. User registration and initial settings

[0039] When the user accesses the site for the first time, the user's device displays a registration form for entering basic information (such as name, address, email address, and family concerns). The server receives the information entered by the user, validates it, and stores it in a database. Similarly, the senior mentor's device displays a form for entering the senior mentor's basic information and skill set, and sends the entered data to the server. The server also validates the information entered by the senior mentor and stores it in a database.

[0040] 2. Input your questions and concerns and receive answers from AI

[0041] The user's device provides a dedicated form for entering questions and concerns about the home. When the user enters and submits their concerns, the server passes this information to a generative AI. The generative AI analyzes the question or concern and generates optimal advice. The generated advice is then sent back to the user's device via the server and displayed to the user.

[0042] 3. Senior mentor matching

[0043] The server runs an algorithm to match users with appropriate senior mentors based on their questions and concerns. The algorithm selects the best candidates by taking into account the senior mentors' skill sets and user ratings. The server then presents the selected senior mentors to the user.

[0044] As a specific example, if a user inputs "I would like some help with my child's studies," the server will select and suggest highly rated senior mentors who have education-related skills.

[0045] 4. Adjust your schedule

[0046] If both the user and the selected senior mentor accept the proposal, the server compares their schedules and proposes the optimal date and time. If the user and the senior mentor agree on the optimal date and time, the date and time of the support is confirmed.

[0047] 5. On-site support

[0048] The senior mentor visits the user's home at the specified date and time and provides the necessary support (e.g., housework support, childcare support). The support content and progress are sent to the server and recorded.

[0049] For example, if a senior mentor prepares dinner at the user's request, details such as the cooking steps and the time it will be ready will be recorded.

[0050] 6. Feedback and Ratings

[0051] After the support is completed, the user's device displays a feedback form, allowing the user to enter their opinion and evaluation of the support they received. The server receives the feedback and reflects it in the senior mentor's evaluation system. It also provides a feedback function to senior mentors, allowing them to enter their evaluation and thoughts about the user. This improves the quality of the entire system and the accuracy of the next match.

[0052] In this way, the home support platform of the present invention is a system that utilizes AI technology and senior mentors to reduce worries and burdens within the home, strengthen ties with the local community, and provide social roles and opportunities for interaction for the elderly.

[0053] The processing flow will be explained below.

[0054] Step 1:

[0055] When the user accesses the site for the first time, the user's device displays a registration form for entering basic information (such as name, address, email address, and household concerns).

[0056] Step 2:

[0057] The user enters the necessary information and clicks the registration button.

[0058] Step 3:

[0059] The server receives the information entered by the user and performs validation. If the input data is valid, it is saved in the database. At the same time, a welcome message is displayed on the user's terminal.

[0060] Step 4:

[0061] The senior mentor's device also displays a registration form where the senior mentor can enter their skills, background, and support details.

[0062] Step 5:

[0063] The senior mentor enters the required information and clicks the registration button.

[0064] Step 6:

[0065] The server receives the information entered by the senior mentor, validates it, and if the input data is valid, stores it in the database.

[0066] Step 7:

[0067] The user's device displays a dedicated form where the user can enter questions or concerns about their home. The user enters their question or concern and clicks the send button.

[0068] Step 8:

[0069] The server receives the user's input information and passes it to the generative artificial intelligence.

[0070] Step 9:

[0071] Generative AI analyzes users' questions and concerns and generates optimal advice.

[0072] Step 10:

[0073] The server receives the generated advice and returns it to the user's terminal.

[0074] Step 11:

[0075] The user's terminal displays the received advice.

[0076] Step 12:

[0077] The server runs a matching algorithm to select the most suitable senior mentor based on the user's questions and concerns, the senior mentor's skill set, and user ratings.

[0078] Step 13:

[0079] The server presents information about the selected senior mentor to the user's terminal.

[0080] Step 14:

[0081] Once the user selects a suitable senior mentor from the candidates, the information is sent to the server.

[0082] Step 15:

[0083] The server compares the schedules of the user and the selected senior mentor and suggests the most suitable date and time.

[0084] Step 16:

[0085] The user's terminal and the senior mentor's terminal check the proposed date and time, and return to the server their consent or desire to amend it.

[0086] Step 17:

[0087] The server confirms the date and time agreed upon by both the user and the senior mentor as the schedule, and again notifies the details to both users' terminals.

[0088] Step 18:

[0089] The senior mentor visits the user's home at a fixed date and time and provides the necessary support (e.g., housework support, childcare support).

[0090] Step 19:

[0091] After the support is completed, the user's terminal displays a feedback form, allowing the user to input their opinions and evaluations of the support they received.

[0092] Step 20:

[0093] The server records the feedback received from the user and reflects it in the senior mentor's evaluation system. It also processes the senior mentor's evaluation in the same way.

[0094] In this way, the home support platform of the present invention provides professional advice and direct support in response to the user's concerns and requests.

[0095] Example 1

[0096] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0097] Modern families require immediate and appropriate advice and support for domestic worries and problems. However, in busy daily lives, it is not easy to immediately obtain the necessary support. Furthermore, there is a lack of mechanisms to utilize the wealth of experience and knowledge that older people possess and to strengthen their ties with the local community. An effective system to resolve these issues is needed.

[0098] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0099] In this invention, the server includes a means for users to input questions and concerns about their home, a means for a generative AI to analyze the input information and generate advice, and a means for selecting the most suitable mentor based on the mentor's skills and user ratings. This makes it possible to provide prompt and appropriate advice and support for problems and concerns within the home, as well as to provide elderly people with social roles and opportunities for interaction.

[0100] "User" refers to an individual who uses this system to input questions and concerns about their home and receive advice and support.

[0101] "Server" refers to the computer system that receives and sends information from users and mentors, and manages and processes the advice and feedback generated by the generative AI.

[0102] "Generative AI" refers to AI technology that has the ability to analyze received input information and generate appropriate advice.

[0103] "Advice" refers to solutions and suggestions provided by generative artificial intelligence based on the user's questions and concerns.

[0104] A "mentor" is a support provider, such as an older person, who has the skills and experience to provide support for the home.

[0105] "Skills" refers collectively to the knowledge and experience related to the specific support that a mentor can provide.

[0106] "User ratings" refer to feedback and ratings provided by users who have received support from a mentor in the past.

[0107] "Feedback" refers to evaluations and opinions about the support provided by users and mentors and about the system as a whole.

[0108] "Schedule" refers to the specific date and time for the user and mentor to provide support.

[0109] The present invention relates to a family support system that provides effective advice and support for questions and concerns of families through the cooperation of generative artificial intelligence (AI) and senior mentors. Specific embodiments for carrying out the invention are described below.

[0110] User registration and initial settings

[0111] Users access the system from their own devices and use a form to enter basic information (such as name, address, email address, and family concerns). The entered information is sent to the server, where data validation takes place. Once validation is complete, the server stores the data in a database. Similarly, senior mentors also use their own devices to enter basic information and skill sets, which are also sent to the server, where they are validated and stored in the database.

[0112] Enter your questions and concerns and receive answers from AI

[0113] Users enter questions or concerns about their home into a dedicated question form and send it to the server. The server passes the received question information to a generative AI. The generative AI analyzes the entered question and generates the most appropriate advice. The generated advice is sent back to the user's device via the server. For example, if a user enters, "I would like you to support my child's studies," the server sends this to the AI ​​as a prompt: "Please introduce me to a mentor who can provide support for my child's studies at home. My child is in the fifth grade of elementary school and particularly needs support with math and English."

[0114] Senior mentor matching

[0115] The server analyzes the user's questions and concerns and runs an algorithm to match them with an appropriate senior mentor. This algorithm considers the senior mentor's skill set and past user ratings to select the most suitable candidate. Information about the selected senior mentor is displayed on the user's device. For example, if a user enters "I would like some help with my child's studies," the server will present senior mentors with education-related skills and high user ratings.

[0116] Schedule adjustments

[0117] When the user and the selected senior mentor accept the proposal, the server checks their respective schedules and proposes the optimal date and time. If both parties agree on the optimal date and time, the date and time of the support is confirmed and the server notifies the user and the senior mentor of this information.

[0118] On-site support

[0119] The senior mentor visits the user's home at the confirmed date and time and provides the necessary support (for example, housework or childcare support). The progress and content of the support are sent to the server and recorded. For example, if the senior mentor prepares dinner, details such as the cooking procedure and the time it is ready are recorded on the server.

[0120] Feedback and Ratings

[0121] After receiving assistance, the user enters their opinions and evaluations into a feedback form on their device and sends it to the server. The server receives this feedback and reflects it in the senior mentor's evaluation system. Similarly, the senior mentor also enters feedback for the user and sends it to the server. This two-way feedback improves the quality of the entire system and the accuracy of the next match.

[0122] The home support system of the present invention utilizes generative AI models and the skills of senior mentors to reduce worries and burdens within the home, strengthen connections with the local community, and provide social roles and opportunities for interaction for the elderly.

[0123] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0124] Step 1: User registration and initial setup

[0125] When a user accesses the system for the first time, they enter basic information such as their name, address, email address, and family concerns into the registration form displayed on their terminal. This entered information is sent to the server. The server validates the received information and ensures that it is in the correct format. For example, it checks the format of the email address and whether any fields are required. Once validated, the information is stored in the database. Similarly, senior mentors use their terminals to enter basic information and skill sets and send it to the server. The server similarly validates this information and stores it in the database.

[0126] Step 2: Enter your question or concern

[0127] The user accesses a dedicated form for entering questions and concerns about their home and enters the details. For example, they might enter, "I would like some help with my child's studies," and press the send button. The entered information is sent to the server. The server then generates a prompt to pass the received question information to the generative AI model. For example, it generates a prompt such as, "Please introduce me to a mentor who can provide support for my child's studies at home. My child is in the fifth grade of elementary school and needs particular support with math and English."

[0128] Step 3: Generate answers with AI

[0129] The server sends the generated prompt to the generative AI model, which generates optimal advice based on the received prompt. For example, the generated advice might be, "To support children's learning, it is effective to repeatedly practice a specific subject for 30 minutes every day." This advice is then sent back to the server.

[0130] Step 4: Providing advice

[0131] The server provides the user with the advice returned by the generative AI model. Specifically, the advice is output in the form of a display on the user's device. By referring to this advice, the user can obtain specific measures to solve problems at home.

[0132] Step 5: Matching with a senior mentor

[0133] The server runs an algorithm that matches the most suitable senior mentor based on the user's questions and concerns, their skill sets, and user ratings. The input data is the user's question and the senior mentor's skill sets and rating data, and the output data is a list of suitable mentor candidates. For example, in response to a request to "help support my child's studies," the server selects and presents mentors with education-related skills and high ratings.

[0134] Step 6: Adjust your schedule

[0135] The server compares the schedules of the user and the selected senior mentor and proposes the optimal date and time. The input data is the time slots available to the user and mentor, and the output data is the optimal date and time for support that both parties agree on. Once both parties agree on this date and time, the date and time for support is confirmed. This confirmation information is notified to both the user and mentor via the server.

[0136] Step 7: Implementing on-site support

[0137] The senior mentor visits the user's home at the confirmed date and time and provides the promised support (e.g., housework or childcare support). The progress and status of the support are recorded in real time and sent to the server. For example, if dinner is prepared, the cooking steps and completion time are recorded. This allows the user to check the progress of the support.

[0138] Step 8: Feedback and Rating

[0139] After completing the assistance, the user enters their opinion and evaluation in a feedback form on their device and sends it to the server. The server receives this feedback and reflects it in the senior mentor's evaluation system. The senior mentor also enters feedback for the user on their device and sends it to the server. This improves the quality of the entire system and the accuracy of the next match.

[0140] (Application example 1)

[0141] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0142] Modern households face a variety of problems and worries, and require quick and appropriate solutions. However, there are many situations where it is difficult to receive reliable advice and support immediately. In particular, it is difficult to provide specialized household support when dealing with customers in physical stores. Another problem is that responding individually to every customer requires a huge amount of time and effort, placing a heavy burden on store staff. This has led to issues such as a decline in customer satisfaction and an increased burden on staff.

[0143] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0144] In this invention, the server includes a means for the user to input questions and concerns about the home, a means for the server to receive the user's input information and pass it to the generative AI, and a means for the generative AI to analyze the input information and generate advice, which enables the following effects.

[0145] 1. Users can input their questions or concerns through their smart devices, and advice will be provided through generative AI and senior mentors, enabling customers to receive quick and reliable advice.

[0146] 2. The server selects the most suitable senior mentor based on the advice, the senior mentor's skill set, and the user's ratings, and determines the date and time of support, ensuring that a senior mentor with the appropriate skills can respond quickly.

[0147] 3. By receiving feedback and reflecting it in the evaluation system, the quality of the entire system and the accuracy of the next match can be improved.

[0148] A "user" is a person who inputs questions or concerns about the home and receives advice or support using this system.

[0149] "Questions and concerns about the home" include various issues and concerns in everyday life, such as housework, child-rearing, and interior design.

[0150] A "smart device" is a portable electronic device that can connect to the Internet, such as a smartphone, smart glasses, or a head-mounted display.

[0151] "Generative AI" is an AI program that analyzes information entered by the user and provides optimal advice based on that information.

[0152] The "server" is an information processing device that manages information for the entire system, exchanges data with generative AI, selects senior mentors, and coordinates schedules.

[0153] A "senior mentor" is a senior citizen who provides advice and support to help users solve their household problems.

[0154] A "skill set" is the collection of knowledge, experience, specific abilities and qualifications that a senior mentor possesses.

[0155] "User ratings" are the results of feedback and ratings given to senior mentors by past users.

[0156] "Schedule adjustment" is the process of determining the most suitable date and time for support based on the availability of the user and senior mentor.

[0157] "Feedback" refers to the act of a user inputting their thoughts and evaluations of the support they have received, and this data is reflected in the senior mentor's evaluation system.

[0158] "Interior consultation" refers to the act of providing advice on home decoration, furniture placement, etc.

[0159] This invention relates to a family support platform, which is a system that provides advice on family questions and concerns through the cooperation of generative artificial intelligence (AI) and senior mentors. Specific embodiments for implementing the present invention will be described below.

[0160] 1. User registration and initial settings

[0161] Users access the application using a device such as a smartphone. When they access it for the first time, a form is displayed in which they can enter basic information (such as name, address, email address, and family concerns). The information they enter is sent to the server, where it is validated and then saved in a database. Senior mentors also enter their own basic information and skill set and send it to the server. This completes the registration of the user and senior mentor.

[0162] 2. Input your questions and concerns and receive answers from AI

[0163] Users input questions or concerns about their home through their smart device. The input information is sent to a server and passed to a generative AI. The AI ​​analyzes the input information and generates appropriate advice. This advice is then sent back to the user's smart device via the server.

[0164] 3. Senior mentor matching

[0165] The server runs an algorithm to select the most suitable senior mentor based on the user's concerns, the senior mentor's skill set, and the user's ratings. Information on the matched senior mentor is then presented to the user.

[0166] 4. Adjust your schedule

[0167] If both the user and the senior mentor accept the proposal, the server compares their schedules and proposes the optimal date and time. The date and time agreed upon by both parties is confirmed and the date and time of the support is decided.

[0168] 5. On-site support

[0169] The senior mentor visits the user's home at the specified date and time and provides the necessary support, such as housework assistance, childcare assistance, interior design advice, etc. The content of the support and progress are sent to the server and recorded.

[0170] 6. Feedback and Ratings

[0171] After completing the support, the user enters their evaluation through a feedback form. The feedback is sent to the server and reflected in the senior mentor's evaluation system. Senior mentors can also enter their evaluations and thoughts about the user. This improves the overall quality of the system and the accuracy of the next match.

[0172] Hardware and software used

[0173] Server: The server manages the database, exchanges data with the generative AI, adjusts schedules, and manages the evaluation system. Specifically, Django (web framework) and PostgreSQL (database) are used.

[0174] Generative AI: Generative AI, such as OpenAI's GPT-3 model, is used to analyze users' questions and concerns and generate appropriate advice.

[0175] Smart devices: Smartphones, smart glasses, head-mounted displays, etc. are used by users to input questions or concerns and receive advice.

[0176] Examples of specific examples and prompts

[0177] For example, if a user inputs a request for home interior design advice, the generative AI will generate detailed advice such as "change the color of the curtains in the living room, add plants, and adjust the lighting."

[0178] Prompt Sentence Examples

[0179] I'd like to consult with a home support platform application about recommended interior changes. I'd like specific advice, such as changing the color of the curtains in the living room or adding some plants.

[0180] Through this system, users can quickly and appropriately resolve various family-related issues, and senior mentors can gain social roles and opportunities for interaction.

[0181] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0182] Step 1:

[0183] User registration and initial settings

[0184] Users access the application using a device such as a smartphone. When they access it for the first time, a form is displayed in which they can enter basic information (such as name, address, email address, and family concerns). The information entered by the user is sent to the server. The server receives the information, validates it, and stores it in a database. Senior mentors also enter their own basic information and skill set and send it to the server.

[0185] Step 2:

[0186] Enter your questions and concerns

[0187] Users input questions or concerns about their home through their smart devices. When a user inputs a question or concern and presses the send button, the information is sent to the server. The server receives this input information and passes it to the generative AI.

[0188] Step 3:

[0189] Answer generation using generative artificial intelligence

[0190] The server passes the received questions and concerns to a generative AI, which analyzes the input information and generates optimal advice. During this process, an AI model (e.g., GPT-3) understands the context and constructs appropriate solutions and advice. The generated advice is then sent back to the server.

[0191] Step 4:

[0192] Conveying advice

[0193] The server receives the advice sent back from the generative AI and sends it back to the user's smart device, where the user can check the content of the advice.

[0194] Step 5:

[0195] Senior mentor matching

[0196] The server runs an algorithm to select the most suitable senior mentor based on the user's concerns, the senior mentor's skill set, and the user's ratings. When the algorithm is run, the senior mentor's past ratings and areas of expertise are taken into consideration. The server then presents information about the selected senior mentor to the user.

[0197] Step 6:

[0198] Schedule adjustment

[0199] If both the user and the senior mentor accept the proposal, the server compares their schedules and proposes the optimal date and time. If the proposed date and time is approved by both parties, the server confirms the date and time and notifies both parties.

[0200] Step 7:

[0201] On-site support

[0202] The senior mentor will visit the user's home at the agreed date and time and provide the necessary support. For example, specific support such as housework assistance, childcare assistance, and interior design advice will be provided. The senior mentor will then send the support process and results to the server as recorded data.

[0203] Step 8:

[0204] Feedback and Ratings

[0205] After completing the support, the user enters their evaluation through a feedback form. The feedback information entered by the user is sent to the server and reflected in the senior mentor's evaluation system. Senior mentors can also enter their evaluations and thoughts about the user. The server stores this feedback information in a database and uses it to improve the quality of the entire system.

[0206] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0207] The present invention provides a system that combines a home support platform with an emotion engine to provide advice and support that takes into account the user's emotional state. Specific embodiments for carrying out the present invention will be described below.

[0208] Program processing and system configuration

[0209] 1. User registration and initial settings

[0210] When the user accesses the site for the first time, the user's device displays a registration form for entering basic information (such as name, address, email address, and family concerns). The server receives the information entered by the user, validates it, and stores it in a database. Similarly, the senior mentor's device displays a form for entering the senior mentor's basic information and skill set, and sends the entered data to the server. The server also validates the information entered by the senior mentor and stores it in a database.

[0211] 2. Inputting questions and concerns and emotion recognition

[0212] The user's device provides a dedicated form for inputting questions or concerns about the home. When the user inputs and submits the question or concern, the server passes the information to the emotion engine, which analyzes the user's emotional state from the input information.

[0213] 3. AI-generated and tailored advice

[0214] The server passes the emotional state analyzed by the emotion engine to the generative AI. The generative AI analyzes the user's question, concerns, and emotional state, and generates optimal advice. Because the emotional state is taken into consideration, if the user is feeling stressed, for example, advice including a gentler tone and stress reduction measures will be generated. The generated advice is sent back to the user's device via the server and displayed to the user.

[0215] As a specific example, if a user asks for advice about their child not studying, but the emotion engine detects stress or anxiety, the generative AI will provide advice such as, "Start by creating a relaxing environment. It's also important to spend time relaxing with your child."

[0216] 4. Senior mentor matching

[0217] The server runs a matching algorithm to select the most suitable senior mentor based on the user's question or concern, emotional state, the senior mentor's skill set, and user ratings. The user's emotional state is also taken into consideration, so if the emotional state is negative, for example, a senior mentor with high responsiveness and empathy will be prioritized. The server then presents information about the selected senior mentor to the user.

[0218] 5. Adjust your schedule

[0219] If both the user and the selected senior mentor accept the proposal, the server compares their schedules and proposes the optimal date and time. If the user and the senior mentor agree on the optimal date and time, the date and time of the support is confirmed.

[0220] 6. On-site support

[0221] The senior mentor visits the user's home at the specified date and time to provide necessary support such as housework assistance and childcare assistance. The content of the assistance and progress are sent to the server and recorded.

[0222] For example, if a senior mentor prepares dinner at the user's request, details such as the cooking steps and the time it will be ready will be recorded.

[0223] 7. Feedback and Ratings

[0224] After the support is completed, the user's device displays a feedback form, allowing the user to enter their opinion and evaluation of the support they received. The server receives the feedback and reflects it in the senior mentor's evaluation system. It also provides a feedback function to senior mentors, allowing them to enter their evaluation and thoughts about the user. This improves the quality of the entire system and the accuracy of the next match.

[0225] In this way, the home support platform of the present invention is a system that provides more appropriate and personalized support to users by utilizing an emotion engine that can recognize and respond to the user's emotional state, generative AI, and senior mentors, thereby reducing the burden on families, strengthening ties in the local community, and providing social roles and opportunities for elderly people to interact.

[0226] The processing flow will be explained below.

[0227] Step 1:

[0228] When the user accesses the site for the first time, the user's device displays a registration form for entering basic information (such as name, address, email address, and household concerns).

[0229] Step 2:

[0230] The user enters the necessary information and clicks the registration button.

[0231] Step 3:

[0232] The server receives the information entered by the user and performs validation. If the input data is valid, it is saved in the database. At the same time, a welcome message is displayed on the user's terminal.

[0233] Step 4:

[0234] The senior mentor's device also displays a registration form where the senior mentor can enter their skills, background, and support details.

[0235] Step 5:

[0236] The senior mentor enters the required information and clicks the registration button.

[0237] Step 6:

[0238] The server receives the information entered by the senior mentor, validates it, and if the input data is valid, stores it in the database.

[0239] Step 7:

[0240] The user's device displays a dedicated form where the user can enter questions or concerns about their home. The user enters their question or concern and clicks the send button.

[0241] Step 8:

[0242] The server receives the user's input information and passes it to the emotion engine.

[0243] Step 9:

[0244] The emotion engine analyzes the user's emotional state (stress, anxiety, joy, etc.) from their input information.

[0245] Step 10:

[0246] The emotion engine sends the analysis results to the server.

[0247] Step 11:

[0248] The server passes the emotional state analyzed by the emotion engine to the generative AI.

[0249] Step 12:

[0250] Generative AI analyzes the user's questions, concerns, and emotional state to generate optimal advice.

[0251] Step 13:

[0252] The server receives the generated advice and returns it to the user's terminal.

[0253] Step 14:

[0254] The user's terminal displays the received advice.

[0255] Step 15:

[0256] The server runs a matching algorithm to select the most suitable senior mentor based on the user's question or concern, emotional state, the senior mentor's skill set, and user ratings.

[0257] Step 16:

[0258] The server presents information about the selected senior mentor to the user's terminal.

[0259] Step 17:

[0260] Once the user selects a suitable senior mentor from the candidates, the information is sent to the server.

[0261] Step 18:

[0262] The server compares the schedules of the user and the selected senior mentor and suggests the most suitable date and time.

[0263] Step 19:

[0264] The user's terminal and the senior mentor's terminal check the proposed date and time, and return to the server their consent or desire to amend it.

[0265] Step 20:

[0266] The server confirms the date and time agreed upon by both the user and the senior mentor as the schedule, and again notifies the details to both users' terminals.

[0267] Step 21:

[0268] The senior mentor visits the user's home at a fixed date and time and provides the necessary support (e.g., housework support, childcare support).

[0269] Step 22:

[0270] After the support is completed, the user's terminal displays a feedback form, allowing the user to input their opinions and evaluations of the support they received.

[0271] Step 23:

[0272] The server records the feedback received from the user and reflects it in the senior mentor's evaluation system. It also processes the senior mentor's evaluation in the same way.

[0273] Step 24:

[0274] The server stores all feedback in a database and analyzes the data to reflect it in the next matching algorithm.

[0275] Example 2

[0276] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0277] Conventional home support platforms provide uniform advice and support without considering the user's emotional state, which means they are unable to fully alleviate the stress and frustration felt by users. This results in problems that make it difficult to resolve family problems and reduces user satisfaction. Another issue is the low accuracy of matching users with senior mentors, which limits the efficiency and effectiveness of support.

[0278] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0279] In this invention, the server includes a means for a user to input questions and concerns about the home, a means for an emotion engine to analyze the user's emotional state, and a means for a generative artificial intelligence to generate and adjust advice taking into account the user's input information and emotional state. This makes it possible to provide personalized advice that reflects the user's emotional state, resulting in effective solutions to home problems.

[0280] "User" refers to an individual with a household concern or question who uses this system.

[0281] "Device" refers to the electronic device used by users and senior mentors to access the system, such as a smartphone, tablet, or PC.

[0282] "Server" refers to the computer system that processes and stores information received from Users and Senior Mentors and manages the entire system.

[0283] An "emotion engine" refers to software or algorithms that analyze information entered by a user and recognize the user's emotional state (e.g., stress, anxiety, joy, etc.).

[0284] "Generative artificial intelligence (AI)" refers to an AI system that has the ability to generate optimal advice based on a user's questions, concerns, and emotional state.

[0285] "Advice" refers to the advice or instructions that generative artificial intelligence provides to solve a user's questions or concerns.

[0286] "Senior Mentor" refers to an experienced individual who is responsible for providing family support to a user.

[0287] "Support" refers to specific services such as housework assistance and childcare support that senior mentors provide by visiting users' homes.

[0288] "Feedback" refers to the user's opinions and evaluations of the support they have received, as well as the evaluations and impressions that senior mentors provide to users.

[0289] The "evaluation system" refers to a system that collects and analyzes feedback from users and senior mentors to improve the accuracy of matching and service quality for the next time.

[0290] "Matching algorithm" refers to a calculation method for selecting the most suitable senior mentor based on the content of the user's question or concern, emotional state, the senior mentor's skill set, and user evaluation.

[0291] "Database" refers to data storage for saving and managing data such as user information, senior mentor information, questions and concerns, support details, and feedback processed by the system.

[0292] "Validation" refers to the process by which the server verifies that the information entered by the user or senior mentor is accurate and complete.

[0293] "Personalization" refers to optimizing the advice and assistance provided based on the individual characteristics and emotional state of each user.

[0294] MODE FOR CARRYING OUT THE INVENTION

[0295] The present invention provides a system that combines a home support platform with an emotion engine to provide advice and support that takes into account the user's emotional state. Specific embodiments for carrying out the present invention will be described below.

[0296] User registration and initial settings

[0297] When the user accesses the site for the first time, the user's device displays a registration form for entering basic information (name, address, email address, family concerns, etc.). The server receives the information entered by the user, validates it, and stores it in a database. Similarly, the senior mentor's device displays a form for entering the senior mentor's basic information and skill set, and sends the entered data to the server. The server also validates the information entered by the senior mentor and stores it in a database. For example, MySQL or PostgreSQL is used as the database.

[0298] Inputting questions and concerns and recognizing emotions

[0299] The user's device provides a dedicated form for entering questions or concerns about the home. When the user enters and submits their question or concern, the server receives this information and passes it to the emotion engine. The emotion engine uses natural language processing (NLP) technology to analyze the user's emotional state from the information they input. Specifically, it identifies emotions such as stress, anxiety, and joy.

[0300] AI-powered advice generation and tailoring

[0301] The server passes the emotional state analyzed by the emotion engine to a generative artificial intelligence (AI). The generative AI generates optimal advice based on the user's questions, concerns, and emotional state. Because the emotional state is taken into consideration, if the user is feeling stressed, for example, advice including a gentler tone and stress reduction measures will be generated. The generated advice is sent back to the user's device via the server and displayed to the user.

[0302] Examples:

[0303] If a user asks for advice about their child not studying, but the emotion engine detects stress or anxiety, the generative AI will provide advice such as, "Start by creating a relaxing environment. It's also important to spend time relaxing with your child."

[0304] Example prompt sentence:

[0305] "Please advise on my child not studying. The user seems to be experiencing stress and anxiety."

[0306] Senior mentor matching

[0307] The server runs a matching algorithm to select the most suitable senior mentor based on the user's question or concern, emotional state, the senior mentor's skill set, and user ratings. The server also takes into account the user's emotional state, so if the emotional state is negative, for example, a senior mentor with high responsiveness and empathy will be prioritized. The server then presents information about the selected senior mentor to the user.

[0308] Schedule adjustments

[0309] If both the user and the selected senior mentor accept the proposal, the server compares their schedules and proposes the optimal date and time. If the user and the senior mentor agree on the optimal date and time, the date and time of the support is confirmed.

[0310] On-site support

[0311] The senior mentor visits the user's home at the specified date and time to provide necessary support such as housework assistance and childcare assistance. The content of the assistance and progress are sent to the server and recorded.

[0312] Examples:

[0313] If a senior mentor prepares dinner at the user's request, details such as the cooking steps and the time it is ready are recorded.

[0314] Feedback and Ratings

[0315] After the support is completed, the user's device displays a feedback form, allowing the user to enter their opinion and evaluation of the support they received. The server receives the feedback and reflects it in the senior mentor's evaluation system. It also provides a feedback function to senior mentors, allowing them to enter their evaluation and thoughts about the user. This improves the quality of the entire system and the accuracy of the next match.

[0316] In this way, the home support platform of the present invention is a system that utilizes emotion recognition technology and generative artificial intelligence to provide personalized support that takes into account the user's emotional state, thereby reducing the burden on the home and strengthening ties in the local community.

[0317] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0318] Step 1:

[0319] When a user accesses the system for the first time, the user's terminal displays a registration form for entering basic information.

[0320] Input: User's basic information (name, address, email address, family concerns, etc.)

[0321] What happens: The user enters information into the fields and clicks the "Submit" button.

[0322] Output: The basic information data entered by the user is sent to the server.

[0323] Step 2:

[0324] The server receives the basic information data sent by the user.

[0325] Input: User's basic information data

[0326] Specific operation: Validate the received data, check the format of the email address, and confirm required fields.

[0327] Output: Basic information data that has passed validation is saved in the database.

[0328] Step 3:

[0329] When the senior mentor accesses the system for the first time, the terminal of the senior mentor displays a registration form for inputting basic information and skill sets.

[0330] Input: Senior Mentor's basic information and skill set

[0331] Specific Actions: The senior mentor fills in the information in each field and clicks the "Submit" button.

[0332] Output: The basic information and skill set data entered by the senior mentor is sent to the server.

[0333] Step 4:

[0334] The server receives the basic information and skill set data sent by the senior mentor.

[0335] Input: Senior Mentor's basic information and skill set data

[0336] Specific operation: Validate the received data and check the format of the input data.

[0337] Output: The information of senior mentors who pass validation is saved in the database.

[0338] Step 5:

[0339] The user's terminal displays a form for entering questions or concerns about the home.

[0340] Input: Questions and concerns about the home

[0341] Specific operation: The user enters a question or concern and clicks the "Submit" button.

[0342] Output: Questions and concerns entered by the user are sent to the server.

[0343] Step 6:

[0344] The server receives questions and worry data sent by users.

[0345] Input: User questions and concerns

[0346] Specific operation: Pass the received data to the emotion engine.

[0347] Output: Data passed to the emotion engine

[0348] Step 7:

[0349] The emotion engine analyzes the user's questions and worries data to identify the user's emotional state.

[0350] Input: User questions and concerns

[0351] What it does: It uses natural language processing (NLP) techniques to analyze text and identify emotional states (stress, anxiety, joy, etc.).

[0352] Output: Emotional state data (type and degree of emotion)

[0353] Step 8:

[0354] The server passes the emotional state data analyzed by the emotion engine to a generative artificial intelligence (AI).

[0355] Input: Emotional state data

[0356] Specific operation: Emotional state data is passed as input to generative artificial intelligence.

[0357] Output: Emotional state data passed to the generative AI

[0358] Step 9:

[0359] Generative AI generates appropriate advice based on the user's questions, concerns, and emotional state data.

[0360] Input: User questions, concerns, and emotional state data

[0361] How it works: The AI ​​model analyzes both sets of data and generates optimal advice.

[0362] Output: Generated advice data

[0363] Example: If a user asks for advice about their child not studying, but the emotion engine detects stress or anxiety, the AI ​​will generate advice like, "Start by creating a relaxing environment. It's also important to spend time relaxing with your child."

[0364] Step 10:

[0365] The server returns the generated advice data to the user's terminal.

[0366] Input: Generated advice data

[0367] Specific operation: Advice data is sent to the user's device.

[0368] Output: Advice displayed on the user's terminal

[0369] Step 11:

[0370] The server runs a matching algorithm to select the most suitable senior mentor based on the user's question or concern, emotional state, the senior mentor's skill set, and user ratings.

[0371] Input: User questions and concerns, emotional state data, senior mentor skill data, user evaluation data

[0372] Specific operation: Apply a matching algorithm to select the most suitable senior mentor.

[0373] Output: Information about the selected senior mentor

[0374] Step 12:

[0375] The server compares the schedules of the user and senior mentor and suggests the best date and time.

[0376] Input: User's schedule data, Senior Mentor's schedule data

[0377] Specific behavior: Match schedules and suggest the best time and date.

[0378] Output: Suggested best time

[0379] Step 13:

[0380] The senior mentor will visit the user's home at the proposed date and time to provide assistance.

[0381] Input: Suggested best date and time

[0382] Specific actions: A senior mentor will visit the home at the proposed date and time to provide assistance with housework and childcare.

[0383] Output: Data on completed support activities

[0384] Step 14:

[0385] After the support is completed, the user's terminal displays a feedback form, allowing the user to input their opinions and evaluations of the support they received.

[0386] Input: User opinions and ratings

[0387] What happens: A user fills out a feedback form and clicks the "Submit" button.

[0388] Output: User feedback data

[0389] Step 15:

[0390] The server receives feedback from users and reflects it in the senior mentor's evaluation system, and also provides a feedback form to the senior mentor.

[0391] Input: User feedback data, Senior Mentor feedback data

[0392] Specific actions: Feedback data will be reflected in the evaluation system and the data will be used to improve matching accuracy and service quality next time.

[0393] Output: Updated rating system data

[0394] (Application example 2)

[0395] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0396] When providing meal suggestions or cooking assistance at home, suggestions or assistance that do not take into account the user's emotional state may not provide sufficient satisfaction. Furthermore, matching or responses that do not take the user's emotional state into account may lead to discrepancies between the provider and the user. Conventional methods have difficulty providing detailed advice based on emotions or efficiently matching providers.

[0397] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for the user to input questions, concerns, or emotional state related to the home, means for the server to receive the user's input information and pass it on to the emotion engine, and means for the emotion engine to analyze the user's emotional state and pass the results on to the generative AI. This makes it possible to match appropriate meal suggestions and providers such as chefs according to the user's emotional state.

[0398] A "user" is an individual who uses the system to ask questions or concerns about their home, as well as to seek meal suggestions.

[0399] An "emotion engine" is software or hardware for analyzing the user's emotional state from input information.

[0400] "Generative AI" is an AI system that analyzes a user's input information and emotional state and generates appropriate advice.

[0401] A "provider" is a person or organization that provides a service to a user, and includes chefs, housekeeping assistants, etc.

[0402] "Server" refers to a computer system that performs the central data processing and management of this system.

[0403] A "skill set" is a list of skills and techniques possessed by a provider, and is information for providing appropriate support to users.

[0404] "User Ratings" refers to other users' ratings and feedback on services provided in the past.

[0405] "Feedback" refers to evaluations and opinions given by users regarding the services provided.

[0406] "Emotional state" refers to the psychological state analyzed from the information entered by the user, examples of which include stress and relaxation.

[0407] 1. Overall system configuration

[0408] An embodiment of this invention is a system that provides advice and services that take into account a user's emotional state when they request meal suggestions or cooking assistance. This system is composed of a user terminal, a server, an emotion engine, a generative artificial intelligence, a provider terminal, etc.

[0409] 2. Hardware and Software Used

[0410] This system uses the following hardware and software:

[0411] Emotion engine: Uses various emotion analysis APIs, such as Microsoft Azure Emotion API and IBM Watson Tone Analyzer.

[0412] Generative AI: Use generative AI models such as OpenAI GPT-4.

[0413] Backend: Uses cloud computing services, such as AWS Lambda and its database service AWS RDS.

[0414] Frontend: Using React Native for smartphone applications.

[0415] Database: Use a relational database such as PostgreSQL.

[0416] 3. Data processing and calculation

[0417] User registration and initial settings

[0418] When a user accesses the system for the first time, he enters basic information (name, address, email address, etc.) in the user registration form. The server receives this information, validates it, and then stores it in the database.

[0419] Inputting questions and concerns and recognizing emotions

[0420] Users input questions and concerns about their home into the app and express their emotional state. This information is sent to the server and passed to the emotion engine. The emotion engine analyzes the user's emotional state from the input information and returns the results to the server.

[0421] Generating Advice

[0422] The server passes the emotional state data received from the emotion engine to the generative AI, which takes into account the user's questions, concerns, and emotional state to generate optimal advice. The advice is then sent back to the user from the server and displayed on the app.

[0423] Provider matching

[0424] The server selects the best provider for the user based on advice generated by the emotion engine and generative AI. The provider's skill set and past reviews are also taken into consideration. For example, if the user's emotional state is unstable, a chef with a high level of empathy will be prioritized.

[0425] Scheduling and feedback

[0426] The system checks the schedules of the user and provider and proposes the optimal date and time. If this is accepted, the date and time of the service is confirmed and the provider provides the service at the specified date and time. After that, the user's feedback is sent to the server, stored in a database, and reflected in the rating system.

[0427] 4. Specific Examples

[0428] When a user types "I'm very tired today," and the emotion engine analyzes "tired," the generative AI suggests a relaxing meal. The meal suggestion includes "grilled salmon and steamed vegetables," and the system matches the user with a highly rated chef near the user. The following prompt appears on the user's smartphone:

[0429] "The user is extremely tired. Based on this emotional state, suggest a relaxing meal."

[0430] This system will significantly improve satisfaction at home by suggesting meals based on the user's emotional state and matching them with chefs and other providers.

[0431] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0432] Step 1:

[0433] On the user's device, the user inputs questions, concerns, and emotional state about the home. Specifically, the user enters text into an input form within the app. This becomes input data and is sent to the server.

[0434] Step 2:

[0435] The server passes the received user input data to the emotion engine. The emotion engine analyzes the user's emotional state from the text and returns the result (e.g., stress, relaxation, etc.) to the server. The data processing performed in this step is text analysis, and generates output data called the emotional state.

[0436] Step 3:

[0437] The server passes the analyzed emotional state to a generative AI (such as GPT-4). The generative AI receives the user's questions, concerns, and emotional state as input data and generates optimal advice. This advice is returned to the server in text format. The data calculation in this step is advice generation using natural language processing.

[0438] Step 4:

[0439] The server returns the advice received from the generative AI to the user. This advice is displayed on the user's device. The specific processing performed here involves API communication and retrieval from a database.

[0440] Step 5:

[0441] The server selects an appropriate provider based on the generated advice, emotional state, and user input information. The provider's skill set is compared with the user rating database to perform matching. Information about the selected provider is presented to the user. The data calculation in this step is the execution of a matching algorithm.

[0442] Step 6:

[0443] The server adjusts the schedules of the user and provider and proposes the optimal date and time. The proposed date and time are sent to the user's device and the provider's device, and both parties confirm them. In this step, the date and time are adjusted using the calendar API.

[0444] Step 7:

[0445] The provider will visit the user's designated location at the date and time determined by the server, and provide meal suggestions and cooking assistance services. At this time, the provider's device will report the progress to the server. Specific operations include GPS tracking and check-in functions.

[0446] Step 8:

[0447] After the service is provided, the user enters feedback and sends it to the server. The server stores the feedback in a database and reflects it in the provider's evaluation system. In this step, the questionnaire form and database are updated.

[0448] These processing steps realize an automated emotion-based meal suggestion and cooking assistance system.

[0449] 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 a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the 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.

[0450] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0451] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0452] [Second embodiment]

[0453] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0454] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0455] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. 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. The database 24 and the communication I / F 26 are also 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).

[0456] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0457] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0458] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0459] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0460] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0461] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0462] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0463] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0464] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0465] The present invention relates to a family support platform, which is a system that provides advice and support for family questions and concerns through the cooperation of generative artificial intelligence (AI) and senior mentors. Specific embodiments for implementing the present invention will be described below.

[0466] Program processing and system configuration

[0467] 1. User registration and initial settings

[0468] When the user accesses the site for the first time, the user's device displays a registration form for entering basic information (such as name, address, email address, and family concerns). The server receives the information entered by the user, validates it, and stores it in a database. Similarly, the senior mentor's device displays a form for entering the senior mentor's basic information and skill set, and sends the entered data to the server. The server also validates the information entered by the senior mentor and stores it in a database.

[0469] 2. Input your questions and concerns and receive answers from AI

[0470] The user's device provides a dedicated form for entering questions and concerns about the home. When the user enters and submits their concerns, the server passes this information to a generative AI. The generative AI analyzes the question or concern and generates optimal advice. The generated advice is then sent back to the user's device via the server and displayed to the user.

[0471] 3. Senior mentor matching

[0472] The server runs an algorithm to match users with appropriate senior mentors based on their questions and concerns. The algorithm selects the best candidates by taking into account the senior mentors' skill sets and user ratings. The server then presents the selected senior mentors to the user.

[0473] As a specific example, if a user inputs "I would like some help with my child's studies," the server will select and suggest highly rated senior mentors who have education-related skills.

[0474] 4. Adjust your schedule

[0475] If both the user and the selected senior mentor accept the proposal, the server compares their schedules and proposes the optimal date and time. If the user and the senior mentor agree on the optimal date and time, the date and time of the support is confirmed.

[0476] 5. On-site support

[0477] The senior mentor visits the user's home at the specified date and time and provides the necessary support (e.g., housework support, childcare support). The support content and progress are sent to the server and recorded.

[0478] For example, if a senior mentor prepares dinner at the user's request, details such as the cooking steps and the time it will be ready will be recorded.

[0479] 6. Feedback and Ratings

[0480] After the support is completed, the user's device displays a feedback form, allowing the user to enter their opinion and evaluation of the support they received. The server receives the feedback and reflects it in the senior mentor's evaluation system. It also provides a feedback function to senior mentors, allowing them to enter their evaluation and thoughts about the user. This improves the quality of the entire system and the accuracy of the next match.

[0481] In this way, the home support platform of the present invention is a system that utilizes AI technology and senior mentors to reduce worries and burdens within the home, strengthen ties with the local community, and provide social roles and opportunities for interaction for the elderly.

[0482] The processing flow will be explained below.

[0483] Step 1:

[0484] When the user accesses the site for the first time, the user's device displays a registration form for entering basic information (such as name, address, email address, and household concerns).

[0485] Step 2:

[0486] The user enters the necessary information and clicks the registration button.

[0487] Step 3:

[0488] The server receives the information entered by the user and performs validation. If the input data is valid, it is saved in the database. At the same time, a welcome message is displayed on the user's terminal.

[0489] Step 4:

[0490] The senior mentor's device also displays a registration form where the senior mentor can enter their skills, background, and support details.

[0491] Step 5:

[0492] The senior mentor enters the required information and clicks the registration button.

[0493] Step 6:

[0494] The server receives the information entered by the senior mentor, validates it, and if the input data is valid, stores it in the database.

[0495] Step 7:

[0496] The user's device displays a dedicated form where the user can enter questions or concerns about their home. The user enters their question or concern and clicks the send button.

[0497] Step 8:

[0498] The server receives the user's input information and passes it to the generative artificial intelligence.

[0499] Step 9:

[0500] Generative AI analyzes users' questions and concerns and generates optimal advice.

[0501] Step 10:

[0502] The server receives the generated advice and returns it to the user's terminal.

[0503] Step 11:

[0504] The user's terminal displays the received advice.

[0505] Step 12:

[0506] The server runs a matching algorithm to select the most suitable senior mentor based on the user's questions and concerns, the senior mentor's skill set, and user ratings.

[0507] Step 13:

[0508] The server presents information about the selected senior mentor to the user's terminal.

[0509] Step 14:

[0510] Once the user selects a suitable senior mentor from the candidates, the information is sent to the server.

[0511] Step 15:

[0512] The server compares the schedules of the user and the selected senior mentor and suggests the most suitable date and time.

[0513] Step 16:

[0514] The user's terminal and the senior mentor's terminal check the proposed date and time, and return to the server their consent or desire to amend it.

[0515] Step 17:

[0516] The server confirms the date and time agreed upon by both the user and the senior mentor as the schedule, and again notifies the details to both users' terminals.

[0517] Step 18:

[0518] The senior mentor visits the user's home at a fixed date and time and provides the necessary support (e.g., housework support, childcare support).

[0519] Step 19:

[0520] After the support is completed, the user's terminal displays a feedback form, allowing the user to input their opinions and evaluations of the support they received.

[0521] Step 20:

[0522] The server records the feedback received from the user and reflects it in the senior mentor's evaluation system. It also processes the senior mentor's evaluation in the same way.

[0523] In this way, the home support platform of the present invention provides professional advice and direct support in response to the user's concerns and requests.

[0524] Example 1

[0525] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0526] Modern families require immediate and appropriate advice and support for domestic worries and problems. However, in busy daily lives, it is not easy to immediately obtain the necessary support. Furthermore, there is a lack of mechanisms to utilize the wealth of experience and knowledge that older people possess and to strengthen their ties with the local community. An effective system to resolve these issues is needed.

[0527] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0528] In this invention, the server includes a means for users to input questions and concerns about their home, a means for a generative AI to analyze the input information and generate advice, and a means for selecting the most suitable mentor based on the mentor's skills and user ratings. This makes it possible to provide prompt and appropriate advice and support for problems and concerns within the home, as well as to provide elderly people with social roles and opportunities for interaction.

[0529] "User" refers to an individual who uses this system to input questions and concerns about their home and receive advice and support.

[0530] "Server" refers to the computer system that receives and sends information from users and mentors, and manages and processes the advice and feedback generated by the generative AI.

[0531] "Generative AI" refers to AI technology that has the ability to analyze received input information and generate appropriate advice.

[0532] "Advice" refers to solutions and suggestions provided by generative artificial intelligence based on the user's questions and concerns.

[0533] A "mentor" is a support provider, such as an older person, who has the skills and experience to provide support for the home.

[0534] "Skills" refers collectively to the knowledge and experience related to the specific support that a mentor can provide.

[0535] "User ratings" refer to feedback and ratings provided by users who have received support from a mentor in the past.

[0536] "Feedback" refers to evaluations and opinions about the support provided by users and mentors and about the system as a whole.

[0537] "Schedule" refers to the specific date and time for the user and mentor to provide support.

[0538] The present invention relates to a family support system that provides effective advice and support for questions and concerns of families through the cooperation of generative artificial intelligence (AI) and senior mentors. Specific embodiments for carrying out the invention are described below.

[0539] User registration and initial settings

[0540] Users access the system from their own devices and use a form to enter basic information (such as name, address, email address, and family concerns). The entered information is sent to the server, where data validation takes place. Once validation is complete, the server stores the data in a database. Similarly, senior mentors also use their own devices to enter basic information and skill sets, which are also sent to the server, where they are validated and stored in the database.

[0541] Enter your questions and concerns and receive answers from AI

[0542] Users enter questions or concerns about their home into a dedicated question form and send it to the server. The server passes the received question information to a generative AI. The generative AI analyzes the entered question and generates the most appropriate advice. The generated advice is sent back to the user's device via the server. For example, if a user enters, "I would like you to support my child's studies," the server sends this to the AI ​​as a prompt: "Please introduce me to a mentor who can provide support for my child's studies at home. My child is in the fifth grade of elementary school and particularly needs support with math and English."

[0543] Senior mentor matching

[0544] The server analyzes the user's questions and concerns and runs an algorithm to match them with an appropriate senior mentor. This algorithm considers the senior mentor's skill set and past user ratings to select the most suitable candidate. Information about the selected senior mentor is displayed on the user's device. For example, if a user enters "I would like some help with my child's studies," the server will present senior mentors with education-related skills and high user ratings.

[0545] Schedule adjustments

[0546] When the user and the selected senior mentor accept the proposal, the server checks their respective schedules and proposes the optimal date and time. If both parties agree on the optimal date and time, the date and time of the support is confirmed and the server notifies the user and the senior mentor of this information.

[0547] On-site support

[0548] The senior mentor visits the user's home at the confirmed date and time and provides the necessary support (for example, housework or childcare support). The progress and content of the support are sent to the server and recorded. For example, if the senior mentor prepares dinner, details such as the cooking procedure and the time it is ready are recorded on the server.

[0549] Feedback and Ratings

[0550] After receiving assistance, the user enters their opinions and evaluations into a feedback form on their device and sends it to the server. The server receives this feedback and reflects it in the senior mentor's evaluation system. Similarly, the senior mentor also enters feedback for the user and sends it to the server. This two-way feedback improves the quality of the entire system and the accuracy of the next match.

[0551] The home support system of the present invention utilizes generative AI models and the skills of senior mentors to reduce worries and burdens within the home, strengthen connections with the local community, and provide social roles and opportunities for interaction for the elderly.

[0552] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0553] Step 1: User registration and initial setup

[0554] When a user accesses the system for the first time, they enter basic information such as their name, address, email address, and family concerns into the registration form displayed on their terminal. This entered information is sent to the server. The server validates the received information and ensures that it is in the correct format. For example, it checks the format of the email address and whether any fields are required. Once validated, the information is stored in the database. Similarly, senior mentors use their terminals to enter basic information and skill sets and send it to the server. The server similarly validates this information and stores it in the database.

[0555] Step 2: Enter your question or concern

[0556] The user accesses a dedicated form for entering questions and concerns about their home and enters the details. For example, they might enter, "I would like some help with my child's studies," and press the send button. The entered information is sent to the server. The server then generates a prompt to pass the received question information to the generative AI model. For example, it generates a prompt such as, "Please introduce me to a mentor who can provide support for my child's studies at home. My child is in the fifth grade of elementary school and needs particular support with math and English."

[0557] Step 3: Generate answers with AI

[0558] The server sends the generated prompt to the generative AI model, which generates optimal advice based on the received prompt. For example, the generated advice might be, "To support children's learning, it is effective to repeatedly practice a specific subject for 30 minutes every day." This advice is then sent back to the server.

[0559] Step 4: Providing advice

[0560] The server provides the user with the advice returned by the generative AI model. Specifically, the advice is output in the form of a display on the user's device. By referring to this advice, the user can obtain specific measures to solve problems at home.

[0561] Step 5: Matching with a senior mentor

[0562] The server runs an algorithm that matches the most suitable senior mentor based on the user's questions and concerns, their skill sets, and user ratings. The input data is the user's question and the senior mentor's skill sets and rating data, and the output data is a list of suitable mentor candidates. For example, in response to a request to "help support my child's studies," the server selects and presents mentors with education-related skills and high ratings.

[0563] Step 6: Adjust your schedule

[0564] The server compares the schedules of the user and the selected senior mentor and proposes the optimal date and time. The input data is the time slots available to the user and mentor, and the output data is the optimal date and time for support that both parties agree on. Once both parties agree on this date and time, the date and time for support is confirmed. This confirmation information is notified to both the user and mentor via the server.

[0565] Step 7: Implementing on-site support

[0566] The senior mentor visits the user's home at the confirmed date and time and provides the promised support (e.g., housework or childcare support). The progress and status of the support are recorded in real time and sent to the server. For example, if dinner is prepared, the cooking steps and completion time are recorded. This allows the user to check the progress of the support.

[0567] Step 8: Feedback and Rating

[0568] After completing the assistance, the user enters their opinion and evaluation in a feedback form on their device and sends it to the server. The server receives this feedback and reflects it in the senior mentor's evaluation system. The senior mentor also enters feedback for the user on their device and sends it to the server. This improves the quality of the entire system and the accuracy of the next match.

[0569] (Application example 1)

[0570] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0571] Modern households face a variety of problems and worries, and require quick and appropriate solutions. However, there are many situations where it is difficult to receive reliable advice and support immediately. In particular, it is difficult to provide specialized household support when dealing with customers in physical stores. Another problem is that responding individually to every customer requires a huge amount of time and effort, placing a heavy burden on store staff. This has led to issues such as a decline in customer satisfaction and an increased burden on staff.

[0572] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0573] In this invention, the server includes a means for the user to input questions and concerns about the home, a means for the server to receive the user's input information and pass it to the generative AI, and a means for the generative AI to analyze the input information and generate advice, which enables the following effects.

[0574] 1. Users can input their questions or concerns through their smart devices, and advice will be provided through generative AI and senior mentors, enabling customers to receive quick and reliable advice.

[0575] 2. The server selects the most suitable senior mentor based on the advice, the senior mentor's skill set, and the user's ratings, and determines the date and time of support, ensuring that a senior mentor with the appropriate skills can respond quickly.

[0576] 3. By receiving feedback and reflecting it in the evaluation system, the quality of the entire system and the accuracy of the next match can be improved.

[0577] A "user" is a person who inputs questions or concerns about the home and receives advice or support using this system.

[0578] "Questions and concerns about the home" include various issues and concerns in everyday life, such as housework, child-rearing, and interior design.

[0579] A "smart device" is a portable electronic device that can connect to the Internet, such as a smartphone, smart glasses, or a head-mounted display.

[0580] "Generative AI" is an AI program that analyzes information entered by the user and provides optimal advice based on that information.

[0581] The "server" is an information processing device that manages information for the entire system, exchanges data with generative AI, selects senior mentors, and coordinates schedules.

[0582] A "senior mentor" is a senior citizen who provides advice and support to help users solve their household problems.

[0583] A "skill set" is the collection of knowledge, experience, specific abilities and qualifications that a senior mentor possesses.

[0584] "User ratings" are the results of feedback and ratings given to senior mentors by past users.

[0585] "Schedule adjustment" is the process of determining the most suitable date and time for support based on the availability of the user and senior mentor.

[0586] "Feedback" refers to the act of a user inputting their thoughts and evaluations of the support they have received, and this data is reflected in the senior mentor's evaluation system.

[0587] "Interior consultation" refers to the act of providing advice on home decoration, furniture placement, etc.

[0588] This invention relates to a family support platform, which is a system that provides advice on family questions and concerns through the cooperation of generative artificial intelligence (AI) and senior mentors. Specific embodiments for implementing the present invention will be described below.

[0589] 1. User registration and initial settings

[0590] Users access the application using a device such as a smartphone. When they access it for the first time, a form is displayed in which they can enter basic information (such as name, address, email address, and family concerns). The information they enter is sent to the server, where it is validated and then saved in a database. Senior mentors also enter their own basic information and skill set and send it to the server. This completes the registration of the user and senior mentor.

[0591] 2. Input your questions and concerns and receive answers from AI

[0592] Users input questions or concerns about their home through their smart device. The input information is sent to a server and passed to a generative AI. The AI ​​analyzes the input information and generates appropriate advice. This advice is then sent back to the user's smart device via the server.

[0593] 3. Senior mentor matching

[0594] The server runs an algorithm to select the most suitable senior mentor based on the user's concerns, the senior mentor's skill set, and the user's ratings. Information on the matched senior mentor is then presented to the user.

[0595] 4. Adjust your schedule

[0596] If both the user and the senior mentor accept the proposal, the server compares their schedules and proposes the optimal date and time. The date and time agreed upon by both parties is confirmed and the date and time of the support is decided.

[0597] 5. On-site support

[0598] The senior mentor visits the user's home at the specified date and time and provides the necessary support, such as housework assistance, childcare assistance, interior design advice, etc. The content of the support and progress are sent to the server and recorded.

[0599] 6. Feedback and Ratings

[0600] After completing the support, the user enters their evaluation through a feedback form. The feedback is sent to the server and reflected in the senior mentor's evaluation system. Senior mentors can also enter their evaluations and thoughts about the user. This improves the overall quality of the system and the accuracy of the next match.

[0601] Hardware and software used

[0602] Server: The server manages the database, exchanges data with the generative AI, adjusts schedules, and manages the evaluation system. Specifically, Django (web framework) and PostgreSQL (database) are used.

[0603] Generative AI: Generative AI, such as OpenAI's GPT-3 model, is used to analyze users' questions and concerns and generate appropriate advice.

[0604] Smart devices: Smartphones, smart glasses, head-mounted displays, etc. are used by users to input questions or concerns and receive advice.

[0605] Examples of specific examples and prompts

[0606] For example, if a user inputs a request for home interior design advice, the generative AI will generate detailed advice such as "change the color of the curtains in the living room, add plants, and adjust the lighting."

[0607] Prompt Sentence Examples

[0608] I'd like to consult with a home support platform application about recommended interior changes. I'd like specific advice, such as changing the color of the curtains in the living room or adding some plants.

[0609] Through this system, users can quickly and appropriately resolve various family-related issues, and senior mentors can gain social roles and opportunities for interaction.

[0610] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0611] Step 1:

[0612] User registration and initial settings

[0613] Users access the application using a device such as a smartphone. When they access it for the first time, a form is displayed in which they can enter basic information (such as name, address, email address, and family concerns). The information entered by the user is sent to the server. The server receives the information, validates it, and stores it in a database. Senior mentors also enter their own basic information and skill set and send it to the server.

[0614] Step 2:

[0615] Enter your questions and concerns

[0616] Users input questions or concerns about their home through their smart devices. When a user inputs a question or concern and presses the send button, the information is sent to the server. The server receives this input information and passes it to the generative AI.

[0617] Step 3:

[0618] Answer generation using generative artificial intelligence

[0619] The server passes the received questions and concerns to a generative AI, which analyzes the input information and generates optimal advice. During this process, an AI model (e.g., GPT-3) understands the context and constructs appropriate solutions and advice. The generated advice is then sent back to the server.

[0620] Step 4:

[0621] Conveying advice

[0622] The server receives the advice sent back from the generative AI and sends it back to the user's smart device, where the user can check the content of the advice.

[0623] Step 5:

[0624] Senior mentor matching

[0625] The server runs an algorithm to select the most suitable senior mentor based on the user's concerns, the senior mentor's skill set, and the user's ratings. When the algorithm is run, the senior mentor's past ratings and areas of expertise are taken into consideration. The server then presents information about the selected senior mentor to the user.

[0626] Step 6:

[0627] Schedule adjustment

[0628] If both the user and the senior mentor accept the proposal, the server compares their schedules and proposes the optimal date and time. If the proposed date and time is approved by both parties, the server confirms the date and time and notifies both parties.

[0629] Step 7:

[0630] On-site support

[0631] The senior mentor will visit the user's home at the agreed date and time and provide the necessary support. For example, specific support such as housework assistance, childcare assistance, and interior design advice will be provided. The senior mentor will then send the support process and results to the server as recorded data.

[0632] Step 8:

[0633] Feedback and Ratings

[0634] After completing the support, the user enters their evaluation through a feedback form. The feedback information entered by the user is sent to the server and reflected in the senior mentor's evaluation system. Senior mentors can also enter their evaluations and thoughts about the user. The server stores this feedback information in a database and uses it to improve the quality of the entire system.

[0635] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0636] The present invention provides a system that combines a home support platform with an emotion engine to provide advice and support that takes into account the user's emotional state. Specific embodiments for carrying out the present invention will be described below.

[0637] Program processing and system configuration

[0638] 1. User registration and initial settings

[0639] When the user accesses the site for the first time, the user's device displays a registration form for entering basic information (such as name, address, email address, and family concerns). The server receives the information entered by the user, validates it, and stores it in a database. Similarly, the senior mentor's device displays a form for entering the senior mentor's basic information and skill set, and sends the entered data to the server. The server also validates the information entered by the senior mentor and stores it in a database.

[0640] 2. Inputting questions and concerns and emotion recognition

[0641] The user's device provides a dedicated form for inputting questions or concerns about the home. When the user inputs and submits the question or concern, the server passes the information to the emotion engine, which analyzes the user's emotional state from the input information.

[0642] 3. AI-generated and tailored advice

[0643] The server passes the emotional state analyzed by the emotion engine to the generative AI. The generative AI analyzes the user's question, concerns, and emotional state, and generates optimal advice. Because the emotional state is taken into consideration, if the user is feeling stressed, for example, advice including a gentler tone and stress reduction measures will be generated. The generated advice is sent back to the user's device via the server and displayed to the user.

[0644] As a specific example, if a user asks for advice about their child not studying, but the emotion engine detects stress or anxiety, the generative AI will provide advice such as, "Start by creating a relaxing environment. It's also important to spend time relaxing with your child."

[0645] 4. Senior mentor matching

[0646] The server runs a matching algorithm to select the most suitable senior mentor based on the user's question or concern, emotional state, the senior mentor's skill set, and user ratings. The user's emotional state is also taken into consideration, so if the emotional state is negative, for example, a senior mentor with high responsiveness and empathy will be prioritized. The server then presents information about the selected senior mentor to the user.

[0647] 5. Adjust your schedule

[0648] If both the user and the selected senior mentor accept the proposal, the server compares their schedules and proposes the optimal date and time. If the user and the senior mentor agree on the optimal date and time, the date and time of the support is confirmed.

[0649] 6. On-site support

[0650] The senior mentor visits the user's home at the specified date and time to provide necessary support such as housework assistance and childcare assistance. The content of the assistance and progress are sent to the server and recorded.

[0651] For example, if a senior mentor prepares dinner at the user's request, details such as the cooking steps and the time it will be ready will be recorded.

[0652] 7. Feedback and Ratings

[0653] After the support is completed, the user's device displays a feedback form, allowing the user to enter their opinion and evaluation of the support they received. The server receives the feedback and reflects it in the senior mentor's evaluation system. It also provides a feedback function to senior mentors, allowing them to enter their evaluation and thoughts about the user. This improves the quality of the entire system and the accuracy of the next match.

[0654] In this way, the home support platform of the present invention is a system that provides more appropriate and personalized support to users by utilizing an emotion engine that can recognize and respond to the user's emotional state, generative AI, and senior mentors, thereby reducing the burden on families, strengthening ties in the local community, and providing social roles and opportunities for elderly people to interact.

[0655] The processing flow will be explained below.

[0656] Step 1:

[0657] When the user accesses the site for the first time, the user's device displays a registration form for entering basic information (such as name, address, email address, and household concerns).

[0658] Step 2:

[0659] The user enters the necessary information and clicks the registration button.

[0660] Step 3:

[0661] The server receives the information entered by the user and performs validation. If the input data is valid, it is saved in the database. At the same time, a welcome message is displayed on the user's terminal.

[0662] Step 4:

[0663] The senior mentor's device also displays a registration form where the senior mentor can enter their skills, background, and support details.

[0664] Step 5:

[0665] The senior mentor enters the required information and clicks the registration button.

[0666] Step 6:

[0667] The server receives the information entered by the senior mentor, validates it, and if the input data is valid, stores it in the database.

[0668] Step 7:

[0669] The user's device displays a dedicated form where the user can enter questions or concerns about their home. The user enters their question or concern and clicks the send button.

[0670] Step 8:

[0671] The server receives the user's input information and passes it to the emotion engine.

[0672] Step 9:

[0673] The emotion engine analyzes the user's emotional state (stress, anxiety, joy, etc.) from their input information.

[0674] Step 10:

[0675] The emotion engine sends the analysis results to the server.

[0676] Step 11:

[0677] The server passes the emotional state analyzed by the emotion engine to the generative AI.

[0678] Step 12:

[0679] Generative AI analyzes the user's questions, concerns, and emotional state to generate optimal advice.

[0680] Step 13:

[0681] The server receives the generated advice and returns it to the user's terminal.

[0682] Step 14:

[0683] The user's terminal displays the received advice.

[0684] Step 15:

[0685] The server runs a matching algorithm to select the most suitable senior mentor based on the user's question or concern, emotional state, the senior mentor's skill set, and user ratings.

[0686] Step 16:

[0687] The server presents information about the selected senior mentor to the user's terminal.

[0688] Step 17:

[0689] Once the user selects a suitable senior mentor from the candidates, the information is sent to the server.

[0690] Step 18:

[0691] The server compares the schedules of the user and the selected senior mentor and suggests the most suitable date and time.

[0692] Step 19:

[0693] The user's terminal and the senior mentor's terminal check the proposed date and time, and return to the server their consent or desire to amend it.

[0694] Step 20:

[0695] The server confirms the date and time agreed upon by both the user and the senior mentor as the schedule, and again notifies the details to both users' terminals.

[0696] Step 21:

[0697] The senior mentor visits the user's home at a fixed date and time and provides the necessary support (e.g., housework support, childcare support).

[0698] Step 22:

[0699] After the support is completed, the user's terminal displays a feedback form, allowing the user to input their opinions and evaluations of the support they received.

[0700] Step 23:

[0701] The server records the feedback received from the user and reflects it in the senior mentor's evaluation system. It also processes the senior mentor's evaluation in the same way.

[0702] Step 24:

[0703] The server stores all feedback in a database and analyzes the data to reflect it in the next matching algorithm.

[0704] Example 2

[0705] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0706] Conventional home support platforms provide uniform advice and support without considering the user's emotional state, which means they are unable to fully alleviate the stress and frustration felt by users. This results in problems that make it difficult to resolve family problems and reduces user satisfaction. Another issue is the low accuracy of matching users with senior mentors, which limits the efficiency and effectiveness of support.

[0707] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0708] In this invention, the server includes a means for a user to input questions and concerns about the home, a means for an emotion engine to analyze the user's emotional state, and a means for a generative artificial intelligence to generate and adjust advice taking into account the user's input information and emotional state. This makes it possible to provide personalized advice that reflects the user's emotional state, resulting in effective solutions to home problems.

[0709] "User" refers to an individual with a household concern or question who uses this system.

[0710] "Device" refers to the electronic device used by users and senior mentors to access the system, such as a smartphone, tablet, or PC.

[0711] "Server" refers to the computer system that processes and stores information received from Users and Senior Mentors and manages the entire system.

[0712] An "emotion engine" refers to software or algorithms that analyze information entered by a user and recognize the user's emotional state (e.g., stress, anxiety, joy, etc.).

[0713] "Generative artificial intelligence (AI)" refers to an AI system that has the ability to generate optimal advice based on a user's questions, concerns, and emotional state.

[0714] "Advice" refers to the advice or instructions that generative artificial intelligence provides to solve a user's questions or concerns.

[0715] "Senior Mentor" refers to an experienced individual who is responsible for providing family support to a user.

[0716] "Support" refers to specific services such as housework assistance and childcare support that senior mentors provide by visiting users' homes.

[0717] "Feedback" refers to the user's opinions and evaluations of the support they have received, as well as the evaluations and impressions that senior mentors provide to users.

[0718] The "evaluation system" refers to a system that collects and analyzes feedback from users and senior mentors to improve the accuracy of matching and service quality for the next time.

[0719] "Matching algorithm" refers to a calculation method for selecting the most suitable senior mentor based on the content of the user's question or concern, emotional state, the senior mentor's skill set, and user evaluation.

[0720] "Database" refers to data storage for saving and managing data such as user information, senior mentor information, questions and concerns, support details, and feedback processed by the system.

[0721] "Validation" refers to the process by which the server verifies that the information entered by the user or senior mentor is accurate and complete.

[0722] "Personalization" refers to optimizing the advice and assistance provided based on the individual characteristics and emotional state of each user.

[0723] MODE FOR CARRYING OUT THE INVENTION

[0724] The present invention provides a system that combines a home support platform with an emotion engine to provide advice and support that takes into account the user's emotional state. Specific embodiments for carrying out the present invention will be described below.

[0725] User registration and initial settings

[0726] When the user accesses the site for the first time, the user's device displays a registration form for entering basic information (name, address, email address, family concerns, etc.). The server receives the information entered by the user, validates it, and stores it in a database. Similarly, the senior mentor's device displays a form for entering the senior mentor's basic information and skill set, and sends the entered data to the server. The server also validates the information entered by the senior mentor and stores it in a database. For example, MySQL or PostgreSQL is used as the database.

[0727] Inputting questions and concerns and recognizing emotions

[0728] The user's device provides a dedicated form for entering questions or concerns about the home. When the user enters and submits their question or concern, the server receives this information and passes it to the emotion engine. The emotion engine uses natural language processing (NLP) technology to analyze the user's emotional state from the information they input. Specifically, it identifies emotions such as stress, anxiety, and joy.

[0729] AI-powered advice generation and tailoring

[0730] The server passes the emotional state analyzed by the emotion engine to a generative artificial intelligence (AI). The generative AI generates optimal advice based on the user's questions, concerns, and emotional state. Because the emotional state is taken into consideration, if the user is feeling stressed, for example, advice including a gentler tone and stress reduction measures will be generated. The generated advice is sent back to the user's device via the server and displayed to the user.

[0731] Examples:

[0732] If a user asks for advice about their child not studying, but the emotion engine detects stress or anxiety, the generative AI will provide advice such as, "Start by creating a relaxing environment. It's also important to spend time relaxing with your child."

[0733] Example prompt sentence:

[0734] "Please advise on my child not studying. The user seems to be experiencing stress and anxiety."

[0735] Senior mentor matching

[0736] The server runs a matching algorithm to select the most suitable senior mentor based on the user's question or concern, emotional state, the senior mentor's skill set, and user ratings. The server also takes into account the user's emotional state, so if the emotional state is negative, for example, a senior mentor with high responsiveness and empathy will be prioritized. The server then presents information about the selected senior mentor to the user.

[0737] Schedule adjustments

[0738] If both the user and the selected senior mentor accept the proposal, the server compares their schedules and proposes the optimal date and time. If the user and the senior mentor agree on the optimal date and time, the date and time of the support is confirmed.

[0739] On-site support

[0740] The senior mentor visits the user's home at the specified date and time to provide necessary support such as housework assistance and childcare assistance. The content of the assistance and progress are sent to the server and recorded.

[0741] Examples:

[0742] If a senior mentor prepares dinner at the user's request, details such as the cooking steps and the time it is ready are recorded.

[0743] Feedback and Ratings

[0744] After the support is completed, the user's device displays a feedback form, allowing the user to enter their opinion and evaluation of the support they received. The server receives the feedback and reflects it in the senior mentor's evaluation system. It also provides a feedback function to senior mentors, allowing them to enter their evaluation and thoughts about the user. This improves the quality of the entire system and the accuracy of the next match.

[0745] In this way, the home support platform of the present invention is a system that utilizes emotion recognition technology and generative artificial intelligence to provide personalized support that takes into account the user's emotional state, thereby reducing the burden on the home and strengthening ties in the local community.

[0746] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0747] Step 1:

[0748] When a user accesses the system for the first time, the user's terminal displays a registration form for entering basic information.

[0749] Input: User's basic information (name, address, email address, family concerns, etc.)

[0750] What happens: The user enters information into the fields and clicks the "Submit" button.

[0751] Output: The basic information data entered by the user is sent to the server.

[0752] Step 2:

[0753] The server receives the basic information data sent by the user.

[0754] Input: User's basic information data

[0755] Specific operation: Validate the received data, check the format of the email address, and confirm required fields.

[0756] Output: Basic information data that has passed validation is saved in the database.

[0757] Step 3:

[0758] When the senior mentor accesses the system for the first time, the terminal of the senior mentor displays a registration form for inputting basic information and skill sets.

[0759] Input: Senior Mentor's basic information and skill set

[0760] Specific Actions: The senior mentor fills in the information in each field and clicks the "Submit" button.

[0761] Output: The basic information and skill set data entered by the senior mentor is sent to the server.

[0762] Step 4:

[0763] The server receives the basic information and skill set data sent by the senior mentor.

[0764] Input: Senior Mentor's basic information and skill set data

[0765] Specific operation: Validate the received data and check the format of the input data.

[0766] Output: The information of senior mentors who pass validation is saved in the database.

[0767] Step 5:

[0768] The user's terminal displays a form for entering questions or concerns about the home.

[0769] Input: Questions and concerns about the home

[0770] Specific operation: The user enters a question or concern and clicks the "Submit" button.

[0771] Output: Questions and concerns entered by the user are sent to the server.

[0772] Step 6:

[0773] The server receives questions and worry data sent by users.

[0774] Input: User questions and concerns

[0775] Specific operation: Pass the received data to the emotion engine.

[0776] Output: Data passed to the emotion engine

[0777] Step 7:

[0778] The emotion engine analyzes the user's questions and worries data to identify the user's emotional state.

[0779] Input: User questions and concerns

[0780] What it does: It uses natural language processing (NLP) techniques to analyze text and identify emotional states (stress, anxiety, joy, etc.).

[0781] Output: Emotional state data (type and degree of emotion)

[0782] Step 8:

[0783] The server passes the emotional state data analyzed by the emotion engine to a generative artificial intelligence (AI).

[0784] Input: Emotional state data

[0785] Specific operation: Emotional state data is passed as input to generative artificial intelligence.

[0786] Output: Emotional state data passed to the generative AI

[0787] Step 9:

[0788] Generative AI generates appropriate advice based on the user's questions, concerns, and emotional state data.

[0789] Input: User questions, concerns, and emotional state data

[0790] How it works: The AI ​​model analyzes both sets of data and generates optimal advice.

[0791] Output: Generated advice data

[0792] Example: If a user asks for advice about their child not studying, but the emotion engine detects stress or anxiety, the AI ​​will generate advice like, "Start by creating a relaxing environment. It's also important to spend time relaxing with your child."

[0793] Step 10:

[0794] The server returns the generated advice data to the user's terminal.

[0795] Input: Generated advice data

[0796] Specific operation: Advice data is sent to the user's device.

[0797] Output: Advice displayed on the user's terminal

[0798] Step 11:

[0799] The server runs a matching algorithm to select the most suitable senior mentor based on the user's question or concern, emotional state, the senior mentor's skill set, and user ratings.

[0800] Input: User questions and concerns, emotional state data, senior mentor skill data, user evaluation data

[0801] Specific operation: Apply a matching algorithm to select the most suitable senior mentor.

[0802] Output: Information about the selected senior mentor

[0803] Step 12:

[0804] The server compares the schedules of the user and senior mentor and suggests the best date and time.

[0805] Input: User's schedule data, Senior Mentor's schedule data

[0806] Specific behavior: Match schedules and suggest the best time and date.

[0807] Output: Suggested best time

[0808] Step 13:

[0809] The senior mentor will visit the user's home at the proposed date and time to provide assistance.

[0810] Input: Suggested best date and time

[0811] Specific actions: A senior mentor will visit the home at the proposed date and time to provide assistance with housework and childcare.

[0812] Output: Data on completed support activities

[0813] Step 14:

[0814] After the support is completed, the user's terminal displays a feedback form, allowing the user to input their opinions and evaluations of the support they received.

[0815] Input: User opinions and ratings

[0816] What happens: A user fills out a feedback form and clicks the "Submit" button.

[0817] Output: User feedback data

[0818] Step 15:

[0819] The server receives feedback from users and reflects it in the senior mentor's evaluation system, and also provides a feedback form to the senior mentor.

[0820] Input: User feedback data, Senior Mentor feedback data

[0821] Specific actions: Feedback data will be reflected in the evaluation system and the data will be used to improve matching accuracy and service quality next time.

[0822] Output: Updated rating system data

[0823] (Application example 2)

[0824] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0825] When providing meal suggestions or cooking assistance at home, suggestions or assistance that do not take into account the user's emotional state may not provide sufficient satisfaction. Furthermore, matching or responses that do not take the user's emotional state into account may lead to discrepancies between the provider and the user. Conventional methods have difficulty providing detailed advice based on emotions or efficiently matching providers.

[0826] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for the user to input questions, concerns, or emotional state related to the home, means for the server to receive the user's input information and pass it on to the emotion engine, and means for the emotion engine to analyze the user's emotional state and pass the results on to the generative AI. This makes it possible to match appropriate meal suggestions and providers such as chefs according to the user's emotional state.

[0827] A "user" is an individual who uses the system to ask questions or concerns about their home, as well as to seek meal suggestions.

[0828] An "emotion engine" is software or hardware for analyzing the user's emotional state from input information.

[0829] "Generative AI" is an AI system that analyzes a user's input information and emotional state and generates appropriate advice.

[0830] A "provider" is a person or organization that provides a service to a user, and includes chefs, housekeeping assistants, etc.

[0831] "Server" refers to a computer system that performs the central data processing and management of this system.

[0832] A "skill set" is a list of skills and techniques possessed by a provider, and is information for providing appropriate support to users.

[0833] "User Ratings" refers to other users' ratings and feedback on services provided in the past.

[0834] "Feedback" refers to evaluations and opinions given by users regarding the services provided.

[0835] "Emotional state" refers to the psychological state analyzed from the information entered by the user, examples of which include stress and relaxation.

[0836] 1. Overall system configuration

[0837] An embodiment of this invention is a system that provides advice and services that take into account a user's emotional state when they request meal suggestions or cooking assistance. This system is composed of a user terminal, a server, an emotion engine, a generative artificial intelligence, a provider terminal, etc.

[0838] 2. Hardware and Software Used

[0839] This system uses the following hardware and software:

[0840] Emotion engine: Uses various emotion analysis APIs, such as Microsoft Azure Emotion API and IBM Watson Tone Analyzer.

[0841] Generative AI: Use generative AI models such as OpenAI GPT-4.

[0842] Backend: Uses cloud computing services, such as AWS Lambda and its database service AWS RDS.

[0843] Frontend: Using React Native for smartphone applications.

[0844] Database: Use a relational database such as PostgreSQL.

[0845] 3. Data processing and calculation

[0846] User registration and initial settings

[0847] When a user accesses the system for the first time, he enters basic information (name, address, email address, etc.) in the user registration form. The server receives this information, validates it, and then stores it in the database.

[0848] Inputting questions and concerns and recognizing emotions

[0849] Users input questions and concerns about their home into the app and express their emotional state. This information is sent to the server and passed to the emotion engine. The emotion engine analyzes the user's emotional state from the input information and returns the results to the server.

[0850] Generating Advice

[0851] The server passes the emotional state data received from the emotion engine to the generative AI, which takes into account the user's questions, concerns, and emotional state to generate optimal advice. The advice is then sent back to the user from the server and displayed on the app.

[0852] Provider matching

[0853] The server selects the best provider for the user based on advice generated by the emotion engine and generative AI. The provider's skill set and past reviews are also taken into consideration. For example, if the user's emotional state is unstable, a chef with a high level of empathy will be prioritized.

[0854] Scheduling and feedback

[0855] The system checks the schedules of the user and provider and proposes the optimal date and time. If this is accepted, the date and time of the service is confirmed and the provider provides the service at the specified date and time. After that, the user's feedback is sent to the server, stored in a database, and reflected in the rating system.

[0856] 4. Specific Examples

[0857] When a user types "I'm very tired today," and the emotion engine analyzes "tired," the generative AI suggests a relaxing meal. The meal suggestion includes "grilled salmon and steamed vegetables," and the system matches the user with a highly rated chef near the user. The following prompt appears on the user's smartphone:

[0858] "The user is extremely tired. Based on this emotional state, suggest a relaxing meal."

[0859] This system will significantly improve satisfaction at home by suggesting meals based on the user's emotional state and matching them with chefs and other providers.

[0860] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0861] Step 1:

[0862] On the user's device, the user inputs questions, concerns, and emotional state about the home. Specifically, the user enters text into an input form within the app. This becomes input data and is sent to the server.

[0863] Step 2:

[0864] The server passes the received user input data to the emotion engine. The emotion engine analyzes the user's emotional state from the text and returns the result (e.g., stress, relaxation, etc.) to the server. The data processing performed in this step is text analysis, and generates output data called the emotional state.

[0865] Step 3:

[0866] The server passes the analyzed emotional state to a generative AI (such as GPT-4). The generative AI receives the user's questions, concerns, and emotional state as input data and generates optimal advice. This advice is returned to the server in text format. The data calculation in this step is advice generation using natural language processing.

[0867] Step 4:

[0868] The server returns the advice received from the generative AI to the user. This advice is displayed on the user's device. The specific processing performed here involves API communication and retrieval from a database.

[0869] Step 5:

[0870] The server selects an appropriate provider based on the generated advice, emotional state, and user input information. The provider's skill set is compared with the user rating database to perform matching. Information about the selected provider is presented to the user. The data calculation in this step is the execution of a matching algorithm.

[0871] Step 6:

[0872] The server adjusts the schedules of the user and provider and proposes the optimal date and time. The proposed date and time are sent to the user's device and the provider's device, and both parties confirm them. In this step, the date and time are adjusted using the calendar API.

[0873] Step 7:

[0874] The provider will visit the user's designated location at the date and time determined by the server, and provide meal suggestions and cooking assistance services. At this time, the provider's device will report the progress to the server. Specific operations include GPS tracking and check-in functions.

[0875] Step 8:

[0876] After the service is provided, the user enters feedback and sends it to the server. The server stores the feedback in a database and reflects it in the provider's evaluation system. In this step, the questionnaire form and database are updated.

[0877] These processing steps realize an automated emotion-based meal suggestion and cooking assistance system.

[0878] 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 a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0879] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0880] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0881] [Third embodiment]

[0882] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0883] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0884] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. 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. The database 24 and the communication I / F 26 are also 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).

[0885] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0886] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0887] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0888] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0889] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0890] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0891] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0892] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0893] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[0894] The present invention relates to a family support platform, which is a system that provides advice and support for family questions and concerns through the cooperation of generative artificial intelligence (AI) and senior mentors. Specific embodiments for implementing the present invention will be described below.

[0895] Program processing and system configuration

[0896] 1. User registration and initial settings

[0897] When the user accesses the site for the first time, the user's device displays a registration form for entering basic information (such as name, address, email address, and family concerns). The server receives the information entered by the user, validates it, and stores it in a database. Similarly, the senior mentor's device displays a form for entering the senior mentor's basic information and skill set, and sends the entered data to the server. The server also validates the information entered by the senior mentor and stores it in a database.

[0898] 2. Input your questions and concerns and receive answers from AI

[0899] The user's device provides a dedicated form for entering questions and concerns about the home. When the user enters and submits their concerns, the server passes this information to a generative AI. The generative AI analyzes the question or concern and generates optimal advice. The generated advice is then sent back to the user's device via the server and displayed to the user.

[0900] 3. Senior mentor matching

[0901] The server runs an algorithm to match users with appropriate senior mentors based on their questions and concerns. The algorithm selects the best candidates by taking into account the senior mentors' skill sets and user ratings. The server then presents the selected senior mentors to the user.

[0902] As a specific example, if a user inputs "I would like some help with my child's studies," the server will select and suggest highly rated senior mentors who have education-related skills.

[0903] 4. Adjust your schedule

[0904] If both the user and the selected senior mentor accept the proposal, the server compares their schedules and proposes the optimal date and time. If the user and the senior mentor agree on the optimal date and time, the date and time of the support is confirmed.

[0905] 5. On-site support

[0906] The senior mentor visits the user's home at the specified date and time and provides the necessary support (e.g., housework support, childcare support). The support content and progress are sent to the server and recorded.

[0907] For example, if a senior mentor prepares dinner at the user's request, details such as the cooking steps and the time it will be ready will be recorded.

[0908] 6. Feedback and Ratings

[0909] After the support is completed, the user's device displays a feedback form, allowing the user to enter their opinion and evaluation of the support they received. The server receives the feedback and reflects it in the senior mentor's evaluation system. It also provides a feedback function to senior mentors, allowing them to enter their evaluation and thoughts about the user. This improves the quality of the entire system and the accuracy of the next match.

[0910] In this way, the home support platform of the present invention is a system that utilizes AI technology and senior mentors to reduce worries and burdens within the home, strengthen ties with the local community, and provide social roles and opportunities for interaction for the elderly.

[0911] The processing flow will be explained below.

[0912] Step 1:

[0913] When the user accesses the site for the first time, the user's device displays a registration form for entering basic information (such as name, address, email address, and household concerns).

[0914] Step 2:

[0915] The user enters the necessary information and clicks the registration button.

[0916] Step 3:

[0917] The server receives the information entered by the user and performs validation. If the input data is valid, it is saved in the database. At the same time, a welcome message is displayed on the user's terminal.

[0918] Step 4:

[0919] The senior mentor's device also displays a registration form where the senior mentor can enter their skills, background, and support details.

[0920] Step 5:

[0921] The senior mentor enters the required information and clicks the registration button.

[0922] Step 6:

[0923] The server receives the information entered by the senior mentor, validates it, and if the input data is valid, stores it in the database.

[0924] Step 7:

[0925] The user's device displays a dedicated form where the user can enter questions or concerns about their home. The user enters their question or concern and clicks the send button.

[0926] Step 8:

[0927] The server receives the user's input information and passes it to the generative artificial intelligence.

[0928] Step 9:

[0929] Generative AI analyzes users' questions and concerns and generates optimal advice.

[0930] Step 10:

[0931] The server receives the generated advice and returns it to the user's terminal.

[0932] Step 11:

[0933] The user's terminal displays the received advice.

[0934] Step 12:

[0935] The server runs a matching algorithm to select the most suitable senior mentor based on the user's questions and concerns, the senior mentor's skill set, and user ratings.

[0936] Step 13:

[0937] The server presents information about the selected senior mentor to the user's terminal.

[0938] Step 14:

[0939] Once the user selects a suitable senior mentor from the candidates, the information is sent to the server.

[0940] Step 15:

[0941] The server compares the schedules of the user and the selected senior mentor and suggests the most suitable date and time.

[0942] Step 16:

[0943] The user's terminal and the senior mentor's terminal check the proposed date and time, and return to the server their consent or desire to amend it.

[0944] Step 17:

[0945] The server confirms the date and time agreed upon by both the user and the senior mentor as the schedule, and again notifies the details to both users' terminals.

[0946] Step 18:

[0947] The senior mentor visits the user's home at a fixed date and time and provides the necessary support (e.g., housework support, childcare support).

[0948] Step 19:

[0949] After the support is completed, the user's terminal displays a feedback form, allowing the user to input their opinions and evaluations of the support they received.

[0950] Step 20:

[0951] The server records the feedback received from the user and reflects it in the senior mentor's evaluation system. It also processes the senior mentor's evaluation in the same way.

[0952] In this way, the home support platform of the present invention provides professional advice and direct support in response to the user's concerns and requests.

[0953] Example 1

[0954] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0955] Modern families require immediate and appropriate advice and support for domestic worries and problems. However, in busy daily lives, it is not easy to immediately obtain the necessary support. Furthermore, there is a lack of mechanisms to utilize the wealth of experience and knowledge that older people possess and to strengthen their ties with the local community. An effective system to resolve these issues is needed.

[0956] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0957] In this invention, the server includes a means for users to input questions and concerns about their home, a means for a generative AI to analyze the input information and generate advice, and a means for selecting the most suitable mentor based on the mentor's skills and user ratings. This makes it possible to provide prompt and appropriate advice and support for problems and concerns within the home, as well as to provide elderly people with social roles and opportunities for interaction.

[0958] "User" refers to an individual who uses this system to input questions and concerns about their home and receive advice and support.

[0959] "Server" refers to the computer system that receives and sends information from users and mentors, and manages and processes the advice and feedback generated by the generative AI.

[0960] "Generative AI" refers to AI technology that has the ability to analyze received input information and generate appropriate advice.

[0961] "Advice" refers to solutions and suggestions provided by generative artificial intelligence based on the user's questions and concerns.

[0962] A "mentor" is a support provider, such as an older person, who has the skills and experience to provide support for the home.

[0963] "Skills" refers collectively to the knowledge and experience related to the specific support that a mentor can provide.

[0964] "User ratings" refer to feedback and ratings provided by users who have received support from a mentor in the past.

[0965] "Feedback" refers to evaluations and opinions about the support provided by users and mentors and about the system as a whole.

[0966] "Schedule" refers to the specific date and time for the user and mentor to provide support.

[0967] The present invention relates to a family support system that provides effective advice and support for questions and concerns of families through the cooperation of generative artificial intelligence (AI) and senior mentors. Specific embodiments for carrying out the invention are described below.

[0968] User registration and initial settings

[0969] Users access the system from their own devices and use a form to enter basic information (such as name, address, email address, and family concerns). The entered information is sent to the server, where data validation takes place. Once validation is complete, the server stores the data in a database. Similarly, senior mentors also use their own devices to enter basic information and skill sets, which are also sent to the server, where they are validated and stored in the database.

[0970] Enter your questions and concerns and receive answers from AI

[0971] Users enter questions or concerns about their home into a dedicated question form and send it to the server. The server passes the received question information to a generative AI. The generative AI analyzes the entered question and generates the most appropriate advice. The generated advice is sent back to the user's device via the server. For example, if a user enters, "I would like you to support my child's studies," the server sends this to the AI ​​as a prompt: "Please introduce me to a mentor who can provide support for my child's studies at home. My child is in the fifth grade of elementary school and particularly needs support with math and English."

[0972] Senior mentor matching

[0973] The server analyzes the user's questions and concerns and runs an algorithm to match them with an appropriate senior mentor. This algorithm considers the senior mentor's skill set and past user ratings to select the most suitable candidate. Information about the selected senior mentor is displayed on the user's device. For example, if a user enters "I would like some help with my child's studies," the server will present senior mentors with education-related skills and high user ratings.

[0974] Schedule adjustments

[0975] When the user and the selected senior mentor accept the proposal, the server checks their respective schedules and proposes the optimal date and time. If both parties agree on the optimal date and time, the date and time of the support is confirmed and the server notifies the user and the senior mentor of this information.

[0976] On-site support

[0977] The senior mentor visits the user's home at the confirmed date and time and provides the necessary support (for example, housework or childcare support). The progress and content of the support are sent to the server and recorded. For example, if the senior mentor prepares dinner, details such as the cooking procedure and the time it is ready are recorded on the server.

[0978] Feedback and Ratings

[0979] After receiving assistance, the user enters their opinions and evaluations into a feedback form on their device and sends it to the server. The server receives this feedback and reflects it in the senior mentor's evaluation system. Similarly, the senior mentor also enters feedback for the user and sends it to the server. This two-way feedback improves the quality of the entire system and the accuracy of the next match.

[0980] The home support system of the present invention utilizes generative AI models and the skills of senior mentors to reduce worries and burdens within the home, strengthen connections with the local community, and provide social roles and opportunities for interaction for the elderly.

[0981] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0982] Step 1: User registration and initial setup

[0983] When a user accesses the system for the first time, they enter basic information such as their name, address, email address, and family concerns into the registration form displayed on their terminal. This entered information is sent to the server. The server validates the received information and ensures that it is in the correct format. For example, it checks the format of the email address and whether any fields are required. Once validated, the information is stored in the database. Similarly, senior mentors use their terminals to enter basic information and skill sets and send it to the server. The server similarly validates this information and stores it in the database.

[0984] Step 2: Enter your question or concern

[0985] The user accesses a dedicated form for entering questions and concerns about their home and enters the details. For example, they might enter, "I would like some help with my child's studies," and press the send button. The entered information is sent to the server. The server then generates a prompt to pass the received question information to the generative AI model. For example, it generates a prompt such as, "Please introduce me to a mentor who can provide support for my child's studies at home. My child is in the fifth grade of elementary school and needs particular support with math and English."

[0986] Step 3: Generate answers with AI

[0987] The server sends the generated prompt to the generative AI model, which generates optimal advice based on the received prompt. For example, the generated advice might be, "To support children's learning, it is effective to repeatedly practice a specific subject for 30 minutes every day." This advice is then sent back to the server.

[0988] Step 4: Providing advice

[0989] The server provides the user with the advice returned by the generative AI model. Specifically, the advice is output in the form of a display on the user's device. By referring to this advice, the user can obtain specific measures to solve problems at home.

[0990] Step 5: Matching with a senior mentor

[0991] The server runs an algorithm that matches the most suitable senior mentor based on the user's questions and concerns, their skill sets, and user ratings. The input data is the user's question and the senior mentor's skill sets and rating data, and the output data is a list of suitable mentor candidates. For example, in response to a request to "help support my child's studies," the server selects and presents mentors with education-related skills and high ratings.

[0992] Step 6: Adjust your schedule

[0993] The server compares the schedules of the user and the selected senior mentor and proposes the optimal date and time. The input data is the time slots available to the user and mentor, and the output data is the optimal date and time for support that both parties agree on. Once both parties agree on this date and time, the date and time for support is confirmed. This confirmation information is notified to both the user and mentor via the server.

[0994] Step 7: Implementing on-site support

[0995] The senior mentor visits the user's home at the confirmed date and time and provides the promised support (e.g., housework or childcare support). The progress and status of the support are recorded in real time and sent to the server. For example, if dinner is prepared, the cooking steps and completion time are recorded. This allows the user to check the progress of the support.

[0996] Step 8: Feedback and Rating

[0997] After completing the assistance, the user enters their opinion and evaluation in a feedback form on their device and sends it to the server. The server receives this feedback and reflects it in the senior mentor's evaluation system. The senior mentor also enters feedback for the user on their device and sends it to the server. This improves the quality of the entire system and the accuracy of the next match.

[0998] (Application example 1)

[0999] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1000] Modern households face a variety of problems and worries, and require quick and appropriate solutions. However, there are many situations where it is difficult to receive reliable advice and support immediately. In particular, it is difficult to provide specialized household support when dealing with customers in physical stores. Another problem is that responding individually to every customer requires a huge amount of time and effort, placing a heavy burden on store staff. This has led to issues such as a decline in customer satisfaction and an increased burden on staff.

[1001] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1002] In this invention, the server includes a means for the user to input questions and concerns about the home, a means for the server to receive the user's input information and pass it to the generative AI, and a means for the generative AI to analyze the input information and generate advice, which enables the following effects.

[1003] 1. Users can input their questions or concerns through their smart devices, and advice will be provided through generative AI and senior mentors, enabling customers to receive quick and reliable advice.

[1004] 2. The server selects the most suitable senior mentor based on the advice, the senior mentor's skill set, and the user's ratings, and determines the date and time of support, ensuring that a senior mentor with the appropriate skills can respond quickly.

[1005] 3. By receiving feedback and reflecting it in the evaluation system, the quality of the entire system and the accuracy of the next match can be improved.

[1006] A "user" is a person who inputs questions or concerns about the home and receives advice or support using this system.

[1007] "Questions and concerns about the home" include various issues and concerns in everyday life, such as housework, child-rearing, and interior design.

[1008] A "smart device" is a portable electronic device that can connect to the Internet, such as a smartphone, smart glasses, or a head-mounted display.

[1009] "Generative AI" is an AI program that analyzes information entered by the user and provides optimal advice based on that information.

[1010] The "server" is an information processing device that manages information for the entire system, exchanges data with generative AI, selects senior mentors, and coordinates schedules.

[1011] A "senior mentor" is a senior citizen who provides advice and support to help users solve their household problems.

[1012] A "skill set" is the collection of knowledge, experience, specific abilities and qualifications that a senior mentor possesses.

[1013] "User ratings" are the results of feedback and ratings given to senior mentors by past users.

[1014] "Schedule adjustment" is the process of determining the most suitable date and time for support based on the availability of the user and senior mentor.

[1015] "Feedback" refers to the act of a user inputting their thoughts and evaluations of the support they have received, and this data is reflected in the senior mentor's evaluation system.

[1016] "Interior consultation" refers to the act of providing advice on home decoration, furniture placement, etc.

[1017] This invention relates to a family support platform, which is a system that provides advice on family questions and concerns through the cooperation of generative artificial intelligence (AI) and senior mentors. Specific embodiments for implementing the present invention will be described below.

[1018] 1. User registration and initial settings

[1019] Users access the application using a device such as a smartphone. When they access it for the first time, a form is displayed in which they can enter basic information (such as name, address, email address, and family concerns). The information they enter is sent to the server, where it is validated and then saved in a database. Senior mentors also enter their own basic information and skill set and send it to the server. This completes the registration of the user and senior mentor.

[1020] 2. Input your questions and concerns and receive answers from AI

[1021] Users input questions or concerns about their home through their smart device. The input information is sent to a server and passed to a generative AI. The AI ​​analyzes the input information and generates appropriate advice. This advice is then sent back to the user's smart device via the server.

[1022] 3. Senior mentor matching

[1023] The server runs an algorithm to select the most suitable senior mentor based on the user's concerns, the senior mentor's skill set, and the user's ratings. Information on the matched senior mentor is then presented to the user.

[1024] 4. Adjust your schedule

[1025] If both the user and the senior mentor accept the proposal, the server compares their schedules and proposes the optimal date and time. The date and time agreed upon by both parties is confirmed and the date and time of the support is decided.

[1026] 5. On-site support

[1027] The senior mentor visits the user's home at the specified date and time and provides the necessary support, such as housework assistance, childcare assistance, interior design advice, etc. The content of the support and progress are sent to the server and recorded.

[1028] 6. Feedback and Ratings

[1029] After completing the support, the user enters their evaluation through a feedback form. The feedback is sent to the server and reflected in the senior mentor's evaluation system. Senior mentors can also enter their evaluations and thoughts about the user. This improves the overall quality of the system and the accuracy of the next match.

[1030] Hardware and software used

[1031] Server: The server manages the database, exchanges data with the generative AI, adjusts schedules, and manages the evaluation system. Specifically, Django (web framework) and PostgreSQL (database) are used.

[1032] Generative AI: Generative AI, such as OpenAI's GPT-3 model, is used to analyze users' questions and concerns and generate appropriate advice.

[1033] Smart devices: Smartphones, smart glasses, head-mounted displays, etc. are used by users to input questions or concerns and receive advice.

[1034] Examples of specific examples and prompts

[1035] For example, if a user inputs a request for home interior design advice, the generative AI will generate detailed advice such as "change the color of the curtains in the living room, add plants, and adjust the lighting."

[1036] Prompt Sentence Examples

[1037] I'd like to consult with a home support platform application about recommended interior changes. I'd like specific advice, such as changing the color of the curtains in the living room or adding some plants.

[1038] Through this system, users can quickly and appropriately resolve various family-related issues, and senior mentors can gain social roles and opportunities for interaction.

[1039] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1040] Step 1:

[1041] User registration and initial settings

[1042] Users access the application using a device such as a smartphone. When they access it for the first time, a form is displayed in which they can enter basic information (such as name, address, email address, and family concerns). The information entered by the user is sent to the server. The server receives the information, validates it, and stores it in a database. Senior mentors also enter their own basic information and skill set and send it to the server.

[1043] Step 2:

[1044] Enter your questions and concerns

[1045] Users input questions or concerns about their home through their smart devices. When a user inputs a question or concern and presses the send button, the information is sent to the server. The server receives this input information and passes it to the generative AI.

[1046] Step 3:

[1047] Answer generation using generative artificial intelligence

[1048] The server passes the received questions and concerns to a generative AI, which analyzes the input information and generates optimal advice. During this process, an AI model (e.g., GPT-3) understands the context and constructs appropriate solutions and advice. The generated advice is then sent back to the server.

[1049] Step 4:

[1050] Conveying advice

[1051] The server receives the advice sent back from the generative AI and sends it back to the user's smart device, where the user can check the content of the advice.

[1052] Step 5:

[1053] Senior mentor matching

[1054] The server runs an algorithm to select the most suitable senior mentor based on the user's concerns, the senior mentor's skill set, and the user's ratings. When the algorithm is run, the senior mentor's past ratings and areas of expertise are taken into consideration. The server then presents information about the selected senior mentor to the user.

[1055] Step 6:

[1056] Schedule adjustment

[1057] If both the user and the senior mentor accept the proposal, the server compares their schedules and proposes the optimal date and time. If the proposed date and time is approved by both parties, the server confirms the date and time and notifies both parties.

[1058] Step 7:

[1059] On-site support

[1060] The senior mentor will visit the user's home at the agreed date and time and provide the necessary support. For example, specific support such as housework assistance, childcare assistance, and interior design advice will be provided. The senior mentor will then send the support process and results to the server as recorded data.

[1061] Step 8:

[1062] Feedback and Ratings

[1063] After completing the support, the user enters their evaluation through a feedback form. The feedback information entered by the user is sent to the server and reflected in the senior mentor's evaluation system. Senior mentors can also enter their evaluations and thoughts about the user. The server stores this feedback information in a database and uses it to improve the quality of the entire system.

[1064] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1065] The present invention provides a system that combines a home support platform with an emotion engine to provide advice and support that takes into account the user's emotional state. Specific embodiments for carrying out the present invention will be described below.

[1066] Program processing and system configuration

[1067] 1. User registration and initial settings

[1068] When the user accesses the site for the first time, the user's device displays a registration form for entering basic information (such as name, address, email address, and family concerns). The server receives the information entered by the user, validates it, and stores it in a database. Similarly, the senior mentor's device displays a form for entering the senior mentor's basic information and skill set, and sends the entered data to the server. The server also validates the information entered by the senior mentor and stores it in a database.

[1069] 2. Inputting questions and concerns and emotion recognition

[1070] The user's device provides a dedicated form for inputting questions or concerns about the home. When the user inputs and submits the question or concern, the server passes the information to the emotion engine, which analyzes the user's emotional state from the input information.

[1071] 3. AI-generated and tailored advice

[1072] The server passes the emotional state analyzed by the emotion engine to the generative AI. The generative AI analyzes the user's question, concerns, and emotional state, and generates optimal advice. Because the emotional state is taken into consideration, if the user is feeling stressed, for example, advice including a gentler tone and stress reduction measures will be generated. The generated advice is sent back to the user's device via the server and displayed to the user.

[1073] As a specific example, if a user asks for advice about their child not studying, but the emotion engine detects stress or anxiety, the generative AI will provide advice such as, "Start by creating a relaxing environment. It's also important to spend time relaxing with your child."

[1074] 4. Senior mentor matching

[1075] The server runs a matching algorithm to select the most suitable senior mentor based on the user's question or concern, emotional state, the senior mentor's skill set, and user ratings. The user's emotional state is also taken into consideration, so if the emotional state is negative, for example, a senior mentor with high responsiveness and empathy will be prioritized. The server then presents information about the selected senior mentor to the user.

[1076] 5. Adjust your schedule

[1077] If both the user and the selected senior mentor accept the proposal, the server compares their schedules and proposes the optimal date and time. If the user and the senior mentor agree on the optimal date and time, the date and time of the support is confirmed.

[1078] 6. On-site support

[1079] The senior mentor visits the user's home at the specified date and time to provide necessary support such as housework assistance and childcare assistance. The content of the assistance and progress are sent to the server and recorded.

[1080] For example, if a senior mentor prepares dinner at the user's request, details such as the cooking steps and the time it will be ready will be recorded.

[1081] 7. Feedback and Ratings

[1082] After the support is completed, the user's device displays a feedback form, allowing the user to enter their opinion and evaluation of the support they received. The server receives the feedback and reflects it in the senior mentor's evaluation system. It also provides a feedback function to senior mentors, allowing them to enter their evaluation and thoughts about the user. This improves the quality of the entire system and the accuracy of the next match.

[1083] In this way, the home support platform of the present invention is a system that provides more appropriate and personalized support to users by utilizing an emotion engine that can recognize and respond to the user's emotional state, generative AI, and senior mentors, thereby reducing the burden on families, strengthening ties in the local community, and providing social roles and opportunities for elderly people to interact.

[1084] The processing flow will be explained below.

[1085] Step 1:

[1086] When the user accesses the site for the first time, the user's device displays a registration form for entering basic information (such as name, address, email address, and household concerns).

[1087] Step 2:

[1088] The user enters the necessary information and clicks the registration button.

[1089] Step 3:

[1090] The server receives the information entered by the user and performs validation. If the input data is valid, it is saved in the database. At the same time, a welcome message is displayed on the user's terminal.

[1091] Step 4:

[1092] The senior mentor's device also displays a registration form where the senior mentor can enter their skills, background, and support details.

[1093] Step 5:

[1094] The senior mentor enters the required information and clicks the registration button.

[1095] Step 6:

[1096] The server receives the information entered by the senior mentor, validates it, and if the input data is valid, stores it in the database.

[1097] Step 7:

[1098] The user's device displays a dedicated form where the user can enter questions or concerns about their home. The user enters their question or concern and clicks the send button.

[1099] Step 8:

[1100] The server receives the user's input information and passes it to the emotion engine.

[1101] Step 9:

[1102] The emotion engine analyzes the user's emotional state (stress, anxiety, joy, etc.) from their input information.

[1103] Step 10:

[1104] The emotion engine sends the analysis results to the server.

[1105] Step 11:

[1106] The server passes the emotional state analyzed by the emotion engine to the generative AI.

[1107] Step 12:

[1108] Generative AI analyzes the user's questions, concerns, and emotional state to generate optimal advice.

[1109] Step 13:

[1110] The server receives the generated advice and returns it to the user's terminal.

[1111] Step 14:

[1112] The user's terminal displays the received advice.

[1113] Step 15:

[1114] The server runs a matching algorithm to select the most suitable senior mentor based on the user's question or concern, emotional state, the senior mentor's skill set, and user ratings.

[1115] Step 16:

[1116] The server presents information about the selected senior mentor to the user's terminal.

[1117] Step 17:

[1118] Once the user selects a suitable senior mentor from the candidates, the information is sent to the server.

[1119] Step 18:

[1120] The server compares the schedules of the user and the selected senior mentor and suggests the most suitable date and time.

[1121] Step 19:

[1122] The user's terminal and the senior mentor's terminal check the proposed date and time, and return to the server their consent or desire to amend it.

[1123] Step 20:

[1124] The server confirms the date and time agreed upon by both the user and the senior mentor as the schedule, and again notifies the details to both users' terminals.

[1125] Step 21:

[1126] The senior mentor visits the user's home at a fixed date and time and provides the necessary support (e.g., housework support, childcare support).

[1127] Step 22:

[1128] After the support is completed, the user's terminal displays a feedback form, allowing the user to input their opinions and evaluations of the support they received.

[1129] Step 23:

[1130] The server records the feedback received from the user and reflects it in the senior mentor's evaluation system. It also processes the senior mentor's evaluation in the same way.

[1131] Step 24:

[1132] The server stores all feedback in a database and analyzes the data to reflect it in the next matching algorithm.

[1133] Example 2

[1134] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1135] Conventional home support platforms provide uniform advice and support without considering the user's emotional state, which means they are unable to fully alleviate the stress and frustration felt by users. This results in problems that make it difficult to resolve family problems and reduces user satisfaction. Another issue is the low accuracy of matching users with senior mentors, which limits the efficiency and effectiveness of support.

[1136] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1137] In this invention, the server includes a means for a user to input questions and concerns about the home, a means for an emotion engine to analyze the user's emotional state, and a means for a generative artificial intelligence to generate and adjust advice taking into account the user's input information and emotional state. This makes it possible to provide personalized advice that reflects the user's emotional state, resulting in effective solutions to home problems.

[1138] "User" refers to an individual with a household concern or question who uses this system.

[1139] "Device" refers to the electronic device used by users and senior mentors to access the system, such as a smartphone, tablet, or PC.

[1140] "Server" refers to the computer system that processes and stores information received from Users and Senior Mentors and manages the entire system.

[1141] An "emotion engine" refers to software or algorithms that analyze information entered by a user and recognize the user's emotional state (e.g., stress, anxiety, joy, etc.).

[1142] "Generative artificial intelligence (AI)" refers to an AI system that has the ability to generate optimal advice based on a user's questions, concerns, and emotional state.

[1143] "Advice" refers to the advice or instructions that generative artificial intelligence provides to solve a user's questions or concerns.

[1144] "Senior Mentor" refers to an experienced individual who is responsible for providing family support to a user.

[1145] "Support" refers to specific services such as housework assistance and childcare support that senior mentors provide by visiting users' homes.

[1146] "Feedback" refers to the user's opinions and evaluations of the support they have received, as well as the evaluations and impressions that senior mentors provide to users.

[1147] The "evaluation system" refers to a system that collects and analyzes feedback from users and senior mentors to improve the accuracy of matching and service quality for the next time.

[1148] "Matching algorithm" refers to a calculation method for selecting the most suitable senior mentor based on the content of the user's question or concern, emotional state, the senior mentor's skill set, and user evaluation.

[1149] "Database" refers to data storage for saving and managing data such as user information, senior mentor information, questions and concerns, support details, and feedback processed by the system.

[1150] "Validation" refers to the process by which the server verifies that the information entered by the user or senior mentor is accurate and complete.

[1151] "Personalization" refers to optimizing the advice and assistance provided based on the individual characteristics and emotional state of each user.

[1152] MODE FOR CARRYING OUT THE INVENTION

[1153] The present invention provides a system that combines a home support platform with an emotion engine to provide advice and support that takes into account the user's emotional state. Specific embodiments for carrying out the present invention will be described below.

[1154] User registration and initial settings

[1155] When the user accesses the site for the first time, the user's device displays a registration form for entering basic information (name, address, email address, family concerns, etc.). The server receives the information entered by the user, validates it, and stores it in a database. Similarly, the senior mentor's device displays a form for entering the senior mentor's basic information and skill set, and sends the entered data to the server. The server also validates the information entered by the senior mentor and stores it in a database. For example, MySQL or PostgreSQL is used as the database.

[1156] Inputting questions and concerns and recognizing emotions

[1157] The user's device provides a dedicated form for entering questions or concerns about the home. When the user enters and submits their question or concern, the server receives this information and passes it to the emotion engine. The emotion engine uses natural language processing (NLP) technology to analyze the user's emotional state from the information they input. Specifically, it identifies emotions such as stress, anxiety, and joy.

[1158] AI-powered advice generation and tailoring

[1159] The server passes the emotional state analyzed by the emotion engine to a generative artificial intelligence (AI). The generative AI generates optimal advice based on the user's questions, concerns, and emotional state. Because the emotional state is taken into consideration, if the user is feeling stressed, for example, advice including a gentler tone and stress reduction measures will be generated. The generated advice is sent back to the user's device via the server and displayed to the user.

[1160] Examples:

[1161] If a user asks for advice about their child not studying, but the emotion engine detects stress or anxiety, the generative AI will provide advice such as, "Start by creating a relaxing environment. It's also important to spend time relaxing with your child."

[1162] Example prompt sentence:

[1163] "Please advise on my child not studying. The user seems to be experiencing stress and anxiety."

[1164] Senior mentor matching

[1165] The server runs a matching algorithm to select the most suitable senior mentor based on the user's question or concern, emotional state, the senior mentor's skill set, and user ratings. The server also takes into account the user's emotional state, so if the emotional state is negative, for example, a senior mentor with high responsiveness and empathy will be prioritized. The server then presents information about the selected senior mentor to the user.

[1166] Schedule adjustments

[1167] If both the user and the selected senior mentor accept the proposal, the server compares their schedules and proposes the optimal date and time. If the user and the senior mentor agree on the optimal date and time, the date and time of the support is confirmed.

[1168] On-site support

[1169] The senior mentor visits the user's home at the specified date and time to provide necessary support such as housework assistance and childcare assistance. The content of the assistance and progress are sent to the server and recorded.

[1170] Examples:

[1171] If a senior mentor prepares dinner at the user's request, details such as the cooking steps and the time it is ready are recorded.

[1172] Feedback and Ratings

[1173] After the support is completed, the user's device displays a feedback form, allowing the user to enter their opinion and evaluation of the support they received. The server receives the feedback and reflects it in the senior mentor's evaluation system. It also provides a feedback function to senior mentors, allowing them to enter their evaluation and thoughts about the user. This improves the quality of the entire system and the accuracy of the next match.

[1174] In this way, the home support platform of the present invention is a system that utilizes emotion recognition technology and generative artificial intelligence to provide personalized support that takes into account the user's emotional state, thereby reducing the burden on the home and strengthening ties in the local community.

[1175] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1176] Step 1:

[1177] When a user accesses the system for the first time, the user's terminal displays a registration form for entering basic information.

[1178] Input: User's basic information (name, address, email address, family concerns, etc.)

[1179] What happens: The user enters information into the fields and clicks the "Submit" button.

[1180] Output: The basic information data entered by the user is sent to the server.

[1181] Step 2:

[1182] The server receives the basic information data sent by the user.

[1183] Input: User's basic information data

[1184] Specific operation: Validate the received data, check the format of the email address, and confirm required fields.

[1185] Output: Basic information data that has passed validation is saved in the database.

[1186] Step 3:

[1187] When the senior mentor accesses the system for the first time, the terminal of the senior mentor displays a registration form for inputting basic information and skill sets.

[1188] Input: Senior Mentor's basic information and skill set

[1189] Specific Actions: The senior mentor fills in the information in each field and clicks the "Submit" button.

[1190] Output: The basic information and skill set data entered by the senior mentor is sent to the server.

[1191] Step 4:

[1192] The server receives the basic information and skill set data sent by the senior mentor.

[1193] Input: Senior Mentor's basic information and skill set data

[1194] Specific operation: Validate the received data and check the format of the input data.

[1195] Output: The information of senior mentors who pass validation is saved in the database.

[1196] Step 5:

[1197] The user's terminal displays a form for entering questions or concerns about the home.

[1198] Input: Questions and concerns about the home

[1199] Specific operation: The user enters a question or concern and clicks the "Submit" button.

[1200] Output: Questions and concerns entered by the user are sent to the server.

[1201] Step 6:

[1202] The server receives questions and worry data sent by users.

[1203] Input: User questions and concerns

[1204] Specific operation: Pass the received data to the emotion engine.

[1205] Output: Data passed to the emotion engine

[1206] Step 7:

[1207] The emotion engine analyzes the user's questions and worries data to identify the user's emotional state.

[1208] Input: User questions and concerns

[1209] What it does: It uses natural language processing (NLP) techniques to analyze text and identify emotional states (stress, anxiety, joy, etc.).

[1210] Output: Emotional state data (type and degree of emotion)

[1211] Step 8:

[1212] The server passes the emotional state data analyzed by the emotion engine to a generative artificial intelligence (AI).

[1213] Input: Emotional state data

[1214] Specific operation: Emotional state data is passed as input to generative artificial intelligence.

[1215] Output: Emotional state data passed to the generative AI

[1216] Step 9:

[1217] Generative AI generates appropriate advice based on the user's questions, concerns, and emotional state data.

[1218] Input: User questions, concerns, and emotional state data

[1219] How it works: The AI ​​model analyzes both sets of data and generates optimal advice.

[1220] Output: Generated advice data

[1221] Example: If a user asks for advice about their child not studying, but the emotion engine detects stress or anxiety, the AI ​​will generate advice like, "Start by creating a relaxing environment. It's also important to spend time relaxing with your child."

[1222] Step 10:

[1223] The server returns the generated advice data to the user's terminal.

[1224] Input: Generated advice data

[1225] Specific operation: Advice data is sent to the user's device.

[1226] Output: Advice displayed on the user's terminal

[1227] Step 11:

[1228] The server runs a matching algorithm to select the most suitable senior mentor based on the user's question or concern, emotional state, the senior mentor's skill set, and user ratings.

[1229] Input: User questions and concerns, emotional state data, senior mentor skill data, user evaluation data

[1230] Specific operation: Apply a matching algorithm to select the most suitable senior mentor.

[1231] Output: Information about the selected senior mentor

[1232] Step 12:

[1233] The server compares the schedules of the user and senior mentor and suggests the best date and time.

[1234] Input: User's schedule data, Senior Mentor's schedule data

[1235] Specific behavior: Match schedules and suggest the best time and date.

[1236] Output: Suggested best time

[1237] Step 13:

[1238] The senior mentor will visit the user's home at the proposed date and time to provide assistance.

[1239] Input: Suggested best date and time

[1240] Specific actions: A senior mentor will visit the home at the proposed date and time to provide assistance with housework and childcare.

[1241] Output: Data on completed support activities

[1242] Step 14:

[1243] After the support is completed, the user's terminal displays a feedback form, allowing the user to input their opinions and evaluations of the support they received.

[1244] Input: User opinions and ratings

[1245] What happens: A user fills out a feedback form and clicks the "Submit" button.

[1246] Output: User feedback data

[1247] Step 15:

[1248] The server receives feedback from users and reflects it in the senior mentor's evaluation system, and also provides a feedback form to the senior mentor.

[1249] Input: User feedback data, Senior Mentor feedback data

[1250] Specific actions: Feedback data will be reflected in the evaluation system and the data will be used to improve matching accuracy and service quality next time.

[1251] Output: Updated rating system data

[1252] (Application example 2)

[1253] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1254] When providing meal suggestions or cooking assistance at home, suggestions or assistance that do not take into account the user's emotional state may not provide sufficient satisfaction. Furthermore, matching or responses that do not take the user's emotional state into account may lead to discrepancies between the provider and the user. Conventional methods have difficulty providing detailed advice based on emotions or efficiently matching providers.

[1255] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for the user to input questions, concerns, or emotional state related to the home, means for the server to receive the user's input information and pass it on to the emotion engine, and means for the emotion engine to analyze the user's emotional state and pass the results on to the generative AI. This makes it possible to match appropriate meal suggestions and providers such as chefs according to the user's emotional state.

[1256] A "user" is an individual who uses the system to ask questions or concerns about their home, as well as to seek meal suggestions.

[1257] An "emotion engine" is software or hardware for analyzing the user's emotional state from input information.

[1258] "Generative AI" is an AI system that analyzes a user's input information and emotional state and generates appropriate advice.

[1259] A "provider" is a person or organization that provides a service to a user, and includes chefs, housekeeping assistants, etc.

[1260] "Server" refers to a computer system that performs the central data processing and management of this system.

[1261] A "skill set" is a list of skills and techniques possessed by a provider, and is information for providing appropriate support to users.

[1262] "User Ratings" refers to other users' ratings and feedback on services provided in the past.

[1263] "Feedback" refers to evaluations and opinions given by users regarding the services provided.

[1264] "Emotional state" refers to the psychological state analyzed from the information entered by the user, examples of which include stress and relaxation.

[1265] 1. Overall system configuration

[1266] An embodiment of this invention is a system that provides advice and services that take into account a user's emotional state when they request meal suggestions or cooking assistance. This system is composed of a user terminal, a server, an emotion engine, a generative artificial intelligence, a provider terminal, etc.

[1267] 2. Hardware and Software Used

[1268] This system uses the following hardware and software:

[1269] Emotion engine: Uses various emotion analysis APIs, such as Microsoft Azure Emotion API and IBM Watson Tone Analyzer.

[1270] Generative AI: Use generative AI models such as OpenAI GPT-4.

[1271] Backend: Uses cloud computing services, such as AWS Lambda and its database service AWS RDS.

[1272] Frontend: Using React Native for smartphone applications.

[1273] Database: Use a relational database such as PostgreSQL.

[1274] 3. Data processing and calculation

[1275] User registration and initial settings

[1276] When a user accesses the system for the first time, he enters basic information (name, address, email address, etc.) in the user registration form. The server receives this information, validates it, and then stores it in the database.

[1277] Inputting questions and concerns and recognizing emotions

[1278] Users input questions and concerns about their home into the app and express their emotional state. This information is sent to the server and passed to the emotion engine. The emotion engine analyzes the user's emotional state from the input information and returns the results to the server.

[1279] Generating Advice

[1280] The server passes the emotional state data received from the emotion engine to the generative AI, which takes into account the user's questions, concerns, and emotional state to generate optimal advice. The advice is then sent back to the user from the server and displayed on the app.

[1281] Provider matching

[1282] The server selects the best provider for the user based on advice generated by the emotion engine and generative AI. The provider's skill set and past reviews are also taken into consideration. For example, if the user's emotional state is unstable, a chef with a high level of empathy will be prioritized.

[1283] Scheduling and feedback

[1284] The system checks the schedules of the user and provider and proposes the optimal date and time. If this is accepted, the date and time of the service is confirmed and the provider provides the service at the specified date and time. After that, the user's feedback is sent to the server, stored in a database, and reflected in the rating system.

[1285] 4. Specific Examples

[1286] When a user types "I'm very tired today," and the emotion engine analyzes "tired," the generative AI suggests a relaxing meal. The meal suggestion includes "grilled salmon and steamed vegetables," and the system matches the user with a highly rated chef near the user. The following prompt appears on the user's smartphone:

[1287] "The user is extremely tired. Based on this emotional state, suggest a relaxing meal."

[1288] This system will significantly improve satisfaction at home by suggesting meals based on the user's emotional state and matching them with chefs and other providers.

[1289] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1290] Step 1:

[1291] On the user's device, the user inputs questions, concerns, and emotional state about the home. Specifically, the user enters text into an input form within the app. This becomes input data and is sent to the server.

[1292] Step 2:

[1293] The server passes the received user input data to the emotion engine. The emotion engine analyzes the user's emotional state from the text and returns the result (e.g., stress, relaxation, etc.) to the server. The data processing performed in this step is text analysis, and generates output data called the emotional state.

[1294] Step 3:

[1295] The server passes the analyzed emotional state to a generative AI (such as GPT-4). The generative AI receives the user's questions, concerns, and emotional state as input data and generates optimal advice. This advice is returned to the server in text format. The data calculation in this step is advice generation using natural language processing.

[1296] Step 4:

[1297] The server returns the advice received from the generative AI to the user. This advice is displayed on the user's device. The specific processing performed here involves API communication and retrieval from a database.

[1298] Step 5:

[1299] The server selects an appropriate provider based on the generated advice, emotional state, and user input information. The provider's skill set is compared with the user rating database to perform matching. Information about the selected provider is presented to the user. The data calculation in this step is the execution of a matching algorithm.

[1300] Step 6:

[1301] The server adjusts the schedules of the user and provider and proposes the optimal date and time. The proposed date and time are sent to the user's device and the provider's device, and both parties confirm them. In this step, the date and time are adjusted using the calendar API.

[1302] Step 7:

[1303] The provider will visit the user's designated location at the date and time determined by the server, and provide meal suggestions and cooking assistance services. At this time, the provider's device will report the progress to the server. Specific operations include GPS tracking and check-in functions.

[1304] Step 8:

[1305] After the service is provided, the user enters feedback and sends it to the server. The server stores the feedback in a database and reflects it in the provider's evaluation system. In this step, the questionnaire form and database are updated.

[1306] These processing steps realize an automated emotion-based meal suggestion and cooking assistance system.

[1307] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1308] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1309] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1310] [Fourth embodiment]

[1311] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1312] 7, a 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.

[1313] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. 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. The database 24 and the communication I / F 26 are also 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).

[1314] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1315] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1316] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1317] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1318] The control object 443 includes a display device, LEDs in the eyes, and motors for driving 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 emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1319] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1320] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1321] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1322] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1323] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1324] The present invention relates to a family support platform, which is a system that provides advice and support for family questions and concerns through the cooperation of generative artificial intelligence (AI) and senior mentors. Specific embodiments for implementing the present invention will be described below.

[1325] Program processing and system configuration

[1326] 1. User registration and initial settings

[1327] When the user accesses the site for the first time, the user's device displays a registration form for entering basic information (such as name, address, email address, and family concerns). The server receives the information entered by the user, validates it, and stores it in a database. Similarly, the senior mentor's device displays a form for entering the senior mentor's basic information and skill set, and sends the entered data to the server. The server also validates the information entered by the senior mentor and stores it in a database.

[1328] 2. Input your questions and concerns and receive answers from AI

[1329] The user's device provides a dedicated form for entering questions and concerns about the home. When the user enters and submits their concerns, the server passes this information to a generative AI. The generative AI analyzes the question or concern and generates optimal advice. The generated advice is then sent back to the user's device via the server and displayed to the user.

[1330] 3. Senior mentor matching

[1331] The server runs an algorithm to match users with appropriate senior mentors based on their questions and concerns. The algorithm selects the best candidates by taking into account the senior mentors' skill sets and user ratings. The server then presents the selected senior mentors to the user.

[1332] As a specific example, if a user inputs "I would like some help with my child's studies," the server will select and suggest highly rated senior mentors who have education-related skills.

[1333] 4. Adjust your schedule

[1334] If both the user and the selected senior mentor accept the proposal, the server compares their schedules and proposes the optimal date and time. If the user and the senior mentor agree on the optimal date and time, the date and time of the support is confirmed.

[1335] 5. On-site support

[1336] The senior mentor visits the user's home at the specified date and time and provides the necessary support (e.g., housework support, childcare support). The support content and progress are sent to the server and recorded.

[1337] For example, if a senior mentor prepares dinner at the user's request, details such as the cooking steps and the time it will be ready will be recorded.

[1338] 6. Feedback and Ratings

[1339] After the support is completed, the user's device displays a feedback form, allowing the user to enter their opinion and evaluation of the support they received. The server receives the feedback and reflects it in the senior mentor's evaluation system. It also provides a feedback function to senior mentors, allowing them to enter their evaluation and thoughts about the user. This improves the quality of the entire system and the accuracy of the next match.

[1340] In this way, the home support platform of the present invention is a system that utilizes AI technology and senior mentors to reduce worries and burdens within the home, strengthen ties with the local community, and provide social roles and opportunities for interaction for the elderly.

[1341] The processing flow will be explained below.

[1342] Step 1:

[1343] When the user accesses the site for the first time, the user's device displays a registration form for entering basic information (such as name, address, email address, and household concerns).

[1344] Step 2:

[1345] The user enters the necessary information and clicks the registration button.

[1346] Step 3:

[1347] The server receives the information entered by the user and performs validation. If the input data is valid, it is saved in the database. At the same time, a welcome message is displayed on the user's terminal.

[1348] Step 4:

[1349] The senior mentor's device also displays a registration form where the senior mentor can enter their skills, background, and support details.

[1350] Step 5:

[1351] The senior mentor enters the required information and clicks the registration button.

[1352] Step 6:

[1353] The server receives the information entered by the senior mentor, validates it, and if the input data is valid, stores it in the database.

[1354] Step 7:

[1355] The user's device displays a dedicated form where the user can enter questions or concerns about their home. The user enters their question or concern and clicks the send button.

[1356] Step 8:

[1357] The server receives the user's input information and passes it to the generative artificial intelligence.

[1358] Step 9:

[1359] Generative AI analyzes users' questions and concerns and generates optimal advice.

[1360] Step 10:

[1361] The server receives the generated advice and returns it to the user's terminal.

[1362] Step 11:

[1363] The user's terminal displays the received advice.

[1364] Step 12:

[1365] The server runs a matching algorithm to select the most suitable senior mentor based on the user's questions and concerns, the senior mentor's skill set, and user ratings.

[1366] Step 13:

[1367] The server presents information about the selected senior mentor to the user's terminal.

[1368] Step 14:

[1369] Once the user selects a suitable senior mentor from the candidates, the information is sent to the server.

[1370] Step 15:

[1371] The server compares the schedules of the user and the selected senior mentor and suggests the most suitable date and time.

[1372] Step 16:

[1373] The user's terminal and the senior mentor's terminal check the proposed date and time, and return to the server their consent or desire to amend it.

[1374] Step 17:

[1375] The server confirms the date and time agreed upon by both the user and the senior mentor as the schedule, and again notifies the details to both users' terminals.

[1376] Step 18:

[1377] The senior mentor visits the user's home at a fixed date and time and provides the necessary support (e.g., housework support, childcare support).

[1378] Step 19:

[1379] After the support is completed, the user's terminal displays a feedback form, allowing the user to input their opinions and evaluations of the support they received.

[1380] Step 20:

[1381] The server records the feedback received from the user and reflects it in the senior mentor's evaluation system. It also processes the senior mentor's evaluation in the same way.

[1382] In this way, the home support platform of the present invention provides professional advice and direct support in response to the user's concerns and requests.

[1383] Example 1

[1384] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1385] Modern families require immediate and appropriate advice and support for domestic worries and problems. However, in busy daily lives, it is not easy to immediately obtain the necessary support. Furthermore, there is a lack of mechanisms to utilize the wealth of experience and knowledge that older people possess and to strengthen their ties with the local community. An effective system to resolve these issues is needed.

[1386] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1387] In this invention, the server includes a means for users to input questions and concerns about their home, a means for a generative AI to analyze the input information and generate advice, and a means for selecting the most suitable mentor based on the mentor's skills and user ratings. This makes it possible to provide prompt and appropriate advice and support for problems and concerns within the home, as well as to provide elderly people with social roles and opportunities for interaction.

[1388] "User" refers to an individual who uses this system to input questions and concerns about their home and receive advice and support.

[1389] "Server" refers to the computer system that receives and sends information from users and mentors, and manages and processes the advice and feedback generated by the generative AI.

[1390] "Generative AI" refers to AI technology that has the ability to analyze received input information and generate appropriate advice.

[1391] "Advice" refers to solutions and suggestions provided by generative artificial intelligence based on the user's questions and concerns.

[1392] A "mentor" is a support provider, such as an older person, who has the skills and experience to provide support for the home.

[1393] "Skills" refers collectively to the knowledge and experience related to the specific support that a mentor can provide.

[1394] "User ratings" refer to feedback and ratings provided by users who have received support from a mentor in the past.

[1395] "Feedback" refers to evaluations and opinions about the support provided by users and mentors and about the system as a whole.

[1396] "Schedule" refers to the specific date and time for the user and mentor to provide support.

[1397] The present invention relates to a family support system that provides effective advice and support for questions and concerns of families through the cooperation of generative artificial intelligence (AI) and senior mentors. Specific embodiments for carrying out the invention are described below.

[1398] User registration and initial settings

[1399] Users access the system from their own devices and use a form to enter basic information (such as name, address, email address, and family concerns). The entered information is sent to the server, where data validation takes place. Once validation is complete, the server stores the data in a database. Similarly, senior mentors also use their own devices to enter basic information and skill sets, which are also sent to the server, where they are validated and stored in the database.

[1400] Enter your questions and concerns and receive answers from AI

[1401] Users enter questions or concerns about their home into a dedicated question form and send it to the server. The server passes the received question information to a generative AI. The generative AI analyzes the entered question and generates the most appropriate advice. The generated advice is sent back to the user's device via the server. For example, if a user enters, "I would like you to support my child's studies," the server sends this to the AI ​​as a prompt: "Please introduce me to a mentor who can provide support for my child's studies at home. My child is in the fifth grade of elementary school and particularly needs support with math and English."

[1402] Senior mentor matching

[1403] The server analyzes the user's questions and concerns and runs an algorithm to match them with an appropriate senior mentor. This algorithm considers the senior mentor's skill set and past user ratings to select the most suitable candidate. Information about the selected senior mentor is displayed on the user's device. For example, if a user enters "I would like some help with my child's studies," the server will present senior mentors with education-related skills and high user ratings.

[1404] Schedule adjustments

[1405] When the user and the selected senior mentor accept the proposal, the server checks their respective schedules and proposes the optimal date and time. If both parties agree on the optimal date and time, the date and time of the support is confirmed and the server notifies the user and the senior mentor of this information.

[1406] On-site support

[1407] The senior mentor visits the user's home at the confirmed date and time and provides the necessary support (for example, housework or childcare support). The progress and content of the support are sent to the server and recorded. For example, if the senior mentor prepares dinner, details such as the cooking procedure and the time it is ready are recorded on the server.

[1408] Feedback and Ratings

[1409] After receiving assistance, the user enters their opinions and evaluations into a feedback form on their device and sends it to the server. The server receives this feedback and reflects it in the senior mentor's evaluation system. Similarly, the senior mentor also enters feedback for the user and sends it to the server. This two-way feedback improves the quality of the entire system and the accuracy of the next match.

[1410] The home support system of the present invention utilizes generative AI models and the skills of senior mentors to reduce worries and burdens within the home, strengthen connections with the local community, and provide social roles and opportunities for interaction for the elderly.

[1411] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1412] Step 1: User registration and initial setup

[1413] When a user accesses the system for the first time, they enter basic information such as their name, address, email address, and family concerns into the registration form displayed on their terminal. This entered information is sent to the server. The server validates the received information and ensures that it is in the correct format. For example, it checks the format of the email address and whether any fields are required. Once validated, the information is stored in the database. Similarly, senior mentors use their terminals to enter basic information and skill sets and send it to the server. The server similarly validates this information and stores it in the database.

[1414] Step 2: Enter your question or concern

[1415] The user accesses a dedicated form for entering questions and concerns about their home and enters the details. For example, they might enter, "I would like some help with my child's studies," and press the send button. The entered information is sent to the server. The server then generates a prompt to pass the received question information to the generative AI model. For example, it generates a prompt such as, "Please introduce me to a mentor who can provide support for my child's studies at home. My child is in the fifth grade of elementary school and needs particular support with math and English."

[1416] Step 3: Generate answers with AI

[1417] The server sends the generated prompt to the generative AI model, which generates optimal advice based on the received prompt. For example, the generated advice might be, "To support children's learning, it is effective to repeatedly practice a specific subject for 30 minutes every day." This advice is then sent back to the server.

[1418] Step 4: Providing advice

[1419] The server provides the user with the advice returned by the generative AI model. Specifically, the advice is output in the form of a display on the user's device. By referring to this advice, the user can obtain specific measures to solve problems at home.

[1420] Step 5: Matching with a senior mentor

[1421] The server runs an algorithm that matches the most suitable senior mentor based on the user's questions and concerns, their skill sets, and user ratings. The input data is the user's question and the senior mentor's skill sets and rating data, and the output data is a list of suitable mentor candidates. For example, in response to a request to "help support my child's studies," the server selects and presents mentors with education-related skills and high ratings.

[1422] Step 6: Adjust your schedule

[1423] The server compares the schedules of the user and the selected senior mentor and proposes the optimal date and time. The input data is the time slots available to the user and mentor, and the output data is the optimal date and time for support that both parties agree on. Once both parties agree on this date and time, the date and time for support is confirmed. This confirmation information is notified to both the user and mentor via the server.

[1424] Step 7: Implementing on-site support

[1425] The senior mentor visits the user's home at the confirmed date and time and provides the promised support (e.g., housework or childcare support). The progress and status of the support are recorded in real time and sent to the server. For example, if dinner is prepared, the cooking steps and completion time are recorded. This allows the user to check the progress of the support.

[1426] Step 8: Feedback and Rating

[1427] After completing the assistance, the user enters their opinion and evaluation in a feedback form on their device and sends it to the server. The server receives this feedback and reflects it in the senior mentor's evaluation system. The senior mentor also enters feedback for the user on their device and sends it to the server. This improves the quality of the entire system and the accuracy of the next match.

[1428] (Application example 1)

[1429] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1430] Modern households face a variety of problems and worries, and require quick and appropriate solutions. However, there are many situations where it is difficult to receive reliable advice and support immediately. In particular, it is difficult to provide specialized household support when dealing with customers in physical stores. Another problem is that responding individually to every customer requires a huge amount of time and effort, placing a heavy burden on store staff. This has led to issues such as a decline in customer satisfaction and an increased burden on staff.

[1431] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1432] In this invention, the server includes a means for the user to input questions and concerns about the home, a means for the server to receive the user's input information and pass it to the generative AI, and a means for the generative AI to analyze the input information and generate advice, which enables the following effects.

[1433] 1. Users can input their questions or concerns through their smart devices, and advice will be provided through generative AI and senior mentors, enabling customers to receive quick and reliable advice.

[1434] 2. The server selects the most suitable senior mentor based on the advice, the senior mentor's skill set, and the user's ratings, and determines the date and time of support, ensuring that a senior mentor with the appropriate skills can respond quickly.

[1435] 3. By receiving feedback and reflecting it in the evaluation system, the quality of the entire system and the accuracy of the next match can be improved.

[1436] A "user" is a person who inputs questions or concerns about the home and receives advice or support using this system.

[1437] "Questions and concerns about the home" include various issues and concerns in everyday life, such as housework, child-rearing, and interior design.

[1438] A "smart device" is a portable electronic device that can connect to the Internet, such as a smartphone, smart glasses, or a head-mounted display.

[1439] "Generative AI" is an AI program that analyzes information entered by the user and provides optimal advice based on that information.

[1440] The "server" is an information processing device that manages information for the entire system, exchanges data with generative AI, selects senior mentors, and coordinates schedules.

[1441] A "senior mentor" is a senior citizen who provides advice and support to help users solve their household problems.

[1442] A "skill set" is the collection of knowledge, experience, specific abilities and qualifications that a senior mentor possesses.

[1443] "User ratings" are the results of feedback and ratings given to senior mentors by past users.

[1444] "Schedule adjustment" is the process of determining the most suitable date and time for support based on the availability of the user and senior mentor.

[1445] "Feedback" refers to the act of a user inputting their thoughts and evaluations of the support they have received, and this data is reflected in the senior mentor's evaluation system.

[1446] "Interior consultation" refers to the act of providing advice on home decoration, furniture placement, etc.

[1447] This invention relates to a family support platform, which is a system that provides advice on family questions and concerns through the cooperation of generative artificial intelligence (AI) and senior mentors. Specific embodiments for implementing the present invention will be described below.

[1448] 1. User registration and initial settings

[1449] Users access the application using a device such as a smartphone. When they access it for the first time, a form is displayed in which they can enter basic information (such as name, address, email address, and family concerns). The information they enter is sent to the server, where it is validated and then saved in a database. Senior mentors also enter their own basic information and skill set and send it to the server. This completes the registration of the user and senior mentor.

[1450] 2. Input your questions and concerns and receive answers from AI

[1451] Users input questions or concerns about their home through their smart device. The input information is sent to a server and passed to a generative AI. The AI ​​analyzes the input information and generates appropriate advice. This advice is then sent back to the user's smart device via the server.

[1452] 3. Senior mentor matching

[1453] The server runs an algorithm to select the most suitable senior mentor based on the user's concerns, the senior mentor's skill set, and the user's ratings. Information on the matched senior mentor is then presented to the user.

[1454] 4. Adjust your schedule

[1455] If both the user and the senior mentor accept the proposal, the server compares their schedules and proposes the optimal date and time. The date and time agreed upon by both parties is confirmed and the date and time of the support is decided.

[1456] 5. On-site support

[1457] The senior mentor visits the user's home at the specified date and time and provides the necessary support, such as housework assistance, childcare assistance, interior design advice, etc. The content of the support and progress are sent to the server and recorded.

[1458] 6. Feedback and Ratings

[1459] After completing the support, the user enters their evaluation through a feedback form. The feedback is sent to the server and reflected in the senior mentor's evaluation system. Senior mentors can also enter their evaluations and thoughts about the user. This improves the overall quality of the system and the accuracy of the next match.

[1460] Hardware and software used

[1461] Server: The server manages the database, exchanges data with the generative AI, adjusts schedules, and manages the evaluation system. Specifically, Django (web framework) and PostgreSQL (database) are used.

[1462] Generative AI: Generative AI, such as OpenAI's GPT-3 model, is used to analyze users' questions and concerns and generate appropriate advice.

[1463] Smart devices: Smartphones, smart glasses, head-mounted displays, etc. are used by users to input questions or concerns and receive advice.

[1464] Examples of specific examples and prompts

[1465] For example, if a user inputs a request for home interior design advice, the generative AI will generate detailed advice such as "change the color of the curtains in the living room, add plants, and adjust the lighting."

[1466] Prompt Sentence Examples

[1467] I'd like to consult with a home support platform application about recommended interior changes. I'd like specific advice, such as changing the color of the curtains in the living room or adding some plants.

[1468] Through this system, users can quickly and appropriately resolve various family-related issues, and senior mentors can gain social roles and opportunities for interaction.

[1469] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1470] Step 1:

[1471] User registration and initial settings

[1472] Users access the application using a device such as a smartphone. When they access it for the first time, a form is displayed in which they can enter basic information (such as name, address, email address, and family concerns). The information entered by the user is sent to the server. The server receives the information, validates it, and stores it in a database. Senior mentors also enter their own basic information and skill set and send it to the server.

[1473] Step 2:

[1474] Enter your questions and concerns

[1475] Users input questions or concerns about their home through their smart devices. When a user inputs a question or concern and presses the send button, the information is sent to the server. The server receives this input information and passes it to the generative AI.

[1476] Step 3:

[1477] Answer generation using generative artificial intelligence

[1478] The server passes the received questions and concerns to a generative AI, which analyzes the input information and generates optimal advice. During this process, an AI model (e.g., GPT-3) understands the context and constructs appropriate solutions and advice. The generated advice is then sent back to the server.

[1479] Step 4:

[1480] Conveying advice

[1481] The server receives the advice sent back from the generative AI and sends it back to the user's smart device, where the user can check the content of the advice.

[1482] Step 5:

[1483] Senior mentor matching

[1484] The server runs an algorithm to select the most suitable senior mentor based on the user's concerns, the senior mentor's skill set, and the user's ratings. When the algorithm is run, the senior mentor's past ratings and areas of expertise are taken into consideration. The server then presents information about the selected senior mentor to the user.

[1485] Step 6:

[1486] Schedule adjustment

[1487] If both the user and the senior mentor accept the proposal, the server compares their schedules and proposes the optimal date and time. If the proposed date and time is approved by both parties, the server confirms the date and time and notifies both parties.

[1488] Step 7:

[1489] On-site support

[1490] The senior mentor will visit the user's home at the agreed date and time and provide the necessary support. For example, specific support such as housework assistance, childcare assistance, and interior design advice will be provided. The senior mentor will then send the support process and results to the server as recorded data.

[1491] Step 8:

[1492] Feedback and Ratings

[1493] After completing the support, the user enters their evaluation through a feedback form. The feedback information entered by the user is sent to the server and reflected in the senior mentor's evaluation system. Senior mentors can also enter their evaluations and thoughts about the user. The server stores this feedback information in a database and uses it to improve the quality of the entire system.

[1494] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1495] The present invention provides a system that combines a home support platform with an emotion engine to provide advice and support that takes into account the user's emotional state. Specific embodiments for carrying out the present invention will be described below.

[1496] Program processing and system configuration

[1497] 1. User registration and initial settings

[1498] When the user accesses the site for the first time, the user's device displays a registration form for entering basic information (such as name, address, email address, and family concerns). The server receives the information entered by the user, validates it, and stores it in a database. Similarly, the senior mentor's device displays a form for entering the senior mentor's basic information and skill set, and sends the entered data to the server. The server also validates the information entered by the senior mentor and stores it in a database.

[1499] 2. Inputting questions and concerns and emotion recognition

[1500] The user's device provides a dedicated form for inputting questions or concerns about the home. When the user inputs and submits the question or concern, the server passes the information to the emotion engine, which analyzes the user's emotional state from the input information.

[1501] 3. AI-generated and tailored advice

[1502] The server passes the emotional state analyzed by the emotion engine to the generative AI. The generative AI analyzes the user's question, concerns, and emotional state, and generates optimal advice. Because the emotional state is taken into consideration, if the user is feeling stressed, for example, advice including a gentler tone and stress reduction measures will be generated. The generated advice is sent back to the user's device via the server and displayed to the user.

[1503] As a specific example, if a user asks for advice about their child not studying, but the emotion engine detects stress or anxiety, the generative AI will provide advice such as, "Start by creating a relaxing environment. It's also important to spend time relaxing with your child."

[1504] 4. Senior mentor matching

[1505] The server runs a matching algorithm to select the most suitable senior mentor based on the user's question or concern, emotional state, the senior mentor's skill set, and user ratings. The user's emotional state is also taken into consideration, so if the emotional state is negative, for example, a senior mentor with high responsiveness and empathy will be prioritized. The server then presents information about the selected senior mentor to the user.

[1506] 5. Adjust your schedule

[1507] If both the user and the selected senior mentor accept the proposal, the server compares their schedules and proposes the optimal date and time. If the user and the senior mentor agree on the optimal date and time, the date and time of the support is confirmed.

[1508] 6. On-site support

[1509] The senior mentor visits the user's home at the specified date and time to provide necessary support such as housework assistance and childcare assistance. The content of the assistance and progress are sent to the server and recorded.

[1510] For example, if a senior mentor prepares dinner at the user's request, details such as the cooking steps and the time it will be ready will be recorded.

[1511] 7. Feedback and Ratings

[1512] After the support is completed, the user's device displays a feedback form, allowing the user to enter their opinion and evaluation of the support they received. The server receives the feedback and reflects it in the senior mentor's evaluation system. It also provides a feedback function to senior mentors, allowing them to enter their evaluation and thoughts about the user. This improves the quality of the entire system and the accuracy of the next match.

[1513] In this way, the home support platform of the present invention is a system that provides more appropriate and personalized support to users by utilizing an emotion engine that can recognize and respond to the user's emotional state, generative AI, and senior mentors, thereby reducing the burden on families, strengthening ties in the local community, and providing social roles and opportunities for elderly people to interact.

[1514] The processing flow will be explained below.

[1515] Step 1:

[1516] When the user accesses the site for the first time, the user's device displays a registration form for entering basic information (such as name, address, email address, and household concerns).

[1517] Step 2:

[1518] The user enters the necessary information and clicks the registration button.

[1519] Step 3:

[1520] The server receives the information entered by the user and performs validation. If the input data is valid, it is saved in the database. At the same time, a welcome message is displayed on the user's terminal.

[1521] Step 4:

[1522] The senior mentor's device also displays a registration form where the senior mentor can enter their skills, background, and support details.

[1523] Step 5:

[1524] The senior mentor enters the required information and clicks the registration button.

[1525] Step 6:

[1526] The server receives the information entered by the senior mentor, validates it, and if the input data is valid, stores it in the database.

[1527] Step 7:

[1528] The user's device displays a dedicated form where the user can enter questions or concerns about their home. The user enters their question or concern and clicks the send button.

[1529] Step 8:

[1530] The server receives the user's input information and passes it to the emotion engine.

[1531] Step 9:

[1532] The emotion engine analyzes the user's emotional state (stress, anxiety, joy, etc.) from their input information.

[1533] Step 10:

[1534] The emotion engine sends the analysis results to the server.

[1535] Step 11:

[1536] The server passes the emotional state analyzed by the emotion engine to the generative AI.

[1537] Step 12:

[1538] Generative AI analyzes the user's questions, concerns, and emotional state to generate optimal advice.

[1539] Step 13:

[1540] The server receives the generated advice and returns it to the user's terminal.

[1541] Step 14:

[1542] The user's terminal displays the received advice.

[1543] Step 15:

[1544] The server runs a matching algorithm to select the most suitable senior mentor based on the user's question or concern, emotional state, the senior mentor's skill set, and user ratings.

[1545] Step 16:

[1546] The server presents information about the selected senior mentor to the user's terminal.

[1547] Step 17:

[1548] Once the user selects a suitable senior mentor from the candidates, the information is sent to the server.

[1549] Step 18:

[1550] The server compares the schedules of the user and the selected senior mentor and suggests the most suitable date and time.

[1551] Step 19:

[1552] The user's terminal and the senior mentor's terminal check the proposed date and time, and return to the server their consent or desire to amend it.

[1553] Step 20:

[1554] The server confirms the date and time agreed upon by both the user and the senior mentor as the schedule, and again notifies the details to both users' terminals.

[1555] Step 21:

[1556] The senior mentor visits the user's home at a fixed date and time and provides the necessary support (e.g., housework support, childcare support).

[1557] Step 22:

[1558] After the support is completed, the user's terminal displays a feedback form, allowing the user to input their opinions and evaluations of the support they received.

[1559] Step 23:

[1560] The server records the feedback received from the user and reflects it in the senior mentor's evaluation system. It also processes the senior mentor's evaluation in the same way.

[1561] Step 24:

[1562] The server stores all feedback in a database and analyzes the data to reflect it in the next matching algorithm.

[1563] Example 2

[1564] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1565] Conventional home support platforms provide uniform advice and support without considering the user's emotional state, which means they are unable to fully alleviate the stress and frustration felt by users. This results in problems that make it difficult to resolve family problems and reduces user satisfaction. Another issue is the low accuracy of matching users with senior mentors, which limits the efficiency and effectiveness of support.

[1566] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1567] In this invention, the server includes a means for a user to input questions and concerns about the home, a means for an emotion engine to analyze the user's emotional state, and a means for a generative artificial intelligence to generate and adjust advice taking into account the user's input information and emotional state. This makes it possible to provide personalized advice that reflects the user's emotional state, resulting in effective solutions to home problems.

[1568] "User" refers to an individual with a household concern or question who uses this system.

[1569] "Device" refers to the electronic device used by users and senior mentors to access the system, such as a smartphone, tablet, or PC.

[1570] "Server" refers to the computer system that processes and stores information received from Users and Senior Mentors and manages the entire system.

[1571] An "emotion engine" refers to software or algorithms that analyze information entered by a user and recognize the user's emotional state (e.g., stress, anxiety, joy, etc.).

[1572] "Generative artificial intelligence (AI)" refers to an AI system that has the ability to generate optimal advice based on a user's questions, concerns, and emotional state.

[1573] "Advice" refers to the advice or instructions that generative artificial intelligence provides to solve a user's questions or concerns.

[1574] "Senior Mentor" refers to an experienced individual who is responsible for providing family support to a user.

[1575] "Support" refers to specific services such as housework assistance and childcare support that senior mentors provide by visiting users' homes.

[1576] "Feedback" refers to the user's opinions and evaluations of the support they have received, as well as the evaluations and impressions that senior mentors provide to users.

[1577] The "evaluation system" refers to a system that collects and analyzes feedback from users and senior mentors to improve the accuracy of matching and service quality for the next time.

[1578] "Matching algorithm" refers to a calculation method for selecting the most suitable senior mentor based on the content of the user's question or concern, emotional state, the senior mentor's skill set, and user evaluation.

[1579] "Database" refers to data storage for saving and managing data such as user information, senior mentor information, questions and concerns, support details, and feedback processed by the system.

[1580] "Validation" refers to the process by which the server verifies that the information entered by the user or senior mentor is accurate and complete.

[1581] "Personalization" refers to optimizing the advice and assistance provided based on the individual characteristics and emotional state of each user.

[1582] MODE FOR CARRYING OUT THE INVENTION

[1583] The present invention provides a system that combines a home support platform with an emotion engine to provide advice and support that takes into account the user's emotional state. Specific embodiments for carrying out the present invention will be described below.

[1584] User registration and initial settings

[1585] When the user accesses the site for the first time, the user's device displays a registration form for entering basic information (name, address, email address, family concerns, etc.). The server receives the information entered by the user, validates it, and stores it in a database. Similarly, the senior mentor's device displays a form for entering the senior mentor's basic information and skill set, and sends the entered data to the server. The server also validates the information entered by the senior mentor and stores it in a database. For example, MySQL or PostgreSQL is used as the database.

[1586] Inputting questions and concerns and recognizing emotions

[1587] The user's device provides a dedicated form for entering questions or concerns about the home. When the user enters and submits their question or concern, the server receives this information and passes it to the emotion engine. The emotion engine uses natural language processing (NLP) technology to analyze the user's emotional state from the information they input. Specifically, it identifies emotions such as stress, anxiety, and joy.

[1588] AI-powered advice generation and tailoring

[1589] The server passes the emotional state analyzed by the emotion engine to a generative artificial intelligence (AI). The generative AI generates optimal advice based on the user's questions, concerns, and emotional state. Because the emotional state is taken into consideration, if the user is feeling stressed, for example, advice including a gentler tone and stress reduction measures will be generated. The generated advice is sent back to the user's device via the server and displayed to the user.

[1590] Examples:

[1591] If a user asks for advice about their child not studying, but the emotion engine detects stress or anxiety, the generative AI will provide advice such as, "Start by creating a relaxing environment. It's also important to spend time relaxing with your child."

[1592] Example prompt sentence:

[1593] "Please advise on my child not studying. The user seems to be experiencing stress and anxiety."

[1594] Senior mentor matching

[1595] The server runs a matching algorithm to select the most suitable senior mentor based on the user's question or concern, emotional state, the senior mentor's skill set, and user ratings. The server also takes into account the user's emotional state, so if the emotional state is negative, for example, a senior mentor with high responsiveness and empathy will be prioritized. The server then presents information about the selected senior mentor to the user.

[1596] Schedule adjustments

[1597] If both the user and the selected senior mentor accept the proposal, the server compares their schedules and proposes the optimal date and time. If the user and the senior mentor agree on the optimal date and time, the date and time of the support is confirmed.

[1598] On-site support

[1599] The senior mentor visits the user's home at the specified date and time to provide necessary support such as housework assistance and childcare assistance. The content of the assistance and progress are sent to the server and recorded.

[1600] Examples:

[1601] If a senior mentor prepares dinner at the user's request, details such as the cooking steps and the time it is ready are recorded.

[1602] Feedback and Ratings

[1603] After the support is completed, the user's device displays a feedback form, allowing the user to enter their opinion and evaluation of the support they received. The server receives the feedback and reflects it in the senior mentor's evaluation system. It also provides a feedback function to senior mentors, allowing them to enter their evaluation and thoughts about the user. This improves the quality of the entire system and the accuracy of the next match.

[1604] In this way, the home support platform of the present invention is a system that utilizes emotion recognition technology and generative artificial intelligence to provide personalized support that takes into account the user's emotional state, thereby reducing the burden on the home and strengthening ties in the local community.

[1605] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1606] Step 1:

[1607] When a user accesses the system for the first time, the user's terminal displays a registration form for entering basic information.

[1608] Input: User's basic information (name, address, email address, family concerns, etc.)

[1609] What happens: The user enters information into the fields and clicks the "Submit" button.

[1610] Output: The basic information data entered by the user is sent to the server.

[1611] Step 2:

[1612] The server receives the basic information data sent by the user.

[1613] Input: User's basic information data

[1614] Specific operation: Validate the received data, check the format of the email address, and confirm required fields.

[1615] Output: Basic information data that has passed validation is saved in the database.

[1616] Step 3:

[1617] When the senior mentor accesses the system for the first time, the terminal of the senior mentor displays a registration form for inputting basic information and skill sets.

[1618] Input: Senior Mentor's basic information and skill set

[1619] Specific Actions: The senior mentor fills in the information in each field and clicks the "Submit" button.

[1620] Output: The basic information and skill set data entered by the senior mentor is sent to the server.

[1621] Step 4:

[1622] The server receives the basic information and skill set data sent by the senior mentor.

[1623] Input: Senior Mentor's basic information and skill set data

[1624] Specific operation: Validate the received data and check the format of the input data.

[1625] Output: The information of senior mentors who pass validation is saved in the database.

[1626] Step 5:

[1627] The user's terminal displays a form for entering questions or concerns about the home.

[1628] Input: Questions and concerns about the home

[1629] Specific operation: The user enters a question or concern and clicks the "Submit" button.

[1630] Output: Questions and concerns entered by the user are sent to the server.

[1631] Step 6:

[1632] The server receives questions and worry data sent by users.

[1633] Input: User questions and concerns

[1634] Specific operation: Pass the received data to the emotion engine.

[1635] Output: Data passed to the emotion engine

[1636] Step 7:

[1637] The emotion engine analyzes the user's questions and worries data to identify the user's emotional state.

[1638] Input: User questions and concerns

[1639] What it does: It uses natural language processing (NLP) techniques to analyze text and identify emotional states (stress, anxiety, joy, etc.).

[1640] Output: Emotional state data (type and degree of emotion)

[1641] Step 8:

[1642] The server passes the emotional state data analyzed by the emotion engine to a generative artificial intelligence (AI).

[1643] Input: Emotional state data

[1644] Specific operation: Emotional state data is passed as input to generative artificial intelligence.

[1645] Output: Emotional state data passed to the generative AI

[1646] Step 9:

[1647] Generative AI generates appropriate advice based on the user's questions, concerns, and emotional state data.

[1648] Input: User questions, concerns, and emotional state data

[1649] How it works: The AI ​​model analyzes both sets of data and generates optimal advice.

[1650] Output: Generated advice data

[1651] Example: If a user asks for advice about their child not studying, but the emotion engine detects stress or anxiety, the AI ​​will generate advice like, "Start by creating a relaxing environment. It's also important to spend time relaxing with your child."

[1652] Step 10:

[1653] The server returns the generated advice data to the user's terminal.

[1654] Input: Generated advice data

[1655] Specific operation: Advice data is sent to the user's device.

[1656] Output: Advice displayed on the user's terminal

[1657] Step 11:

[1658] The server runs a matching algorithm to select the most suitable senior mentor based on the user's question or concern, emotional state, the senior mentor's skill set, and user ratings.

[1659] Input: User questions and concerns, emotional state data, senior mentor skill data, user evaluation data

[1660] Specific operation: Apply a matching algorithm to select the most suitable senior mentor.

[1661] Output: Information about the selected senior mentor

[1662] Step 12:

[1663] The server compares the schedules of the user and senior mentor and suggests the best date and time.

[1664] Input: User's schedule data, Senior Mentor's schedule data

[1665] Specific behavior: Match schedules and suggest the best time and date.

[1666] Output: Suggested best time

[1667] Step 13:

[1668] The senior mentor will visit the user's home at the proposed date and time to provide assistance.

[1669] Input: Suggested best date and time

[1670] Specific actions: A senior mentor will visit the home at the proposed date and time to provide assistance with housework and childcare.

[1671] Output: Data on completed support activities

[1672] Step 14:

[1673] After the support is completed, the user's terminal displays a feedback form, allowing the user to input their opinions and evaluations of the support they received.

[1674] Input: User opinions and ratings

[1675] What happens: A user fills out a feedback form and clicks the "Submit" button.

[1676] Output: User feedback data

[1677] Step 15:

[1678] The server receives feedback from users and reflects it in the senior mentor's evaluation system, and also provides a feedback form to the senior mentor.

[1679] Input: User feedback data, Senior Mentor feedback data

[1680] Specific actions: Feedback data will be reflected in the evaluation system and the data will be used to improve matching accuracy and service quality next time.

[1681] Output: Updated rating system data

[1682] (Application example 2)

[1683] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1684] When providing meal suggestions or cooking assistance at home, suggestions or assistance that do not take into account the user's emotional state may not provide sufficient satisfaction. Furthermore, matching or responses that do not take the user's emotional state into account may lead to discrepancies between the provider and the user. Conventional methods have difficulty providing detailed advice based on emotions or efficiently matching providers.

[1685] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for the user to input questions, concerns, or emotional state related to the home, means for the server to receive the user's input information and pass it on to the emotion engine, and means for the emotion engine to analyze the user's emotional state and pass the results on to the generative AI. This makes it possible to match appropriate meal suggestions and providers such as chefs according to the user's emotional state.

[1686] A "user" is an individual who uses the system to ask questions or concerns about their home, as well as to seek meal suggestions.

[1687] An "emotion engine" is software or hardware for analyzing the user's emotional state from input information.

[1688] "Generative AI" is an AI system that analyzes a user's input information and emotional state and generates appropriate advice.

[1689] A "provider" is a person or organization that provides a service to a user, and includes chefs, housekeeping assistants, etc.

[1690] "Server" refers to a computer system that performs the central data processing and management of this system.

[1691] A "skill set" is a list of skills and techniques possessed by a provider, and is information for providing appropriate support to users.

[1692] "User Ratings" refers to other users' ratings and feedback on services provided in the past.

[1693] "Feedback" refers to evaluations and opinions given by users regarding the services provided.

[1694] "Emotional state" refers to the psychological state analyzed from the information entered by the user, examples of which include stress and relaxation.

[1695] 1. Overall system configuration

[1696] An embodiment of this invention is a system that provides advice and services that take into account a user's emotional state when they request meal suggestions or cooking assistance. This system is composed of a user terminal, a server, an emotion engine, a generative artificial intelligence, a provider terminal, etc.

[1697] 2. Hardware and Software Used

[1698] This system uses the following hardware and software:

[1699] Emotion engine: Uses various emotion analysis APIs, such as Microsoft Azure Emotion API and IBM Watson Tone Analyzer.

[1700] Generative AI: Use generative AI models such as OpenAI GPT-4.

[1701] Backend: Uses cloud computing services, such as AWS Lambda and its database service AWS RDS.

[1702] Frontend: Using React Native for smartphone applications.

[1703] Database: Use a relational database such as PostgreSQL.

[1704] 3. Data processing and calculation

[1705] User registration and initial settings

[1706] When a user accesses the system for the first time, he enters basic information (name, address, email address, etc.) in the user registration form. The server receives this information, validates it, and then stores it in the database.

[1707] Inputting questions and concerns and recognizing emotions

[1708] Users input questions and concerns about their home into the app and express their emotional state. This information is sent to the server and passed to the emotion engine. The emotion engine analyzes the user's emotional state from the input information and returns the results to the server.

[1709] Generating Advice

[1710] The server passes the emotional state data received from the emotion engine to the generative AI, which takes into account the user's questions, concerns, and emotional state to generate optimal advice. The advice is then sent back to the user from the server and displayed on the app.

[1711] Provider matching

[1712] The server selects the best provider for the user based on advice generated by the emotion engine and generative AI. The provider's skill set and past reviews are also taken into consideration. For example, if the user's emotional state is unstable, a chef with a high level of empathy will be prioritized.

[1713] Scheduling and feedback

[1714] The system checks the schedules of the user and provider and proposes the optimal date and time. If this is accepted, the date and time of the service is confirmed and the provider provides the service at the specified date and time. After that, the user's feedback is sent to the server, stored in a database, and reflected in the rating system.

[1715] 4. Specific Examples

[1716] When a user types "I'm very tired today," and the emotion engine analyzes "tired," the generative AI suggests a relaxing meal. The meal suggestion includes "grilled salmon and steamed vegetables," and the system matches the user with a highly rated chef near the user. The following prompt appears on the user's smartphone:

[1717] "The user is extremely tired. Based on this emotional state, suggest a relaxing meal."

[1718] This system will significantly improve satisfaction at home by suggesting meals based on the user's emotional state and matching them with chefs and other providers.

[1719] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1720] Step 1:

[1721] On the user's device, the user inputs questions, concerns, and emotional state about the home. Specifically, the user enters text into an input form within the app. This becomes input data and is sent to the server.

[1722] Step 2:

[1723] The server passes the received user input data to the emotion engine. The emotion engine analyzes the user's emotional state from the text and returns the result (e.g., stress, relaxation, etc.) to the server. The data processing performed in this step is text analysis, and generates output data called the emotional state.

[1724] Step 3:

[1725] The server passes the analyzed emotional state to a generative AI (such as GPT-4). The generative AI receives the user's questions, concerns, and emotional state as input data and generates optimal advice. This advice is returned to the server in text format. The data calculation in this step is advice generation using natural language processing.

[1726] Step 4:

[1727] The server returns the advice received from the generative AI to the user. This advice is displayed on the user's device. The specific processing performed here involves API communication and retrieval from a database.

[1728] Step 5:

[1729] The server selects an appropriate provider based on the generated advice, emotional state, and user input information. The provider's skill set is compared with the user rating database to perform matching. Information about the selected provider is presented to the user. The data calculation in this step is the execution of a matching algorithm.

[1730] Step 6:

[1731] The server adjusts the schedules of the user and provider and proposes the optimal date and time. The proposed date and time are sent to the user's device and the provider's device, and both parties confirm them. In this step, the date and time are adjusted using the calendar API.

[1732] Step 7:

[1733] The provider will visit the user's designated location at the date and time determined by the server, and provide meal suggestions and cooking assistance services. At this time, the provider's device will report the progress to the server. Specific operations include GPS tracking and check-in functions.

[1734] Step 8:

[1735] After the service is provided, the user enters feedback and sends it to the server. The server stores the feedback in a database and reflects it in the provider's evaluation system. In this step, the questionnaire form and database are updated.

[1736] These processing steps realize an automated emotion-based meal suggestion and cooking assistance system.

[1737] 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 control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1738] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1739] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1740] The emotion identification model 59 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 an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1741] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1742] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1743] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1744] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, motorcycles, and other devices, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1745] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs 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 a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1746] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1747] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1748] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1749] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1750] 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.

[1751] It is not necessary to store all 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 all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1752] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1753] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with 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). Also, the hardware resource that executes the specific processing may be a single processor.

[1754] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1755] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1756] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1757] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1758] The following is further disclosed regarding the above embodiment.

[1759] (Claim 1)

[1760] A means for users to input questions or concerns about their home;

[1761] A means for the server to receive user input information and pass it to the generative artificial intelligence;

[1762] A means for the generative artificial intelligence to analyze input information and generate advice;

[1763] means for the server to return the generated advice to the user;

[1764] A means for the server to select the most suitable senior mentor based on the senior mentor's skill set and user ratings based on the advice;

[1765] A means for the server to adjust the schedules of the user and the senior mentor and determine the date and time of support;

[1766] A means for a senior mentor to visit the user's home at a confirmed date and time to provide assistance;

[1767] A means for receiving feedback from users and incorporating it into the senior mentor evaluation system;

[1768] A system including:

[1769] (Claim 2)

[1770] 2. The system according to claim 1, wherein the server further comprises means for checking the schedules of the user and the senior mentor and proposing the most suitable date and time.

[1771] (Claim 3)

[1772] 2. The system according to claim 1, wherein the support provided by the senior mentor includes assistance with housework and childcare.

[1773] "Example 1"

[1774] (Claim 1)

[1775] A means for users to input questions or concerns about their home;

[1776] A means for the server to receive user input information and pass it to the generative artificial intelligence;

[1777] A means for the generative artificial intelligence to analyze input information and generate advice;

[1778] means for the server to return the generated advice to the user;

[1779] A means for the server to select the most suitable mentor based on the advice, the mentor's skills, and user ratings;

[1780] A means for the server to adjust the schedules of the user and the mentor and determine the date and time of support;

[1781] A means for the mentor to visit the user's home at a confirmed date and time to provide assistance;

[1782] A means for receiving feedback from users and incorporating it into the mentor evaluation system;

[1783] A system including:

[1784] (Claim 2)

[1785] 2. The system according to claim 1, wherein the server further comprises means for checking the schedules of the user and the mentor and proposing the most suitable date and time.

[1786] (Claim 3)

[1787] 2. The system according to claim 1, wherein the support provided by the mentor includes assistance with housework and childcare.

[1788] "Application Example 1"

[1789] (Claim 1)

[1790] A means for users to input questions or concerns about their home;

[1791] A means for the server to receive user input information and pass it to the generative artificial intelligence;

[1792] A means for the generative artificial intelligence to analyze input information and generate advice;

[1793] means for the server to return the generated advice to the user;

[1794] A means for the server to select the most suitable senior mentor based on the senior mentor's skill set and user ratings based on the advice;

[1795] A means for the server to adjust the schedules of the user and the senior mentor and determine the date and time of support;

[1796] A means for a senior mentor to visit the user's home at a confirmed date and time to provide assistance;

[1797] A means for users to input questions or concerns through a smart device, and receive advice through the cooperation of generative AI and senior mentors.

[1798] A means for receiving feedback from users and incorporating it into the senior mentor evaluation system;

[1799] A system including:

[1800] (Claim 2)

[1801] 2. The system according to claim 1, wherein the server further comprises means for checking the schedules of the user and the senior mentor and proposing the most suitable date and time.

[1802] (Claim 3)

[1803] 2. The system according to claim 1, wherein the support provided by the senior mentor includes housework assistance, childcare assistance, and interior design consultation.

[1804] "Example 2: Combining Emotion Engines"

[1805] (Claim 1)

[1806] A means for users to input questions or concerns about their home;

[1807] A means for the server to receive user input information and pass it to the generative artificial intelligence;

[1808] A means for the generative artificial intelligence to analyze input information and generate advice;

[1809] means for the server to return the generated advice to the user;

[1810] means including an emotion engine for analyzing an emotional state of a user;

[1811] A means for the server to consider the emotional state analyzed by the emotion engine and pass it to the generative artificial intelligence;

[1812] a means for the generative artificial intelligence to adjust advice taking into account the user's emotional state; and

[1813] A means for the server to select the most suitable senior mentor based on the advice, the senior mentor's skill set, and user evaluation;

[1814] A means for the server to adjust the schedules of the user and the senior mentor and determine the date and time of support;

[1815] A means for a senior mentor to visit the user's home at a confirmed date and time to provide assistance;

[1816] A means for receiving feedback from users and incorporating it into the senior mentor evaluation system;

[1817] A system including:

[1818] (Claim 2)

[1819] 2. The system according to claim 1, wherein the server includes means for checking the schedules of the user and the senior mentor and proposing the most suitable date and time.

[1820] (Claim 3)

[1821] 2. The system according to claim 1, wherein the support provided by the senior mentor includes assistance with housework and childcare.

[1822] "Application example 2 when combining emotion engines"

[1823] (Claim 1)

[1824] a means for the user to input questions, concerns, or emotional states about the home;

[1825] A means for the server to receive user input information and pass it to the emotion engine;

[1826] A means for the emotion engine to analyze the user's emotional state and pass the results to the generative AI;

[1827] A means for the generative artificial intelligence to analyze input information and emotional state and generate advice;

[1828] means for the server to return the generated advice to the user;

[1829] A means for the server to select the most suitable provider based on the advice and the associated skill set and user ratings;

[1830] A means for the server to coordinate the schedules of the user and the provider and determine the date and time of the service;

[1831] A means for a provider to visit the user's designated location at a fixed date and time and provide assistance;

[1832] A means for receiving feedback from users and incorporating it into the rating system;

[1833] A system including:

[1834] (Claim 2)

[1835] 2. The system according to claim 1, wherein the server further comprises means for checking the schedules of the user and the provider and proposing the optimal date and time.

[1836] (Claim 3)

[1837] 2. The system of claim 1, wherein the assistance provided by the provider includes meal suggestions and food preparation. [Explanation of symbols]

[1838] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. A means for users to input questions or concerns about their home; A means for the server to receive user input information and pass it to the generative artificial intelligence; A means for the generative artificial intelligence to analyze input information and generate advice; means for the server to return the generated advice to the user; A means for the server to select the most suitable senior mentor based on the senior mentor's skill set and user ratings based on the advice; A means for the server to adjust the schedules of the user and the senior mentor and determine the date and time of support; A means for a senior mentor to visit the user's home at a confirmed date and time to provide assistance; A means for receiving feedback from users and incorporating it into the senior mentor evaluation system; A system including:

2. 2. The system according to claim 1, wherein the server further comprises means for checking the schedules of the user and the senior mentor and proposing the most suitable date and time.

3. The system according to claim 1 , wherein the support provided by the senior mentor includes assistance with housework and childcare.

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