system

Abstract

The system according to this embodiment aims to enable procedures to be performed online easily and accurately. [Solution] The system according to the embodiment comprises a reception unit, a guidance unit, an input unit, and a notification unit. The reception unit inputs information to start a procedure. The guidance unit automatically guides the user through the procedure flow based on the information entered by the reception unit. The input unit automatically inputs documents based on the procedure guided by the guidance unit. The notification unit notifies the user of the progress of the documents entered by the input unit.

Description

Technical Field

[0006] ,

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

Background Art

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

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In the conventional technology, there is a problem that it is difficult to perform procedures at city halls or tax offices online simply and accurately, which takes time and effort.

[0005] The system according to the embodiment aims to perform procedures online simply and accurately.

Means for Solving the Problems

[0006] The system according to this embodiment comprises a reception unit, a guidance unit, an input unit, and a notification unit. The reception unit inputs information to start a procedure. The guidance unit automatically guides the user through the procedure flow based on the information entered by the reception unit. The input unit automatically inputs documents based on the procedure guided by the guidance unit. The notification unit notifies the user of the progress of the documents entered by the input unit. [Effects of the Invention]

[0007] The system according to this embodiment allows procedures to be performed online easily and accurately. [Brief explanation of the drawing]

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

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

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

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

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

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

[0014] In the following embodiments, the numbered communication I / F (Interface) is an interface including a communication processor, an antenna, and the like. The communication I / F manages communication between a plurality of 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), or Bluetooth (registered trademark).

[0015] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B". That is, "A and / or B" means that it may be only A, only B, or a combination of A and B. Also, in this specification, when expressing three or more matters connected by "and / or", the same concept as "A and / or B" is applied.

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

[0017] As shown in FIG. 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

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

[0019] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0020] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, and accepts user input. The touch panel 38A accepts user input via touch by detecting contact with an object (e.g., a pen or finger). The microphone 38B accepts user input via voice by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 (see Figure 2) acquires the data indicating the user input.

[0021] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user by outputting the data in a form perceptible to the user (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0022] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

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

[0024] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0025] Storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotions using the emotion identification model 59 and perform identification processing using the user's emotions. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotions, including but not limited to these examples. Furthermore, emotion estimation and prediction also include, for example, emotion analysis.

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

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

[0028] (Example of form 1) The procedural support system according to an embodiment of the present invention is a procedural support system aimed at enabling easy and accurate online processing of procedures at city halls and tax offices. This procedural support system provides users with automatic guidance of the procedural flow, automatic document input support, and progress notifications, enabling quick and accurate applications to be submitted easily. First, the user inputs the information necessary to start the procedure. For example, the user selects the necessary procedure, such as issuing a resident certificate or submitting a change of address notification. This information is input into the generating AI agent. Next, the generating AI agent analyzes the input information and automatically guides the user through the procedural flow. The generating AI agent proposes the optimal procedural flow according to the user's situation and guides the user through the necessary documents and procedural steps. For example, in the case of issuing a resident certificate, it guides the user through the necessary documents and submission destinations. Furthermore, the generating AI agent provides automatic document input support. Based on the information entered by the user, it automatically inputs various application documents and performs format checks. This allows the user to create accurate documents without any effort. In addition, the generating AI agent notifies the user of the progress of the procedure in real time. The user can check the progress of the procedure and take necessary actions quickly. For example, users can receive notifications when a procedure is completed or when additional documents are required. This procedural support system handles high-demand procedures such as resident registration, moving-out notifications, and tax returns, significantly reducing the time and effort users need to complete them. It is particularly convenient for busy business people, the elderly, and those unfamiliar with digital technology. As a result, the procedural support system reduces the time and effort users need to complete, leading to increased efficiency and reduced congestion at service counters.

[0029] The procedure support system according to this embodiment comprises a reception unit, a guidance unit, an input unit, and a notification unit. The reception unit inputs information necessary to start a procedure. This information includes, but is not limited to, personal information, application details, and required documents. The reception unit provides, for example, an interface for the user to input the information necessary to start a procedure. The guidance unit automatically guides the user through the procedure flow based on the information entered by the reception unit. The guidance unit proposes, for example, the optimal procedure flow according to the user's situation and guides the user through the necessary documents and procedural steps. The guidance unit uses a generation AI to analyze the user's input information and generate the optimal procedure flow. For example, in the case of a procedure for issuing a resident certificate, the guidance unit guides the user through the necessary documents and submission destinations. The input unit automatically inputs documents based on the procedure guided by the guidance unit. The input unit automatically inputs various application forms and performs format checks based on the information entered by the user. The input unit uses a generation AI to analyze the user's input information and generate accurate documents. For example, the input unit automatically inputs an application form for issuing a resident certificate based on the information entered by the user. The notification unit notifies users of the progress of documents entered by the input unit. For example, the notification unit notifies users of the progress of a procedure in real time and prompts them to take necessary actions. The notification unit uses AI to analyze the progress of the procedure and provides notifications at the appropriate time. For example, the notification unit notifies users when a procedure is completed or when additional documents are required. As a result, the procedure support system can proceed with procedures efficiently and reduce the effort and time required of the user.

[0030] The reception desk inputs the information necessary to initiate the process. This information includes, but is not limited to, personal information, application details, and required documents. The reception desk provides an interface for users to input the information necessary to initiate the process. Specifically, the reception desk provides an intuitive user interface and displays forms for inputting personal information and application details. The forms include input fields such as name, address, contact information, and application details, and users input the necessary information into these fields. Furthermore, the reception desk also has a document upload function, allowing users to upload scanned documents or photographs. The reception desk verifies the entered information in real time, checking for missing or incorrect information. For example, the address input field performs format checks for postal codes and checks for missing required fields. This allows users to input the necessary information accurately and quickly to initiate the process. The reception desk stores the entered information securely in a database for use in subsequent processing. The database is equipped with security measures to protect users' personal information from leakage. This allows the reception department to efficiently collect the information needed to initiate the procedure and support the smooth progress of the process.

[0031] The guidance department automatically guides users through the procedure flow based on the information entered by the reception department. For example, the guidance department proposes the optimal procedure flow according to the user's situation and guides them through the necessary documents and procedural steps. The guidance department uses generative AI to analyze the user's input information and generate the optimal procedure flow. Specifically, the generative AI analyzes the personal information and application details entered by the user and proposes the optimal procedure flow based on past data and rules. For example, in the case of issuing a resident certificate, the generative AI analyzes the user's address and application details to identify the necessary documents and submission locations. Furthermore, the generative AI can optimize the procedure flow in real time based on the progress of the procedure and user feedback. The guidance department clearly guides users through each step of the procedure and provides details on the necessary documents and procedures. For example, the guidance department displays information on the next steps and submission locations for the user, supporting the progress of the procedure. The guidance department can also provide support through chatbots and FAQs if users have questions or concerns about the procedure. In this way, the guidance department can help users proceed with the procedure smoothly, contributing to the efficiency of the procedure and improved user convenience.

[0032] The input unit automatically fills in documents based on the procedures guided by the guidance unit. For example, the input unit automatically fills in various application forms based on information entered by the user and performs format checks. The input unit uses a generation AI to analyze the user's input information and generate accurate documents. Specifically, the generation AI analyzes the personal information and application details entered by the user and automatically enters them into templates for various application forms. For example, in the case of an application for a resident certificate, the generation AI accurately enters the information such as the user's name, address, and reason for application into each field of the application form. Furthermore, the input unit performs format checks on the generated documents to confirm that the necessary information has been entered correctly. For example, it checks for missing required fields and input format checks, and notifies the user if there are any errors. The input unit saves the generated documents as PDFs or electronic files so that users can download them. The input unit also has a function to automatically send the generated documents to the submission destination, saving the user the trouble of manual submission. In this way, the input unit can support users in efficiently proceeding with procedures and improve the accuracy and speed of the procedures.

[0033] The notification unit notifies users of the progress of documents entered by the input unit. For example, the notification unit notifies users of the progress of a procedure in real time and prompts them to take necessary actions. The notification unit uses AI to analyze the progress of the procedure and notify users at the appropriate time. Specifically, the AI ​​monitors the progress of the procedure and detects important events and status changes. For example, if a procedure is completed or additional documents are required, the AI ​​immediately notifies the user. Notifications are made using multiple communication methods, such as email, SMS, and app push notifications, to ensure that users receive the information reliably. Furthermore, the notification unit can collect user feedback and continuously improve the accuracy and timing of notifications. For example, it can analyze the user's actions and reactions after receiving a notification and optimize the content and timing of the notification. In this way, the notification unit can help users proceed with procedures smoothly and contribute to the efficiency of procedures and improved user convenience.

[0034] The Inquiry Department handles inquiries from users. For example, the Inquiry Department uses a chatbot to automatically respond to user inquiries. The Inquiry Department also uses AI to analyze user inquiries and provide appropriate answers. For instance, when a user enters a question about a procedure, the chatbot automatically generates an answer. The Inquiry Department can also handle inquiries by phone and email. For example, if a user makes an inquiry by phone, the Inquiry Department uses AI for speech recognition to provide an appropriate answer. This allows the Inquiry Department to respond to user inquiries quickly.

[0035] The Visualization Unit visualizes the progress of the procedure. For example, it displays the progress of the procedure visually using graphs or progress bars. The Visualization Unit uses AI to analyze the progress of the procedure and provide appropriate visualization methods. For example, the Visualization Unit displays the progress of each step of the procedure in a graph, allowing users to grasp the progress at a glance. The Visualization Unit can also display the overall progress of the procedure using a dashboard. This allows the Visualization Unit to visually confirm the progress of the procedure.

[0036] The guidance department proposes the optimal procedure flow according to the user's situation. For example, the guidance department analyzes the user's input information and generates the optimal procedure flow. The guidance department uses generation AI to propose a procedure flow that is appropriate for the user's situation. For example, if a user is applying for a resident registration certificate, the guidance department will guide them on the necessary documents and where to submit them. In this way, the guidance department can provide the optimal procedure flow according to the user's situation.

[0037] The input unit automatically fills in various application forms based on information entered by the user. For example, the input unit automatically fills in an application form for the issuance of a resident registration certificate based on information entered by the user. The input unit uses generation AI to analyze the user's input information and generate accurate documents. For example, the input unit automatically fills in passport application forms and visa application forms based on information entered by the user. This allows the input unit to create accurate documents without requiring any effort from the user.

[0038] The notification unit provides real-time updates on the progress of the procedure. For example, it notifies users of the procedure's progress in real time and prompts them to take necessary actions. The notification unit uses AI to analyze the progress of the procedure and provides notifications at the appropriate time. For example, it notifies users when the procedure is completed or when additional documents are required. This allows the notification unit to keep users informed of the procedure's progress in real time.

[0039] The reception department analyzes the user's past procedure history and selects the optimal reception method. For example, the reception department prioritizes displaying procedures that the user has frequently performed in the past. The reception department uses AI to analyze the user's past procedure history. For example, the reception department analyzes the user's past application content and procedure results and proposes the optimal reception method. In this way, the reception department can provide the optimal reception method based on the user's past procedure history.

[0040] The reception desk filters the user's current situation and areas of interest at the start of the process. For example, the reception desk prioritizes displaying relevant procedures based on the user's current situation. The reception desk uses AI to analyze the user's current situation and areas of interest. For example, the reception desk analyzes the user's survey results and behavioral history and suggests relevant procedures. This allows the reception desk to prioritize displaying procedures that match the user's current situation and areas of interest.

[0041] The reception desk prioritizes accepting procedures that are highly relevant to the user, taking into account the user's geographical location information at the start of the process. For example, the reception desk prioritizes displaying relevant procedures based on the user's current location. The reception desk uses AI to analyze the user's geographical location information. For example, the reception desk uses GPS data and IP addresses to identify the user's current location and suggest relevant procedures. This allows the reception desk to prioritize accepting procedures that are highly relevant to the user based on their geographical location information.

[0042] The reception desk analyzes the user's social media activity at the start of the process and accepts the relevant procedures. For example, the reception desk analyzes the user's social media activity and proposes relevant procedures. The reception desk uses AI to analyze the user's social media activity. For example, the reception desk analyzes the user's posts and follower information and proposes relevant procedures. This allows the reception desk to accept relevant procedures based on the user's social media activity.

[0043] The guidance system adjusts the level of detail in the guidance based on the importance of the procedure. For example, the guidance system provides detailed guidance for important procedures. The guidance system uses generative AI to analyze the importance of procedures and adjust the level of detail in the guidance. For example, the guidance system analyzes the legal requirements and impact of the procedure the user is performing and provides detailed guidance. This allows the guidance system to adjust the level of detail in the guidance according to the importance of the procedure.

[0044] The guidance system applies different guidance algorithms depending on the category of the procedure. For example, in the case of a procedure for issuing a resident registration certificate, the guidance system applies a guidance algorithm specifically for resident registration certificates. The guidance system uses a generation AI to analyze the category of the procedure and apply the most suitable guidance algorithm. For example, the guidance system selects an appropriate guidance algorithm depending on the type of procedure the user is performing. This allows the guidance system to provide optimal guidance according to the category of the procedure.

[0045] The guidance department determines the priority of guidance based on the submission timing of the procedures. For example, the guidance department prioritizes guidance for procedures with approaching deadlines. The guidance department uses a generation AI to analyze the submission timing of procedures and determine the priority of guidance. For example, the guidance department analyzes the submission deadlines for procedures that users are performing and provides priority guidance. In this way, the guidance department can adjust the priority of guidance according to the submission timing of procedures.

[0046] The guidance system adjusts the order of instructions based on the relevance of the procedures. For example, it prioritizes highly relevant procedures. The guidance system uses generative AI to analyze the relevance of procedures and adjust the order of instructions. For example, it analyzes the content of the procedures the user will perform and the relevant laws and regulations, and provides instructions in the optimal order. This allows the guidance system to adjust the order of instructions according to the relevance of the procedures.

[0047] The input unit analyzes the user's past input history to select the optimal input method during input. For example, the input unit prioritizes suggesting input methods that the user has frequently used in the past. The input unit uses AI to analyze the user's past input history. For example, the input unit analyzes the user's past input content and frequency to suggest the optimal input method. As a result, the input unit can provide the optimal input method based on the user's past input history.

[0048] The input unit customizes the input method based on the user's current situation during input. For example, the input unit suggests the optimal input method based on the user's current situation. The input unit uses AI to analyze the user's current situation. For example, the input unit analyzes the user's device and current task to suggest the optimal input method. As a result, the input unit can provide the optimal input method according to the user's current situation.

[0049] The input unit selects the optimal input method when inputting data, taking into account the user's geographical location. For example, the input unit suggests the optimal input method based on the user's current location. The input unit uses AI to analyze the user's geographical location. For example, the input unit uses GPS data or IP addresses to identify the user's current location and suggests the optimal input method. This allows the input unit to provide the optimal input method based on the user's geographical location.

[0050] The input unit analyzes the user's social media activity during input and suggests input methods. For example, the input unit analyzes the user's social media activity and suggests the optimal input method. The input unit uses AI to analyze the user's social media activity. For example, the input unit analyzes the user's posts and follower information and suggests the optimal input method. This allows the input unit to provide the optimal input method based on the user's social media activity.

[0051] The notification unit selects the optimal notification method by referring to the user's past notification history when sending a notification. For example, the notification unit prioritizes suggesting notification methods that the user has preferred to use in the past. The notification unit uses AI to analyze the user's past notification history. For example, the notification unit analyzes the content and frequency of the user's past notifications and suggests the optimal notification method. In this way, the notification unit can provide the optimal notification method based on the user's past notification history.

[0052] The notification unit selects the optimal notification method when sending a notification, taking into account the user's device information. For example, if the user is using a smartphone, the notification unit prioritizes push notifications. The notification unit uses AI to analyze the user's device information. For example, the notification unit analyzes the type and usage of the user's device and proposes the optimal notification method. This allows the notification unit to provide the most suitable notification method based on the user's device information.

[0053] The inquiry department selects the most appropriate response method when handling inquiries by referring to the user's past inquiry history. For example, the inquiry department prioritizes suggesting response methods that the user has preferred in the past. The inquiry department uses AI to analyze the user's past inquiry history. For example, the inquiry department analyzes the content of the user's past inquiries and the results of the responses to suggest the most appropriate response method. In this way, the inquiry department can provide the most appropriate response method based on the user's past inquiry history.

[0054] The customer support department selects the most appropriate response method when handling inquiries, taking into account the user's device information. For example, if the user is using a smartphone, the department will prioritize chat support. The customer support department uses AI to analyze the user's device information. For example, the department analyzes the type and usage of the user's device and proposes the most appropriate response method. This allows the customer support department to provide the most suitable response method based on the user's device information.

[0055] The visualization unit selects the optimal visualization method by referring to the user's past operation history during visualization. For example, the visualization unit prioritizes suggesting visualization methods that the user has preferred to use in the past. The visualization unit uses AI to analyze the user's past operation history. For example, the visualization unit analyzes the user's past operations and their frequency to suggest the optimal visualization method. In this way, the visualization unit can provide the optimal visualization method based on the user's past operation history.

[0056] The visualization unit selects the optimal visualization method when visualizing data, taking into account the user's device information. For example, if the user is using a smartphone, the visualization unit provides a visualization method that matches the screen size. The visualization unit uses AI to analyze the user's device information. For example, the visualization unit analyzes the type and usage of the user's device and proposes the optimal visualization method. This allows the visualization unit to provide the optimal visualization method based on the user's device information.

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

[0058] The reception desk can also automatically determine the priority of procedures based on the user's input information. For example, if a user is performing multiple procedures simultaneously, the reception desk will prioritize them based on their importance and submission deadline. Furthermore, the reception desk can refer to the user's past procedure history and prioritize frequently performed procedures. In addition, the reception desk can prioritize relevant procedures based on the user's current situation and areas of interest. This allows the reception desk to efficiently process the user's procedures.

[0059] The reception desk can also prioritize processing procedures based on the user's geographical location at the start of the process. For example, it can display relevant procedures first based on the user's current location. The reception desk can also use AI to analyze the user's geographical location and suggest the optimal processing method. This allows the reception desk to provide the most suitable processing method based on the user's geographical location.

[0060] The guidance department can also apply different guidance algorithms depending on the category of the procedure. For example, in the case of the procedure for issuing a resident registration certificate, a guidance algorithm specifically for resident registration certificates will be applied. The guidance department can also use generative AI to analyze the category of the procedure and select the most suitable guidance algorithm. This allows the guidance department to provide the most appropriate guidance according to the category of the procedure.

[0061] The input unit can also analyze the user's past input history to select the optimal input method during input. For example, it can prioritize suggesting input methods that the user has frequently used in the past. The input unit can also use AI to analyze the user's past input history and suggest the optimal input method. This allows the input unit to provide the optimal input method based on the user's past input history.

[0062] The notification unit can also select the optimal notification method by considering the user's device information when sending a notification. For example, if the user is using a smartphone, push notifications will be prioritized. The notification unit can also use AI to analyze the user's device information and suggest the optimal notification method. This allows the notification unit to provide the most suitable notification method based on the user's device information.

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

[0064] Step 1: The reception desk enters the information necessary to start the procedure. This information includes, for example, personal information, application details, and required documents. The reception desk provides an interface for the user to enter the information necessary to start the procedure. Step 2: The guidance department automatically guides the user through the procedure flow based on the information entered by the reception department. The guidance department proposes the optimal procedure flow according to the user's situation and guides the user through the necessary documents and procedural steps. The guidance department uses a generation AI to analyze the user's input information and generate the optimal procedure flow. Step 3: The input unit automatically enters documents based on the procedures guided by the guidance unit. The input unit automatically enters various application forms based on the information entered by the user and performs format checks. The input unit uses generation AI to analyze the user's input information and generate accurate documents. Step 4: The notification unit notifies the user of the progress of the documents entered by the input unit. The notification unit notifies the user of the progress of the procedure in real time and prompts the user to take necessary actions. The notification unit uses AI to analyze the progress of the procedure and provides notifications at the appropriate time.

[0065] (Example of form 2) The procedural support system according to an embodiment of the present invention is a procedural support system aimed at enabling easy and accurate online processing of procedures at city halls and tax offices. This procedural support system provides users with automatic guidance of the procedural flow, automatic document input support, and progress notifications, enabling quick and accurate applications to be submitted easily. First, the user inputs the information necessary to start the procedure. For example, the user selects the necessary procedure, such as issuing a resident certificate or submitting a change of address notification. This information is input into the generating AI agent. Next, the generating AI agent analyzes the input information and automatically guides the user through the procedural flow. The generating AI agent proposes the optimal procedural flow according to the user's situation and guides the user through the necessary documents and procedural steps. For example, in the case of issuing a resident certificate, it guides the user through the necessary documents and submission destinations. Furthermore, the generating AI agent provides automatic document input support. Based on the information entered by the user, it automatically inputs various application documents and performs format checks. This allows the user to create accurate documents without any effort. In addition, the generating AI agent notifies the user of the progress of the procedure in real time. The user can check the progress of the procedure and take necessary actions quickly. For example, users can receive notifications when a procedure is completed or when additional documents are required. This procedural support system handles high-demand procedures such as resident registration, moving-out notifications, and tax returns, significantly reducing the time and effort users need to complete them. It is particularly convenient for busy business people, the elderly, and those unfamiliar with digital technology. As a result, the procedural support system reduces the time and effort users need to complete, leading to increased efficiency and reduced congestion at service counters.

[0066] The procedure support system according to this embodiment comprises a reception unit, a guidance unit, an input unit, and a notification unit. The reception unit inputs information necessary to start a procedure. This information includes, but is not limited to, personal information, application details, and required documents. The reception unit provides, for example, an interface for the user to input the information necessary to start a procedure. The guidance unit automatically guides the user through the procedure flow based on the information entered by the reception unit. The guidance unit proposes, for example, the optimal procedure flow according to the user's situation and guides the user through the necessary documents and procedural steps. The guidance unit uses a generation AI to analyze the user's input information and generate the optimal procedure flow. For example, in the case of a procedure for issuing a resident certificate, the guidance unit guides the user through the necessary documents and submission destinations. The input unit automatically inputs documents based on the procedure guided by the guidance unit. The input unit automatically inputs various application forms and performs format checks based on the information entered by the user. The input unit uses a generation AI to analyze the user's input information and generate accurate documents. For example, the input unit automatically inputs an application form for issuing a resident certificate based on the information entered by the user. The notification unit notifies users of the progress of documents entered by the input unit. For example, the notification unit notifies users of the progress of a procedure in real time and prompts them to take necessary actions. The notification unit uses AI to analyze the progress of the procedure and provides notifications at the appropriate time. For example, the notification unit notifies users when a procedure is completed or when additional documents are required. As a result, the procedure support system can proceed with procedures efficiently and reduce the effort and time required of the user.

[0067] The reception desk inputs the information necessary to initiate the process. This information includes, but is not limited to, personal information, application details, and required documents. The reception desk provides an interface for users to input the information necessary to initiate the process. Specifically, the reception desk provides an intuitive user interface and displays forms for inputting personal information and application details. The forms include input fields such as name, address, contact information, and application details, and users input the necessary information into these fields. Furthermore, the reception desk also has a document upload function, allowing users to upload scanned documents or photographs. The reception desk verifies the entered information in real time, checking for missing or incorrect information. For example, the address input field performs format checks for postal codes and checks for missing required fields. This allows users to input the necessary information accurately and quickly to initiate the process. The reception desk stores the entered information securely in a database for use in subsequent processing. The database is equipped with security measures to protect users' personal information from leakage. This allows the reception department to efficiently collect the information needed to initiate the procedure and support the smooth progress of the process.

[0068] The guidance department automatically guides users through the procedure flow based on the information entered by the reception department. For example, the guidance department proposes the optimal procedure flow according to the user's situation and guides them through the necessary documents and procedural steps. The guidance department uses generative AI to analyze the user's input information and generate the optimal procedure flow. Specifically, the generative AI analyzes the personal information and application details entered by the user and proposes the optimal procedure flow based on past data and rules. For example, in the case of issuing a resident certificate, the generative AI analyzes the user's address and application details to identify the necessary documents and submission locations. Furthermore, the generative AI can optimize the procedure flow in real time based on the progress of the procedure and user feedback. The guidance department clearly guides users through each step of the procedure and provides details on the necessary documents and procedures. For example, the guidance department displays information on the next steps and submission locations for the user, supporting the progress of the procedure. The guidance department can also provide support through chatbots and FAQs if users have questions or concerns about the procedure. In this way, the guidance department can help users proceed with the procedure smoothly, contributing to the efficiency of the procedure and improved user convenience.

[0069] The input unit automatically fills in documents based on the procedures guided by the guidance unit. For example, the input unit automatically fills in various application forms based on information entered by the user and performs format checks. The input unit uses a generation AI to analyze the user's input information and generate accurate documents. Specifically, the generation AI analyzes the personal information and application details entered by the user and automatically enters them into templates for various application forms. For example, in the case of an application for a resident certificate, the generation AI accurately enters the information such as the user's name, address, and reason for application into each field of the application form. Furthermore, the input unit performs format checks on the generated documents to confirm that the necessary information has been entered correctly. For example, it checks for missing required fields and input format checks, and notifies the user if there are any errors. The input unit saves the generated documents as PDFs or electronic files so that users can download them. The input unit also has a function to automatically send the generated documents to the submission destination, saving the user the trouble of manual submission. In this way, the input unit can support users in efficiently proceeding with procedures and improve the accuracy and speed of the procedures.

[0070] The notification unit notifies users of the progress of documents entered by the input unit. For example, the notification unit notifies users of the progress of a procedure in real time and prompts them to take necessary actions. The notification unit uses AI to analyze the progress of the procedure and notify users at the appropriate time. Specifically, the AI ​​monitors the progress of the procedure and detects important events and status changes. For example, if a procedure is completed or additional documents are required, the AI ​​immediately notifies the user. Notifications are made using multiple communication methods, such as email, SMS, and app push notifications, to ensure that users receive the information reliably. Furthermore, the notification unit can collect user feedback and continuously improve the accuracy and timing of notifications. For example, it can analyze the user's actions and reactions after receiving a notification and optimize the content and timing of the notification. In this way, the notification unit can help users proceed with procedures smoothly and contribute to the efficiency of procedures and improved user convenience.

[0071] The Inquiry Department handles inquiries from users. For example, the Inquiry Department uses a chatbot to automatically respond to user inquiries. The Inquiry Department also uses AI to analyze user inquiries and provide appropriate answers. For instance, when a user enters a question about a procedure, the chatbot automatically generates an answer. The Inquiry Department can also handle inquiries by phone and email. For example, if a user makes an inquiry by phone, the Inquiry Department uses AI for speech recognition to provide an appropriate answer. This allows the Inquiry Department to respond to user inquiries quickly.

[0072] The Visualization Unit visualizes the progress of the procedure. For example, it displays the progress of the procedure visually using graphs or progress bars. The Visualization Unit uses AI to analyze the progress of the procedure and provide appropriate visualization methods. For example, the Visualization Unit displays the progress of each step of the procedure in a graph, allowing users to grasp the progress at a glance. The Visualization Unit can also display the overall progress of the procedure using a dashboard. This allows the Visualization Unit to visually confirm the progress of the procedure.

[0073] The guidance department proposes the optimal procedure flow according to the user's situation. For example, the guidance department analyzes the user's input information and generates the optimal procedure flow. The guidance department uses generation AI to propose a procedure flow that is appropriate for the user's situation. For example, if a user is applying for a resident registration certificate, the guidance department will guide them on the necessary documents and where to submit them. In this way, the guidance department can provide the optimal procedure flow according to the user's situation.

[0074] The input unit automatically fills in various application forms based on information entered by the user. For example, the input unit automatically fills in an application form for the issuance of a resident registration certificate based on information entered by the user. The input unit uses generation AI to analyze the user's input information and generate accurate documents. For example, the input unit automatically fills in passport application forms and visa application forms based on information entered by the user. This allows the input unit to create accurate documents without requiring any effort from the user.

[0075] The notification unit provides real-time updates on the progress of the procedure. For example, it notifies users of the procedure's progress in real time and prompts them to take necessary actions. The notification unit uses AI to analyze the progress of the procedure and provides notifications at the appropriate time. For example, it notifies users when the procedure is completed or when additional documents are required. This allows the notification unit to keep users informed of the procedure's progress in real time.

[0076] The reception desk estimates the user's emotions and adjusts the timing of the procedure start based on the estimated emotions. For example, if the user is feeling stressed, the reception desk will delay the start of the procedure to give them time to relax. The reception desk estimates the user's emotions using an emotion engine or generative AI. For example, the reception desk analyzes the user's facial expressions to estimate their emotions. Also, if the user is in a hurry, the reception desk will start the procedure quickly to ensure a smooth process. In this way, the reception desk can adjust the timing of the procedure start according to the user's emotions.

[0077] The reception department analyzes the user's past procedure history and selects the optimal reception method. For example, the reception department prioritizes displaying procedures that the user has frequently performed in the past. The reception department uses AI to analyze the user's past procedure history. For example, the reception department analyzes the user's past application content and procedure results and proposes the optimal reception method. In this way, the reception department can provide the optimal reception method based on the user's past procedure history.

[0078] The reception desk filters the user's current situation and areas of interest at the start of the process. For example, the reception desk prioritizes displaying relevant procedures based on the user's current situation. The reception desk uses AI to analyze the user's current situation and areas of interest. For example, the reception desk analyzes the user's survey results and behavioral history and suggests relevant procedures. This allows the reception desk to prioritize displaying procedures that match the user's current situation and areas of interest.

[0079] The reception desk estimates the user's emotions and determines the priority of procedures to process based on those emotions. For example, if the user is stressed, the reception desk will prioritize simple procedures. The reception desk estimates the user's emotions using an emotion engine or generative AI. For example, the reception desk analyzes the user's voice to estimate their emotions. Also, if the user is in a hurry, the reception desk will prioritize important procedures. This allows the reception desk to determine the priority of procedures according to the user's emotions.

[0080] The reception desk prioritizes accepting procedures that are highly relevant to the user, taking into account the user's geographical location information at the start of the process. For example, the reception desk prioritizes displaying relevant procedures based on the user's current location. The reception desk uses AI to analyze the user's geographical location information. For example, the reception desk uses GPS data and IP addresses to identify the user's current location and suggest relevant procedures. This allows the reception desk to prioritize accepting procedures that are highly relevant to the user based on their geographical location information.

[0081] The reception desk analyzes the user's social media activity at the start of the process and accepts the relevant procedures. For example, the reception desk analyzes the user's social media activity and proposes relevant procedures. The reception desk uses AI to analyze the user's social media activity. For example, the reception desk analyzes the user's posts and follower information and proposes relevant procedures. This allows the reception desk to accept relevant procedures based on the user's social media activity.

[0082] The guidance unit estimates the user's emotions and adjusts the way it presents the guidance based on those emotions. For example, if the user is nervous, the guidance unit will use a calm and composed approach. The guidance unit estimates the user's emotions using an emotion engine or generative AI. For example, the guidance unit analyzes the user's facial expressions to estimate their emotions. Conversely, if the user is relaxed, the guidance unit will use a cheerful approach. This allows the guidance unit to adjust the way it presents the guidance according to the user's emotions.

[0083] The guidance system adjusts the level of detail in the guidance based on the importance of the procedure. For example, the guidance system provides detailed guidance for important procedures. The guidance system uses generative AI to analyze the importance of procedures and adjust the level of detail in the guidance. For example, the guidance system analyzes the legal requirements and impact of the procedure the user is performing and provides detailed guidance. This allows the guidance system to adjust the level of detail in the guidance according to the importance of the procedure.

[0084] The guidance system applies different guidance algorithms depending on the category of the procedure. For example, in the case of a procedure for issuing a resident registration certificate, the guidance system applies a guidance algorithm specifically for resident registration certificates. The guidance system uses a generation AI to analyze the category of the procedure and apply the most suitable guidance algorithm. For example, the guidance system selects an appropriate guidance algorithm depending on the type of procedure the user is performing. This allows the guidance system to provide optimal guidance according to the category of the procedure.

[0085] The guidance system estimates the user's emotions and adjusts the length of the guidance based on those emotions. For example, if the user is in a hurry, the guidance system will provide short, concise instructions. The guidance system estimates the user's emotions using an emotion engine or generative AI. For example, the guidance system analyzes the user's voice to estimate their emotions. Conversely, if the user is relaxed, the guidance system will provide detailed instructions. This allows the guidance system to adjust the length of the guidance according to the user's emotions.

[0086] The guidance department determines the priority of guidance based on the submission timing of the procedures. For example, the guidance department prioritizes guidance for procedures with approaching deadlines. The guidance department uses a generation AI to analyze the submission timing of procedures and determine the priority of guidance. For example, the guidance department analyzes the submission deadlines for procedures that users are performing and provides priority guidance. In this way, the guidance department can adjust the priority of guidance according to the submission timing of procedures.

[0087] The guidance system adjusts the order of instructions based on the relevance of the procedures. For example, it prioritizes highly relevant procedures. The guidance system uses generative AI to analyze the relevance of procedures and adjust the order of instructions. For example, it analyzes the content of the procedures the user will perform and the relevant laws and regulations, and provides instructions in the optimal order. This allows the guidance system to adjust the order of instructions according to the relevance of the procedures.

[0088] The input unit estimates the user's emotions and adjusts the input method based on the estimated emotions. For example, if the user is feeling stressed, the input unit provides a simpler input method. The input unit estimates the user's emotions using an emotion engine or generative AI. For example, the input unit analyzes the user's facial expressions to estimate emotions. Also, if the user is in a hurry, the input unit prioritizes voice input. This allows the input unit to adjust the input method according to the user's emotions.

[0089] The input unit analyzes the user's past input history to select the optimal input method during input. For example, the input unit prioritizes suggesting input methods that the user has frequently used in the past. The input unit uses AI to analyze the user's past input history. For example, the input unit analyzes the user's past input content and frequency to suggest the optimal input method. As a result, the input unit can provide the optimal input method based on the user's past input history.

[0090] The input unit customizes the input method based on the user's current situation during input. For example, the input unit suggests the optimal input method based on the user's current situation. The input unit uses AI to analyze the user's current situation. For example, the input unit analyzes the user's device and current task to suggest the optimal input method. As a result, the input unit can provide the optimal input method according to the user's current situation.

[0091] The input unit estimates the user's emotions and prioritizes inputs based on those emotions. For example, if the user is stressed, the input unit prioritizes simple inputs. The input unit estimates the user's emotions using an emotion engine or generative AI. For example, the input unit analyzes the user's voice to estimate their emotions. Also, if the user is in a hurry, the input unit prioritizes important inputs. In this way, the input unit can determine the priority of inputs according to the user's emotions.

[0092] The input unit selects the optimal input method when inputting data, taking into account the user's geographical location. For example, the input unit suggests the optimal input method based on the user's current location. The input unit uses AI to analyze the user's geographical location. For example, the input unit uses GPS data or IP addresses to identify the user's current location and suggests the optimal input method. This allows the input unit to provide the optimal input method based on the user's geographical location.

[0093] The input unit analyzes the user's social media activity during input and suggests input methods. For example, the input unit analyzes the user's social media activity and suggests the optimal input method. The input unit uses AI to analyze the user's social media activity. For example, the input unit analyzes the user's posts and follower information and suggests the optimal input method. This allows the input unit to provide the optimal input method based on the user's social media activity.

[0094] The notification unit estimates the user's emotions and adjusts the notification method based on the estimated emotions. For example, if the user is nervous, the notification unit will send a calm notification. The notification unit estimates the user's emotions using an emotion engine or generative AI. For example, the notification unit analyzes the user's facial expressions to estimate their emotions. Also, if the user is in a hurry, the notification unit will send a quick notification. In this way, the notification unit can adjust the notification method according to the user's emotions.

[0095] The notification unit selects the optimal notification method by referring to the user's past notification history when sending a notification. For example, the notification unit prioritizes suggesting notification methods that the user has preferred to use in the past. The notification unit uses AI to analyze the user's past notification history. For example, the notification unit analyzes the content and frequency of the user's past notifications and suggests the optimal notification method. In this way, the notification unit can provide the optimal notification method based on the user's past notification history.

[0096] The notification unit estimates the user's emotions and determines notification priorities based on those emotions. For example, if the user is stressed, the notification unit will prioritize important notifications. The notification unit estimates the user's emotions using an emotion engine or generative AI. For example, the notification unit analyzes the user's voice to estimate their emotions. Also, if the user is in a hurry, the notification unit will prioritize urgent notifications. This allows the notification unit to determine notification priorities according to the user's emotions.

[0097] The notification unit selects the optimal notification method when sending a notification, taking into account the user's device information. For example, if the user is using a smartphone, the notification unit prioritizes push notifications. The notification unit uses AI to analyze the user's device information. For example, the notification unit analyzes the type and usage of the user's device and proposes the optimal notification method. This allows the notification unit to provide the most suitable notification method based on the user's device information.

[0098] The inquiry department estimates the user's emotions and adjusts its response based on those emotions. For example, if the user is nervous, the inquiry department will respond calmly. The inquiry department estimates the user's emotions using an emotion engine or generative AI. For example, the inquiry department analyzes the user's facial expressions to estimate their emotions. Also, if the user is in a hurry, the inquiry department will respond quickly. This allows the inquiry department to adjust its response based on the user's emotions.

[0099] The inquiry department selects the most appropriate response method when handling inquiries by referring to the user's past inquiry history. For example, the inquiry department prioritizes suggesting response methods that the user has preferred in the past. The inquiry department uses AI to analyze the user's past inquiry history. For example, the inquiry department analyzes the content of the user's past inquiries and the results of the responses to suggest the most appropriate response method. In this way, the inquiry department can provide the most appropriate response method based on the user's past inquiry history.

[0100] The inquiry department estimates the user's emotions and prioritizes inquiries based on those emotions. For example, if the user is stressed, the inquiry department will prioritize important inquiries. The inquiry department estimates the user's emotions using an emotion engine or generative AI. For example, the inquiry department analyzes the user's voice to estimate their emotions. Also, if the user is in a hurry, the inquiry department will prioritize urgent inquiries. This allows the inquiry department to prioritize inquiries according to the user's emotions.

[0101] The customer support department selects the most appropriate response method when handling inquiries, taking into account the user's device information. For example, if the user is using a smartphone, the department will prioritize chat support. The customer support department uses AI to analyze the user's device information. For example, the department analyzes the type and usage of the user's device and proposes the most appropriate response method. This allows the customer support department to provide the most suitable response method based on the user's device information.

[0102] The visualization unit estimates the user's emotions and adjusts the visualization method based on the estimated emotions. For example, if the user is nervous, the visualization unit will use calm colors. The visualization unit estimates the user's emotions using an emotion engine or generative AI. For example, the visualization unit analyzes the user's facial expressions to estimate emotions. Also, if the user is in a hurry, the visualization unit will use a concise display method. In this way, the visualization unit can adjust the visualization method according to the user's emotions.

[0103] The visualization unit selects the optimal visualization method by referring to the user's past operation history during visualization. For example, the visualization unit prioritizes suggesting visualization methods that the user has preferred to use in the past. The visualization unit uses AI to analyze the user's past operation history. For example, the visualization unit analyzes the user's past operations and their frequency to suggest the optimal visualization method. In this way, the visualization unit can provide the optimal visualization method based on the user's past operation history.

[0104] The visualization unit estimates the user's emotions and determines the visualization priority based on the estimated emotions. For example, if the user is stressed, the visualization unit prioritizes visualizing important information. The visualization unit estimates the user's emotions using an emotion engine or generative AI. For example, the visualization unit analyzes the user's voice to estimate emotions. Also, if the user is in a hurry, the visualization unit prioritizes visualizing urgent information. In this way, the visualization unit can determine the visualization priority according to the user's emotions.

[0105] The visualization unit selects the optimal visualization method when visualizing data, taking into account the user's device information. For example, if the user is using a smartphone, the visualization unit provides a visualization method that matches the screen size. The visualization unit uses AI to analyze the user's device information. For example, the visualization unit analyzes the type and usage of the user's device and proposes the optimal visualization method. This allows the visualization unit to provide the optimal visualization method based on the user's device information.

[0106] The system according to the embodiment is not limited to the example described above, and various modifications are possible, for example, as follows.

[0107] The reception desk can also automatically determine the priority of procedures based on the user's input information. For example, if a user is performing multiple procedures simultaneously, the reception desk will prioritize them based on their importance and submission deadline. Furthermore, the reception desk can refer to the user's past procedure history and prioritize frequently performed procedures. In addition, the reception desk can prioritize relevant procedures based on the user's current situation and areas of interest. This allows the reception desk to efficiently process the user's procedures.

[0108] The inquiry department can also estimate the user's emotions and adjust its response based on those emotions. For example, if the user is nervous, the inquiry department will respond calmly. If the user is in a hurry, the inquiry department can respond quickly. Furthermore, the inquiry department can refer to the user's past inquiry history to select the most appropriate response. This allows the inquiry department to provide the best possible response according to the user's emotions.

[0109] The visualization unit not only visualizes the progress of a procedure, but can also estimate the user's emotions and adjust the visualization method based on those emotions. For example, if the user is nervous, the visualization unit will use calming colors. If the user is in a hurry, it can use a concise display method. Furthermore, the visualization unit can refer to the user's past operation history and select the optimal visualization method. This allows the visualization unit to provide the most appropriate visualization method according to the user's emotions.

[0110] The guidance system can also estimate the user's emotions and adjust the way it presents the guidance based on those emotions. For example, if the user is nervous, the guidance system will use a calmer tone. Conversely, if the user is relaxed, it can use a more cheerful tone. Furthermore, the guidance system can adjust the level of detail in the guidance based on the importance of the procedure. This allows the guidance system to provide the most appropriate guidance according to the user's emotions.

[0111] The input unit can also estimate the user's emotions and adjust the input method based on those emotions. For example, if the user is stressed, the input unit will provide a simpler input method. If the user is in a hurry, the input unit can prioritize voice input. Furthermore, the input unit can analyze the user's past input history and select the optimal input method. This allows the input unit to provide the most suitable input method according to the user's emotions.

[0112] The notification unit not only provides real-time updates on the progress of a procedure, but can also estimate the user's emotions and adjust the notification method based on those emotions. For example, if the user is stressed, the notification unit will send a calm notification. If the user is in a hurry, it can send a quick notification. Furthermore, the notification unit can refer to the user's past notification history and select the most appropriate notification method. This allows the notification unit to provide the most suitable notification method according to the user's emotions.

[0113] The reception desk can also prioritize processing procedures based on the user's geographical location at the start of the process. For example, it can display relevant procedures first based on the user's current location. The reception desk can also use AI to analyze the user's geographical location and suggest the optimal processing method. This allows the reception desk to provide the most suitable processing method based on the user's geographical location.

[0114] The guidance department can also apply different guidance algorithms depending on the category of the procedure. For example, in the case of the procedure for issuing a resident registration certificate, a guidance algorithm specifically for resident registration certificates will be applied. The guidance department can also use generative AI to analyze the category of the procedure and select the most suitable guidance algorithm. This allows the guidance department to provide the most appropriate guidance according to the category of the procedure.

[0115] The input unit can also analyze the user's past input history to select the optimal input method during input. For example, it can prioritize suggesting input methods that the user has frequently used in the past. The input unit can also use AI to analyze the user's past input history and suggest the optimal input method. This allows the input unit to provide the optimal input method based on the user's past input history.

[0116] The notification unit can also select the optimal notification method by considering the user's device information when sending a notification. For example, if the user is using a smartphone, push notifications will be prioritized. The notification unit can also use AI to analyze the user's device information and suggest the optimal notification method. This allows the notification unit to provide the most suitable notification method based on the user's device information.

[0117] The following briefly describes the processing flow for example form 2.

[0118] Step 1: The reception desk enters the information necessary to start the procedure. This information includes, for example, personal information, application details, and required documents. The reception desk provides an interface for the user to enter the information necessary to start the procedure. Step 2: The guidance department automatically guides the user through the procedure flow based on the information entered by the reception department. The guidance department proposes the optimal procedure flow according to the user's situation and guides the user through the necessary documents and procedural steps. The guidance department uses a generation AI to analyze the user's input information and generate the optimal procedure flow. Step 3: The input unit automatically enters documents based on the procedures guided by the guidance unit. The input unit automatically enters various application forms based on the information entered by the user and performs format checks. The input unit uses generation AI to analyze the user's input information and generate accurate documents. Step 4: The notification unit notifies the user of the progress of the documents entered by the input unit. The notification unit notifies the user of the progress of the procedure in real time and prompts the user to take necessary actions. The notification unit uses AI to analyze the progress of the procedure and provides notifications at the appropriate time.

[0119] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0120] Data generation model 58 is a form of so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> Examples of generative AI include text generation AI, image generation AI, and multimodal generation AI. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images (e.g., still image data or video data). The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference result in one or more data formats from audio data, text data, and image data. The data generation model 58 includes, for example, text generation AI, image generation AI, and multimodal generation AI. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specific processing unit 290 performs the specific processing described above using the data generation model 58. The data generation model 58 may be a fine-tuned model that outputs inference results from prompts that do not contain instructions, in which case the data generation model 58 can output inference results from prompts that do not contain instructions. In the data processing device 12, etc., there are multiple types of data generation models 58, and the data generation model 58 includes AI other than generative AI. AI other than generative AI includes, for example, linear regression, logistic regression, decision trees, random forests, support vector machines (SVMs), k-means clustering, convolutional neural networks (CNNs), recurrent neural networks (RNNs), generative adversarial networks (GANs), or naive Bayes, and can perform various processes, but is not limited to these examples. Also, the AI ​​may be an AI agent. Furthermore, when the processing of each of the above parts is performed by the AI, the processing may be performed by the AI ​​in part or in whole, but is not limited to this example.Furthermore, processing performed by AI, including generative AI, may be replaced with rule-based processing, and rule-based processing may be replaced with processing performed by AI, including generative AI.

[0121] Furthermore, the processing performed by the data processing system 10 described above is carried out by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart device 14, but it may also be carried out by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart device 14. In addition, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the smart device 14 or an external device, and the smart device 14 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0122] Each of the multiple elements described above, including the reception unit, guidance unit, input unit, notification unit, inquiry unit, and visualization unit, is implemented by, for example, at least one of the smart device 14 and the data processing unit 12. For example, the reception unit is implemented by the control unit 46A of the smart device 14 and provides an interface for the user to input information to start a procedure. The guidance unit is implemented by, for example, the specific processing unit 290 of the data processing unit 12 and proposes an optimal procedure flow according to the user's situation. The input unit is implemented by, for example, the control unit 46A of the smart device 14 and automatically inputs various application forms based on the information entered by the user. The notification unit is implemented by, for example, the specific processing unit 290 of the data processing unit 12 and notifies the user of the progress of the procedure in real time. The inquiry unit is implemented by, for example, the control unit 46A of the smart device 14 and automatically responds to user inquiries using a chatbot. The visualization unit is implemented by, for example, the specific processing unit 290 of the data processing unit 12 and visually displays the progress of the procedure using graphs and progress bars. The correspondence between each part and the device or control unit is not limited to the examples described above, and various modifications are possible.

[0123] [Second Embodiment] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0124] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0125] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN and / or LAN.

[0126] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0127] The microphone 238 receives voice signals from the user and accepts instructions from the user. The microphone 238 captures the voice signals from the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0128] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, which captures images of the area around the user (for example, an imaging range defined by a field of view equivalent to the field of vision of a typical healthy person).

[0129] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0130] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing by the processor 28. The storage 32 stores the specific processing program 56.

[0131] The processor 28 reads a specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 acting as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0132] Storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotions using the emotion identification model 59 and perform identification processing using the user's emotions. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotions, including but not limited to these examples. Furthermore, emotion estimation and prediction also include, for example, emotion analysis.

[0133] In the smart glasses 214, specific processing is performed by the processor 46. The storage 50 stores a specific processing program 60. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 acting as a control unit 46A according to the specific processing program 60 executed on the RAM 48. The smart glasses 214 also have a data generation model 58 and an emotion identification model 59, similar to the data generation model and emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0134] Furthermore, other devices besides the data processing device 12 may also have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 obtains processing results (such as prediction results) using the data generation model 58 by communicating with the server device that has the data generation model 58. Also, the data processing device 12 may be a server device or a terminal device owned by the user (for example, a mobile phone, robot, home appliance, etc.).

[0135] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0136] The data generation model 58 is a so-called generative AI. An example of a data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and inference data such as audio data representing speech, text data representing text, and image data representing images (e.g., still image data or video data). The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference result in one or more data formats such as audio data, text data, and image data. The data generation model 58 includes, for example, text generation AI, image generation AI, and multimodal generation AI. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specific processing unit 290 performs the specific processing described above using the data generation model 58. The data generation model 58 may be a fine-tuned model that outputs inference results from prompts that do not contain instructions, in which case the data generation model 58 can output inference results from prompts that do not contain instructions. In the data processing device 12, etc., there are multiple types of data generation models 58, and the data generation model 58 includes AI other than generative AI. AI other than generative AI includes, for example, linear regression, logistic regression, decision trees, random forests, support vector machines (SVM), k-means clustering, convolutional neural networks (CNN), recurrent neural networks (RNN), generative adversarial networks (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. Also, the AI ​​may be an AI agent. Furthermore, when the processing of each part described above is performed by the AI, the processing may be performed by the AI ​​in part or in whole, but is not limited to this example. Also, processing performed by an AI including a generative AI may be replaced by rule-based processing, and rule-based processing may be replaced by processing performed by an AI including a generative AI.

[0137] The data processing system 210 according to the second embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 210 is performed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart glasses 214, but it may also be performed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart glasses 214. In addition, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the smart glasses 214 or an external device, and the smart glasses 214 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0138] Each of the multiple elements described above, including the reception unit, guidance unit, input unit, notification unit, inquiry unit, and visualization unit, is implemented by, for example, at least one of the smart glasses 214 and the data processing unit 12. For example, the reception unit is implemented by the control unit 46A of the smart glasses 214 and provides an interface for the user to input information to start a procedure. The guidance unit is implemented by, for example, the specific processing unit 290 of the data processing unit 12 and proposes an optimal procedure flow according to the user's situation. The input unit is implemented by, for example, the control unit 46A of the smart glasses 214 and automatically inputs various application forms based on the information entered by the user. The notification unit is implemented by, for example, the specific processing unit 290 of the data processing unit 12 and notifies the user of the progress of the procedure in real time. The inquiry unit is implemented by, for example, the control unit 46A of the smart glasses 214 and automatically responds to user inquiries using a chatbot. The visualization unit is implemented by, for example, the specific processing unit 290 of the data processing unit 12 and visually displays the progress of the procedure using graphs and progress bars. The correspondence between each part and the device or control unit is not limited to the examples described above, and various modifications are possible.

[0139] [Third Embodiment] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0140] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0141] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN and / or LAN.

[0142] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0143] The microphone 238 receives voice signals from the user and accepts instructions from the user. The microphone 238 captures the voice signals from the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0144] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, which captures images of the area around the user (for example, an imaging range defined by a field of view equivalent to the field of vision of a typical healthy person).

[0145] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0146] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0147] The processor 28 reads a specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 acting as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0148] Storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotions using the emotion identification model 59 and perform identification processing using the user's emotions. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotions, including but not limited to these examples. Furthermore, emotion estimation and prediction also include, for example, emotion analysis.

[0149] In the headset terminal 314, specific processing is performed by the processor 46. The storage 50 stores a specific program 60. The processor 46 reads the specific program 60 from the storage 50 and executes the read specific program 60 on the RAM 48. The specific processing is realized by the processor 46 acting as a control unit 46A according to the specific program 60 executed on the RAM 48. The headset terminal 314 also has a data generation model 58 and an emotion identification model 59, similar to the data generation model and emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0150] Furthermore, other devices besides the data processing device 12 may also have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 obtains processing results (such as prediction results) using the data generation model 58 by communicating with the server device that has the data generation model 58. Also, the data processing device 12 may be a server device or a terminal device owned by the user (for example, a mobile phone, robot, home appliance, etc.).

[0151] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0152] The data generation model 58 is a so-called generative AI. An example of a data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and inference data such as audio data representing speech, text data representing text, and image data representing images (e.g., still image data or video data). The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference result in one or more data formats such as audio data, text data, and image data. The data generation model 58 includes, for example, text generation AI, image generation AI, and multimodal generation AI. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specific processing unit 290 performs the specific processing described above using the data generation model 58. The data generation model 58 may be a fine-tuned model that outputs inference results from prompts that do not contain instructions, in which case the data generation model 58 can output inference results from prompts that do not contain instructions. In the data processing device 12, etc., there are multiple types of data generation models 58, and the data generation model 58 includes AI other than generative AI. AI other than generative AI includes, for example, linear regression, logistic regression, decision trees, random forests, support vector machines (SVM), k-means clustering, convolutional neural networks (CNN), recurrent neural networks (RNN), generative adversarial networks (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. Also, the AI ​​may be an AI agent. Furthermore, when the processing of each part described above is performed by the AI, the processing may be performed by the AI ​​in part or in whole, but is not limited to this example. Also, processing performed by an AI including a generative AI may be replaced by rule-based processing, and rule-based processing may be replaced by processing performed by an AI including a generative AI.

[0153] The data processing system 310 according to the third embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 310 is performed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the headset terminal 314, but may also be performed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the headset terminal 314. In addition, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the headset terminal 314 or an external device, and the headset terminal 314 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0154] Each of the multiple elements described above, including the reception unit, guidance unit, input unit, notification unit, inquiry unit, and visualization unit, is implemented by, for example, at least one of the headset terminal 314 and the data processing unit 12. For example, the reception unit is implemented by the control unit 46A of the headset terminal 314 and provides an interface for the user to input information to start a procedure. The guidance unit is implemented by, for example, the specific processing unit 290 of the data processing unit 12 and proposes an optimal procedure flow according to the user's situation. The input unit is implemented by, for example, the control unit 46A of the headset terminal 314 and automatically inputs various application documents based on the information entered by the user. The notification unit is implemented by, for example, the specific processing unit 290 of the data processing unit 12 and notifies the user of the progress of the procedure in real time. The inquiry unit is implemented by, for example, the control unit 46A of the headset terminal 314 and automatically responds to user inquiries using a chatbot. The visualization unit is implemented by, for example, the specific processing unit 290 of the data processing unit 12 and visually displays the progress of the procedure using graphs and progress bars. The correspondence between each part and the device or control unit is not limited to the examples described above, and various modifications are possible.

[0155] [Fourth Embodiment] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0156] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0157] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN and / or LAN.

[0158] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0159] The microphone 238 receives voice signals from the user and accepts instructions from the user. The microphone 238 captures the voice signals from the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0160] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS image sensor or CCD image sensor, which captures images of the area around the user (for example, an imaging range defined by a field of view equivalent to the field of vision of a typical healthy person).

[0161] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0162] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. The robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0163] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0164] The processor 28 reads a specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 acting as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0165] Storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotions using the emotion identification model 59 and perform identification processing using the user's emotions. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotions, including but not limited to these examples. Furthermore, emotion estimation and prediction also include, for example, emotion analysis.

[0166] In robot 414, specific processing is performed by processor 46. A specific program 60 is stored in storage 50. Processor 46 reads the specific program 60 from storage 50 and executes it on RAM 48. The specific processing is achieved by processor 46 acting as a control unit 46A according to the specific program 60 executed on RAM 48. Robot 414 also has data generation model 58 and emotion identification model 59, similar to those of the robot, and can perform processing similar to that of the specific processing unit 290 using these models.

[0167] Furthermore, other devices besides the data processing device 12 may also have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 obtains processing results (such as prediction results) using the data generation model 58 by communicating with the server device that has the data generation model 58. Also, the data processing device 12 may be a server device or a terminal device owned by the user (for example, a mobile phone, robot, home appliance, etc.).

[0168] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0169] The data generation model 58 is a so-called generative AI. An example of a data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and inference data such as audio data representing speech, text data representing text, and image data representing images (e.g., still image data or video data). The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference result in one or more data formats such as audio data, text data, and image data. The data generation model 58 includes, for example, text generation AI, image generation AI, and multimodal generation AI. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specific processing unit 290 performs the specific processing described above using the data generation model 58. The data generation model 58 may be a fine-tuned model that outputs inference results from prompts that do not contain instructions, in which case the data generation model 58 can output inference results from prompts that do not contain instructions. In the data processing device 12, etc., there are multiple types of data generation models 58, and the data generation model 58 includes AI other than generative AI. AI other than generative AI includes, for example, linear regression, logistic regression, decision trees, random forests, support vector machines (SVM), k-means clustering, convolutional neural networks (CNN), recurrent neural networks (RNN), generative adversarial networks (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. Also, the AI ​​may be an AI agent. Furthermore, when the processing of each part described above is performed by the AI, the processing may be performed by the AI ​​in part or in whole, but is not limited to this example. Also, processing performed by an AI including a generative AI may be replaced by rule-based processing, and rule-based processing may be replaced by processing performed by an AI including a generative AI.

[0170] The data processing system 410 according to the fourth embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 410 is performed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the robot 414, but it may also be performed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the robot 414. In addition, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the robot 414 or an external device, and the robot 414 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0171] Each of the multiple elements described above, including the reception unit, guidance unit, input unit, notification unit, inquiry unit, and visualization unit, is implemented by, for example, at least one of the robot 414 and the data processing unit 12. For example, the reception unit is implemented by the control unit 46A of the robot 414 and provides an interface for the user to input information to start a procedure. The guidance unit is implemented by, for example, the specific processing unit 290 of the data processing unit 12 and proposes an optimal procedure flow according to the user's situation. The input unit is implemented by, for example, the control unit 46A of the robot 414 and automatically inputs various application documents based on the information entered by the user. The notification unit is implemented by, for example, the specific processing unit 290 of the data processing unit 12 and notifies the user of the progress of the procedure in real time. The inquiry unit is implemented by, for example, the control unit 46A of the robot 414 and automatically responds to user inquiries using a chatbot. The visualization unit is implemented by, for example, the specific processing unit 290 of the data processing unit 12 and visually displays the progress of the procedure using graphs and progress bars. The correspondence between each part and the device or control unit is not limited to the examples described above, and various modifications are possible.

[0172] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0173] Figure 9 shows the emotion map 400, in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0174] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0175] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0176] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, and motorcycles, emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated based, for example, on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0177] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0178] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0179] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing method for the specific process may be used, which includes computer 22 and multiple other computers.

[0180] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0181] 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.

[0182] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0183] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0184] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0185] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0186] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0187] Furthermore, although the above-described examples were divided into four embodiments, some or all of these embodiments may be combined. Also, the smart device 14, smart glasses 214, headset terminal 314, and robot 414 are just examples, and they may be combined, or other devices may be used. Also, although the above-described examples were divided into two embodiments, Embodiment 1 and Embodiment 2, these may be combined.

[0188] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and other things that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0189] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0190] (Note 1) The reception area where you enter the information to start the procedure, A guidance unit that automatically guides the procedure flow based on the information entered by the reception unit, An input unit that automatically inputs documents based on the procedures guided by the aforementioned guidance unit, A notification unit that notifies the progress of the document entered by the input unit, Equipped with A system characterized by the following features. (Note 2) It includes a customer support department to handle inquiries from users. The system described in Appendix 1, characterized by the features described herein. (Note 3) It includes a visualization unit that visualizes the progress of the procedure. The system described in Appendix 1, characterized by the features described herein. (Note 4) The aforementioned guide section is We propose the optimal procedure flow tailored to the user's situation. The system described in Appendix 1, characterized by the features described herein. (Note 5) The aforementioned input unit is The system automatically fills in various application forms based on the information entered by the user. The system described in Appendix 1, characterized by the features described herein. (Note 6) The aforementioned notification unit, Notify the progress of the procedure in real time. The system described in Appendix 1, characterized by the features described herein. (Note 7) The aforementioned reception unit is The system estimates the user's emotions and adjusts the timing of the procedure's initiation based on those emotions. The system described in Appendix 1, characterized by the features described herein. (Note 8) The aforementioned reception unit is Analyze the user's past transaction history and select the optimal application method. The system described in Appendix 1, characterized by the features described herein. (Note 9) The aforementioned reception unit is At the start of the process, filtering is performed based on the user's current situation and areas of interest. The system described in Appendix 1, characterized by the features described herein. (Note 10) The aforementioned reception unit is The system estimates the user's emotions and determines the priority of the procedures to be processed based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 11) The aforementioned reception unit is At the start of a procedure, the system prioritizes processing procedures that are highly relevant to the user, taking into account their geographical location. The system described in Appendix 1, characterized by the features described herein. (Note 12) The aforementioned reception unit is At the start of the process, the system analyzes the user's social media activity and accepts relevant applications. The system described in Appendix 1, characterized by the features described herein. (Note 13) The aforementioned guide section is The system estimates the user's emotions and adjusts the way guidance is presented based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 14) The aforementioned guide section is When providing guidance, we adjust the level of detail based on the importance of the procedure. The system described in Appendix 1, characterized by the features described herein. (Note 15) The aforementioned guide section is When providing guidance, different guidance algorithms are applied depending on the category of the procedure. The system described in Appendix 1, characterized by the features described herein. (Note 16) The aforementioned guide section is It estimates the user's emotions and adjusts the length of the guidance based on the estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 17) The aforementioned guide section is When providing instructions, we will determine the priority of the instructions based on when the procedures were submitted. The system described in Appendix 1, characterized by the features described herein. (Note 18) The aforementioned guide section is When providing instructions, we will adjust the order of instructions based on the relevance of the procedures. The system described in Appendix 1, characterized by the features described herein. (Note 19) The aforementioned input unit is It estimates the user's emotions and adjusts the input method based on the estimated user emotions. The system described in Appendix 1, characterized by the features described herein. (Note 20) The aforementioned input unit is During input, the system analyzes the user's past input history to select the optimal input method. The system described in Appendix 1, characterized by the features described herein. (Note 21) The aforementioned input unit is When inputting data, the input method is customized based on the user's current situation. The system described in Appendix 1, characterized by the features described herein. (Note 22) The aforementioned input unit is It estimates the user's emotions and determines the priority of inputs based on the estimated user emotions. The system described in Appendix 1, characterized by the features described herein. (Note 23) The aforementioned input unit is When inputting data, the system selects the optimal input method by considering the user's geographical location. The system described in Appendix 1, characterized by the features described herein. (Note 24) The aforementioned input unit is During input, the system analyzes the user's social media activity and suggests input methods. The system described in Appendix 1, characterized by the features described herein. (Note 25) The aforementioned notification unit, It estimates the user's emotions and adjusts the notification method based on the estimated user emotions. The system described in Appendix 1, characterized by the features described herein. (Note 26) The aforementioned notification unit, When sending a notification, the system will refer to the user's past notification history to select the most suitable notification method. The system described in Appendix 1, characterized by the features described herein. (Note 27) The aforementioned notification unit, It estimates the user's emotions and prioritizes notifications based on those emotions. The system described in Appendix 1, characterized by the features described herein. (Note 28) The aforementioned notification unit, When sending notifications, the system selects the most suitable notification method, taking into account the user's device information. The system described in Appendix 1, characterized by the features described herein. (Note 29) The aforementioned inquiry section is, The system estimates the user's emotions and adjusts the response method to inquiries based on those estimated emotions. The system described in Appendix 2, characterized by the features described herein. (Note 30) The aforementioned inquiry section is, When responding to inquiries, the system selects the most appropriate response method by referring to the user's past inquiry history. The system described in Appendix 2, characterized by the features described herein. (Note 31) The aforementioned inquiry section is, It estimates the user's emotions and prioritizes inquiries based on those estimated emotions. The system described in Appendix 2, characterized by the features described herein. (Note 32) The aforementioned inquiry section is, When responding to inquiries, the optimal response method is selected by considering the user's device information. The system described in Appendix 2, characterized by the features described herein. (Note 33) The aforementioned visualization unit, It estimates the user's emotions and adjusts the visualization method based on the estimated user emotions. The system described in Appendix 3, characterized by the features described herein. (Note 34) The aforementioned visualization unit, During visualization, the system selects the optimal visualization method by referring to the user's past operation history. The system described in Appendix 3, characterized by the features described herein. (Note 35) The aforementioned visualization unit, It estimates the user's emotions and determines the visualization priority based on the estimated user emotions. The system described in Appendix 3, characterized by the features described herein. (Note 36) The aforementioned visualization unit, When visualizing data, the optimal visualization method is selected, taking into account the user's device information. The system described in Appendix 3, characterized by the features described herein. [Explanation of symbols]

[0191] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots

Claims

1. The reception area where you enter the information to start the procedure, A guidance unit that automatically guides the procedure flow based on the information entered by the reception unit, An input unit that automatically inputs documents based on the procedures guided by the aforementioned guidance unit, A notification unit that notifies the progress of the document entered by the input unit, Equipped with A system characterized by the following features.

2. It includes a customer support department to handle inquiries from users. The system according to feature 1.

3. It includes a visualization unit that visualizes the progress of the procedure. The system according to feature 1.

4. The aforementioned guide section is We propose the optimal procedure flow tailored to the user's situation. The system according to feature 1.

5. The aforementioned input unit is The system automatically fills in various application forms based on the information entered by the user. The system according to feature 1.

6. The aforementioned notification unit, Notify the progress of the procedure in real time. The system according to feature 1.

7. The aforementioned reception unit is The system estimates the user's emotions and adjusts the timing of the procedure's initiation based on those emotions. The system according to feature 1.

8. The aforementioned reception unit is Analyze the user's past transaction history and select the optimal application method. The system according to feature 1.

9. The aforementioned reception unit is At the start of the process, filtering is performed based on the user's current situation and areas of interest. The system according to feature 1.

10. The aforementioned reception unit is The system estimates the user's emotions and determines the priority of the procedures to be processed based on those estimated emotions. The system according to feature 1.

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