System

Abstract

An object of the system according to the embodiment is to efficiently support procedures and preparations related to the termination and activation of the deceased.SOLUTION: A system includes a termination / activation support interlocking part, a procedure listing part, and a chat guide part. A termination / activation support linking part lists necessary procedures or preparations on the basis of the termination / activation support information of the deceased. The procedure listing unit lists necessary procedure destinations or deadlines listed by the active / inactive support interlocking unit. The chat guidance unit guides the procedure or preparation listed by the procedure listing unit to the user in a chat form.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] With conventional technology, the procedures and preparations required for the deceased's end of life were complicated, placing a heavy burden on the family.

[0005] The system according to the embodiment aims to efficiently support the procedures and preparations related to the end of life of the deceased. [Means for solving the problem]

[0006] The system according to the embodiment includes an end-of-life planning support linking unit, a procedure listing unit, and a chat guidance unit. The end-of-life planning support linking unit lists the necessary procedures or preparations based on the end-of-life planning support information of the deceased. The procedure listing unit lists the necessary procedure destinations or deadlines listed by the end-of-life planning support linking unit. The chat guidance unit guides the user in chat format about the procedures or preparations listed by the procedure listing unit. [Effects of the Invention]

[0007] The system according to the embodiment can efficiently support procedures and preparations related to the end of life of the deceased. [Brief explanation of the drawings]

[0008] [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. DETAILED DESCRIPTION OF THE INVENTION

[0009] 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.

[0010] First, the terms used in the following description will be explained.

[0011] 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, the 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), an APU (Accelerated Processing Unit), or a TPU (Tensor Processing Unit).

[0012] 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.

[0013] 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.

[0014] 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), and Bluetooth (registered trademark).

[0015] 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."

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

[0017] 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.

[0018] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and 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).

[0019] 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.

[0020] The reception device 38 includes a touch panel 38A and a microphone 38B, and receives user input. The touch panel 38A detects contact with a pointer (for example, a pen or a finger) to receive user input by the touch of the pointer. 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 (see FIG. 2) acquires the data indicating the user input.

[0021] Output device 40 includes a display 40A and a speaker 40B, and presents data to a user by outputting the data in a form of expression that the user can perceive (e.g., audio and / or text). Display 40A displays visible information such as text and images in accordance with instructions from processor 46. Speaker 40B outputs audio in accordance with instructions from processor 46. 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.

[0022] 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.

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

[0024] 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.

[0025] 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. The identification processing unit 290 can estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0026] In the smart device 14, the specific processing is performed by the processor 46. The storage 50 stores a specific processing program 60. The specific processing program 60 is used together with the specific processing program 56 by the data processing system 10. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. Note that the smart device 14 may have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59.

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

[0028] (Example 1) The support app according to an embodiment of the present invention is an app that supports the deceased and their family. This app works in conjunction with the deceased's end-of-life support and provides necessary procedures, deadlines, and contact information in a "list + chat format." This allows the support app to smoothly carry out the necessary procedures for the deceased and their family.

[0029] The support app according to the embodiment includes an end-of-life planning support linkage unit, a procedure listing unit, and a chat guide unit. The end-of-life planning support linkage unit lists the necessary procedures and preparations based on the deceased's end-of-life planning support information. For example, the generation AI analyzes the contents of the will or end-of-life note created by the deceased and lists the necessary procedures. The generation AI also analyzes information entered by the user and suggests appropriate procedures and preparations. The input to the generation AI is a prompt containing instructions on what the user wants the generation AI to do, and the generation AI generates a list based on the prompt. The procedure listing unit lists the necessary procedures and deadlines listed by the end-of-life planning support linkage unit. For example, the generation AI compiles a list of the destination and deadline for submitting a death notification, the start date for inheritance procedures, etc. The generation AI lists the details of each procedure based on information from the user. This allows the user to understand at a glance what to request, by when, and to whom. The chat guide unit guides the user through the procedures and preparations listed by the procedure listing unit in a chat format. For example, the AI ​​generator may provide guidance such as, "The next step is to submit a death notification. This should be submitted to city hall, and the deadline is within seven days." The AI ​​generator also responds to questions from the user and provides appropriate answers. This allows the user to smoothly understand the flow of the procedure. As a result, the support app according to the embodiment allows the deceased and their family to smoothly complete the necessary procedures.

[0030] The end-of-life support linkage unit can analyze the social media posts or emails of the deceased while they were alive and propose individual end-of-life support. In the end-of-life support linkage unit, for example, the generation AI analyzes the social media posts of the deceased to identify their hobbies and interests. For example, it proposes specific end-of-life events and activities based on the travel destinations or favorite foods that the deceased frequently posted about. The generation AI can also analyze the emails of the deceased and propose individual end-of-life support. For example, it suggests specific procedures and preparations based on the content of email exchanges between the deceased. This makes it possible to propose individual end-of-life support for the deceased.

[0031] The end-of-life planning support linkage unit can suggest specific end-of-life planning events or activities based on the hobbies or interests of the deceased. In the end-of-life planning support linkage unit, for example, the generation AI suggests specific end-of-life planning events based on the hobbies of the deceased. For example, if the deceased's hobby was gardening, it suggests garden maintenance or donating plants. The generation AI also suggests specific end-of-life planning activities based on the interests of the deceased. For example, if the deceased was interested in environmental issues, it suggests participating in environmental protection activities. In this way, it is possible to suggest end-of-life planning events and activities based on the hobbies and interests of the deceased.

[0032] The end-of-life support linkage unit can collect information about the care of the deceased's pets or plants, and list the procedures necessary for caring for the pets or plants. In the end-of-life support linkage unit, for example, the generation AI collects information about the care of the deceased's pets, and lists the procedures necessary for caring for the pets. For example, it suggests ways to manage the pet's health and find a new owner. The generation AI also collects information about the care of the deceased's plants, and lists the procedures necessary for caring for the plants. For example, it suggests when to water them and how to repot them. This makes it possible to list the procedures necessary for caring for the deceased's pets or plants.

[0033] The end-of-life support linkage unit can collect contact information for the deceased's friends or acquaintances and notify them of the details of end-of-life support. In the end-of-life support linkage unit, for example, the generation AI collects contact information for the deceased's friends and acquaintances and notifies them of the details of end-of-life support. For example, it notifies the deceased's friends of the date, time, and location of the funeral. The generation AI also notifies the deceased's acquaintances of the necessary procedures and preparations. For example, it notifies the deceased's acquaintances of the start date of inheritance procedures and the necessary documents. In this way, the details of end-of-life support can be notified to the deceased's friends and acquaintances.

[0034] The procedure listing unit can automatically provide details of the legal background or required documents for each procedure. For example, the generation AI analyzes the legal background of each procedure and lists the required documents and details of the procedure. For example, it provides the documents and procedure flow required for submitting a death notification. The generation AI also lists the documents and legal background required for inheritance procedures. For example, it provides the method for calculating inheritance tax and the necessary documents. This makes it possible to automatically provide details of the legal background and required documents for each procedure.

[0035] The procedure listing unit can track the progress of procedures in real time and notify the user. In the procedure listing unit, for example, the generation AI tracks the progress of procedures in real time and notifies the user. For example, the status of death notification submission and the progress of inheritance procedures can be checked in real time. The generation AI also notifies the progress of procedures. For example, it notifies the completion status of procedures and the acceptance status of submitted documents. This allows the progress of procedures to be tracked in real time and notified to the user.

[0036] The procedure listing unit can provide a function that allows the list of procedure destinations and deadlines to be shared with other family members and managed jointly. The procedure listing unit provides a function that allows, for example, the generation AI to share the list of procedure destinations and deadlines with other family members and manage them jointly. For example, all family members can check the progress of the procedure. The generation AI also shares the progress of the procedure. For example, it notifies all family members of the completion status of the procedure and the acceptance status of submitted documents. This allows the list of procedure destinations and deadlines to be shared with other family members and managed jointly.

[0037] The procedure listing unit can link the list of procedure destinations and deadlines with a calendar app and provide a function to set reminders. For example, the generation AI links the list of procedure destinations and deadlines with a calendar app and provides a function to set reminders. For example, it sends a reminder when a procedure deadline approaches. The generation AI also links with a calendar app to manage the progress of procedures. For example, it displays the completion status of procedures and the acceptance status of submitted documents on the calendar. This allows the list of procedure destinations and deadlines to be linked with a calendar app and reminders to be set.

[0038] The chat guide unit can analyze the user's past chat history and provide personalized advice. For example, the generation AI analyzes the user's past chat history and provides personalized advice. For example, it suggests appropriate procedures based on the content of past questions. The generation AI also suggests specific procedures and preparations based on the user's past chat history. For example, it lists related procedures based on the content of questions the user has asked in the past. This makes it possible to analyze the user's past chat history and provide personalized advice.

[0039] The chat guide unit can automatically cite relevant legal documents or guidelines in response to a user's question. For example, the generation AI in the chat guide unit automatically cites relevant legal documents or guidelines in response to a user's question. For example, it provides legal documents related to inheritance procedures. The generation AI also cites specific legal documents or guidelines based on the user's question. For example, it provides relevant legal provisions or guidelines based on the content of the user's question. This makes it possible to automatically cite relevant legal documents or guidelines in response to a user's question.

[0040] The chat guidance unit can link chat-style guidance with a voice assistant, making it possible to provide voice guidance as well. For example, the generation AI links chat-style guidance with a voice assistant to provide voice guidance. For example, it provides voice guidance on how to proceed with a procedure. The generation AI also links with the voice assistant to provide voice guidance on specific procedures and preparations. For example, it provides voice responses based on questions asked by the user. This allows chat-style guidance to be linked with a voice assistant, making it possible to provide voice guidance as well.

[0041] The chat guidance unit can link chat-style guidance with a video call function, enabling direct consultation with an expert. For example, the generation AI links chat-style guidance with a video call function to provide direct consultation with an expert. For example, a consultation with an expert regarding inheritance procedures is conducted via video call. The generation AI also links with the video call function to consult with an expert regarding specific procedures and preparations. For example, the expert answers based on the content of questions asked by the user via video call. In this way, the chat-style guidance can be linked with the video call function, enabling direct consultation with an expert.

[0042] The document request unit can automatically calculate the fees or processing time required to request each document and present them to the user. In the document request unit, for example, the generation AI automatically calculates the fees required to request each document and presents them to the user. For example, it informs the user of the fees required to obtain a copy of a family register. The generation AI also automatically calculates the processing time required to request each document and presents it to the user. For example, it informs the user of the processing time required to obtain a copy of a resident registration card. In this way, the fees and processing time required to request each document can be automatically calculated and presented to the user.

[0043] The document ordering unit can track the document ordering status in real time and notify the user. In the document ordering unit, for example, the generation AI tracks the document ordering status in real time and notifies the user. For example, the status of obtaining a family register copy can be checked in real time. The generation AI also notifies the document ordering status. For example, it notifies the document shipping status and acceptance status. This allows the document ordering status to be tracked in real time and notified to the user.

[0044] The material ordering unit can provide a function that allows the request status of materials or documents to be shared with other family members and managed jointly. The material ordering unit provides a function that allows, for example, the generation AI to share the request status of materials or documents with other family members and manage them jointly. For example, all family members can check the status of document acquisition. The generation AI also shares the request status. For example, it notifies all family members of the shipping status and receipt status of documents. This allows the request status of materials or documents to be shared with other family members and managed jointly.

[0045] The document request unit can improve convenience by allowing documents or materials to be requested by mail or through online procedures. For example, the generation AI can make documents or materials requested by mail or through online procedures, improving convenience. For example, the generation AI can provide instructions on how to obtain a copy of a family register online. The generation AI can also request specific documents in response to procedures by mail. For example, the generation AI can provide instructions on how to obtain a copy of a resident registration card by mail. This allows documents or materials to be requested by mail or through online procedures, improving convenience.

[0046] The Chief Mourner Support Department can analyze the chief mourner's past experience or knowledge and provide personalized advice. For example, the generation AI analyzes the chief mourner's past experience and knowledge and provides personalized advice. For example, it suggests appropriate procedures based on past funeral experience. The generation AI also suggests specific procedures and preparations based on the chief mourner's knowledge. For example, it lists appropriate procedures based on legal knowledge that the chief mourner has learned in the past. This makes it possible to analyze the chief mourner's past experience and knowledge and provide personalized advice.

[0047] The chief mourner support unit can automatically manage the chief mourner's schedule and remind him of important tasks. For example, the generation AI automatically manages the chief mourner's schedule and reminds him of important tasks. For example, it can remind him to prepare for the funeral or contact attendees. The generation AI also reminds him of specific tasks based on the chief mourner's schedule. For example, it can prioritize reminders of tasks that the chief mourner considers emotionally important. This makes it possible to automatically manage the chief mourner's schedule and remind him of important tasks.

[0048] The chief mourner support unit can provide a function that allows the chief mourner's tasks or the content of the greeting to be shared with other family members and managed jointly. For example, the chief mourner support unit provides a function that allows the generation AI to share the chief mourner's tasks or the content of the greeting with other family members and manage them jointly. For example, all family members can check the chief mourner's schedule. The generation AI also shares the chief mourner's tasks and the content of the greeting. For example, it notifies all family members of the script for the chief mourner's greeting and the preparations for the funeral. This allows the chief mourner's tasks and the content of the greeting to be shared with other family members and managed jointly.

[0049] The chief mourner support unit can link support for the chief mourner's tasks and greetings with the video call function, and also enable direct consultation with experts. For example, the generation AI can link support for the chief mourner's tasks and greetings with the video call function, and provide direct consultation with experts. For example, consulting with an expert about funeral preparations via video call. The generation AI can also link with the video call function to consult with an expert about specific procedures and preparations. For example, the expert will answer based on the questions the user asks via video call. This allows support for the chief mourner's tasks and greetings to be linked with the video call function, and also enables direct consultation with experts.

[0050] The inheritance support unit can analyze the details of the inherited assets and propose the optimal distribution method. In the inheritance support unit, for example, the generation AI analyzes the details of the inherited assets and proposes the optimal distribution method. For example, it proposes a distribution method based on the type and value of the inheritance. The generation AI also proposes a specific distribution method based on the details of the inherited assets. For example, it lists the optimal distribution methods based on the number and relationships of heirs. This makes it possible to analyze the details of the inherited assets and propose the optimal distribution method.

[0051] The inheritance support unit can automatically calculate inheritance tax and present it to the user. In the inheritance support unit, for example, the generation AI automatically calculates inheritance tax and presents it to the user. For example, it calculates inheritance tax based on the total amount of inherited assets. The generation AI also presents a specific tax amount based on the inheritance tax calculation method. For example, it lists inheritance tax details based on tax rates and deduction amounts. This allows inheritance tax to be calculated automatically and presented to the user.

[0052] The inheritance support unit can provide a function that allows support for inheritance distribution to be shared with other family members and managed jointly. The inheritance support unit provides a function that allows, for example, the generation AI to share support for inheritance distribution with other family members and manage it jointly. For example, all family members can check the progress of inheritance distribution. The generation AI also shares support for inheritance distribution. For example, it notifies all family members of the distribution method and criteria. This allows support for inheritance distribution to be shared with other family members and managed jointly.

[0053] The inheritance support unit can add a function to link with legal experts to support the distribution of inheritance and provide professional advice. For example, the generation AI can add a function to link with legal experts to support the distribution of inheritance and provide professional advice. For example, it can provide advice from legal experts regarding inheritance procedures. The generation AI can also add a function to link with legal experts to support specific procedures and preparations. For example, the user can have an online consultation with a legal expert. This allows the generation AI to add a function to link with legal experts to support the distribution of inheritance and provide professional advice.

[0054] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0055] The support app can suggest specific end-of-life events and activities based on the hobbies and interests of the deceased. For example, if the deceased loved music, it can suggest music-related events and activities. If the deceased was passionate about volunteer work, it can make suggestions for continuing those activities. Furthermore, if the deceased enjoyed a particular sport, it can suggest events and activities related to that sport. This makes it possible to provide end-of-life support based on the hobbies and interests of the deceased.

[0056] The support app can collect contact information for the deceased's friends and acquaintances and notify them of end-of-life support. For example, it can notify the deceased's friends of the date, time, and location of the funeral. It can also notify the deceased's acquaintances of the necessary procedures and preparations. It can also provide a function for the deceased's friends and acquaintances to share memories and stories about the deceased. This allows the deceased's friends and acquaintances to be effectively notified of the end-of-life support.

[0057] The support app can link the procedure listing section with a calendar app to provide a function for setting reminders. For example, it can send a reminder when a procedure deadline is approaching. It can also link with a calendar app to manage the progress of procedures. It can also display the completion status of procedures and the acceptance status of submitted documents on the calendar. This makes it possible to effectively manage the progress of procedures and provide reminders to users.

[0058] The support app can link the chat guidance section with a voice assistant to enable voice guidance. For example, it can provide voice guidance on how to proceed with a procedure. It can also link with a voice assistant to provide voice guidance on specific procedures and preparations. It can also provide voice answers based on questions the user asks. This allows chat-style guidance to be linked with a voice assistant, enabling voice guidance.

[0059] The support app can link the chat guidance section with a video call function, enabling direct consultation with an expert. For example, it is possible to consult with an expert regarding inheritance procedures via video call. It can also link with the video call function to consult with an expert about specific procedures or preparations. Furthermore, the expert can respond to questions asked by the user via video call. In this way, it is possible to link the chat guidance section with the video call function and enable direct consultation with an expert.

[0060] The processing flow of the first embodiment will be briefly explained below.

[0061] Step 1: The end-of-life support linkage section creates a list of the necessary procedures and preparations based on the end-of-life support information for the deceased. For example, the generation AI analyzes the contents of the will and end-of-life note created by the deceased before their death and creates a list of the necessary procedures. The generation AI also analyzes information entered by the user and suggests appropriate procedures and preparations. The input to the generation AI is a prompt containing instructions on what the user wants the generation AI to do, and the generation AI generates a list based on that prompt. Step 2: The procedure listing section lists the necessary procedures and deadlines listed by the end-of-life support linkage section. For example, the generation AI compiles a list of where and by when to submit a death notification, and when to start inheritance procedures. Based on information from the user, the generation AI lists the details of each procedure. This allows the user to see at a glance what they need to request, by when, and to whom. Step 3: The chat guidance section uses chat to guide the user through the procedures and preparations listed by the procedure listing section. For example, the generation AI might provide guidance such as, "The next procedure you need to complete is to submit a death notification. This should be submitted to city hall, and the deadline for submission is within seven days." The generation AI also responds to questions from the user and provides appropriate answers. This allows the user to smoothly understand the flow of procedures.

[0062] (Example 2) The support app according to an embodiment of the present invention is an app that supports the deceased and their family. This app works in conjunction with the deceased's end-of-life support and provides necessary procedures, deadlines, and contact information in a "list + chat format." This allows the support app to smoothly carry out the necessary procedures for the deceased and their family.

[0063] The support app according to the embodiment includes an end-of-life planning support linkage unit, a procedure listing unit, and a chat guide unit. The end-of-life planning support linkage unit lists the necessary procedures and preparations based on the deceased's end-of-life planning support information. For example, the generation AI analyzes the contents of the will or end-of-life note created by the deceased and lists the necessary procedures. The generation AI also analyzes information entered by the user and suggests appropriate procedures and preparations. The input to the generation AI is a prompt containing instructions on what the user wants the generation AI to do, and the generation AI generates a list based on the prompt. The procedure listing unit lists the necessary procedures and deadlines listed by the end-of-life planning support linkage unit. For example, the generation AI compiles a list of the destination and deadline for submitting a death notification, the start date for inheritance procedures, etc. The generation AI lists the details of each procedure based on information from the user. This allows the user to understand at a glance what to request, by when, and to whom. The chat guide unit guides the user through the procedures and preparations listed by the procedure listing unit in a chat format. For example, the AI ​​generator may provide guidance such as, "The next step is to submit a death notification. This should be submitted to city hall, and the deadline is within seven days." The AI ​​generator also responds to questions from the user and provides appropriate answers. This allows the user to smoothly understand the flow of the procedure. As a result, the support app according to the embodiment allows the deceased and their family to smoothly complete the necessary procedures.

[0064] The end-of-life support linkage unit can analyze the social media posts or emails of the deceased while they were alive and propose individual end-of-life support. In the end-of-life support linkage unit, for example, the generation AI analyzes the social media posts of the deceased to identify their hobbies and interests. For example, it proposes specific end-of-life events and activities based on the travel destinations or favorite foods that the deceased frequently posted about. The generation AI can also analyze the emails of the deceased and propose individual end-of-life support. For example, it suggests specific procedures and preparations based on the content of email exchanges between the deceased. This makes it possible to propose individual end-of-life support for the deceased.

[0065] The end-of-life planning support linkage unit can suggest specific end-of-life planning events or activities based on the hobbies or interests of the deceased. In the end-of-life planning support linkage unit, for example, the generation AI suggests specific end-of-life planning events based on the hobbies of the deceased. For example, if the deceased's hobby was gardening, it suggests garden maintenance or donating plants. The generation AI also suggests specific end-of-life planning activities based on the interests of the deceased. For example, if the deceased was interested in environmental issues, it suggests participating in environmental protection activities. In this way, it is possible to suggest end-of-life planning events and activities based on the hobbies and interests of the deceased.

[0066] The end-of-life planning support linkage unit can use the emotion estimation function to estimate the emotions of the deceased and provide end-of-life planning support based on those emotions. In the end-of-life planning support linkage unit, for example, the generation AI estimates the emotions of the deceased and provides end-of-life planning support based on those emotions. For example, it suggests support to reduce the anxiety and stress that the deceased felt during their lifetime. The generation AI also suggests specific procedures and preparations based on the emotions of the deceased. For example, it prioritizes a list of matters that the deceased considered emotionally important. This makes it possible to provide end-of-life planning support based on the emotions of the deceased.

[0067] The end-of-life support linkage unit can collect information about the care of the deceased's pets or plants, and list the procedures necessary for caring for the pets or plants. In the end-of-life support linkage unit, for example, the generation AI collects information about the care of the deceased's pets, and lists the procedures necessary for caring for the pets. For example, it suggests ways to manage the pet's health and find a new owner. The generation AI also collects information about the care of the deceased's plants, and lists the procedures necessary for caring for the plants. For example, it suggests when to water them and how to repot them. This makes it possible to list the procedures necessary for caring for the deceased's pets or plants.

[0068] The end-of-life support linkage unit can collect contact information for the deceased's friends or acquaintances and notify them of the details of end-of-life support. In the end-of-life support linkage unit, for example, the generation AI collects contact information for the deceased's friends and acquaintances and notifies them of the details of end-of-life support. For example, it notifies the deceased's friends of the date, time, and location of the funeral. The generation AI also notifies the deceased's acquaintances of the necessary procedures and preparations. For example, it notifies the deceased's acquaintances of the start date of inheritance procedures and the necessary documents. In this way, the details of end-of-life support can be notified to the deceased's friends and acquaintances.

[0069] The end-of-life planning support linkage unit can use the emotion estimation function to estimate the emotions of the deceased's family and provide end-of-life planning support that takes the family's emotions into consideration. In the end-of-life planning support linkage unit, for example, the generation AI estimates the emotions of the deceased's family and provides end-of-life planning support that takes the family's emotions into consideration. For example, it suggests support to alleviate the sadness and anxiety felt by the family. The generation AI also suggests specific procedures and preparations based on the family's emotions. For example, it prioritizes a list of matters that the family considers emotionally important. This makes it possible to provide end-of-life planning support that takes the family's emotions into consideration.

[0070] The procedure listing unit can automatically provide details of the legal background or required documents for each procedure. For example, the generation AI analyzes the legal background of each procedure and lists the required documents and details of the procedure. For example, it provides the documents and procedure flow required for submitting a death notification. The generation AI also lists the documents and legal background required for inheritance procedures. For example, it provides the method for calculating inheritance tax and the necessary documents. This makes it possible to automatically provide details of the legal background and required documents for each procedure.

[0071] The procedure listing unit can track the progress of procedures in real time and notify the user. In the procedure listing unit, for example, the generation AI tracks the progress of procedures in real time and notifies the user. For example, the status of death notification submission and the progress of inheritance procedures can be checked in real time. The generation AI also notifies the progress of procedures. For example, it notifies the completion status of procedures and the acceptance status of submitted documents. This allows the progress of procedures to be tracked in real time and notified to the user.

[0072] The procedure listing unit can use the emotion estimation function to estimate the user's stress level and provide advice for stress reduction. In the procedure listing unit, for example, the generation AI estimates the user's stress level and provides advice for stress reduction. For example, it suggests relaxation methods based on the progress of procedures. The generation AI also suggests specific procedures and preparations based on the user's stress level. For example, it prioritizes a list of procedures that the user finds stressful. This makes it possible to estimate the user's stress level and provide advice for stress reduction.

[0073] The procedure listing unit can provide a function that allows the list of procedure destinations and deadlines to be shared with other family members and managed jointly. The procedure listing unit provides a function that allows, for example, the generation AI to share the list of procedure destinations and deadlines with other family members and manage them jointly. For example, all family members can check the progress of the procedure. The generation AI also shares the progress of the procedure. For example, it notifies all family members of the completion status of the procedure and the acceptance status of submitted documents. This allows the list of procedure destinations and deadlines to be shared with other family members and managed jointly.

[0074] The procedure listing unit can link the list of procedure destinations and deadlines with a calendar app and provide a function to set reminders. For example, the generation AI links the list of procedure destinations and deadlines with a calendar app and provides a function to set reminders. For example, it sends a reminder when a procedure deadline approaches. The generation AI also links with a calendar app to manage the progress of procedures. For example, it displays the completion status of procedures and the acceptance status of submitted documents on the calendar. This allows the list of procedure destinations and deadlines to be linked with a calendar app and reminders to be set.

[0075] The procedure listing unit can use the emotion estimation function to adjust the frequency and content of reminders according to the user's emotions. For example, the generation AI in the procedure listing unit estimates the user's emotions and adjusts the frequency and content of reminders according to the emotions. For example, it reduces the frequency of reminders when stress is high. The generation AI also adjusts the content of reminders based on the user's emotions. For example, it prioritizes reminders for procedures that the user considers emotionally important. This makes it possible to adjust the frequency and content of reminders according to the user's emotions.

[0076] The chat guide unit can analyze the user's past chat history and provide personalized advice. For example, the generation AI analyzes the user's past chat history and provides personalized advice. For example, it suggests appropriate procedures based on the content of past questions. The generation AI also suggests specific procedures and preparations based on the user's past chat history. For example, it lists related procedures based on the content of questions the user has asked in the past. This makes it possible to analyze the user's past chat history and provide personalized advice.

[0077] The chat guide unit can automatically cite relevant legal documents or guidelines in response to a user's question. For example, the generation AI in the chat guide unit automatically cites relevant legal documents or guidelines in response to a user's question. For example, it provides legal documents related to inheritance procedures. The generation AI also cites specific legal documents or guidelines based on the user's question. For example, it provides relevant legal provisions or guidelines based on the content of the user's question. This makes it possible to automatically cite relevant legal documents or guidelines in response to a user's question.

[0078] The chat guide unit can use the emotion estimation function to provide kind language and encouraging messages that correspond to the user's emotions. For example, the generation AI in the chat guide unit estimates the user's emotions and provides kind language and encouraging messages that correspond to the emotions. For example, if the user is sad, the generation AI sends words of comfort. The generation AI also provides specific messages based on the user's emotions. For example, if the user is emotionally depressed, the generation AI sends an encouraging message. This makes it possible to provide kind language and encouraging messages that correspond to the user's emotions.

[0079] The chat guidance unit can link chat-style guidance with a voice assistant, making it possible to provide voice guidance as well. For example, the generation AI links chat-style guidance with a voice assistant to provide voice guidance. For example, it provides voice guidance on how to proceed with a procedure. The generation AI also links with the voice assistant to provide voice guidance on specific procedures and preparations. For example, it provides voice responses based on questions asked by the user. This allows chat-style guidance to be linked with a voice assistant, making it possible to provide voice guidance as well.

[0080] The chat guidance unit can link chat-style guidance with a video call function, enabling direct consultation with an expert. For example, the generation AI links chat-style guidance with a video call function to provide direct consultation with an expert. For example, a consultation with an expert regarding inheritance procedures is conducted via video call. The generation AI also links with the video call function to consult with an expert regarding specific procedures and preparations. For example, the expert answers based on the content of questions asked by the user via video call. In this way, the chat-style guidance can be linked with the video call function, enabling direct consultation with an expert.

[0081] The chat guide unit can use the emotion estimation function to adjust the chatbot's response speed and content according to the user's emotions. For example, the generation AI in the chat guide unit estimates the user's emotions and adjusts the chatbot's response speed and content according to the emotions. For example, it speeds up the response if the user is in a hurry. The generation AI also adjusts the chatbot's response content based on the user's emotions. For example, it prioritizes responses to procedures that the user considers emotionally important. This makes it possible to adjust the chatbot's response speed and content according to the user's emotions.

[0082] The document request unit can automatically calculate the fees or processing time required to request each document and present them to the user. In the document request unit, for example, the generation AI automatically calculates the fees required to request each document and presents them to the user. For example, it informs the user of the fees required to obtain a copy of a family register. The generation AI also automatically calculates the processing time required to request each document and presents it to the user. For example, it informs the user of the processing time required to obtain a copy of a resident registration card. In this way, the fees and processing time required to request each document can be automatically calculated and presented to the user.

[0083] The document ordering unit can track the document ordering status in real time and notify the user. In the document ordering unit, for example, the generation AI tracks the document ordering status in real time and notifies the user. For example, the status of obtaining a family register copy can be checked in real time. The generation AI also notifies the document ordering status. For example, it notifies the document shipping status and acceptance status. This allows the document ordering status to be tracked in real time and notified to the user.

[0084] The information requesting unit can use the emotion estimation function to provide advice to reduce the user's anxiety. For example, the generation AI estimates the user's anxiety and provides advice to reduce the anxiety. For example, the generation AI suggests relaxation methods depending on the progress of a procedure. The generation AI also suggests specific procedures or preparations based on the user's anxiety. For example, it prioritizes a list of procedures that the user is feeling anxious about. This makes it possible to provide advice to reduce the user's anxiety.

[0085] The material ordering unit can provide a function that allows the request status of materials or documents to be shared with other family members and managed jointly. The material ordering unit provides a function that allows, for example, the generation AI to share the request status of materials or documents with other family members and manage them jointly. For example, all family members can check the status of document acquisition. The generation AI also shares the request status. For example, it notifies all family members of the shipping status and receipt status of documents. This allows the request status of materials or documents to be shared with other family members and managed jointly.

[0086] The document request unit can improve convenience by allowing documents or materials to be requested by mail or through online procedures. For example, the generation AI can make documents or materials requested by mail or through online procedures, improving convenience. For example, the generation AI can provide instructions on how to obtain a copy of a family register online. The generation AI can also request specific documents in response to procedures by mail. For example, the generation AI can provide instructions on how to obtain a copy of a resident registration card by mail. This allows documents or materials to be requested by mail or through online procedures, improving convenience.

[0087] The material ordering unit can use the emotion estimation function to provide a progress report on the ordering procedure that corresponds to the user's emotions. For example, the generation AI infers the user's emotions and provides a progress report on the ordering procedure that corresponds to the emotions. For example, if the user is feeling anxious, a detailed progress report is sent. The generation AI also provides progress reports on specific procedures or preparations based on the user's emotions. For example, it prioritizes progress reports on procedures that the user considers emotionally important. This makes it possible to provide a progress report on the ordering procedure that corresponds to the user's emotions.

[0088] The Chief Mourner Support Department can analyze the chief mourner's past experience or knowledge and provide personalized advice. For example, the generation AI analyzes the chief mourner's past experience and knowledge and provides personalized advice. For example, it suggests appropriate procedures based on past funeral experience. The generation AI also suggests specific procedures and preparations based on the chief mourner's knowledge. For example, it lists appropriate procedures based on legal knowledge that the chief mourner has learned in the past. This makes it possible to analyze the chief mourner's past experience and knowledge and provide personalized advice.

[0089] The chief mourner support unit can automatically manage the chief mourner's schedule and remind him of important tasks. For example, the generation AI automatically manages the chief mourner's schedule and reminds him of important tasks. For example, it can remind him to prepare for the funeral or contact attendees. The generation AI also reminds him of specific tasks based on the chief mourner's schedule. For example, it can prioritize reminders of tasks that the chief mourner considers emotionally important. This makes it possible to automatically manage the chief mourner's schedule and remind him of important tasks.

[0090] The chief mourner support unit can use the emotion estimation function to provide an encouraging or comforting message according to the emotion of the chief mourner. For example, the generation AI in the chief mourner support unit estimates the emotion of the chief mourner and provides an encouraging or comforting message according to the emotion. For example, if the chief mourner is sad, words of comfort are sent. The generation AI also provides a specific message based on the emotion of the chief mourner. For example, if the chief mourner is emotionally depressed, an encouraging message is sent. This makes it possible to provide an encouraging or comforting message according to the emotion of the chief mourner.

[0091] The chief mourner support unit can provide a function that allows the chief mourner's tasks or the content of the greeting to be shared with other family members and managed jointly. For example, the chief mourner support unit provides a function that allows the generation AI to share the chief mourner's tasks or the content of the greeting with other family members and manage them jointly. For example, all family members can check the chief mourner's schedule. The generation AI also shares the chief mourner's tasks and the content of the greeting. For example, it notifies all family members of the script for the chief mourner's greeting and the preparations for the funeral. This allows the chief mourner's tasks and the content of the greeting to be shared with other family members and managed jointly.

[0092] The chief mourner support unit can link support for the chief mourner's tasks and greetings with the video call function, and also enable direct consultation with experts. For example, the generation AI can link support for the chief mourner's tasks and greetings with the video call function, and provide direct consultation with experts. For example, consulting with an expert about funeral preparations via video call. The generation AI can also link with the video call function to consult with an expert about specific procedures and preparations. For example, the expert will answer based on the questions the user asks via video call. This allows support for the chief mourner's tasks and greetings to be linked with the video call function, and also enables direct consultation with experts.

[0093] The chief mourner support unit can use the emotion estimation function to adjust the content of the greeting or message according to the emotions of the chief mourner. For example, the generation AI in the chief mourner support unit estimates the emotions of the chief mourner and adjusts the content of the greeting or message according to the emotions. For example, if the chief mourner is sad, it includes words of comfort. The generation AI also adjusts specific greetings or messages based on the emotions of the chief mourner. For example, it prioritizes including content that the chief mourner considers emotionally important. This makes it possible to adjust the content of the greeting or message according to the emotions of the chief mourner.

[0094] The inheritance support unit can analyze the details of the inherited assets and propose the optimal distribution method. In the inheritance support unit, for example, the generation AI analyzes the details of the inherited assets and proposes the optimal distribution method. For example, it proposes a distribution method based on the type and value of the inheritance. The generation AI also proposes a specific distribution method based on the details of the inherited assets. For example, it lists the optimal distribution methods based on the number and relationships of heirs. This makes it possible to analyze the details of the inherited assets and propose the optimal distribution method.

[0095] The inheritance support unit can automatically calculate inheritance tax and present it to the user. In the inheritance support unit, for example, the generation AI automatically calculates inheritance tax and presents it to the user. For example, it calculates inheritance tax based on the total amount of inherited assets. The generation AI also presents a specific tax amount based on the inheritance tax calculation method. For example, it lists inheritance tax details based on tax rates and deduction amounts. This allows inheritance tax to be calculated automatically and presented to the user.

[0096] The inheritance support unit can use the emotion estimation function to provide advice to reduce emotional conflicts between family members regarding inheritance. For example, the inheritance support unit uses a generation AI to estimate emotions between family members and provide advice to reduce emotional conflicts. For example, it suggests a method to alleviate emotional conflicts regarding inheritance distribution. The generation AI also provides specific advice based on the emotions of the family members. For example, it suggests a distribution method that is emotionally acceptable to the family members. This makes it possible to provide advice to reduce emotional conflicts between family members regarding inheritance.

[0097] The inheritance support unit can provide a function that allows support for inheritance distribution to be shared with other family members and managed jointly. The inheritance support unit provides a function that allows, for example, the generation AI to share support for inheritance distribution with other family members and manage it jointly. For example, all family members can check the progress of inheritance distribution. The generation AI also shares support for inheritance distribution. For example, it notifies all family members of the distribution method and criteria. This allows support for inheritance distribution to be shared with other family members and managed jointly.

[0098] The inheritance support unit can add a function to link with legal experts to support the distribution of inheritance and provide professional advice. For example, the generation AI can add a function to link with legal experts to support the distribution of inheritance and provide professional advice. For example, it can provide advice from legal experts regarding inheritance procedures. The generation AI can also add a function to link with legal experts to support specific procedures and preparations. For example, the user can have an online consultation with a legal expert. This allows the generation AI to add a function to link with legal experts to support the distribution of inheritance and provide professional advice.

[0099] The inheritance support unit can use the emotion estimation function to propose a distribution method that takes into consideration the family's emotions regarding inheritance. For example, the inheritance support unit uses a generation AI to estimate the family's emotions and propose a distribution method that takes those emotions into consideration. For example, it proposes a distribution method that is emotionally acceptable to the family. The generation AI also proposes a specific distribution method based on the family's emotions. For example, it prioritizes a list of items that the family considers emotionally important. This makes it possible to propose a distribution method that takes into consideration the family's emotions regarding inheritance.

[0100] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0101] The support app can suggest specific end-of-life events and activities based on the hobbies and interests of the deceased. For example, if the deceased loved music, it can suggest music-related events and activities. If the deceased was passionate about volunteer work, it can make suggestions for continuing those activities. Furthermore, if the deceased enjoyed a particular sport, it can suggest events and activities related to that sport. This makes it possible to provide end-of-life support based on the hobbies and interests of the deceased.

[0102] The support app can estimate the emotions of the deceased's family and provide support based on their emotions. For example, if a family member is feeling sad, it can provide a comforting message or words of encouragement. If a family member is feeling anxious, it can provide specific advice to alleviate that anxiety. It can also prioritize the matters that the family considers emotionally important and support them as they go through the procedures. This makes it possible to provide end-of-life support that takes into consideration the family's emotions.

[0103] The support app can collect contact information for the deceased's friends and acquaintances and notify them of end-of-life support. For example, it can notify the deceased's friends of the date, time, and location of the funeral. It can also notify the deceased's acquaintances of the necessary procedures and preparations. It can also provide a function for the deceased's friends and acquaintances to share memories and stories about the deceased. This allows the deceased's friends and acquaintances to be effectively notified of the end-of-life support.

[0104] The support app can use the emotion estimation function to estimate the user's stress level and provide advice to reduce stress. For example, it can suggest relaxation methods based on the progress of a procedure. It can also suggest specific procedures or preparations based on the user's stress level. It can also prioritize procedures that the user finds stressful and support the progress of the procedure. This can reduce the user's stress level and make the procedure progress more smoothly.

[0105] The support app can link the procedure listing section with a calendar app to provide a function for setting reminders. For example, it can send a reminder when a procedure deadline is approaching. It can also link with a calendar app to manage the progress of procedures. It can also display the completion status of procedures and the acceptance status of submitted documents on the calendar. This makes it possible to effectively manage the progress of procedures and provide reminders to users.

[0106] The support app can use the emotion estimation function to adjust the frequency and content of reminders according to the user's emotions. For example, it can reduce the frequency of reminders when the user is under high stress. It can also adjust the content of reminders based on the user's emotions. It can also prioritize reminders for procedures that the user considers emotionally important. This allows the frequency and content of reminders to be adjusted according to the user's emotions, making it possible to smoothly progress through procedures.

[0107] The support app can link the chat guidance section with a voice assistant to enable voice guidance. For example, it can provide voice guidance on how to proceed with a procedure. It can also link with a voice assistant to provide voice guidance on specific procedures and preparations. It can also provide voice answers based on questions the user asks. This allows chat-style guidance to be linked with a voice assistant, enabling voice guidance.

[0108] The support app can use the emotion estimation function to provide kind words and encouraging messages according to the user's emotions. For example, if the user is sad, words of comfort can be sent. Also, if the user is feeling depressed, an encouraging message can be sent. Furthermore, it is possible to provide specific messages based on the user's emotions. This allows the app to provide kind words and encouraging messages according to the user's emotions and support the user's emotions.

[0109] The support app can link the chat guidance section with a video call function, enabling direct consultation with an expert. For example, it is possible to consult with an expert regarding inheritance procedures via video call. It can also link with the video call function to consult with an expert about specific procedures or preparations. Furthermore, the expert can respond to questions asked by the user via video call. In this way, it is possible to link the chat guidance section with the video call function and enable direct consultation with an expert.

[0110] The support app can use the emotion estimation function to adjust the chatbot's response speed and content according to the user's emotions. For example, it can speed up the response if the user is in a hurry. It can also adjust the chatbot's response content based on the user's emotions. It can also prioritize responses to procedures that the user considers emotionally important. This allows the chatbot's response speed and content to be adjusted according to the user's emotions, making it possible to smoothly progress through procedures.

[0111] The processing flow of the second embodiment will be briefly explained below.

[0112] Step 1: The end-of-life support linkage section creates a list of the necessary procedures and preparations based on the end-of-life support information for the deceased. For example, the generation AI analyzes the contents of the will and end-of-life note created by the deceased before their death and creates a list of the necessary procedures. The generation AI also analyzes information entered by the user and suggests appropriate procedures and preparations. The input to the generation AI is a prompt containing instructions on what the user wants the generation AI to do, and the generation AI generates a list based on that prompt. Step 2: The procedure listing section lists the necessary procedures and deadlines listed by the end-of-life support linkage section. For example, the generation AI compiles a list of where and by when to submit a death notification, and when to start inheritance procedures. Based on information from the user, the generation AI lists the details of each procedure. This allows the user to see at a glance what they need to request, by when, and to whom. Step 3: The chat guidance section uses chat to guide the user through the procedures and preparations listed by the procedure listing section. For example, the generation AI might provide guidance such as, "The next procedure you need to complete is to submit a death notification. This should be submitted to city hall, and the deadline for submission is within seven days." The generation AI also responds to questions from the user and provides appropriate answers. This allows the user to smoothly understand the flow of procedures.

[0113] 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.

[0114] 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> Examples of generative AIs include the data generation model 58, such as a neural network model (e.g., a neural network model), and a neural network model (e.g., a neural network model). 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 speech, text data indicating text, and image data indicating an image is also input to the data generation model 58. 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. The specification processing unit 290 performs the above-mentioned specification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0115] Furthermore, the processing by the data processing system 10 described above is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart device 14, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart device 14. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the smart device 14 or an external device, and the smart device 14 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0116] [Second embodiment] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0117] 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.

[0118] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and 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 and / or a LAN.

[0119] 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.

[0120] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0121] 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 user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0122] 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.

[0123] 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.

[0124] 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.

[0125] 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. The identification processing unit 290 can estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0126] In the smart glasses 214, the specific processing is performed by the processor 46. A specific processing program 60 is stored in the storage 50. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. Note that the smart glasses 214 may have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59.

[0127] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0128] 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.

[0129] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. 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. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0130] The data processing system 210 according to the second embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 210 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart glasses 214, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart glasses 214. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the smart glasses 214 or an external device, etc., and the smart glasses 214 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0131] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0132] 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.

[0133] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and 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 and / or a LAN.

[0134] 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.

[0135] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0136] 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 user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0137] 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.

[0138] 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.

[0139] 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.

[0140] 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. The identification processing unit 290 can estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0141] In the headset type terminal 314, the identification process is performed by the processor 46. A identification program 60 is stored in the storage 50. The processor 46 reads the identification program 60 from the storage 50 and executes the read identification program 60 on the RAM 48. The identification process is realized by the processor 46 operating as a control unit 46A in accordance with the identification program 60 executed on the RAM 48. Note that the headset type terminal 314 may also have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59.

[0142] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0143] 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.

[0144] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. 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. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0145] The data processing system 310 according to the third embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 310 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the headset type terminal 314, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the headset type terminal 314. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the headset type terminal 314 or an external device, etc., and the headset type terminal 314 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0146] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0147] 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.

[0148] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and 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 and / or a LAN.

[0149] 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.

[0150] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0151] 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 image sensor or a CCD image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0152] 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.

[0153] The control object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the 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.

[0154] 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.

[0155] 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.

[0156] 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. The identification processing unit 290 can estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0157] In the robot 414, the processor 46 performs the identification process. A identification program 60 is stored in the storage 50. The processor 46 reads the identification program 60 from the storage 50 and executes the read identification program 60 on the RAM 48. The identification process is realized by the processor 46 operating as a control unit 46A in accordance with the identification program 60 executed on the RAM 48. The robot 414 may have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59.

[0158] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0159] 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.

[0160] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. 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. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0161] The data processing system 410 according to the fourth embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 410 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the robot 414, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the robot 414. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the robot 414 or an external device, etc., and the robot 414 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0162] 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.

[0163] FIG. 9 illustrates 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 behaviors arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion encompasses both emotions 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.

[0164] 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.

[0165] 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).

[0166] 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 expressed, and when they approach the ideal, a state of pleasure is expressed. Emotions can also be created for robots, cars, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is expressed, and when they approach the ideal, a state of pleasure is expressed. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on speech emotion recognition and brain physiological signal analysis systems for emotions, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the area called "reaction," where sensation is dominant. The right half of the emotion map lists emotions belonging to the area called "situation," where situational awareness is dominant.

[0167] 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."

[0168] 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.

[0169] In the above embodiment, an example was given in which a specific process is performed by one computer 22, but the technology disclosed herein is not limited to this, and distributed processing of the specific process may be performed by multiple computers including computer 22.

[0170] 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.

[0171] 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.

[0172] 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.

[0173] The hardware resource for executing a specific process can be any of the following types of processors: A processor, for example, 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. A processor also includes 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.

[0174] The hardware resource that executes the specific process 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 process may be a single processor.

[0175] 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.

[0176] 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.

[0177] In the above example, the first to fourth embodiments have been described separately, but some or all of these embodiments may be combined. The smart device 14, smart glasses 214, headset terminal 314, and robot 414 are merely examples, and they may be combined, or other devices may be used. In the above example, the first and second embodiments have been described separately, but they may be combined.

[0178] 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.

[0179] 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. [Explanation of symbols]

[0180] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot

Claims

1. The end-of-life support linkage department creates a list of necessary procedures or preparations based on the end-of-life support information of the deceased, and A procedure listing unit that lists the necessary procedure destinations or deadlines listed by the end-of-life planning support linkage unit; a chat guide unit that guides the user in a chat format through the procedures or preparations listed by the procedure listing unit. A system characterized by:

2. The end-of-life support linkage section is: Estimating the feelings of the deceased and providing end-of-life support based on those feelings 2. The system of claim 1.

3. The end-of-life support linkage section is: Collect information about the deceased's pet or plant care and list the procedures required for pet or plant care.

2. The system of claim 1.

4. The procedure listing unit Automatically provide details of the legal background or required documents for each procedure 2. The system of claim 1.

5. The chat guide unit Providing the kind words or the encouraging message according to the user's emotions 2. The system of claim 1.

6. The materials procurement department Providing advice to alleviate the user's anxiety 2. The system of claim 1.

7. The funeral director support department Providing the mourner with a message of encouragement or consolation that corresponds to their feelings 2. The system of claim 1.

8. The Inheritance Support Department Providing advice to reduce emotional conflicts between family members regarding inheritance 2. The system of claim 1.

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