system

Abstract

We provide a system that enables the handover process to proceed quickly and smoothly. [Solution] A system comprising: means for the user to input information about a task; means for the terminal to send the user's input information to a server; means for the server to perform user authentication; means for the server to retrieve and list tasks to be handed over from a database; means for the terminal to display the task list retrieved from the server to the user; means for the user to request advice while processing a task; means for the server to generate appropriate advice regarding the task being processed and send it to the terminal; means for the terminal to display the advice retrieved from the server to the user; means for the user to input feedback after completing a task; and means for the server to save and analyze the feedback in a database.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor and includes steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of 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] [[ID=​​​​​​The present invention is a system that includes means for a user to input information about a task, means for a terminal to transmit the user's input information to a server, means for the server to perform user authentication, means for the server to retrieve and list tasks to be handed over from a database, means for the terminal to display the task list retrieved from the server to the user, means for the user to request advice while processing a task, means for the server to generate appropriate advice regarding the task being processed and send it to the terminal, means for the terminal to display the advice retrieved from the server to the user, means for the user to input feedback after completing a task, and means for the server to save and analyze the feedback in a database, thereby enabling a quick and smooth handover process. In particular, by including means for the server to search for relevant documents and past solutions and generate optimal advice, it is possible to provide quick and appropriate advice when the person in charge is unsure how to handle the task. Furthermore, by providing means for the server to improve the quality of advice based on the analysis results, it becomes possible to effectively improve the entire system.

[0006] "User" refers to individual users who operate the system to manage and hand over tasks.

[0007] "Terminal" refers to a device operated by a user, such as a computer, smartphone, or tablet.

[0008] A "server" refers to a computer system that provides central functions such as user authentication, task management, and advice generation.

[0009] A "task" refers to a specific unit of work or task that a user is responsible for.

[0010] "User authentication" refers to the process of verifying a user's identity using their user ID and password when they access a system.

[0011] A "database" refers to a structured data storage system used by a server to store and manage task information, user information, feedback, and other data.

[0012] A "task list" refers to a list of tasks to be handed over, which is organized by the server and sent to the terminal.

[0013] "Advice" refers to appropriate instructions or solutions provided by the server when a user encounters difficulties while processing a task.

[0014] "Feedback" refers to the evaluations and opinions that users provide to the system after completing a task.

[0015] "Related documents" refers to information sources that the server searches for and uses to generate advice, such as past solutions and reference materials.

[0016] "Analysis" refers to the process of evaluating the feedback and data collected by the server and using it to improve the system and enhance the quality of advice. [Brief explanation of the drawing]

[0017] [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]It is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] It shows an emotion map to which a plurality of emotions are mapped. [Figure 10] It shows an emotion map to which a plurality of emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Example 2 when the emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when the emotion engine is combined.

Mode for Carrying Out the Invention

[0018] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0019] First, the terms used in the following description will be explained.

[0020] In the following embodiments, a processor with a reference numeral (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of a plurality of arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of a plurality of types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0021] 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.

[0022] 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.

[0023] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0024] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0025] [First Embodiment]

[0026] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0027] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0028] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0029] 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.

[0030] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0031] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0032] 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.

[0033] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0034] 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.

[0035] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0036] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0037] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0038] This section will describe specific embodiments for implementing this invention. First, we will begin by understanding the overall flow of this system and the role of each element.

[0039] System Overview

[0040] This system allows users to input information about tasks, and the terminal and server work together to manage the tasks being handed over. It also provides appropriate advice when users are unsure how to proceed. Furthermore, users provide feedback after completing tasks, and the server analyzes this feedback to improve the system.

[0041] A natural language explanation of the program's processing.

[0042] The user logs into the device and starts the transfer mode.

[0043] The user launches a dedicated transfer application on their device and enters their login information (user ID and password). The device sends the entered login information to the server. The server receives this information, compares it with the database, and authenticates the user. Once authenticated, the server generates an authentication token and sends it to the device. The device saves the authentication token and displays the transfer mode screen.

[0044] The server lists the tasks to be handed over.

[0045] When a user enters handover mode, the device requests a list of tasks to be handed over from the server. This request also includes an authentication token. The server retrieves the tasks to be handed over from the database, organizes them by category, and sets their priorities. It then sends the organized task list to the device. The device displays the received task list to the user, allowing the user to select the tasks they wish to handle.

[0046] If a user is unsure how to proceed with a task, they can request advice.

[0047] If a user gets stuck while working on a task, they click the "Request Advice" button. The device sends the current task information and authentication token to the server. The server analyzes the submitted task information and searches for relevant documentation and past solutions. Based on the search results, the server generates appropriate advice and sends it to the device. The device then displays the received advice to the user.

[0048] Users progress through tasks and provide feedback.

[0049] The user follows the advice and completes the task. After task completion, the device displays a feedback input screen. The user provides feedback on the effectiveness of the advice and any problems encountered during task processing. The device sends the entered feedback to the server.

[0050] The server analyzes the feedback and uses it to improve the system.

[0051] The server stores the received feedback in a database. It then analyzes the stored feedback to consider ways to improve the quality of the advice. This enables effective improvements to the entire system.

[0052] Specific example

[0053] Specific examples are given below.

[0054] When User A takes over the task "Create Monthly Report"

[0055] User A launches the transfer application and clicks "Start Transfer".

[0056] The server lists past tasks and solutions related to the creation of the monthly report and sends them to the terminal.

[0057] When User A is having trouble with the report format, they click the "Request Advice" button.

[0058] The server suggests the optimal format based on past formatting examples and sends it to the terminal.

[0059] User A creates a report using the proposed format and completes the task.

[0060] After completion, User A enters feedback on whether the advice was effective and sends it to the server.

[0061] The server uses this feedback to analyze and improve the quality of future advice.

[0062] In this way, this system enables efficient handover processes when personnel changes occur, allowing for the smooth progress of operations.

[0063] The following describes the processing flow.

[0064] Step 1:

[0065] The user launches a dedicated transfer application on their device. The device displays the initial screen.

[0066] Step 2:

[0067] The user enters their user ID and password. The terminal sends this information to the server.

[0068] Step 3:

[0069] The server authenticates the user by comparing the received user ID and password with the database. If authentication is successful, the server generates an authentication token and sends it to the terminal. If authentication fails, the server sends an error message to the terminal.

[0070] Step 4:

[0071] The device saves the authentication token and displays the transfer mode screen to the user. The user clicks the "Start Transfer" button.

[0072] Step 5:

[0073] The device sends a request to the server for the task list to be handed over. This request includes an authentication token.

[0074] Step 6:

[0075] The server retrieves the tasks to be handed over from the database, organizes them by category, and sets their priorities. It then sends the organized task list to the terminal.

[0076] Step 7:

[0077] The terminal displays a list of received tasks to the user. The user selects a task to process from the displayed list.

[0078] Step 8:

[0079] If a user gets lost while processing a task, they can click the "Request Advice" button. The device will then send the current task information and authentication token to the server.

[0080] Step 9:

[0081] The server analyzes the received task information and searches the database for relevant documents and past solutions.

[0082] Step 10:

[0083] The server generates optimal advice based on the search results and sends it to the terminal.

[0084] Step 11:

[0085] The device displays the advice it receives to the user. The user then proceeds with the task while referring to the displayed advice.

[0086] Step 12:

[0087] Once the user completes a task, the device displays a feedback input screen. The user provides feedback on the effectiveness of the advice and any problems encountered during task completion.

[0088] Step 13:

[0089] The terminal sends the input feedback to the server. The server stores the received feedback in a database.

[0090] Step 14:

[0091] The server analyzes the stored feedback and considers ways to improve the quality of the advice.

[0092] In this way, the entire system flows smoothly, allowing users to efficiently take over tasks and quickly receive necessary advice.

[0093] (Example 1)

[0094] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0095] Traditional work handover systems often made it difficult to resolve problems during the process, resulting in decreased work efficiency. Furthermore, feedback was not properly utilized, hindering system improvements.

[0096] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0097] In this invention, the server includes means for user authentication, means for retrieving and listing the tasks to be handed over from a database, and means for searching for relevant documents and past solutions and generating optimal advice. This enables smooth problem-solving during the task process and allows for continuous improvement of the system based on feedback.

[0098] A "user" refers to an individual or group that uses a system to input business information and perform tasks.

[0099] "Business operations" refers to tasks managed within a system and the series of activities related to their processing.

[0100] "Data" refers to various types of information that users input into the system, as well as information that the system generates or acquires based on that information.

[0101] A "terminal" refers to a hardware device, such as a computer or mobile device, operated by a user, and is a device that communicates with a system.

[0102] A "server" refers to a central processing unit that performs various tasks such as user authentication, database management, task list generation, and advice generation.

[0103] A "database" refers to a system for systematically storing data such as business information, user information, past solutions, and feedback.

[0104] "Advice" refers to the knowledge and guidance that users need to carry out their tasks, as well as the solutions and recommendations generated by the system.

[0105] "Authentication" refers to the process by which a system verifies the identity of a user, and is a means of confirming that the user is legitimate.

[0106] "Feedback" refers to the opinions and evaluations that users enter into the system after completing a task.

[0107] "Searching" refers to the process by which a server finds relevant documents or past solutions.

[0108] "Analysis" refers to the process by which a server processes received feedback and task information to derive useful insights and areas for improvement.

[0109] "Listing" refers to the process by which a server organizes and displays business information retrieved from a database.

[0110] The specific embodiments of this invention will be described in detail below. First, we will begin by understanding the overall flow of this system and the role of each element.

[0111] System Overview

[0112] This system allows users to input data related to their work, and the terminal and server work together to manage the tasks being handed over. It also provides appropriate advice when problems arise during the process. Furthermore, users input feedback after completing tasks, and the server analyzes this feedback to improve the system. The main components of the system are described below.

[0113] The user logs into the device and starts the transfer mode.

[0114] The user launches a dedicated transfer application (TaskTransferApp) on their device and enters their login information (user ID and password). The device sends the entered login information to the server as an HTTP POST request. The server verifies the information against the database (MySQL®) and performs user authentication. If authentication is successful, the server generates a JSON Web Token (JWT) and sends it back to the device. The device saves the received authentication token and displays the transfer mode screen.

[0115] The server lists the tasks to be handed over.

[0116] When the device enters handover mode, it sends an authentication token to the server and requests the task list to be handed over. The server retrieves the user's relevant work information from the database, organizes the task list by category, and sorts it by priority. It sends the organized task list to the device, which then displays the task list to the user.

[0117] If a user is unsure how to proceed with their work, they can request advice.

[0118] If a user encounters difficulties while working, they click the "Request Advice" button. The terminal sends current work information and an authentication token to the server. The server analyzes the information received and searches for relevant documents and past solutions. Using a search engine (ElasticSearch®), it generates the best advice and sends it to the terminal. The terminal displays the received advice to the user.

[0119] Users carry out tasks and provide feedback.

[0120] Once the user completes the task following the advice from the server, the terminal displays a feedback input screen. The user enters and submits feedback regarding the effectiveness of the advice and any problems encountered during the task. The terminal then sends the entered feedback to the server.

[0121] The server analyzes the feedback and uses it to improve the system.

[0122] The server receives feedback and stores it in a database. The stored feedback is analyzed periodically, and the data is analyzed using a machine learning model (Scikit-learn). Based on the analysis results, system improvements are considered, and software updates or new features are added as needed.

[0123] Specific example

[0124] Specific examples are given below.

[0125] If User A takes over the creation of the monthly report

[0126] User A launches the transfer application and clicks "Start Transfer".

[0127] The server lists past tasks and solutions related to the creation of monthly reports and sends them to the terminal.

[0128] When User A is having trouble with the report format, they click the "Request Advice" button.

[0129] The server suggests the optimal format and sends it to the terminal.

[0130] User A creates a report using the proposed format and completes the task.

[0131] After completion, User A enters feedback and sends it to the server.

[0132] The server analyzes the feedback to improve the quality of future advice.

[0133] Example of a prompt

[0134] The following are examples of prompts to input into the generative AI model.

[0135] "What is the best format for creating monthly reports?"

[0136] "What should I do when I encounter difficulties in completing a task?"

[0137] By using this prompt, you can receive appropriate advice from the AI ​​model.

[0138] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0139] Step 1:

[0140] The user launches a dedicated transfer application on their device. The user enters their user ID and password on the login screen. The device sends the entered user ID and password to the server as an HTTP POST request. The server compares the received login information with its database and authenticates the user. The input is the user ID and password, and the output is whether the authentication was successful or unsuccessful and a JWT authentication token. If authentication is successful, the server generates an authentication token and sends it back to the device. The device saves the authentication token and displays the transfer mode screen.

[0141] Step 2:

[0142] The user clicks a button to enter handover mode. The terminal issues an authentication token and requests the server for a list of tasks to be handed over. The server retrieves the user's relevant business information from the database. The input is the authentication token and task request, and the output is the user's relevant business information. The server organizes the retrieved information by category and sorts it by priority. The organized task list is sent to the terminal, which then displays the task list to the user.

[0143] Step 3:

[0144] If a user encounters difficulties while working, they click the "Request Advice" button. The terminal sends current work information and an authentication token to the server. The server analyzes the received work information and searches for relevant documents and past solutions. The input is work information and an authentication token, and the output is appropriate advice. The server uses a search engine to search the data, generates the best advice, and sends it to the terminal. The terminal displays the received advice to the user.

[0145] Step 4:

[0146] The user proceeds with the task according to the advice from the server and completes the task. After task completion, the terminal displays a feedback input screen. The user enters feedback on the effectiveness of the advice and any problems encountered during the task, and clicks the submit button. The input is feedback on the effectiveness of the advice and any problems encountered, and the output is feedback data. The terminal sends the entered feedback to the server.

[0147] Step 5:

[0148] The server stores the received feedback in a database. The input is the feedback data, and the output is the collection of stored feedback data. The server periodically analyzes the stored feedback. It uses machine learning models to analyze the data and considers ways to improve the system based on the analysis results. It updates the software and adds new features as needed to improve the overall system performance.

[0149] (Application Example 1)

[0150] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0151] Staff shift changes and handovers at logistics centers are time-consuming and prone to errors and omissions. Furthermore, existing systems lack the means to obtain quick and appropriate advice when problems arise during task execution, leading to decreased operational efficiency. Additionally, there is no mechanism in place to incorporate feedback after task completion into system improvements. To address these challenges, a more efficient and reliable task management system is needed.

[0152] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0153] In this invention, the server includes means for staff at a logistics center to manage handover tasks using smartphones and request advice and procedures; means for displaying a task list obtained from the server via an application installed on the smartphone, allowing staff to request advice during sorting work; means for the server to generate optimal advice using a recommendation algorithm based on past relevant documents and solutions; and means for the server to perform analysis to improve the entire system based on feedback entered by staff after task completion. This enables more efficient task handover at the logistics center, quicker response to problems, and system improvements based on feedback.

[0154] "User authentication" is the process by which a system verifies the user's identity and grants them access rights.

[0155] A "terminal" is a device that a user operates and uses to exchange input and display information.

[0156] A "server" is a computer system that processes and stores data on a network and provides information to other terminals.

[0157] A "task list" is a list of tasks related to a specific job.

[0158] An "advice request" is an operation in which a user asks the server for advice when they get stuck while processing a task.

[0159] A "recommendation algorithm" is a computational method used by a system to generate optimal advice based on historical data and relevant documents.

[0160] "Feedback" refers to the opinions and impressions that users provide after completing a task.

[0161] A "logistics center" is a facility that handles logistics operations such as storing, sorting, and shipping goods and materials.

[0162] A "smartphone" is a portable information terminal that combines the functions of a mobile phone and a computer, and is capable of running applications.

[0163] "Handover tasks" refer to the new responsibilities that need to be taken on due to shift changes or changes in personnel.

[0164] A "document" is an official document or record related to a specific job or task.

[0165] "System improvement" refers to activities aimed at improving overall functionality and performance by analyzing collected feedback and data.

[0166] Specific embodiments for carrying out this invention will now be described. First, this system is intended for task management and advice provision in a logistics center. The entire system consists of a smartphone, a server, and a network.

[0167] System Overview

[0168] This system uses the following methods to perform each step:

[0169] 1. User input information

[0170] Users enter task-related information using a dedicated application installed on their smartphones.

[0171] 2. Data transmission from terminal to server

[0172] A smartphone (device) sends information entered by the user to a server. This transmission uses a network.

[0173] 3. User authentication on the server

[0174] The server performs user authentication based on the user's authentication information (user ID and password). If authentication is successful, an authentication token is returned to the smartphone.

[0175] 4. Retrieving and displaying the task list

[0176] After authentication, the server retrieves the tasks to be handed over from the database and displays them as a list on the smartphone.

[0177] 5. Requesting and providing advice

[0178] If a user gets stuck while working on a task, they can click the "Request Advice" button on their smartphone. The server searches relevant documents and past solutions, and uses a generative AI model to provide the best advice. This advice is then displayed on the smartphone.

[0179] 6. Providing feedback after task completion

[0180] After completing a task, users input feedback on the effectiveness of the advice and any problems encountered during task processing via their smartphones and send it to the server.

[0181] 7. Analysis of feedback and system improvement

[0182] The server analyzes the information in the database based on the collected feedback and works to improve the entire system.

[0183] Hardware and software

[0184] hardware

[0185] Smartphone (user device)

[0186] Server (data processing and storage)

[0187] Network infrastructure (data communication)

[0188] software

[0189] A dedicated application installed on a smartphone

[0190] Server-side authentication system

[0191] Server-side database management system

[0192] Recommended algorithms (including generative AI models)

[0193] Specific example

[0194] Specific examples are given below.

[0195] 1. Handover of sorting duties

[0196] Example of a prompt:

[0197] This scenario involves a user taking over sorting tasks. Please outline the steps for obtaining the task list and starting a new task. Include procedures for requesting advice and providing feedback if difficulties arise during task completion.

[0198] The user logs in using the smartphone app and retrieves the task list.

[0199] Based on the task list, select and begin today's sorting tasks.

[0200] If you get stuck during the sorting process, click the "Request Advice" button to receive appropriate advice from the server.

[0201] Once the sorting process is complete, enter feedback into the app and submit it.

[0202] This system streamlines task handover in logistics centers, enables rapid response to problems, and improves the system based on feedback.

[0203] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0204] Step 1:

[0205] The user launches a dedicated application installed on their smartphone and enters their login information (user ID and password). The device sends this information to the server. The input data consists of the user ID and password, and the output is a request for authentication processing on the server. Specifically, the device receives the user ID and password on the login screen, encrypts them, and sends them to the server.

[0206] Step 2:

[0207] The server performs user authentication. The server compares the received login information with the information in the database to authenticate the user. The input data is the user ID and password, which are compared with the user information retrieved from the database. The output is the generation of an authentication token. Specifically, the server retrieves the user ID and hashed password from the database and compares them with the received information. If authentication is successful, the server generates an authentication token and sends it to the terminal.

[0208] Step 3:

[0209] When a user enters handover mode, the device requests the task list from the server. The input data is an authentication token, and the output is a request for the task list to be handed over. Specifically, the device sends an authentication token to the server and then requests the task list.

[0210] Step 4:

[0211] The server retrieves tasks to be handed over from the database, organizes them by category, and sets their priorities. The input data is an authentication token and user ID, and the output is a task list organized by category. Specifically, the server retrieves relevant task information from the database, classifies it into categories to facilitate handover, and sets its priorities.

[0212] Step 5:

[0213] The terminal displays a task list retrieved from the server to the user. The input data is a task list organized by category, and the output is a task list screen that the user can view. Specifically, the terminal displays the task list retrieved from the server on the screen, allowing the user to review it.

[0214] Step 6:

[0215] If a user gets lost while processing a task, they click the "Request Advice" button. The device then sends the current task information and authentication token to the server. The input data is the current task information and authentication token, and the output is an advice request to the server. Specifically, the user clicks the "Request Advice" button on the screen, which triggers the device to send the task information and authentication token to the server.

[0216] Step 7:

[0217] The server analyzes the submitted task information and searches for relevant documents and past solutions. The input data consists of task information and an authentication token, and the output consists of relevant documents and past solutions. Specifically, the server searches for relevant documents in the database based on the task information and analyzes past solutions using a generative AI model.

[0218] Step 8:

[0219] The server generates optimal advice and sends it to the terminal. The input data consists of relevant documents and past solutions, and the output is the optimal advice. Specifically, the server uses a generation AI model to generate optimal advice and sends it to the terminal.

[0220] Step 9:

[0221] The device displays the advice it receives to the user. The input data is the optimal advice, and the output is an advice screen that the user can view. Specifically, the device displays the advice it receives from the server on the screen, allowing the user to review it.

[0222] Step 10:

[0223] The user enters feedback after completing a task. The device sends the entered feedback to the server. The input data is the feedback content, and the output is the feedback submission request to the server. Specifically, the user enters feedback on the feedback input screen and clicks the submit button.

[0224] Step 11:

[0225] The server stores the feedback in a database and analyzes it. The input data is the feedback content, and the output is the feedback analysis results. Specifically, the server stores the feedback in a database and analyzes that data to use for future system improvements.

[0226] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0227] This invention will now describe a specific embodiment for carrying it out. This system allows the user to input information about a task, and the terminal and server work together to manage the task being handed over, providing appropriate advice when the user is unsure how to proceed. Furthermore, by incorporating an emotion engine that recognizes the user's emotions, it is possible to provide even more appropriate advice. After the user completes a task, they provide feedback, which the server analyzes to improve the system.

[0228] System Overview

[0229] This system consists of the following elements:

[0230] 1. Means by which users can input information about a task.

[0231] 2. Means by which the terminal transmits user input information to the server

[0232] 3. Means by which the server performs user authentication

[0233] 4. A method by which the server retrieves and lists the tasks to be handed over from the database.

[0234] 5. Means for displaying the task list obtained from the server by the terminal to the user.

[0235] 6. Means by which users can request advice while processing a task.

[0236] 7. Means for the server to generate and send appropriate advice regarding the task it is currently processing to the terminal.

[0237] 8. Means for displaying advice obtained from the server by the terminal to the user.

[0238] 9. A means for users to provide feedback after completing a task.

[0239] 10. Means for the server to store and analyze feedback in a database.

[0240] 11. Emotion engine that recognizes user emotions

[0241] 12. A means of generating more appropriate advice based on user emotion data received from the emotion engine.

[0242] A natural language explanation of the program's processing.

[0243] The user logs into the device and starts the transfer mode.

[0244] The user launches a dedicated transfer application on their device and enters their login information (user ID and password). The device sends the entered login information to the server, which receives it, compares it with the database, and authenticates the user. Once authenticated, the server generates an authentication token and sends it to the device. The device saves the authentication token and displays the transfer mode screen.

[0245] The server lists the tasks to be handed over.

[0246] When a user enters handover mode, the device sends a request to the server for a list of tasks to be handed over. The server retrieves the tasks to be handed over from the database, organizes them by category, sets priorities, and sends the task list to the device. The device displays the received task list to the user. The user selects a task to process from the displayed list.

[0247] If a user is unsure how to proceed with a task, they can request advice.

[0248] If a user gets stuck while working on a task, they click the "Request Advice" button. The device sends the current task information and authentication token to the server. The server analyzes the submitted task information and searches for relevant documentation and past solutions. Based on the search results, the server generates the best advice and sends it to the device. The device then displays the received advice to the user.

[0249] Users progress through tasks and provide feedback using an emotion engine.

[0250] As the user progresses through the task following the advice, they input their current emotions using the emotion engine. The device sends the emotion data to the server. Based on the emotion data, the server generates more appropriate advice and sends it to the device. When the user completes the task, the device displays a feedback input screen. The user provides feedback on the effectiveness of the advice and any problems encountered during task completion. The device sends the input feedback to the server.

[0251] The server analyzes feedback and sentiment data and uses it to improve the system.

[0252] The server stores the received feedback and sentiment data in a database and performs analysis. Based on the analysis results, the server considers ways to improve the quality of advice and makes improvements to the entire system.

[0253] Specific example

[0254] Specific examples are given below.

[0255] When User A takes over the task "Create Monthly Report"

[0256] User A launches the transfer application and clicks "Start Transfer".

[0257] The server lists past tasks and solutions related to the creation of the monthly report and sends them to the terminal.

[0258] When User A is having trouble with the report format, they click the "Request Advice" button.

[0259] The server suggests the optimal format based on past formatting examples and sends it to the terminal.

[0260] When User A creates a report following the advice, they input their current emotions using the emotion engine.

[0261] The server takes user A's emotions into consideration and provides more specific advice.

[0262] User A creates a report using the proposed format and completes the task.

[0263] After completion, User A sends feedback to the server indicating whether the advice was effective, along with their own emotional data.

[0264] The server uses this feedback and sentiment data to perform analysis in order to improve the quality of future advice.

[0265] By combining this with an emotion engine, more appropriate advice that takes into account the user's psychological state can be provided, making the handover process more efficient and effective.

[0266] The following describes the processing flow.

[0267] Step 1:

[0268] The user launches a dedicated transfer application on their device. The device displays the initial screen.

[0269] Step 2:

[0270] The user enters their user ID and password. The terminal sends the entered information to the server.

[0271] Step 3:

[0272] The server authenticates the user by comparing the received user ID and password with the database. If authentication is successful, the server generates an authentication token and sends it to the terminal. If authentication fails, the server sends an error message to the terminal.

[0273] Step 4:

[0274] The terminal saves the authentication token and displays the handover mode screen to the user. The user clicks the "Start Handover" button.

[0275] Step 5:

[0276] The terminal sends a request for the task list to be handed over to the server. This request includes the authentication token.

[0277] Step 6:

[0278] The server retrieves the tasks to be handed over from the database, sorts them by category, and sets priorities. The sorted task list is sent to the terminal.

[0279] Step 7:

[0280] The terminal displays the received task list to the user. The user selects the task to be processed from the displayed list.

[0281] Step 8:

[0282] If the user gets lost during task processing, they click the "Request Advice" button. The terminal sends the current task information and the authentication token to the server.

[0283] Step 9:

[0284] The server analyzes the received task information and searches the database for relevant documents and past solutions.

[0285] Step 10:

[0286] Based on the search results, the server generates the optimal advice and sends it to the terminal.

[0287] Step 11:

[0288] The device displays the advice it receives to the user. The user then proceeds with the task while referring to the displayed advice.

[0289] Step 12:

[0290] The user inputs their current emotion using an emotion engine. The device then sends the emotion data to the server.

[0291] Step 13:

[0292] The server analyzes the emotional data, generates additional advice that takes the user's emotional state into account, and sends it to the terminal.

[0293] Step 14:

[0294] The device displays any additional advice it has received to the user. The user then uses this advice to proceed with the task.

[0295] Step 15:

[0296] Once the user completes a task, the device displays a feedback input screen. The user provides feedback on the effectiveness of the advice and any problems encountered during task completion.

[0297] Step 16:

[0298] The device sends the input feedback and sentiment data to the server. The server stores the received feedback and sentiment data in a database.

[0299] Step 17:

[0300] The server analyzes stored feedback and sentiment data to explore ways to improve the quality of advice.

[0301] Through the above processing steps, users can efficiently perform the handover and receive necessary advice quickly and appropriately. Furthermore, the introduction of an emotion engine provides more appropriate advice that takes into account the user's psychological state.

[0302] (Example 2)

[0303] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0304] Current task management systems often fail to provide users with appropriate advice when they encounter difficulties during task completion, and furthermore, they do not offer advice that takes into account the user's emotional state, making efficient task completion difficult. Another issue is that feedback after task completion is not adequately utilized for system improvement.

[0305] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0306] In this invention, the server includes means for the user to input information related to a task, means for the terminal to transmit the user's input information to the server, means for the server to perform user authentication, means for the server to obtain and list up tasks to be taken over from a database, means for the terminal to display the task list obtained from the server to the user, means for the user to request advice during task processing, means for the server to generate appropriate advice regarding the task in progress and transmit it to the terminal, means for the terminal to display the advice obtained from the server to the user, means for the user to input feedback after task completion, means for the server to store and analyze the feedback in a database, means equipped with an emotion engine to recognize the user's emotion, means to generate more appropriate advice based on the user's emotion data received from the emotion engine, means for the server to transmit the advice generated to the terminal, and means for the terminal to display the advice to the user. Thereby, the user can receive appropriate advice during task progress, appropriate support considering the emotional state becomes possible, and the feedback after task completion is effectively utilized for system improvement.

[0307] The "user" is a person who inputs task information and provides feedback using the system.

[0308] The "terminal" is a device that the user operates to transmit input information to the server and receive data from the server.

[0309] The "server" is a central computer system that performs user authentication, obtains tasks from a database, generates advice, and transmits it to the terminal.

[0310] [[ID=ID=16]]The "authentication token" is temporary data for confirming user authentication and maintaining a session.

[0311] The "database" is a system for storing and managing task information, user feedback, and emotion data.

[0312] A "task list" is a list of tasks to be handed over that the server retrieves from the database and displays to the user.

[0313] "Advice" refers to solutions or suggestions that a server provides to a user who is unsure how to proceed with a task.

[0314] An "emotion engine" is a system that recognizes emotions based on user input and analyzes that data.

[0315] "Feedback" refers to the opinions and evaluations of the processing results and the system that users provide after completing a task.

[0316] Specific embodiments for carrying out this invention will now be described. This system allows the user to input information about a task, and the terminal and server work together to take over and manage the task. In particular, it is characterized by providing appropriate advice when the user is unsure during task processing and by providing more accurate support using the user's emotional data.

[0317] System Configuration

[0318] This system consists of the following elements:

[0319] 1. Means by which users can input information about a task.

[0320] The user launches a dedicated handover application on their device and enters information about the task. This information includes the task name, details, and deadline.

[0321] 2. Means by which the terminal transmits user input information to the server

[0322] The terminal sends the entered task information and login information to the server using the HTTPS protocol.

[0323] 3. Means by which the server performs user authentication

[0324] The server compares the received user ID and password with the database to authenticate the user. If authentication is successful, it generates an authentication token and sends it to the terminal.

[0325] 4. A method by which the server retrieves and lists the tasks to be handed over from the database.

[0326] The server retrieves the tasks to be handed over from the database, lists them by category and priority, and sends them to the terminal.

[0327] 5. Means for displaying the task list obtained from the server by the terminal to the user.

[0328] The device displays the received task list on the user's screen. The user can select a task to process from the displayed list.

[0329] 6. Means by which users can request advice while processing a task.

[0330] If a user is unsure how to proceed with a task, they can click the "Request Advice" button to send their current task information to the server.

[0331] 7. Means for the server to generate and send appropriate advice regarding the task it is currently processing to the terminal.

[0332] The server analyzes task information, searches for relevant documents and past solutions, generates optimal advice using an AI model, and sends it to the terminal.

[0333] 8. Means for displaying advice obtained from the server by the terminal to the user.

[0334] The device displays the received advice on the user's screen.

[0335] 9. A means for users to provide feedback after completing a task.

[0336] After completing a task, users provide feedback on the effectiveness of the advice and any problems they encountered.

[0337] 10. Means for the server to store and analyze feedback in a database.

[0338] The server stores feedback in a database, analyzes it, and uses it to improve the system.

[0339] 11. Emotion engine that recognizes user emotions

[0340] The emotion engine receives emotional data from the user and recognizes their emotional state.

[0341] 12. A means of generating more appropriate advice based on user emotion data received from the emotion engine.

[0342] The server generates more personalized advice based on the emotional data received from the emotion engine and sends it to the device.

[0343] Specific example

[0344] Specific examples are given below.

[0345] Example 1: When User A takes over the task "Create Monthly Report"

[0346] User A launches the transfer application and clicks "Start Transfer".

[0347] The server lists past tasks and solutions related to the creation of the monthly report and sends them to the terminal.

[0348] When User A is having trouble with the report format, they click the "Request Advice" button.

[0349] The server suggests the optimal format based on past formatting examples and sends it to the terminal.

[0350] When User A creates a report following the advice, they input their current emotions using the emotion engine.

[0351] The server takes user A's emotions into consideration and provides more specific advice.

[0352] User A creates a report using the proposed format and completes the task.

[0353] After completion, User A sends feedback to the server indicating whether the advice was effective, along with their own emotional data.

[0354] The server uses this feedback and sentiment data to perform analysis in order to improve the quality of future advice.

[0355] Example of a prompt

[0356] Prompt 1: "Describe a system where a user inputs information about a task and receives the best advice. In particular, explain in detail how an emotion engine is used to improve the advice."

[0357] As described above, the present invention is a system that enables more efficient and effective task management by providing advice that takes into account the user's emotional state and by effectively utilizing feedback.

[0358] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0359] Step 1: User logs in and starts transfer mode.

[0360] Input: User ID, Password

[0361] procedure:

[0362] 1. The user launches the transfer application on their device.

[0363] 2. The user enters their user ID and password on the login screen.

[0364] 3. The terminal sends the entered login information to the server using the HTTPS protocol.

[0365] 4. The server compares the received login information with the database and performs user authentication.

[0366] 5. If authentication is successful, the server generates an authentication token and sends it to the device.

[0367] 6. The device saves the authentication token and displays the transfer mode screen.

[0368] Output: Authentication token, display of the handover mode screen

[0369] Step 2: The server lists the tasks to be handed over.

[0370] Input: Authentication token, Task list request

[0371] procedure:

[0372] 1. The user clicks the "Get Task List" button on the handover mode screen.

[0373] 2. The device sends a request to the server for a task list containing an authentication token.

[0374] 3. The server verifies the authentication token and confirms that the user has the necessary permissions.

[0375] 4. The server queries the database for the tasks to be handed over and retrieves them.

[0376] 5. Organize the tasks acquired by the server by category and set their priorities.

[0377] 6. Send the organized task list to your device.

[0378] 7. Display the task list received by the device to the user.

[0379] Output: Task list

[0380] Step 3: If the user gets lost while working on the task, they should request advice.

[0381] Input: Current task information, authentication token

[0382] procedure:

[0383] 1. If a user is unsure how to proceed with a task, they can click the "Request Advice" button.

[0384] 2. The device sends the current task information and authentication token to the server.

[0385] 3. The server analyzes the received data and searches the database for relevant documents and past solutions.

[0386] 4. The server generates optimal advice based on the search results using an AI model.

[0387] 5. The server sends the generated advice to the terminal.

[0388] 6. Display the advice received by the device to the user.

[0389] Output: Advice

[0390] Step 4: The user progresses through the task and provides feedback using the emotion engine.

[0391] Input: Sentiment data, feedback information

[0392] procedure:

[0393] 1. The user proceeds with the task following the advice.

[0394] 2. The user enters their current emotional state on the emotion engine screen.

[0395] 3. The device sends emotional data to the server.

[0396] 4. The server generates more specific advice based on emotional data. A generation AI model is used as needed.

[0397] 5. The generated advice is sent to the device, and the device displays it to the user.

[0398] 6. When the user completes the task, the device displays a feedback input screen.

[0399] 7. Users provide feedback on the effectiveness of the advice and any problems they encountered while completing the task.

[0400] 8. The device sends feedback to the server.

[0401] Output: Sentiment data, feedback

[0402] Step 5: The server analyzes feedback and sentiment data and uses it to improve the system.

[0403] Input: Feedback, sentiment data

[0404] procedure:

[0405] 1. The server saves the feedback and sentiment data received from the terminal to a database.

[0406] 2. The server queries the database and parses the received data.

[0407] 3. The server will consider ways to improve the quality of advice based on the analysis results.

[0408] 4. The server implements the improvements and updates the functionality of the entire system.

[0409] Output: System improvement proposal

[0410] The above outlines the specific processing steps of this system's program, along with details of the operation and input / output for each step.

[0411] (Application Example 2)

[0412] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0413] Traditional task management systems often fail to consider the user's emotions or psychological state, simply providing formulaic advice. This has resulted in insufficient support, especially when users are facing difficult situations or experiencing stress. Furthermore, the lack of adaptive support to improve task processing efficiency degrades the user experience of the system.

[0414] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0415] In this invention, the server includes means for acquiring and transmitting user emotion data to the server, means for generating appropriate advice based on the task being processed and the acquired emotion data and transmitting it to the terminal, and means for generating optimal advice considering the emotion data. This makes it possible to provide appropriate advice that takes into account the user's emotions and psychological state, improving the efficiency of task processing and enhancing the user experience.

[0416] A "task" is a specific task or activity that a user is required to accomplish.

[0417] User authentication is the process of verifying the identification information that a user enters to access a system, and confirming that they are a legitimate user.

[0418] "Emotional data" refers to data that represents the user's psychological state and emotions, and is acquired by an emotion recognition engine.

[0419] "Advice" refers to information and methods that users can use as a reference when carrying out a task.

[0420] "Feedback" refers to the opinions and evaluations that users provide after completing a task, regarding the effectiveness of the advice given and any problems encountered during the task.

[0421] An "emotion recognition engine" is software or algorithms that analyze a user's emotions and psychological state and generate data based on that analysis.

[0422] A "terminal" is a device that a user operates to input information or to view displayed advice.

[0423] A "database" is a system or structure used to organize and store information about tasks, users, and feedback.

[0424] "Advice generation" is the process by which a server creates instructions to provide the user with the best possible support, based on the user's task information and sentiment data.

[0425] A "server" is a central computer system that processes user input, manages tasks, and generates and provides advice.

[0426] To implement this invention, it is necessary to construct a task management system with excellent emotion recognition capabilities. This system is realized through the cooperation of a server, terminals, and users, and uses an emotion recognition engine to provide optimal advice that takes into account the user's psychological state.

[0427] System Configuration

[0428] Hardware and software

[0429] Hardware:

[0430] Device: Smartphone or head-mounted display (HMD)

[0431] Server: High-performance computer system

[0432] software:

[0433] Emotion recognition engine: Emotion recognition libraries such as Affectiva SDK

[0434] Applications: Python, Requests library, etc.

[0435] Explanation of natural language processing

[0436] User authentication and task information retrieval via the device.

[0437] The user logs into the device and sends authentication information to the server. The server generates an authentication token and sends it back to the device to authenticate the user. The server then retrieves the task to be handed over from the database and sends it to the device. The device displays this to the user, and the user selects a specific task.

[0438] Requesting and providing advice

[0439] If a user encounters difficulties while working on a task, they can request advice from their device. The server retrieves the user's emotional data and analyzes it using an emotional recognition engine. It then searches past solutions and documentation to generate the most appropriate advice, taking the emotional data into account. The generated advice is sent to the device and displayed to the user.

[0440] Use of emotional data and feedback

[0441] Users input emotional data during and after tasks and send it to the server. The server generates more appropriate advice based on the received emotional data. Additionally, users can input feedback after completing tasks, which the server stores in a database and analyzes. The analysis results are used to improve the quality of future advice generation.

[0442] Specific example

[0443] When User A performs video editing work on a new project

[0444] User A launches the task management application and logs in. The server performs authentication and retrieves and displays a list of tasks related to the project. User A selects a specific editing task. If User A encounters difficulties in choosing an effect during the editing process, they press the "Request Advice" button. The server analyzes User A's emotional data and suggests the best way to choose an effect. User A follows the suggested advice and continues editing. After completing the task, User A provides feedback on the effectiveness of the advice and sends it to the server along with their emotional data. The server analyzes this data and uses it to improve the entire system.

[0445] Example of a prompt

[0446] Example prompts for generating advice on video editing tasks:

[0447] Generate advice for when you're stuck on choosing effects while editing a new project. Your current emotion is "frustrated." Also, suggest a basic, step-by-step approach.

[0448] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0449] Step 1:

[0450] The user enters their login information (user ID and password) into the terminal and presses the submit button. The terminal sends this input information to the server. The server authenticates the user, and if the correct authentication information is provided, it generates an authentication token and sends it back to the terminal. The terminal saves this authentication token and notifies the user that the login was successful. In this step, the user ID and password are provided as input information, and an authentication token is output.

[0451] Step 2:

[0452] The terminal uses an authentication token to request a list of tasks to be handed over from the server. The server retrieves the tasks to be handed over from the database, organizes them by category, sets priorities, and sends the task list to the terminal. The terminal displays the received task list to the user, allowing the user to select which tasks to process. In this step, the authentication token and the task list request are provided as input information, and the organized task list is output.

[0453] Step 3:

[0454] When a user selects a task, detailed information about that task is displayed on the device. If the user gets lost while working on the task, they click the "Request Advice" button. The device sends the current task information and authentication token to the server. The server analyzes the task information and sentiment data, and searches for relevant documents and past solutions. In this step, task information and an authentication token are provided as input, and advice is output as a result of the analysis.

[0455] Step 4:

[0456] The server generates optimal advice based on sentiment data and sends it to the terminal. The terminal displays the received advice to the user. This information includes specific solutions and next steps. In this step, the analysis results and sentiment data are provided as input information, and appropriate advice is output.

[0457] Step 5:

[0458] As the user progresses through the task, they can request further advice as needed. Once the user completes the task, they input their current emotional data using the emotion engine, and the device sends this data to the server. The server analyzes this data, generates final feedback, and stores it. In this step, emotional data and task information are provided as input, and feedback is output as the analysis result.

[0459] Step 6:

[0460] The server stores accumulated emotional data and feedback in a database and performs analysis. Based on the analysis results, improvements are made to enhance the quality of advice. These improvements are reflected in subsequent advice generation, thereby improving the overall system performance. In this step, emotional data and feedback are provided as input information, and the system improvements are output.

[0461] 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.

[0462] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include those described above. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions shown by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0463] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0464] [Second Embodiment]

[0465] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0466] 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.

[0467] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0468] 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.

[0469] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0470] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0471] 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.

[0472] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0473] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0474] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0475] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0476] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0477] This section will describe specific embodiments for implementing this invention. First, we will begin by understanding the overall flow of this system and the role of each element.

[0478] System Overview

[0479] This system allows users to input information about tasks, and the terminal and server work together to manage the tasks being handed over. It also provides appropriate advice when users are unsure how to proceed. Furthermore, users provide feedback after completing tasks, and the server analyzes this feedback to improve the system.

[0480] A natural language explanation of the program's processing.

[0481] The user logs into the device and starts the transfer mode.

[0482] The user launches a dedicated transfer application on their device and enters their login information (user ID and password). The device sends the entered login information to the server. The server receives this information, compares it with the database, and authenticates the user. Once authenticated, the server generates an authentication token and sends it to the device. The device saves the authentication token and displays the transfer mode screen.

[0483] The server lists the tasks to be handed over.

[0484] When a user enters handover mode, the device requests a list of tasks to be handed over from the server. This request also includes an authentication token. The server retrieves the tasks to be handed over from the database, organizes them by category, and sets their priorities. It then sends the organized task list to the device. The device displays the received task list to the user, allowing the user to select the tasks they wish to handle.

[0485] If a user is unsure how to proceed with a task, they can request advice.

[0486] If a user gets stuck while working on a task, they click the "Request Advice" button. The device sends the current task information and authentication token to the server. The server analyzes the submitted task information and searches for relevant documentation and past solutions. Based on the search results, the server generates appropriate advice and sends it to the device. The device then displays the received advice to the user.

[0487] Users progress through tasks and provide feedback.

[0488] The user follows the advice and completes the task. After task completion, the device displays a feedback input screen. The user provides feedback on the effectiveness of the advice and any problems encountered during task processing. The device sends the entered feedback to the server.

[0489] The server analyzes the feedback and uses it to improve the system.

[0490] The server stores the received feedback in a database. It then analyzes the stored feedback to consider ways to improve the quality of the advice. This enables effective improvements to the entire system.

[0491] Specific example

[0492] Specific examples are given below.

[0493] When User A takes over the task "Create Monthly Report"

[0494] User A launches the transfer application and clicks "Start Transfer".

[0495] The server lists past tasks and solutions related to the creation of the monthly report and sends them to the terminal.

[0496] When User A is having trouble with the report format, they click the "Request Advice" button.

[0497] The server suggests the optimal format based on past formatting examples and sends it to the terminal.

[0498] User A creates a report using the proposed format and completes the task.

[0499] After completion, User A enters feedback on whether the advice was effective and sends it to the server.

[0500] The server uses this feedback to analyze and improve the quality of future advice.

[0501] In this way, this system enables efficient handover processes when personnel changes occur, allowing for the smooth progress of operations.

[0502] The following describes the processing flow.

[0503] Step 1:

[0504] The user launches a dedicated transfer application on their device. The device displays the initial screen.

[0505] Step 2:

[0506] The user enters their user ID and password. The terminal sends this information to the server.

[0507] Step 3:

[0508] The server authenticates the user by comparing the received user ID and password with the database. If authentication is successful, the server generates an authentication token and sends it to the terminal. If authentication fails, the server sends an error message to the terminal.

[0509] Step 4:

[0510] The device saves the authentication token and displays the transfer mode screen to the user. The user clicks the "Start Transfer" button.

[0511] Step 5:

[0512] The device sends a request to the server for the task list to be handed over. This request includes an authentication token.

[0513] Step 6:

[0514] The server retrieves the tasks to be handed over from the database, organizes them by category, and sets their priorities. It then sends the organized task list to the terminal.

[0515] Step 7:

[0516] The terminal displays a list of received tasks to the user. The user selects a task to process from the displayed list.

[0517] Step 8:

[0518] If a user gets lost while processing a task, they can click the "Request Advice" button. The device will then send the current task information and authentication token to the server.

[0519] Step 9:

[0520] The server analyzes the received task information and searches the database for relevant documents and past solutions.

[0521] Step 10:

[0522] The server generates optimal advice based on the search results and sends it to the terminal.

[0523] Step 11:

[0524] The device displays the advice it receives to the user. The user then proceeds with the task while referring to the displayed advice.

[0525] Step 12:

[0526] Once the user completes a task, the device displays a feedback input screen. The user provides feedback on the effectiveness of the advice and any problems encountered during task completion.

[0527] Step 13:

[0528] The terminal sends the input feedback to the server. The server stores the received feedback in a database.

[0529] Step 14:

[0530] The server analyzes the stored feedback and considers ways to improve the quality of the advice.

[0531] In this way, the entire system flows smoothly, allowing users to efficiently take over tasks and quickly receive necessary advice.

[0532] (Example 1)

[0533] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0534] Traditional work handover systems often made it difficult to resolve problems during the process, resulting in decreased work efficiency. Furthermore, feedback was not properly utilized, hindering system improvements.

[0535] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0536] In this invention, the server includes means for user authentication, means for retrieving and listing the tasks to be handed over from a database, and means for searching for relevant documents and past solutions and generating optimal advice. This enables smooth problem-solving during the progress of tasks and allows for continuous improvement of the system based on feedback.

[0537] A "user" refers to an individual or group that uses a system to input business information and perform tasks.

[0538] "Business operations" refers to tasks managed within a system and the series of activities related to their processing.

[0539] "Data" refers to various types of information that users input into the system, as well as information that the system generates or acquires based on that information.

[0540] A "terminal" refers to a hardware device, such as a computer or mobile device, operated by a user, and is a device that communicates with a system.

[0541] A "server" refers to a central processing unit that performs various tasks such as user authentication, database management, task list generation, and advice generation.

[0542] A "database" refers to a system for systematically storing data such as business information, user information, past solutions, and feedback.

[0543] "Advice" refers to the knowledge and guidance that users need to carry out their tasks, as well as the solutions and recommendations generated by the system.

[0544] "Authentication" refers to the process by which a system verifies the identity of a user, and is a means of confirming that the user is legitimate.

[0545] "Feedback" refers to the opinions and evaluations that users enter into the system after completing a task.

[0546] "Searching" refers to the process by which a server finds relevant documents or past solutions.

[0547] "Analysis" refers to the process by which a server processes received feedback and task information to derive useful insights and areas for improvement.

[0548] "Listing" refers to the process by which a server organizes and displays business information retrieved from a database.

[0549] The specific embodiments of this invention will be described in detail below. First, we will begin by understanding the overall flow of this system and the role of each element.

[0550] System Overview

[0551] This system allows users to input data related to their work, and the terminal and server work together to manage the tasks being handed over. It also provides appropriate advice when problems arise during the process. Furthermore, users input feedback after completing tasks, and the server analyzes this feedback to improve the system. The main components of the system are described below.

[0552] The user logs into the device and starts the transfer mode.

[0553] The user launches a dedicated transfer application (TaskTransferApp) on their device and enters their login information (user ID and password). The device sends the entered login information to the server as an HTTP POST request. The server verifies the information against the database (MySQL) and performs user authentication. If authentication is successful, the server generates a JSON Web Token (JWT) and sends it back to the device. The device saves the received authentication token and displays the transfer mode screen.

[0554] The server lists the tasks to be handed over.

[0555] When the device enters handover mode, it sends an authentication token to the server and requests the task list to be handed over. The server retrieves the user's relevant work information from the database, organizes the task list by category, and sorts it by priority. It sends the organized task list to the device, which then displays the task list to the user.

[0556] If a user is unsure how to proceed with their work, they can request advice.

[0557] If a user encounters difficulties while working, they click the "Request Advice" button. The terminal sends current work information and an authentication token to the server. The server analyzes the information received and searches for relevant documents and past solutions. Using a search engine (Elasticsearch), it generates the best advice and sends it to the terminal. The terminal then displays the received advice to the user.

[0558] Users carry out tasks and provide feedback.

[0559] Once the user completes the task following the advice from the server, the terminal displays a feedback input screen. The user enters and submits feedback regarding the effectiveness of the advice and any problems encountered during the task. The terminal then sends the entered feedback to the server.

[0560] The server analyzes the feedback and uses it to improve the system.

[0561] The server receives feedback and stores it in a database. The stored feedback is analyzed periodically, and the data is analyzed using a machine learning model (Scikit-learn). Based on the analysis results, system improvements are considered, and software updates or new features are added as needed.

[0562] Specific example

[0563] Specific examples are given below.

[0564] If User A takes over the creation of the monthly report

[0565] User A launches the transfer application and clicks "Start Transfer".

[0566] The server lists past tasks and solutions related to the creation of monthly reports and sends them to the terminal.

[0567] When User A is having trouble with the report format, they click the "Request Advice" button.

[0568] The server suggests the optimal format and sends it to the terminal.

[0569] User A creates a report using the proposed format and completes the task.

[0570] After completion, User A enters feedback and sends it to the server.

[0571] The server analyzes the feedback to improve the quality of future advice.

[0572] Example of a prompt

[0573] The following are examples of prompts to input into the generative AI model.

[0574] "What is the best format for creating monthly reports?"

[0575] "What should I do when I encounter difficulties in completing a task?"

[0576] By using this prompt, you can receive appropriate advice from the AI ​​model.

[0577] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0578] Step 1:

[0579] The user launches a dedicated transfer application on their device. The user enters their user ID and password on the login screen. The device sends the entered user ID and password to the server as an HTTP POST request. The server compares the received login information with its database and authenticates the user. The input is the user ID and password, and the output is whether the authentication was successful or unsuccessful and a JWT authentication token. If authentication is successful, the server generates an authentication token and sends it back to the device. The device saves the authentication token and displays the transfer mode screen.

[0580] Step 2:

[0581] The user clicks a button to enter handover mode. The terminal issues an authentication token and requests the server for a list of tasks to be handed over. The server retrieves the user's relevant business information from the database. The input is the authentication token and task request, and the output is the user's relevant business information. The server organizes the retrieved information by category and sorts it by priority. The organized task list is sent to the terminal, which then displays the task list to the user.

[0582] Step 3:

[0583] If a user encounters difficulties while working, they click the "Request Advice" button. The terminal sends current work information and an authentication token to the server. The server analyzes the received work information and searches for relevant documents and past solutions. The input is work information and an authentication token, and the output is appropriate advice. The server uses a search engine to search the data, generates the best advice, and sends it to the terminal. The terminal displays the received advice to the user.

[0584] Step 4:

[0585] The user proceeds with the task according to the advice from the server and completes the task. After task completion, the terminal displays a feedback input screen. The user enters feedback on the effectiveness of the advice and any problems encountered during the task, and clicks the submit button. The input is feedback on the effectiveness of the advice and any problems encountered, and the output is feedback data. The terminal sends the entered feedback to the server.

[0586] Step 5:

[0587] The server stores the received feedback in a database. The input is the feedback data, and the output is the collection of stored feedback data. The server periodically analyzes the stored feedback. It uses machine learning models to analyze the data and considers ways to improve the system based on the analysis results. It updates the software and adds new features as needed to improve the overall system performance.

[0588] (Application Example 1)

[0589] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0590] Staff shift changes and handovers at logistics centers are time-consuming and prone to errors and omissions. Furthermore, existing systems lack the means to obtain quick and appropriate advice when problems arise during task execution, leading to decreased operational efficiency. Additionally, there is no mechanism in place to incorporate feedback after task completion into system improvements. To address these challenges, a more efficient and reliable task management system is needed.

[0591] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0592] In this invention, the server includes means for staff at a logistics center to manage handover tasks using smartphones and request advice and procedures; means for displaying a task list obtained from the server via an application installed on the smartphone, allowing staff to request advice during sorting work; means for the server to generate optimal advice using a recommendation algorithm based on past relevant documents and solutions; and means for the server to perform analysis to improve the entire system based on feedback entered by staff after task completion. This enables more efficient task handover at the logistics center, quicker response to problems, and system improvements based on feedback.

[0593] "User authentication" is the process by which a system verifies the user's identity and grants them access rights.

[0594] A "terminal" is a device that a user operates and uses to exchange input and display information.

[0595] A "server" is a computer system that processes and stores data on a network and provides information to other terminals.

[0596] A "task list" is a list of tasks related to a specific job.

[0597] An "advice request" is an operation in which a user asks the server for advice when they get stuck while processing a task.

[0598] A "recommendation algorithm" is a computational method used by a system to generate optimal advice based on historical data and relevant documents.

[0599] "Feedback" refers to the opinions and impressions that users provide after completing a task.

[0600] A "logistics center" is a facility that handles logistics operations such as storing, sorting, and shipping goods and materials.

[0601] A "smartphone" is a portable information terminal that combines the functions of a mobile phone and a computer, and is capable of running applications.

[0602] "Handover tasks" refer to the new responsibilities that need to be taken on due to shift changes or changes in personnel.

[0603] A "document" is an official document or record related to a specific job or task.

[0604] "System improvement" refers to activities aimed at improving overall functionality and performance by analyzing collected feedback and data.

[0605] Specific embodiments for carrying out this invention will now be described. First, this system is intended for task management and advice provision in a logistics center. The entire system consists of a smartphone, a server, and a network.

[0606] System Overview

[0607] This system uses the following methods to perform each step:

[0608] 1. User input information

[0609] Users enter task-related information using a dedicated application installed on their smartphones.

[0610] 2. Data transmission from terminal to server

[0611] A smartphone (device) sends information entered by the user to a server. This transmission uses a network.

[0612] 3. User authentication on the server

[0613] The server performs user authentication based on the user's authentication information (user ID and password). If authentication is successful, an authentication token is returned to the smartphone.

[0614] 4. Retrieving and displaying the task list

[0615] After authentication, the server retrieves the tasks to be handed over from the database and displays them as a list on the smartphone.

[0616] 5. Requesting and providing advice

[0617] If a user gets stuck while working on a task, they can click the "Request Advice" button on their smartphone. The server searches relevant documents and past solutions, and uses a generative AI model to provide the best advice. This advice is then displayed on the smartphone.

[0618] 6. Providing feedback after task completion

[0619] After completing a task, users input feedback on the effectiveness of the advice and any problems encountered during task processing via their smartphones and send it to the server.

[0620] 7. Analysis of feedback and system improvement

[0621] The server analyzes the information in the database based on the collected feedback and works to improve the entire system.

[0622] Hardware and software

[0623] hardware

[0624] Smartphone (user device)

[0625] Server (data processing and storage)

[0626] Network infrastructure (data communication)

[0627] software

[0628] A dedicated application installed on a smartphone

[0629] Server-side authentication system

[0630] Server-side database management system

[0631] Recommended algorithms (including generative AI models)

[0632] Specific example

[0633] Specific examples are given below.

[0634] 1. Handover of sorting duties

[0635] Example of a prompt:

[0636] This scenario involves a user taking over sorting tasks. Please outline the steps for obtaining the task list and starting a new task. Include procedures for requesting advice and providing feedback if difficulties arise during task completion.

[0637] The user logs in using the smartphone app and retrieves the task list.

[0638] Based on the task list, select and begin today's sorting tasks.

[0639] If you get stuck during the sorting process, click the "Request Advice" button to receive appropriate advice from the server.

[0640] Once the sorting process is complete, enter feedback into the app and submit it.

[0641] This system streamlines task handover in logistics centers, enables rapid response to problems, and improves the system based on feedback.

[0642] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0643] Step 1:

[0644] The user launches a dedicated application installed on their smartphone and enters their login information (user ID and password). The device sends this information to the server. The input data consists of the user ID and password, and the output is a request for authentication processing on the server. Specifically, the device receives the user ID and password on the login screen, encrypts them, and sends them to the server.

[0645] Step 2:

[0646] The server performs user authentication. The server compares the received login information with the information in the database to authenticate the user. The input data is the user ID and password, which are compared with the user information retrieved from the database. The output is the generation of an authentication token. Specifically, the server retrieves the user ID and hashed password from the database and compares them with the received information. If authentication is successful, the server generates an authentication token and sends it to the terminal.

[0647] Step 3:

[0648] When a user enters handover mode, the device requests the task list from the server. The input data is an authentication token, and the output is a request for the task list to be handed over. Specifically, the device sends an authentication token to the server and then requests the task list.

[0649] Step 4:

[0650] The server retrieves tasks to be handed over from the database, organizes them by category, and sets their priorities. The input data is an authentication token and user ID, and the output is a task list organized by category. Specifically, the server retrieves relevant task information from the database, classifies it into categories to facilitate handover, and sets its priorities.

[0651] Step 5:

[0652] The terminal displays a task list retrieved from the server to the user. The input data is a task list organized by category, and the output is a task list screen that the user can view. Specifically, the terminal displays the task list retrieved from the server on the screen, allowing the user to review it.

[0653] Step 6:

[0654] If a user gets lost while processing a task, they click the "Request Advice" button. The device then sends the current task information and authentication token to the server. The input data is the current task information and authentication token, and the output is an advice request to the server. Specifically, the user clicks the "Request Advice" button on the screen, which triggers the device to send the task information and authentication token to the server.

[0655] Step 7:

[0656] The server analyzes the submitted task information and searches for relevant documents and past solutions. The input data consists of task information and an authentication token, and the output consists of relevant documents and past solutions. Specifically, the server searches for relevant documents in the database based on the task information and analyzes past solutions using a generative AI model.

[0657] Step 8:

[0658] The server generates optimal advice and sends it to the terminal. The input data consists of relevant documents and past solutions, and the output is the optimal advice. Specifically, the server uses a generation AI model to generate optimal advice and sends it to the terminal.

[0659] Step 9:

[0660] The device displays the advice it receives to the user. The input data is the optimal advice, and the output is an advice screen that the user can view. Specifically, the device displays the advice it receives from the server on the screen, allowing the user to review it.

[0661] Step 10:

[0662] The user enters feedback after completing a task. The device sends the entered feedback to the server. The input data is the feedback content, and the output is the feedback submission request to the server. Specifically, the user enters feedback on the feedback input screen and clicks the submit button.

[0663] Step 11:

[0664] The server stores the feedback in a database and analyzes it. The input data is the feedback content, and the output is the feedback analysis results. Specifically, the server stores the feedback in a database and analyzes that data to use for future system improvements.

[0665] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0666] This section describes a specific embodiment for carrying out this invention. The system allows the user to input information about a task, and the terminal and server work together to manage the task being handed over, providing appropriate advice when the user is unsure how to proceed. Furthermore, by incorporating an emotion engine that recognizes the user's emotions, it is possible to provide even more appropriate advice. After the user completes a task, they provide feedback, which the server analyzes to improve the system.

[0667] System Overview

[0668] This system consists of the following elements:

[0669] 1. Means by which users can input information about a task.

[0670] 2. Means by which the terminal transmits user input information to the server

[0671] 3. Means by which the server performs user authentication

[0672] 4. A method by which the server retrieves and lists the tasks to be handed over from the database.

[0673] 5. Means for displaying the task list obtained from the server by the terminal to the user.

[0674] 6. Means by which users can request advice while processing a task.

[0675] 7. Means for the server to generate and send appropriate advice regarding the task being processed to the terminal.

[0676] 8. Means for displaying advice obtained from the server by the terminal to the user.

[0677] 9. A means for users to provide feedback after completing a task.

[0678] 10. Means for the server to store and analyze feedback in a database.

[0679] 11. Emotion engine that recognizes user emotions

[0680] 12. A means of generating more appropriate advice based on user emotion data received from the emotion engine.

[0681] A natural language explanation of the program's processing.

[0682] The user logs into the device and starts the transfer mode.

[0683] The user launches a dedicated transfer application on their device and enters their login information (user ID and password). The device sends the entered login information to the server, which receives it, compares it with the database, and authenticates the user. Once authenticated, the server generates an authentication token and sends it to the device. The device saves the authentication token and displays the transfer mode screen.

[0684] The server lists the tasks to be handed over.

[0685] When a user enters handover mode, the device sends a request to the server for a list of tasks to be handed over. The server retrieves the tasks to be handed over from the database, organizes them by category, sets priorities, and sends the task list to the device. The device displays the received task list to the user. The user selects a task to process from the displayed list.

[0686] If a user is unsure how to proceed with a task, they can request advice.

[0687] If a user gets stuck while working on a task, they click the "Request Advice" button. The device sends the current task information and authentication token to the server. The server analyzes the submitted task information and searches for relevant documentation and past solutions. Based on the search results, the server generates the best advice and sends it to the device. The device then displays the received advice to the user.

[0688] Users progress through tasks and provide feedback using an emotion engine.

[0689] As the user progresses through a task following the advice, they input their current emotions using the emotion engine. The device sends this emotion data to the server. Based on the emotion data, the server generates more appropriate advice and sends it back to the device. Once the user completes the task, the device displays a feedback input screen. The user provides feedback on the effectiveness of the advice and any problems encountered during task completion. The device sends the input feedback back to the server.

[0690] The server analyzes feedback and sentiment data and uses it to improve the system.

[0691] The server stores the received feedback and sentiment data in a database and performs analysis. Based on the analysis results, the server considers ways to improve the quality of advice and makes improvements to the entire system.

[0692] Specific example

[0693] Specific examples are given below.

[0694] When User A takes over the task "Create Monthly Report"

[0695] User A launches the transfer application and clicks "Start Transfer".

[0696] The server lists past tasks and solutions related to the creation of the monthly report and sends them to the terminal.

[0697] When User A is having trouble with the report format, they click the "Request Advice" button.

[0698] The server suggests the optimal format based on past formatting examples and sends it to the terminal.

[0699] When User A creates a report following the advice, they input their current emotions using the emotion engine.

[0700] The server takes user A's emotions into consideration and provides more specific advice.

[0701] User A creates a report using the proposed format and completes the task.

[0702] After completion, User A sends feedback to the server indicating whether the advice was effective, along with their own emotional data.

[0703] The server uses this feedback and sentiment data to perform analysis in order to improve the quality of future advice.

[0704] By combining this with an emotion engine, more appropriate advice that takes into account the user's psychological state is provided, making the handover process more efficient and effective.

[0705] The following describes the processing flow.

[0706] Step 1:

[0707] The user launches a dedicated transfer application on their device. The device displays the initial screen.

[0708] Step 2:

[0709] The user enters their user ID and password. The terminal sends the entered information to the server.

[0710] Step 3:

[0711] The server authenticates the user by comparing the received user ID and password with the database. If authentication is successful, the server generates an authentication token and sends it to the terminal. If authentication fails, the server sends an error message to the terminal.

[0712] Step 4:

[0713] The device saves the authentication token and displays the transfer mode screen to the user. The user clicks the "Start Transfer" button.

[0714] Step 5:

[0715] The device sends a request to the server for the task list to be handed over. This request includes an authentication token.

[0716] Step 6:

[0717] The server retrieves the tasks to be handed over from the database, organizes them by category, and sets their priorities. It then sends the organized task list to the terminal.

[0718] Step 7:

[0719] The terminal displays a list of received tasks to the user. The user selects a task to process from the displayed list.

[0720] Step 8:

[0721] If a user gets lost while processing a task, they can click the "Request Advice" button. The device will then send the current task information and authentication token to the server.

[0722] Step 9:

[0723] The server analyzes the received task information and searches the database for relevant documents and past solutions.

[0724] Step 10:

[0725] The server generates optimal advice based on the search results and sends it to the terminal.

[0726] Step 11:

[0727] The device displays the advice it receives to the user. The user then proceeds with the task while referring to the displayed advice.

[0728] Step 12:

[0729] The user inputs their current emotion using an emotion engine. The device then sends the emotion data to the server.

[0730] Step 13:

[0731] The server analyzes the emotional data, generates additional advice that takes the user's emotional state into account, and sends it to the terminal.

[0732] Step 14:

[0733] The device displays any additional advice it has received to the user. The user then uses this advice to proceed with the task.

[0734] Step 15:

[0735] Once the user completes a task, the device displays a feedback input screen. The user provides feedback on the effectiveness of the advice and any problems encountered during task completion.

[0736] Step 16:

[0737] The device sends the input feedback and sentiment data to the server. The server stores the received feedback and sentiment data in a database.

[0738] Step 17:

[0739] The server analyzes stored feedback and sentiment data to explore ways to improve the quality of advice.

[0740] Through the above processing steps, users can efficiently perform the handover and receive necessary advice quickly and appropriately. Furthermore, the introduction of an emotion engine provides more appropriate advice that takes into account the user's psychological state.

[0741] (Example 2)

[0742] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0743] Current task management systems often fail to provide users with appropriate advice when they encounter difficulties during task completion, and furthermore, they do not offer advice that takes into account the user's emotional state, making efficient task completion difficult. Another issue is that feedback after task completion is not adequately utilized for system improvement.

[0744] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0745] In this invention, the server includes means for the user to input information about a task, means for the terminal to transmit the user's input information to the server, means for the server to perform user authentication, means for the server to retrieve and list tasks to be handed over from a database, means for the terminal to display the task list retrieved from the server to the user, means for the user to request advice while processing a task, means for the server to generate appropriate advice regarding the task being processed and send it to the terminal, means for the terminal to display the advice retrieved from the server to the user, means for the user to input feedback after completing a task, means for the server to store and analyze the feedback in a database, means equipped with an emotion engine that recognizes the user's emotions, means for generating more appropriate advice based on the user's emotion data received from the emotion engine, means for the server to send the generated advice to the terminal, and means for the terminal to display the advice to the user. As a result, the user can receive appropriate advice while working on a task, appropriate support that takes into account their emotional state is possible, and feedback after task completion is effectively utilized for system improvement.

[0746] A "user" is someone who uses the system to input task information and provide feedback.

[0747] A "terminal" is a device that a user operates, sends input information to a server, and receives data from the server.

[0748] A "server" is a central computing system that performs user authentication, retrieves tasks from a database, generates advice, and sends it to terminals.

[0749] An "authentication token" is temporary data used to verify user authentication and maintain a session.

[0750] A "database" is a system for storing and managing task information, user feedback, and sentiment data.

[0751] A "task list" is a list of tasks to be handed over that the server retrieves from the database and displays to the user.

[0752] "Advice" refers to solutions or suggestions that a server provides to a user who is unsure how to proceed with a task.

[0753] An "emotion engine" is a system that recognizes emotions based on user input and analyzes that data.

[0754] "Feedback" refers to the opinions and evaluations of the processing results and the system that users provide after completing a task.

[0755] Specific embodiments for carrying out this invention will now be described. This system allows the user to input information about a task, and the terminal and server work together to take over and manage the task. In particular, it is characterized by providing appropriate advice when the user is unsure during task processing and by providing more accurate support using the user's emotional data.

[0756] System Configuration

[0757] This system consists of the following elements:

[0758] 1. Means by which users can input information about a task.

[0759] The user launches a dedicated handover application on their device and enters information about the task. This information includes the task name, details, and deadline.

[0760] 2. Means by which the terminal transmits user input information to the server

[0761] The terminal sends the entered task information and login information to the server using the HTTPS protocol.

[0762] 3. Means by which the server performs user authentication

[0763] The server compares the received user ID and password with the database to authenticate the user. If authentication is successful, it generates an authentication token and sends it to the terminal.

[0764] 4. A method by which the server retrieves and lists the tasks to be handed over from the database.

[0765] The server retrieves the tasks to be handed over from the database, lists them by category and priority, and sends them to the terminal.

[0766] 5. Means for displaying the task list obtained from the server by the terminal to the user.

[0767] The device displays the received task list on the user's screen. The user can select a task to process from the displayed list.

[0768] 6. Means by which users can request advice while processing a task.

[0769] If a user is unsure how to proceed with a task, they can click the "Request Advice" button to send their current task information to the server.

[0770] 7. Means for the server to generate and send appropriate advice regarding the task being processed to the terminal.

[0771] The server analyzes task information, searches for relevant documents and past solutions, generates optimal advice using an AI model, and sends it to the terminal.

[0772] 8. Means for displaying advice obtained from the server by the terminal to the user.

[0773] The device displays the received advice on the user's screen.

[0774] 9. A means for users to provide feedback after completing a task.

[0775] After completing a task, users provide feedback on the effectiveness of the advice and any problems they encountered.

[0776] 10. Means for the server to store and analyze feedback in a database.

[0777] The server stores feedback in a database, analyzes it, and uses it to improve the system.

[0778] 11. Emotion engine that recognizes user emotions

[0779] The emotion engine receives emotional data from the user and recognizes their emotional state.

[0780] 12. A means of generating more appropriate advice based on user emotion data received from the emotion engine.

[0781] The server generates more personalized advice based on the emotional data received from the emotion engine and sends it to the device.

[0782] Specific example

[0783] Specific examples are given below.

[0784] Example 1: When User A takes over the task "Create Monthly Report"

[0785] User A launches the transfer application and clicks "Start Transfer".

[0786] The server lists past tasks and solutions related to the creation of the monthly report and sends them to the terminal.

[0787] When User A is having trouble with the report format, they click the "Request Advice" button.

[0788] The server suggests the optimal format based on past formatting examples and sends it to the terminal.

[0789] When User A creates a report following the advice, they input their current emotions using the emotion engine.

[0790] The server takes user A's emotions into consideration and provides more specific advice.

[0791] User A creates a report using the proposed format and completes the task.

[0792] After completion, User A sends feedback to the server indicating whether the advice was effective, along with their own emotional data.

[0793] The server uses this feedback and sentiment data to perform analysis in order to improve the quality of future advice.

[0794] Example of a prompt

[0795] Prompt 1: "Describe a system where a user inputs information about a task and receives the best advice. In particular, explain in detail how an emotion engine is used to improve the advice."

[0796] As described above, the present invention is a system that enables more efficient and effective task management by providing advice that takes into account the user's emotional state and by effectively utilizing feedback.

[0797] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0798] Step 1: User logs in and starts transfer mode.

[0799] Input: User ID, Password

[0800] procedure:

[0801] 1. The user launches the transfer application on their device.

[0802] 2. The user enters their user ID and password on the login screen.

[0803] 3. The terminal sends the entered login information to the server using the HTTPS protocol.

[0804] 4. The server compares the received login information with the database and performs user authentication.

[0805] 5. If authentication is successful, the server generates an authentication token and sends it to the device.

[0806] 6. The device saves the authentication token and displays the transfer mode screen.

[0807] Output: Authentication token, display of the handover mode screen

[0808] Step 2: The server lists the tasks to be handed over.

[0809] Input: Authentication token, Task list request

[0810] procedure:

[0811] 1. The user clicks the "Get Task List" button on the handover mode screen.

[0812] 2. The device sends a request to the server for a task list containing an authentication token.

[0813] 3. The server verifies the authentication token and confirms that the user has the necessary permissions.

[0814] 4. The server queries the database for the tasks to be handed over and retrieves them.

[0815] 5. Organize the tasks acquired by the server by category and set their priorities.

[0816] 6. Send the organized task list to your device.

[0817] 7. Display the task list received by the device to the user.

[0818] Output: Task list

[0819] Step 3: If the user gets lost while working on the task, they should request advice.

[0820] Input: Current task information, authentication token

[0821] procedure:

[0822] 1. If a user is unsure how to proceed with a task, they can click the "Request Advice" button.

[0823] 2. The device sends the current task information and authentication token to the server.

[0824] 3. The server analyzes the received data and searches the database for relevant documents and past solutions.

[0825] 4. The server generates optimal advice based on the search results using an AI model.

[0826] 5. The server sends the generated advice to the terminal.

[0827] 6. Display the advice received by the device to the user.

[0828] Output: Advice

[0829] Step 4: The user progresses through the task and provides feedback using the emotion engine.

[0830] Input: Sentiment data, feedback information

[0831] procedure:

[0832] 1. The user proceeds with the task following the advice.

[0833] 2. The user enters their current emotional state on the emotion engine screen.

[0834] 3. The device sends emotional data to the server.

[0835] 4. The server generates more specific advice based on emotional data. A generation AI model is used as needed.

[0836] 5. The generated advice is sent to the device, and the device displays it to the user.

[0837] 6. When the user completes the task, the device displays a feedback input screen.

[0838] 7. Users provide feedback on the effectiveness of the advice and any problems they encountered while completing the task.

[0839] 8. The device sends feedback to the server.

[0840] Output: Sentiment data, feedback

[0841] Step 5: The server analyzes feedback and sentiment data and uses it to improve the system.

[0842] Input: Feedback, sentiment data

[0843] procedure:

[0844] 1. The server saves the feedback and sentiment data received from the terminal to a database.

[0845] 2. The server queries the database and parses the received data.

[0846] 3. The server will consider ways to improve the quality of advice based on the analysis results.

[0847] 4. The server implements the improvements and updates the functionality of the entire system.

[0848] Output: System improvement proposal

[0849] The above outlines the specific processing steps of this system's program, along with details of the operation and input / output for each step.

[0850] (Application Example 2)

[0851] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0852] Traditional task management systems often fail to consider the user's emotions or psychological state, simply providing formulaic advice. This has resulted in insufficient support, especially when users are facing difficult situations or experiencing stress. Furthermore, the lack of adaptive support to improve task processing efficiency degrades the user experience of the system.

[0853] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0854] In this invention, the server includes means for acquiring and transmitting user emotion data to the server, means for generating appropriate advice based on the task being processed and the acquired emotion data and transmitting it to the terminal, and means for generating optimal advice considering the emotion data. This makes it possible to provide appropriate advice that takes into account the user's emotions and psychological state, improving the efficiency of task processing and enhancing the user experience.

[0855] A "task" is a specific task or activity that a user is required to accomplish.

[0856] User authentication is the process of verifying the identification information that a user enters to access a system, and confirming that they are a legitimate user.

[0857] "Emotional data" refers to data that represents the user's psychological state and emotions, and is acquired by an emotion recognition engine.

[0858] "Advice" refers to information and methods that users can use as a reference when carrying out a task.

[0859] "Feedback" refers to the opinions and evaluations that users provide after completing a task, regarding the effectiveness of the advice given and any problems encountered during the task.

[0860] An "emotion recognition engine" is software or algorithms that analyze a user's emotions and psychological state and generate data based on that analysis.

[0861] A "terminal" is a device that a user operates to input information or to view displayed advice.

[0862] A "database" is a system or structure used to organize and store information about tasks, users, and feedback.

[0863] "Advice generation" is the process by which a server creates instructions to provide the user with the best possible support, based on the user's task information and sentiment data.

[0864] A "server" is a central computer system that processes user input, manages tasks, and generates and provides advice.

[0865] To implement this invention, it is necessary to construct a task management system with excellent emotion recognition capabilities. This system is realized through the cooperation of a server, terminals, and users, and uses an emotion recognition engine to provide optimal advice that takes into account the user's psychological state.

[0866] System Configuration

[0867] Hardware and software

[0868] Hardware:

[0869] Device: Smartphone or head-mounted display (HMD)

[0870] Server: High-performance computer system

[0871] software:

[0872] Emotion recognition engine: Emotion recognition libraries such as Affectiva SDK

[0873] Applications: Python, Requests library, etc.

[0874] Explanation of natural language processing

[0875] User authentication and task information retrieval via the device.

[0876] The user logs into the device and sends authentication information to the server. The server generates an authentication token and sends it back to the device to authenticate the user. The server then retrieves the task to be handed over from the database and sends it to the device. The device displays this to the user, and the user selects a specific task.

[0877] Requesting and providing advice

[0878] If a user encounters difficulties while working on a task, they can request advice from their device. The server retrieves the user's emotional data and analyzes it using an emotional recognition engine. It then searches past solutions and documentation to generate the most appropriate advice, taking the emotional data into account. The generated advice is sent to the device and displayed to the user.

[0879] Use of emotional data and feedback

[0880] Users input emotional data during and after tasks and send it to the server. The server generates more appropriate advice based on the received emotional data. Additionally, users can input feedback after completing tasks, which the server stores in a database and analyzes. The analysis results are used to improve the quality of future advice generation.

[0881] Specific example

[0882] When User A performs video editing work on a new project

[0883] User A launches the task management application and logs in. The server performs authentication and retrieves and displays a list of tasks related to the project. User A selects a specific editing task. If User A encounters difficulties in choosing an effect during the editing process, they press the "Request Advice" button. The server analyzes User A's emotional data and suggests the best way to choose an effect. User A follows the suggested advice and continues editing. After completing the task, User A provides feedback on the effectiveness of the advice and sends it to the server along with their emotional data. The server analyzes this data and uses it to improve the entire system.

[0884] Example of a prompt

[0885] Example prompts for generating advice on video editing tasks:

[0886] Generate advice for when you're stuck on choosing effects while editing a new project. Your current emotion is "frustrated." Also, suggest a basic, step-by-step approach.

[0887] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0888] Step 1:

[0889] The user enters their login information (user ID and password) into the terminal and presses the submit button. The terminal sends this input information to the server. The server authenticates the user, and if the correct authentication information is provided, it generates an authentication token and sends it back to the terminal. The terminal saves this authentication token and notifies the user that the login was successful. In this step, the user ID and password are provided as input information, and an authentication token is output.

[0890] Step 2:

[0891] The terminal uses an authentication token to request a list of tasks to be handed over from the server. The server retrieves the tasks to be handed over from the database, organizes them by category, sets priorities, and sends the task list to the terminal. The terminal displays the received task list to the user, allowing the user to select which tasks to process. In this step, the authentication token and the task list request are provided as input information, and the organized task list is output.

[0892] Step 3:

[0893] When a user selects a task, detailed information about that task is displayed on the device. If the user gets lost while working on the task, they click the "Request Advice" button. The device sends the current task information and authentication token to the server. The server analyzes the task information and sentiment data, and searches for relevant documents and past solutions. In this step, task information and an authentication token are provided as input, and advice is output as a result of the analysis.

[0894] Step 4:

[0895] The server generates optimal advice based on sentiment data and sends it to the terminal. The terminal displays the received advice to the user. This information includes specific solutions and next steps. In this step, the analysis results and sentiment data are provided as input information, and appropriate advice is output.

[0896] Step 5:

[0897] As the user progresses through the task, they can request further advice as needed. Once the user completes the task, they input their current emotional data using the emotion engine, and the device sends this data to the server. The server analyzes this data, generates final feedback, and stores it. In this step, emotional data and task information are provided as input, and feedback is output as the analysis result.

[0898] Step 6:

[0899] The server stores accumulated emotional data and feedback in a database and performs analysis. Based on the analysis results, improvements are made to enhance the quality of advice. These improvements are reflected in subsequent advice generation, thereby improving the overall system performance. In this step, emotional data and feedback are provided as input information, and the system improvements are output.

[0900] 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.

[0901] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include those described above. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions shown by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0902] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0903] [Third Embodiment]

[0904] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0905] 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.

[0906] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0907] 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.

[0908] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0909] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0910] 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.

[0911] 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.

[0912] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0913] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0914] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0915] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0916] This section will describe specific embodiments for implementing this invention. First, we will begin by understanding the overall flow of this system and the role of each element.

[0917] System Overview

[0918] This system allows users to input information about tasks, and the terminal and server work together to manage the tasks being handed over. It also provides appropriate advice when users are unsure how to proceed. Furthermore, users provide feedback after completing tasks, and the server analyzes this feedback to improve the system.

[0919] A natural language explanation of the program's processing.

[0920] The user logs into the device and starts the transfer mode.

[0921] The user launches a dedicated transfer application on their device and enters their login information (user ID and password). The device sends the entered login information to the server. The server receives this information, compares it with the database, and authenticates the user. Once authenticated, the server generates an authentication token and sends it to the device. The device saves the authentication token and displays the transfer mode screen.

[0922] The server lists the tasks to be handed over.

[0923] When a user enters handover mode, the device requests a list of tasks to be handed over from the server. This request also includes an authentication token. The server retrieves the tasks to be handed over from the database, organizes them by category, and sets their priorities. It then sends the organized task list to the device. The device displays the received task list to the user, allowing the user to select the tasks they wish to handle.

[0924] If a user is unsure how to proceed with a task, they can request advice.

[0925] If a user gets stuck while working on a task, they click the "Request Advice" button. The device sends the current task information and authentication token to the server. The server analyzes the submitted task information and searches for relevant documentation and past solutions. Based on the search results, the server generates appropriate advice and sends it to the device. The device then displays the received advice to the user.

[0926] Users progress through tasks and provide feedback.

[0927] The user follows the advice and completes the task. After task completion, the device displays a feedback input screen. The user provides feedback on the effectiveness of the advice and any problems encountered during task processing. The device sends the entered feedback to the server.

[0928] The server analyzes the feedback and uses it to improve the system.

[0929] The server stores the received feedback in a database. It then analyzes the stored feedback to consider ways to improve the quality of the advice. This enables effective improvements to the entire system.

[0930] Specific example

[0931] Specific examples are given below.

[0932] When User A takes over the task "Create Monthly Report"

[0933] User A launches the transfer application and clicks "Start Transfer".

[0934] The server lists past tasks and solutions related to the creation of the monthly report and sends them to the terminal.

[0935] When User A is having trouble with the report format, they click the "Request Advice" button.

[0936] The server suggests the optimal format based on past formatting examples and sends it to the terminal.

[0937] User A creates a report using the proposed format and completes the task.

[0938] After completion, User A enters feedback on whether the advice was effective and sends it to the server.

[0939] The server uses this feedback to analyze and improve the quality of future advice.

[0940] In this way, this system enables efficient handover processes when personnel changes occur, allowing for the smooth progress of operations.

[0941] The following describes the processing flow.

[0942] Step 1:

[0943] The user launches a dedicated transfer application on their device. The device displays the initial screen.

[0944] Step 2:

[0945] The user enters their user ID and password. The terminal sends this information to the server.

[0946] Step 3:

[0947] The server authenticates the user by comparing the received user ID and password with the database. If authentication is successful, the server generates an authentication token and sends it to the terminal. If authentication fails, the server sends an error message to the terminal.

[0948] Step 4:

[0949] The device saves the authentication token and displays the transfer mode screen to the user. The user clicks the "Start Transfer" button.

[0950] Step 5:

[0951] The device sends a request to the server for the task list to be handed over. This request includes an authentication token.

[0952] Step 6:

[0953] The server retrieves the tasks to be handed over from the database, organizes them by category, and sets their priorities. It then sends the organized task list to the terminal.

[0954] Step 7:

[0955] The terminal displays a list of received tasks to the user. The user selects a task to process from the displayed list.

[0956] Step 8:

[0957] If a user gets lost while processing a task, they can click the "Request Advice" button. The device will then send the current task information and authentication token to the server.

[0958] Step 9:

[0959] The server analyzes the received task information and searches the database for relevant documents and past solutions.

[0960] Step 10:

[0961] The server generates optimal advice based on the search results and sends it to the terminal.

[0962] Step 11:

[0963] The device displays the advice it receives to the user. The user then proceeds with the task while referring to the displayed advice.

[0964] Step 12:

[0965] Once the user completes a task, the device displays a feedback input screen. The user provides feedback on the effectiveness of the advice and any problems encountered during task completion.

[0966] Step 13:

[0967] The terminal sends the input feedback to the server. The server stores the received feedback in a database.

[0968] Step 14:

[0969] The server analyzes the stored feedback and considers ways to improve the quality of the advice.

[0970] In this way, the entire system flows smoothly, allowing users to efficiently take over tasks and quickly receive necessary advice.

[0971] (Example 1)

[0972] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0973] Traditional work handover systems often made it difficult to resolve problems during the process, resulting in decreased work efficiency. Furthermore, feedback was not properly utilized, hindering system improvements.

[0974] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0975] In this invention, the server includes means for user authentication, means for retrieving and listing the tasks to be handed over from a database, and means for searching for relevant documents and past solutions and generating optimal advice. This enables smooth problem-solving during the progress of tasks and allows for continuous improvement of the system based on feedback.

[0976] A "user" refers to an individual or group that uses a system to input business information and perform tasks.

[0977] "Business operations" refers to tasks managed within a system and the series of activities related to their processing.

[0978] "Data" refers to various types of information that users input into the system, as well as information that the system generates or acquires based on that information.

[0979] A "terminal" refers to a hardware device, such as a computer or mobile device, operated by a user, and is a device that communicates with a system.

[0980] A "server" refers to a central processing unit that performs various tasks such as user authentication, database management, task list generation, and advice generation.

[0981] A "database" refers to a system for systematically storing data such as business information, user information, past solutions, and feedback.

[0982] "Advice" refers to the knowledge and guidance that users need to carry out their tasks, as well as the solutions and recommendations generated by the system.

[0983] "Authentication" refers to the process by which a system verifies the identity of a user, and is a means of confirming that the user is legitimate.

[0984] "Feedback" refers to the opinions and evaluations that users enter into the system after completing a task.

[0985] "Searching" refers to the process by which a server finds relevant documents or past solutions.

[0986] "Analysis" refers to the process by which a server processes received feedback and task information to derive useful insights and areas for improvement.

[0987] "Listing" refers to the process by which a server organizes and displays business information retrieved from a database.

[0988] The specific embodiments of this invention will be described in detail below. First, we will begin by understanding the overall flow of this system and the role of each element.

[0989] System Overview

[0990] This system allows users to input data related to their work, and the terminal and server work together to manage the tasks being handed over. It also provides appropriate advice when problems arise during the process. Furthermore, users input feedback after completing tasks, and the server analyzes this feedback to improve the system. The main components of the system are described below.

[0991] The user logs into the device and starts the transfer mode.

[0992] The user launches a dedicated transfer application (TaskTransferApp) on their device and enters their login information (user ID and password). The device sends the entered login information to the server as an HTTP POST request. The server verifies the information against the database (MySQL) and performs user authentication. If authentication is successful, the server generates a JSON Web Token (JWT) and sends it back to the device. The device saves the received authentication token and displays the transfer mode screen.

[0993] The server lists the tasks to be handed over.

[0994] When the device enters handover mode, it sends an authentication token to the server and requests the task list to be handed over. The server retrieves the user's relevant work information from the database, organizes the task list by category, and sorts it by priority. It sends the organized task list to the device, which then displays the task list to the user.

[0995] If a user is unsure how to proceed with their work, they can request advice.

[0996] If a user encounters difficulties while working, they click the "Request Advice" button. The terminal sends current work information and an authentication token to the server. The server analyzes the information received and searches for relevant documents and past solutions. Using a search engine (Elasticsearch), it generates the best advice and sends it to the terminal. The terminal then displays the received advice to the user.

[0997] Users carry out tasks and provide feedback.

[0998] Once the user completes the task following the advice from the server, the terminal displays a feedback input screen. The user enters and submits feedback regarding the effectiveness of the advice and any problems encountered during the task. The terminal then sends the entered feedback to the server.

[0999] The server analyzes the feedback and uses it to improve the system.

[1000] The server receives feedback and stores it in a database. The stored feedback is analyzed periodically, and the data is analyzed using a machine learning model (Scikit-learn). Based on the analysis results, system improvements are considered, and software updates or new features are added as needed.

[1001] Specific example

[1002] Specific examples are given below.

[1003] If User A takes over the creation of the monthly report

[1004] User A launches the transfer application and clicks "Start Transfer".

[1005] The server lists past tasks and solutions related to the creation of monthly reports and sends them to the terminal.

[1006] When User A is having trouble with the report format, they click the "Request Advice" button.

[1007] The server suggests the optimal format and sends it to the terminal.

[1008] User A creates a report using the proposed format and completes the task.

[1009] After completion, User A enters feedback and sends it to the server.

[1010] The server analyzes the feedback to improve the quality of future advice.

[1011] Example of a prompt

[1012] The following are examples of prompts to input into the generative AI model.

[1013] "What is the best format for creating monthly reports?"

[1014] "What should I do when I encounter difficulties in completing a task?"

[1015] By using this prompt, you can receive appropriate advice from the AI ​​model.

[1016] The flow of the specific processing in Example 1 will be explained using Figure 11.

[1017] Step 1:

[1018] The user launches a dedicated transfer application on their device. The user enters their user ID and password on the login screen. The device sends the entered user ID and password to the server as an HTTP POST request. The server compares the received login information with its database and authenticates the user. The input is the user ID and password, and the output is whether the authentication was successful or unsuccessful and a JWT authentication token. If authentication is successful, the server generates an authentication token and sends it back to the device. The device saves the authentication token and displays the transfer mode screen.

[1019] Step 2:

[1020] The user clicks a button to enter handover mode. The terminal issues an authentication token and requests the server for a list of tasks to be handed over. The server retrieves the user's relevant business information from the database. The input is the authentication token and task request, and the output is the user's relevant business information. The server organizes the retrieved information by category and sorts it by priority. The organized task list is sent to the terminal, which then displays the task list to the user.

[1021] Step 3:

[1022] If a user encounters difficulties while working, they click the "Request Advice" button. The terminal sends current work information and an authentication token to the server. The server analyzes the received work information and searches for relevant documents and past solutions. The input is work information and an authentication token, and the output is appropriate advice. The server uses a search engine to search the data, generates the best advice, and sends it to the terminal. The terminal displays the received advice to the user.

[1023] Step 4:

[1024] The user proceeds with the task according to the advice from the server and completes the task. After task completion, the terminal displays a feedback input screen. The user enters feedback on the effectiveness of the advice and any problems encountered during the task, and clicks the submit button. The input is feedback on the effectiveness of the advice and any problems encountered, and the output is feedback data. The terminal sends the entered feedback to the server.

[1025] Step 5:

[1026] The server stores the received feedback in a database. The input is the feedback data, and the output is the collection of stored feedback data. The server periodically analyzes the stored feedback. It uses machine learning models to analyze the data and considers ways to improve the system based on the analysis results. It updates the software and adds new features as needed to improve the overall system performance.

[1027] (Application Example 1)

[1028] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[1029] Staff shift changes and handovers at logistics centers are time-consuming and prone to errors and omissions. Furthermore, existing systems lack the means to obtain quick and appropriate advice when problems arise during task execution, leading to decreased operational efficiency. Additionally, there is no mechanism in place to incorporate feedback after task completion into system improvements. To address these challenges, a more efficient and reliable task management system is needed.

[1030] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[1031] In this invention, the server includes means for staff at a logistics center to manage handover tasks using smartphones and request advice and procedures; means for displaying a task list obtained from the server via an application installed on the smartphone, allowing staff to request advice during sorting work; means for the server to generate optimal advice using a recommendation algorithm based on past relevant documents and solutions; and means for the server to perform analysis to improve the entire system based on feedback entered by staff after task completion. This enables more efficient task handover at the logistics center, quicker response to problems, and system improvements based on feedback.

[1032] "User authentication" is the process by which a system verifies the user's identity and grants them access rights.

[1033] A "terminal" is a device that a user operates and uses to exchange input and display information.

[1034] A "server" is a computer system that processes and stores data on a network and provides information to other terminals.

[1035] A "task list" is a list of tasks related to a specific job.

[1036] An "advice request" is an operation in which a user asks the server for advice when they get stuck while processing a task.

[1037] A "recommendation algorithm" is a computational method used by a system to generate optimal advice based on historical data and relevant documents.

[1038] "Feedback" refers to the opinions and impressions that users provide after completing a task.

[1039] A "logistics center" is a facility that handles logistics operations such as storing, sorting, and shipping goods and materials.

[1040] A "smartphone" is a portable information terminal that combines the functions of a mobile phone and a computer, and is capable of running applications.

[1041] "Handover tasks" refer to the new responsibilities that need to be taken on due to shift changes or changes in personnel.

[1042] A "document" is an official document or record related to a specific job or task.

[1043] "System improvement" refers to activities aimed at improving overall functionality and performance by analyzing collected feedback and data.

[1044] Specific embodiments for carrying out this invention will now be described. First, this system is intended for task management and advice provision in a logistics center. The entire system consists of a smartphone, a server, and a network.

[1045] System Overview

[1046] This system uses the following methods to perform each step:

[1047] 1. User input information

[1048] Users enter task-related information using a dedicated application installed on their smartphones.

[1049] 2. Data transmission from terminal to server

[1050] A smartphone (device) sends information entered by the user to a server. This transmission uses a network.

[1051] 3. User authentication on the server

[1052] The server performs user authentication based on the user's authentication information (user ID and password). If authentication is successful, an authentication token is returned to the smartphone.

[1053] 4. Retrieving and displaying the task list

[1054] After authentication, the server retrieves the tasks to be handed over from the database and displays them as a list on the smartphone.

[1055] 5. Requesting and providing advice

[1056] If a user gets stuck while working on a task, they can click the "Request Advice" button on their smartphone. The server searches relevant documents and past solutions, and uses a generative AI model to provide the best advice. This advice is then displayed on the smartphone.

[1057] 6. Providing feedback after task completion

[1058] After completing a task, users input feedback on the effectiveness of the advice and any problems encountered during task processing via their smartphones and send it to the server.

[1059] 7. Analysis of feedback and system improvement

[1060] The server analyzes the information in the database based on the collected feedback and works to improve the entire system.

[1061] Hardware and software

[1062] hardware

[1063] Smartphone (user device)

[1064] Server (data processing and storage)

[1065] Network infrastructure (data communication)

[1066] software

[1067] A dedicated application installed on a smartphone

[1068] Server-side authentication system

[1069] Server-side database management system

[1070] Recommended algorithms (including generative AI models)

[1071] Specific example

[1072] Specific examples are given below.

[1073] 1. Handover of sorting duties

[1074] Example of a prompt:

[1075] This scenario involves a user taking over sorting tasks. Please outline the steps for obtaining the task list and starting a new task. Include procedures for requesting advice and providing feedback if difficulties arise during task completion.

[1076] The user logs in using the smartphone app and retrieves the task list.

[1077] Based on the task list, select and begin today's sorting tasks.

[1078] If you get stuck during the sorting process, click the "Request Advice" button to receive appropriate advice from the server.

[1079] Once the sorting process is complete, enter feedback into the app and submit it.

[1080] This system streamlines task handover in logistics centers, enables rapid response to problems, and improves the system based on feedback.

[1081] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[1082] Step 1:

[1083] The user launches a dedicated application installed on their smartphone and enters their login information (user ID and password). The device sends this information to the server. The input data consists of the user ID and password, and the output is a request for authentication processing on the server. Specifically, the device receives the user ID and password on the login screen, encrypts them, and sends them to the server.

[1084] Step 2:

[1085] The server performs user authentication. The server compares the received login information with the information in the database to authenticate the user. The input data is the user ID and password, which are compared with the user information retrieved from the database. The output is the generation of an authentication token. Specifically, the server retrieves the user ID and hashed password from the database and compares them with the received information. If authentication is successful, the server generates an authentication token and sends it to the terminal.

[1086] Step 3:

[1087] When a user enters handover mode, the device requests the task list from the server. The input data is an authentication token, and the output is a request for the task list to be handed over. Specifically, the device sends an authentication token to the server and then requests the task list.

[1088] Step 4:

[1089] The server retrieves tasks to be handed over from the database, organizes them by category, and sets their priorities. The input data is an authentication token and user ID, and the output is a task list organized by category. Specifically, the server retrieves relevant task information from the database, classifies it into categories to facilitate handover, and sets its priorities.

[1090] Step 5:

[1091] The terminal displays a task list retrieved from the server to the user. The input data is a task list organized by category, and the output is a task list screen that the user can view. Specifically, the terminal displays the task list retrieved from the server on the screen, allowing the user to review it.

[1092] Step 6:

[1093] If a user gets lost while processing a task, they click the "Request Advice" button. The device then sends the current task information and authentication token to the server. The input data is the current task information and authentication token, and the output is an advice request to the server. Specifically, the user clicks the "Request Advice" button on the screen, which triggers the device to send the task information and authentication token to the server.

[1094] Step 7:

[1095] The server analyzes the submitted task information and searches for relevant documents and past solutions. The input data consists of task information and an authentication token, and the output consists of relevant documents and past solutions. Specifically, the server searches for relevant documents in the database based on the task information and analyzes past solutions using a generative AI model.

[1096] Step 8:

[1097] The server generates optimal advice and sends it to the terminal. The input data consists of relevant documents and past solutions, and the output is the optimal advice. Specifically, the server uses a generation AI model to generate optimal advice and sends it to the terminal.

[1098] Step 9:

[1099] The device displays the advice it receives to the user. The input data is the optimal advice, and the output is an advice screen that the user can view. Specifically, the device displays the advice it receives from the server on the screen, allowing the user to review it.

[1100] Step 10:

[1101] The user enters feedback after completing a task. The device sends the entered feedback to the server. The input data is the feedback content, and the output is the feedback submission request to the server. Specifically, the user enters feedback on the feedback input screen and clicks the submit button.

[1102] Step 11:

[1103] The server stores the feedback in a database and analyzes it. The input data is the feedback content, and the output is the feedback analysis results. Specifically, the server stores the feedback in a database and analyzes that data to use for future system improvements.

[1104] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[1105] This section describes a specific embodiment for carrying out this invention. The system allows the user to input information about a task, and the terminal and server work together to manage the task being handed over, providing appropriate advice when the user is unsure how to proceed. Furthermore, by incorporating an emotion engine that recognizes the user's emotions, it is possible to provide even more appropriate advice. After the user completes a task, they provide feedback, which the server analyzes to improve the system.

[1106] System Overview

[1107] This system consists of the following elements:

[1108] 1. Means by which users can input information about a task.

[1109] 2. Means by which the terminal transmits user input information to the server

[1110] 3. Means by which the server performs user authentication

[1111] 4. A method by which the server retrieves and lists the tasks to be handed over from the database.

[1112] 5. Means for displaying the task list obtained from the server by the terminal to the user.

[1113] 6. Means by which users can request advice while processing a task.

[1114] 7. Means for the server to generate and send appropriate advice regarding the task being processed to the terminal.

[1115] 8. Means for displaying advice obtained from the server by the terminal to the user.

[1116] 9. A means for users to provide feedback after completing a task.

[1117] 10. Means for the server to store and analyze feedback in a database.

[1118] 11. Emotion engine that recognizes user emotions

[1119] 12. A means of generating more appropriate advice based on user emotion data received from the emotion engine.

[1120] A natural language explanation of the program's processing.

[1121] The user logs into the device and starts the transfer mode.

[1122] The user launches a dedicated transfer application on their device and enters their login information (user ID and password). The device sends the entered login information to the server, which receives it, compares it with the database, and authenticates the user. Once authenticated, the server generates an authentication token and sends it to the device. The device saves the authentication token and displays the transfer mode screen.

[1123] The server lists the tasks to be handed over.

[1124] When a user enters handover mode, the device sends a request to the server for a list of tasks to be handed over. The server retrieves the tasks to be handed over from the database, organizes them by category, sets priorities, and sends the task list to the device. The device displays the received task list to the user. The user selects a task to process from the displayed list.

[1125] If a user is unsure how to proceed with a task, they can request advice.

[1126] If a user gets stuck while working on a task, they click the "Request Advice" button. The device sends the current task information and authentication token to the server. The server analyzes the submitted task information and searches for relevant documentation and past solutions. Based on the search results, the server generates the best advice and sends it to the device. The device then displays the received advice to the user.

[1127] Users progress through tasks and provide feedback using an emotion engine.

[1128] As the user progresses through a task following the advice, they input their current emotions using the emotion engine. The device sends this emotion data to the server. Based on the emotion data, the server generates more appropriate advice and sends it back to the device. Once the user completes the task, the device displays a feedback input screen. The user provides feedback on the effectiveness of the advice and any problems encountered during task completion. The device sends the input feedback back to the server.

[1129] The server analyzes feedback and sentiment data and uses it to improve the system.

[1130] The server stores the received feedback and sentiment data in a database and performs analysis. Based on the analysis results, the server considers ways to improve the quality of advice and makes improvements to the entire system.

[1131] Specific example

[1132] Specific examples are given below.

[1133] When User A takes over the task "Create Monthly Report"

[1134] User A launches the transfer application and clicks "Start Transfer".

[1135] The server lists past tasks and solutions related to the creation of the monthly report and sends them to the terminal.

[1136] When User A is having trouble with the report format, they click the "Request Advice" button.

[1137] The server suggests the optimal format based on past formatting examples and sends it to the terminal.

[1138] When User A creates a report following the advice, they input their current emotions using the emotion engine.

[1139] The server takes user A's emotions into consideration and provides more specific advice.

[1140] User A creates a report using the proposed format and completes the task.

[1141] After completion, User A sends feedback to the server indicating whether the advice was effective, along with their own emotional data.

[1142] The server uses this feedback and sentiment data to perform analysis in order to improve the quality of future advice.

[1143] By combining this with an emotion engine, more appropriate advice that takes into account the user's psychological state is provided, making the handover process more efficient and effective.

[1144] The following describes the processing flow.

[1145] Step 1:

[1146] The user launches a dedicated transfer application on their device. The device displays the initial screen.

[1147] Step 2:

[1148] The user enters their user ID and password. The terminal sends the entered information to the server.

[1149] Step 3:

[1150] The server authenticates the user by comparing the received user ID and password with the database. If authentication is successful, the server generates an authentication token and sends it to the terminal. If authentication fails, the server sends an error message to the terminal.

[1151] Step 4:

[1152] The device saves the authentication token and displays the transfer mode screen to the user. The user clicks the "Start Transfer" button.

[1153] Step 5:

[1154] The device sends a request to the server for the task list to be handed over. This request includes an authentication token.

[1155] Step 6:

[1156] The server retrieves the tasks to be handed over from the database, organizes them by category, and sets their priorities. It then sends the organized task list to the terminal.

[1157] Step 7:

[1158] The terminal displays a list of received tasks to the user. The user selects a task to process from the displayed list.

[1159] Step 8:

[1160] If a user gets lost while processing a task, they can click the "Request Advice" button. The device will then send the current task information and authentication token to the server.

[1161] Step 9:

[1162] The server analyzes the received task information and searches the database for relevant documents and past solutions.

[1163] Step 10:

[1164] The server generates optimal advice based on the search results and sends it to the terminal.

[1165] Step 11:

[1166] The device displays the advice it receives to the user. The user then proceeds with the task while referring to the displayed advice.

[1167] Step 12:

[1168] The user inputs their current emotion using an emotion engine. The device then sends the emotion data to the server.

[1169] Step 13:

[1170] The server analyzes the emotional data, generates additional advice that takes the user's emotional state into account, and sends it to the terminal.

[1171] Step 14:

[1172] The device displays any additional advice it has received to the user. The user then uses this advice to proceed with the task.

[1173] Step 15:

[1174] Once the user completes a task, the device displays a feedback input screen. The user provides feedback on the effectiveness of the advice and any problems encountered during task completion.

[1175] Step 16:

[1176] The device sends the input feedback and sentiment data to the server. The server stores the received feedback and sentiment data in a database.

[1177] Step 17:

[1178] The server analyzes stored feedback and sentiment data to explore ways to improve the quality of advice.

[1179] Through the above processing steps, users can efficiently perform the handover and receive necessary advice quickly and appropriately. Furthermore, the introduction of an emotion engine provides more appropriate advice that takes into account the user's psychological state.

[1180] (Example 2)

[1181] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[1182] Current task management systems often fail to provide users with appropriate advice when they encounter difficulties during task completion, and furthermore, they do not offer advice that takes into account the user's emotional state, making efficient task completion difficult. Another issue is that feedback after task completion is not adequately utilized for system improvement.

[1183] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[1184] In this invention, the server includes means for the user to input information about a task, means for the terminal to transmit the user's input information to the server, means for the server to perform user authentication, means for the server to retrieve and list tasks to be handed over from a database, means for the terminal to display the task list retrieved from the server to the user, means for the user to request advice while processing a task, means for the server to generate appropriate advice regarding the task being processed and send it to the terminal, means for the terminal to display the advice retrieved from the server to the user, means for the user to input feedback after completing a task, means for the server to store and analyze the feedback in a database, means equipped with an emotion engine that recognizes the user's emotions, means for generating more appropriate advice based on the user's emotion data received from the emotion engine, means for the server to send the generated advice to the terminal, and means for the terminal to display the advice to the user. As a result, the user can receive appropriate advice while working on a task, appropriate support that takes into account their emotional state is possible, and feedback after task completion is effectively utilized for system improvement.

[1185] A "user" is someone who uses the system to input task information and provide feedback.

[1186] A "terminal" is a device that a user operates, sends input information to a server, and receives data from the server.

[1187] A "server" is a central computing system that performs user authentication, retrieves tasks from a database, generates advice, and sends it to terminals.

[1188] An "authentication token" is temporary data used to verify user authentication and maintain a session.

[1189] A "database" is a system for storing and managing task information, user feedback, and sentiment data.

[1190] A "task list" is a list of tasks to be handed over that the server retrieves from the database and displays to the user.

[1191] "Advice" refers to solutions or suggestions that a server provides to a user who is unsure how to proceed with a task.

[1192] An "emotion engine" is a system that recognizes emotions based on user input and analyzes that data.

[1193] "Feedback" refers to the opinions and evaluations of the processing results and the system that users provide after completing a task.

[1194] Specific embodiments for carrying out this invention will now be described. This system allows the user to input information about a task, and the terminal and server work together to take over and manage the task. In particular, it is characterized by providing appropriate advice when the user is unsure during task processing and by providing more accurate support using the user's emotional data.

[1195] System Configuration

[1196] This system consists of the following elements:

[1197] 1. Means by which users can input information about a task.

[1198] The user launches a dedicated handover application on their device and enters information about the task. This information includes the task name, details, and deadline.

[1199] 2. Means by which the terminal transmits user input information to the server

[1200] The terminal sends the entered task information and login information to the server using the HTTPS protocol.

[1201] 3. Means by which the server performs user authentication

[1202] The server compares the received user ID and password with the database to authenticate the user. If authentication is successful, it generates an authentication token and sends it to the terminal.

[1203] 4. A method by which the server retrieves and lists the tasks to be handed over from the database.

[1204] The server retrieves the tasks to be handed over from the database, lists them by category and priority, and sends them to the terminal.

[1205] 5. Means for displaying the task list obtained from the server by the terminal to the user.

[1206] The device displays the received task list on the user's screen. The user can select a task to process from the displayed list.

[1207] 6. Means by which users can request advice while processing a task.

[1208] If a user is unsure how to proceed with a task, they can click the "Request Advice" button to send their current task information to the server.

[1209] 7. Means for the server to generate and send appropriate advice regarding the task being processed to the terminal.

[1210] The server analyzes task information, searches for relevant documents and past solutions, generates optimal advice using an AI model, and sends it to the terminal.

[1211] 8. Means for displaying advice obtained from the server by the terminal to the user.

[1212] The device displays the received advice on the user's screen.

[1213] 9. A means for users to provide feedback after completing a task.

[1214] After completing a task, users provide feedback on the effectiveness of the advice and any problems they encountered.

[1215] 10. Means for the server to store and analyze feedback in a database.

[1216] The server stores feedback in a database, analyzes it, and uses it to improve the system.

[1217] 11. Emotion engine that recognizes user emotions

[1218] The emotion engine receives emotional data from the user and recognizes their emotional state.

[1219] 12. A means of generating more appropriate advice based on user emotion data received from the emotion engine.

[1220] The server generates more personalized advice based on the emotional data received from the emotion engine and sends it to the device.

[1221] Specific example

[1222] Specific examples are given below.

[1223] Example 1: When User A takes over the task "Create Monthly Report"

[1224] User A launches the transfer application and clicks "Start Transfer".

[1225] The server lists past tasks and solutions related to the creation of the monthly report and sends them to the terminal.

[1226] When User A is having trouble with the report format, they click the "Request Advice" button.

[1227] The server suggests the optimal format based on past formatting examples and sends it to the terminal.

[1228] When User A creates a report following the advice, they input their current emotions using the emotion engine.

[1229] The server takes user A's emotions into consideration and provides more specific advice.

[1230] User A creates a report using the proposed format and completes the task.

[1231] After completion, User A sends feedback to the server indicating whether the advice was effective, along with their own emotional data.

[1232] The server uses this feedback and sentiment data to perform analysis in order to improve the quality of future advice.

[1233] Example of a prompt

[1234] Prompt 1: "Describe a system where a user inputs information about a task and receives the best advice. In particular, explain in detail how an emotion engine is used to improve the advice."

[1235] As described above, the present invention is a system that enables more efficient and effective task management by providing advice that takes into account the user's emotional state and by effectively utilizing feedback.

[1236] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1237] Step 1: User logs in and starts transfer mode.

[1238] Input: User ID, Password

[1239] procedure:

[1240] 1. The user launches the transfer application on their device.

[1241] 2. The user enters their user ID and password on the login screen.

[1242] 3. The terminal sends the entered login information to the server using the HTTPS protocol.

[1243] 4. The server compares the received login information with the database and performs user authentication.

[1244] 5. If authentication is successful, the server generates an authentication token and sends it to the device.

[1245] 6. The device saves the authentication token and displays the transfer mode screen.

[1246] Output: Authentication token, display of the handover mode screen

[1247] Step 2: The server lists the tasks to be handed over.

[1248] Input: Authentication token, Task list request

[1249] procedure:

[1250] 1. The user clicks the "Get Task List" button on the handover mode screen.

[1251] 2. The device sends a request to the server for a task list containing an authentication token.

[1252] 3. The server verifies the authentication token and confirms that the user has the necessary permissions.

[1253] 4. The server queries the database for the tasks to be handed over and retrieves them.

[1254] 5. Organize the tasks acquired by the server by category and set their priorities.

[1255] 6. Send the organized task list to your device.

[1256] 7. Display the task list received by the device to the user.

[1257] Output: Task list

[1258] Step 3: If the user gets lost while working on the task, they should request advice.

[1259] Input: Current task information, authentication token

[1260] procedure:

[1261] 1. If a user is unsure how to proceed with a task, they can click the "Request Advice" button.

[1262] 2. The device sends the current task information and authentication token to the server.

[1263] 3. The server analyzes the received data and searches the database for relevant documents and past solutions.

[1264] 4. The server generates optimal advice based on the search results using an AI model.

[1265] 5. The server sends the generated advice to the terminal.

[1266] 6. Display the advice received by the device to the user.

[1267] Output: Advice

[1268] Step 4: The user progresses through the task and provides feedback using the emotion engine.

[1269] Input: Sentiment data, feedback information

[1270] procedure:

[1271] 1. The user proceeds with the task following the advice.

[1272] 2. The user enters their current emotional state on the emotion engine screen.

[1273] 3. The device sends emotional data to the server.

[1274] 4. The server generates more specific advice based on emotional data. A generation AI model is used as needed.

[1275] 5. The generated advice is sent to the device, and the device displays it to the user.

[1276] 6. When the user completes the task, the device displays a feedback input screen.

[1277] 7. Users provide feedback on the effectiveness of the advice and any problems they encountered while completing the task.

[1278] 8. The device sends feedback to the server.

[1279] Output: Sentiment data, feedback

[1280] Step 5: The server analyzes feedback and sentiment data and uses it to improve the system.

[1281] Input: Feedback, sentiment data

[1282] procedure:

[1283] 1. The server saves the feedback and sentiment data received from the terminal to a database.

[1284] 2. The server queries the database and parses the received data.

[1285] 3. The server will consider ways to improve the quality of advice based on the analysis results.

[1286] 4. The server implements the improvements and updates the functionality of the entire system.

[1287] Output: System improvement proposal

[1288] The above outlines the specific processing steps of this system's program, along with details of the operation and input / output for each step.

[1289] (Application Example 2)

[1290] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[1291] Traditional task management systems often fail to consider the user's emotions or psychological state, simply providing formulaic advice. This has resulted in insufficient support, especially when users are facing difficult situations or experiencing stress. Furthermore, the lack of adaptive support to improve task processing efficiency degrades the user experience of the system.

[1292] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[1293] In this invention, the server includes means for acquiring and transmitting user emotion data to the server, means for generating appropriate advice based on the task being processed and the acquired emotion data and transmitting it to the terminal, and means for generating optimal advice considering the emotion data. This makes it possible to provide appropriate advice that takes into account the user's emotions and psychological state, improving the efficiency of task processing and enhancing the user experience.

[1294] A "task" is a specific task or activity that a user is required to accomplish.

[1295] User authentication is the process of verifying the identification information that a user enters to access a system, and confirming that they are a legitimate user.

[1296] "Emotional data" refers to data that represents the user's psychological state and emotions, and is acquired by an emotion recognition engine.

[1297] "Advice" refers to information and methods that users can use as a reference when carrying out a task.

[1298] "Feedback" refers to the opinions and evaluations that users provide after completing a task, regarding the effectiveness of the advice given and any problems encountered during the task.

[1299] An "emotion recognition engine" is software or algorithms that analyze a user's emotions and psychological state and generate data based on that analysis.

[1300] A "terminal" is a device that a user operates to input information or to view displayed advice.

[1301] A "database" is a system or structure used to organize and store information about tasks, users, and feedback.

[1302] "Advice generation" is the process by which a server creates instructions to provide the user with the best possible support, based on the user's task information and sentiment data.

[1303] A "server" is a central computer system that processes user input, manages tasks, and generates and provides advice.

[1304] To implement this invention, it is necessary to construct a task management system with excellent emotion recognition capabilities. This system is realized through the cooperation of a server, terminals, and users, and uses an emotion recognition engine to provide optimal advice that takes into account the user's psychological state.

[1305] System Configuration

[1306] Hardware and software

[1307] Hardware:

[1308] Device: Smartphone or head-mounted display (HMD)

[1309] Server: High-performance computer system

[1310] software:

[1311] Emotion recognition engine: Emotion recognition libraries such as Affectiva SDK

[1312] Applications: Python, Requests library, etc.

[1313] Explanation of natural language processing

[1314] User authentication and task information retrieval via the device.

[1315] The user logs into the device and sends authentication information to the server. The server generates an authentication token and sends it back to the device to authenticate the user. The server then retrieves the task to be handed over from the database and sends it to the device. The device displays this to the user, and the user selects a specific task.

[1316] Requesting and providing advice

[1317] If a user encounters difficulties while working on a task, they can request advice from their device. The server retrieves the user's emotional data and analyzes it using an emotional recognition engine. It then searches past solutions and documentation to generate the most appropriate advice, taking the emotional data into account. The generated advice is sent to the device and displayed to the user.

[1318] Use of emotional data and feedback

[1319] Users input emotional data during and after tasks and send it to the server. The server generates more appropriate advice based on the received emotional data. Additionally, users can input feedback after completing tasks, which the server stores in a database and analyzes. The analysis results are used to improve the quality of future advice generation.

[1320] Specific example

[1321] When User A performs video editing work on a new project

[1322] User A launches the task management application and logs in. The server performs authentication and retrieves and displays a list of tasks related to the project. User A selects a specific editing task. If User A encounters difficulties in choosing an effect during the editing process, they press the "Request Advice" button. The server analyzes User A's emotional data and suggests the best way to choose an effect. User A follows the suggested advice and continues editing. After completing the task, User A provides feedback on the effectiveness of the advice and sends it to the server along with their emotional data. The server analyzes this data and uses it to improve the entire system.

[1323] Example of a prompt

[1324] Example prompts for generating advice on video editing tasks:

[1325] Generate advice for when you're stuck on choosing effects while editing a new project. Your current emotion is "frustrated." Also, suggest a basic, step-by-step approach.

[1326] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1327] Step 1:

[1328] The user enters their login information (user ID and password) into the terminal and presses the submit button. The terminal sends this input information to the server. The server authenticates the user, and if the correct authentication information is provided, it generates an authentication token and sends it back to the terminal. The terminal saves this authentication token and notifies the user that the login was successful. In this step, the user ID and password are provided as input information, and an authentication token is output.

[1329] Step 2:

[1330] The terminal uses an authentication token to request a list of tasks to be handed over from the server. The server retrieves the tasks to be handed over from the database, organizes them by category, sets priorities, and sends the task list to the terminal. The terminal displays the received task list to the user, allowing the user to select which tasks to process. In this step, the authentication token and the task list request are provided as input information, and the organized task list is output.

[1331] Step 3:

[1332] When a user selects a task, detailed information about that task is displayed on the device. If the user gets lost while working on the task, they click the "Request Advice" button. The device sends the current task information and authentication token to the server. The server analyzes the task information and sentiment data, and searches for relevant documents and past solutions. In this step, task information and an authentication token are provided as input, and advice is output as a result of the analysis.

[1333] Step 4:

[1334] The server generates optimal advice based on sentiment data and sends it to the terminal. The terminal displays the received advice to the user. This information includes specific solutions and next steps. In this step, the analysis results and sentiment data are provided as input information, and appropriate advice is output.

[1335] Step 5:

[1336] As the user progresses through the task, they can request further advice as needed. Once the user completes the task, they input their current emotional data using the emotion engine, and the device sends this data to the server. The server analyzes this data, generates final feedback, and stores it. In this step, emotional data and task information are provided as input, and feedback is output as the analysis result.

[1337] Step 6:

[1338] The server stores accumulated emotional data and feedback in a database and performs analysis. Based on the analysis results, improvements are made to enhance the quality of advice. These improvements are reflected in subsequent advice generation, thereby improving the overall system performance. In this step, emotional data and feedback are provided as input information, and the system improvements are output.

[1339] 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.

[1340] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1341] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[1342] [Fourth Embodiment]

[1343] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[1344] 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.

[1345] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1346] 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.

[1347] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[1348] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[1349] 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.

[1350] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[1351] 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.

[1352] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1353] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1354] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[1355] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1356] This section will describe specific embodiments for implementing this invention. First, we will begin by understanding the overall flow of this system and the role of each element.

[1357] System Overview

[1358] This system allows users to input information about tasks, and the terminal and server work together to manage the tasks being handed over. It also provides appropriate advice when users are unsure how to proceed. Furthermore, users provide feedback after completing tasks, and the server analyzes this feedback to improve the system.

[1359] A natural language explanation of the program's processing.

[1360] The user logs into the device and starts the transfer mode.

[1361] The user launches a dedicated transfer application on their device and enters their login information (user ID and password). The device sends the entered login information to the server. The server receives this information, compares it with the database, and authenticates the user. Once authenticated, the server generates an authentication token and sends it to the device. The device saves the authentication token and displays the transfer mode screen.

[1362] The server lists the tasks to be handed over.

[1363] When a user enters handover mode, the device requests a list of tasks to be handed over from the server. This request also includes an authentication token. The server retrieves the tasks to be handed over from the database, organizes them by category, and sets their priorities. It then sends the organized task list to the device. The device displays the received task list to the user, allowing the user to select the tasks they wish to handle.

[1364] If a user is unsure how to proceed with a task, they can request advice.

[1365] If a user gets stuck while working on a task, they click the "Request Advice" button. The device sends the current task information and authentication token to the server. The server analyzes the submitted task information and searches for relevant documentation and past solutions. Based on the search results, the server generates appropriate advice and sends it to the device. The device then displays the received advice to the user.

[1366] Users progress through tasks and provide feedback.

[1367] The user follows the advice and completes the task. After task completion, the device displays a feedback input screen. The user provides feedback on the effectiveness of the advice and any problems encountered during task processing. The device sends the entered feedback to the server.

[1368] The server analyzes the feedback and uses it to improve the system.

[1369] The server stores the received feedback in a database. It then analyzes the stored feedback to consider ways to improve the quality of the advice. This enables effective improvements to the entire system.

[1370] Specific example

[1371] Specific examples are given below.

[1372] When User A takes over the task "Create Monthly Report"

[1373] User A launches the transfer application and clicks "Start Transfer".

[1374] The server lists past tasks and solutions related to the creation of the monthly report and sends them to the terminal.

[1375] When User A is having trouble with the report format, they click the "Request Advice" button.

[1376] The server suggests the optimal format based on past formatting examples and sends it to the terminal.

[1377] User A creates a report using the proposed format and completes the task.

[1378] After completion, User A enters feedback on whether the advice was effective and sends it to the server.

[1379] The server uses this feedback to analyze and improve the quality of future advice.

[1380] In this way, this system enables efficient handover processes when personnel changes occur, allowing for the smooth progress of operations.

[1381] The following describes the processing flow.

[1382] Step 1:

[1383] The user launches a dedicated transfer application on their device. The device displays the initial screen.

[1384] Step 2:

[1385] The user enters their user ID and password. The terminal sends this information to the server.

[1386] Step 3:

[1387] The server authenticates the user by comparing the received user ID and password with the database. If authentication is successful, the server generates an authentication token and sends it to the terminal. If authentication fails, the server sends an error message to the terminal.

[1388] Step 4:

[1389] The device saves the authentication token and displays the transfer mode screen to the user. The user clicks the "Start Transfer" button.

[1390] Step 5:

[1391] The device sends a request to the server for the task list to be handed over. This request includes an authentication token.

[1392] Step 6:

[1393] The server retrieves the tasks to be handed over from the database, organizes them by category, and sets their priorities. It then sends the organized task list to the terminal.

[1394] Step 7:

[1395] The terminal displays a list of received tasks to the user. The user selects a task to process from the displayed list.

[1396] Step 8:

[1397] If a user gets lost while processing a task, they can click the "Request Advice" button. The device will then send the current task information and authentication token to the server.

[1398] Step 9:

[1399] The server analyzes the received task information and searches the database for relevant documents and past solutions.

[1400] Step 10:

[1401] The server generates optimal advice based on the search results and sends it to the terminal.

[1402] Step 11:

[1403] The device displays the advice it receives to the user. The user then proceeds with the task while referring to the displayed advice.

[1404] Step 12:

[1405] Once the user completes a task, the device displays a feedback input screen. The user provides feedback on the effectiveness of the advice and any problems encountered during task completion.

[1406] Step 13:

[1407] The terminal sends the input feedback to the server. The server stores the received feedback in a database.

[1408] Step 14:

[1409] The server analyzes the stored feedback and considers ways to improve the quality of the advice.

[1410] In this way, the entire system flows smoothly, allowing users to efficiently take over tasks and quickly receive necessary advice.

[1411] (Example 1)

[1412] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1413] Traditional work handover systems often made it difficult to resolve problems during the process, resulting in decreased work efficiency. Furthermore, feedback was not properly utilized, hindering system improvements.

[1414] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[1415] In this invention, the server includes means for user authentication, means for retrieving and listing the tasks to be handed over from a database, and means for searching for relevant documents and past solutions and generating optimal advice. This enables smooth problem-solving during the task process and allows for continuous improvement of the system based on feedback.

[1416] A "user" refers to an individual or group that uses a system to input business information and perform tasks.

[1417] "Business operations" refers to tasks managed within a system and the series of activities related to their processing.

[1418] "Data" refers to various types of information that users input into the system, as well as information that the system generates or acquires based on that information.

[1419] A "terminal" refers to a hardware device, such as a computer or mobile device, operated by a user, and is a device that communicates with a system.

[1420] A "server" refers to a central processing unit that performs various tasks such as user authentication, database management, task list generation, and advice generation.

[1421] A "database" refers to a system for systematically storing data such as business information, user information, past solutions, and feedback.

[1422] "Advice" refers to the knowledge and guidance that users need to carry out their tasks, as well as the solutions and recommendations generated by the system.

[1423] "Authentication" refers to the process by which a system verifies the identity of a user, and is a means of confirming that the user is legitimate.

[1424] "Feedback" refers to the opinions and evaluations that users enter into the system after completing a task.

[1425] "Searching" refers to the process by which a server finds relevant documents or past solutions.

[1426] "Analysis" refers to the process by which a server processes received feedback and task information to derive useful insights and areas for improvement.

[1427] "Listing" refers to the process by which a server organizes and displays business information retrieved from a database.

[1428] The specific embodiments of this invention will be described in detail below. First, we will begin by understanding the overall flow of this system and the role of each element.

[1429] System Overview

[1430] This system allows users to input data related to their work, and the terminal and server work together to manage the tasks being handed over. It also provides appropriate advice when problems arise during the process. Furthermore, users input feedback after completing tasks, and the server analyzes this feedback to improve the system. The main components of the system are described below.

[1431] The user logs into the device and starts the transfer mode.

[1432] The user launches a dedicated transfer application (TaskTransferApp) on their device and enters their login information (user ID and password). The device sends the entered login information to the server as an HTTP POST request. The server verifies the information against the database (MySQL) and performs user authentication. If authentication is successful, the server generates a JSON Web Token (JWT) and sends it back to the device. The device saves the received authentication token and displays the transfer mode screen.

[1433] The server lists the tasks to be handed over.

[1434] When the device enters handover mode, it sends an authentication token to the server and requests the task list to be handed over. The server retrieves the user's relevant work information from the database, organizes the task list by category, and sorts it by priority. It sends the organized task list to the device, which then displays the task list to the user.

[1435] If a user is unsure how to proceed with their work, they can request advice.

[1436] If a user encounters difficulties while working, they click the "Request Advice" button. The terminal sends current work information and an authentication token to the server. The server analyzes the information received and searches for relevant documents and past solutions. Using a search engine (Elasticsearch), it generates the best advice and sends it to the terminal. The terminal then displays the received advice to the user.

[1437] Users carry out tasks and provide feedback.

[1438] Once the user completes the task following the advice from the server, the terminal displays a feedback input screen. The user enters and submits feedback regarding the effectiveness of the advice and any problems encountered during the task. The terminal then sends the entered feedback to the server.

[1439] The server analyzes the feedback and uses it to improve the system.

[1440] The server receives feedback and stores it in a database. The stored feedback is analyzed periodically, and the data is analyzed using a machine learning model (Scikit-learn). Based on the analysis results, system improvements are considered, and software updates or new features are added as needed.

[1441] Specific example

[1442] Specific examples are given below.

[1443] If User A takes over the creation of the monthly report

[1444] User A launches the transfer application and clicks "Start Transfer".

[1445] The server lists past tasks and solutions related to the creation of monthly reports and sends them to the terminal.

[1446] When User A is having trouble with the report format, they click the "Request Advice" button.

[1447] The server suggests the optimal format and sends it to the terminal.

[1448] User A creates a report using the proposed format and completes the task.

[1449] After completion, User A enters feedback and sends it to the server.

[1450] The server analyzes the feedback to improve the quality of future advice.

[1451] Example of a prompt

[1452] The following are examples of prompts to input into the generative AI model.

[1453] "What is the best format for creating monthly reports?"

[1454] "What should I do when I encounter difficulties in completing a task?"

[1455] By using this prompt, you can receive appropriate advice from the AI ​​model.

[1456] The flow of the specific processing in Example 1 will be explained using Figure 11.

[1457] Step 1:

[1458] The user launches a dedicated transfer application on their device. The user enters their user ID and password on the login screen. The device sends the entered user ID and password to the server as an HTTP POST request. The server compares the received login information with its database and authenticates the user. The input is the user ID and password, and the output is whether the authentication was successful or unsuccessful and a JWT authentication token. If authentication is successful, the server generates an authentication token and sends it back to the device. The device saves the authentication token and displays the transfer mode screen.

[1459] Step 2:

[1460] The user clicks a button to enter handover mode. The terminal issues an authentication token and requests the server for a list of tasks to be handed over. The server retrieves the user's relevant business information from the database. The input is the authentication token and task request, and the output is the user's relevant business information. The server organizes the retrieved information by category and sorts it by priority. The organized task list is sent to the terminal, which then displays the task list to the user.

[1461] Step 3:

[1462] If a user encounters difficulties while working, they click the "Request Advice" button. The terminal sends current work information and an authentication token to the server. The server analyzes the received work information and searches for relevant documents and past solutions. The input is work information and an authentication token, and the output is appropriate advice. The server uses a search engine to search the data, generates the best advice, and sends it to the terminal. The terminal displays the received advice to the user.

[1463] Step 4:

[1464] The user proceeds with the task according to the advice from the server and completes the task. After task completion, the terminal displays a feedback input screen. The user enters feedback on the effectiveness of the advice and any problems encountered during the task, and clicks the submit button. The input is feedback on the effectiveness of the advice and any problems encountered, and the output is feedback data. The terminal sends the entered feedback to the server.

[1465] Step 5:

[1466] The server stores the received feedback in a database. The input is the feedback data, and the output is the collection of stored feedback data. The server periodically analyzes the stored feedback. It uses machine learning models to analyze the data and considers ways to improve the system based on the analysis results. It updates the software and adds new features as needed to improve the overall system performance.

[1467] (Application Example 1)

[1468] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1469] Staff shift changes and handovers at logistics centers are time-consuming and prone to errors and omissions. Furthermore, existing systems lack the means to obtain quick and appropriate advice when problems arise during task execution, leading to decreased operational efficiency. Additionally, there is no mechanism in place to incorporate feedback after task completion into system improvements. To address these challenges, a more efficient and reliable task management system is needed.

[1470] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[1471] In this invention, the server includes means for staff at a logistics center to manage handover tasks using smartphones and request advice and procedures; means for displaying a task list obtained from the server via an application installed on the smartphone, allowing staff to request advice during sorting work; means for the server to generate optimal advice using a recommendation algorithm based on past relevant documents and solutions; and means for the server to perform analysis to improve the entire system based on feedback entered by staff after task completion. This enables more efficient task handover at the logistics center, quicker response to problems, and system improvements based on feedback.

[1472] "User authentication" is the process by which a system verifies the user's identity and grants them access rights.

[1473] A "terminal" is a device that a user operates and uses to exchange input and display information.

[1474] A "server" is a computer system that processes and stores data on a network and provides information to other terminals.

[1475] A "task list" is a list of tasks related to a specific job.

[1476] An "advice request" is an operation in which a user asks the server for advice when they get stuck while processing a task.

[1477] A "recommendation algorithm" is a computational method used by a system to generate optimal advice based on historical data and relevant documents.

[1478] "Feedback" refers to the opinions and impressions that users provide after completing a task.

[1479] A "logistics center" is a facility that handles logistics operations such as storing, sorting, and shipping goods and materials.

[1480] A "smartphone" is a portable information terminal that combines the functions of a mobile phone and a computer, and is capable of running applications.

[1481] "Handover tasks" refer to the new responsibilities that need to be taken on due to shift changes or changes in personnel.

[1482] A "document" is an official document or record related to a specific job or task.

[1483] "System improvement" refers to activities aimed at improving overall functionality and performance by analyzing collected feedback and data.

[1484] Specific embodiments for carrying out this invention will now be described. First, this system is intended for task management and advice provision in a logistics center. The entire system consists of a smartphone, a server, and a network.

[1485] System Overview

[1486] This system uses the following methods to perform each step:

[1487] 1. User input information

[1488] Users enter task-related information using a dedicated application installed on their smartphones.

[1489] 2. Data transmission from terminal to server

[1490] A smartphone (device) sends information entered by the user to a server. This transmission uses a network.

[1491] 3. User authentication on the server

[1492] The server performs user authentication based on the user's authentication information (user ID and password). If authentication is successful, an authentication token is returned to the smartphone.

[1493] 4. Retrieving and displaying the task list

[1494] After authentication, the server retrieves the tasks to be handed over from the database and displays them as a list on the smartphone.

[1495] 5. Requesting and providing advice

[1496] If a user gets stuck while working on a task, they can click the "Request Advice" button on their smartphone. The server searches relevant documents and past solutions, and uses a generative AI model to provide the best advice. This advice is then displayed on the smartphone.

[1497] 6. Providing feedback after task completion

[1498] After completing a task, users input feedback on the effectiveness of the advice and any problems encountered during task processing via their smartphones and send it to the server.

[1499] 7. Analysis of feedback and system improvement

[1500] The server analyzes the information in the database based on the collected feedback and works to improve the entire system.

[1501] Hardware and software

[1502] hardware

[1503] Smartphone (user device)

[1504] Server (data processing and storage)

[1505] Network infrastructure (data communication)

[1506] software

[1507] A dedicated application installed on a smartphone

[1508] Server-side authentication system

[1509] Server-side database management system

[1510] Recommended algorithms (including generative AI models)

[1511] Specific example

[1512] Specific examples are given below.

[1513] 1. Handover of sorting duties

[1514] Example of a prompt:

[1515] This scenario involves a user taking over sorting tasks. Please outline the steps for obtaining the task list and starting a new task. Include procedures for requesting advice and providing feedback if difficulties arise during task completion.

[1516] The user logs in using the smartphone app and retrieves the task list.

[1517] Based on the task list, select and begin today's sorting tasks.

[1518] If you get stuck during the sorting process, click the "Request Advice" button to receive appropriate advice from the server.

[1519] Once the sorting process is complete, enter feedback into the app and submit it.

[1520] This system streamlines task handover in logistics centers, enables rapid response to problems, and improves the system based on feedback.

[1521] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[1522] Step 1:

[1523] The user launches a dedicated application installed on their smartphone and enters their login information (user ID and password). The device sends this information to the server. The input data consists of the user ID and password, and the output is a request for authentication processing on the server. Specifically, the device receives the user ID and password on the login screen, encrypts them, and sends them to the server.

[1524] Step 2:

[1525] The server performs user authentication. The server compares the received login information with the information in the database to authenticate the user. The input data is the user ID and password, which are compared with the user information retrieved from the database. The output is the generation of an authentication token. Specifically, the server retrieves the user ID and hashed password from the database and compares them with the received information. If authentication is successful, the server generates an authentication token and sends it to the terminal.

[1526] Step 3:

[1527] When a user enters handover mode, the device requests the task list from the server. The input data is an authentication token, and the output is a request for the task list to be handed over. Specifically, the device sends an authentication token to the server and then requests the task list.

[1528] Step 4:

[1529] The server retrieves tasks to be handed over from the database, organizes them by category, and sets their priorities. The input data is an authentication token and user ID, and the output is a task list organized by category. Specifically, the server retrieves relevant task information from the database, classifies it into categories to facilitate handover, and sets its priorities.

[1530] Step 5:

[1531] The terminal displays a task list retrieved from the server to the user. The input data is a task list organized by category, and the output is a task list screen that the user can view. Specifically, the terminal displays the task list retrieved from the server on the screen, allowing the user to review it.

[1532] Step 6:

[1533] If a user gets lost while processing a task, they click the "Request Advice" button. The device then sends the current task information and authentication token to the server. The input data is the current task information and authentication token, and the output is an advice request to the server. Specifically, the user clicks the "Request Advice" button on the screen, which triggers the device to send the task information and authentication token to the server.

[1534] Step 7:

[1535] The server analyzes the submitted task information and searches for relevant documents and past solutions. The input data consists of task information and an authentication token, and the output consists of relevant documents and past solutions. Specifically, the server searches for relevant documents in the database based on the task information and analyzes past solutions using a generative AI model.

[1536] Step 8:

[1537] The server generates optimal advice and sends it to the terminal. The input data consists of relevant documents and past solutions, and the output is the optimal advice. Specifically, the server uses a generation AI model to generate optimal advice and sends it to the terminal.

[1538] Step 9:

[1539] The device displays the advice it receives to the user. The input data is the optimal advice, and the output is an advice screen that the user can view. Specifically, the device displays the advice it receives from the server on the screen, allowing the user to review it.

[1540] Step 10:

[1541] The user enters feedback after completing a task. The device sends the entered feedback to the server. The input data is the feedback content, and the output is the feedback submission request to the server. Specifically, the user enters feedback on the feedback input screen and clicks the submit button.

[1542] Step 11:

[1543] The server stores the feedback in a database and analyzes it. The input data is the feedback content, and the output is the feedback analysis results. Specifically, the server stores the feedback in a database and analyzes that data to use for future system improvements.

[1544] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[1545] This invention will now describe a specific embodiment for carrying it out. This system allows the user to input information about a task, and the terminal and server work together to manage the task being handed over, providing appropriate advice when the user is unsure how to proceed. Furthermore, by incorporating an emotion engine that recognizes the user's emotions, it is possible to provide even more appropriate advice. After the user completes a task, they provide feedback, which the server analyzes to improve the system.

[1546] System Overview

[1547] This system consists of the following elements:

[1548] 1. Means by which users can input information about a task.

[1549] 2. Means by which the terminal transmits user input information to the server

[1550] 3. Means by which the server performs user authentication

[1551] 4. A method by which the server retrieves and lists the tasks to be handed over from the database.

[1552] 5. Means for displaying the task list obtained from the server by the terminal to the user.

[1553] 6. Means by which users can request advice while processing a task.

[1554] 7. Means for the server to generate and send appropriate advice regarding the task it is currently processing to the terminal.

[1555] 8. Means for displaying advice obtained from the server by the terminal to the user.

[1556] 9. A means for users to provide feedback after completing a task.

[1557] 10. Means for the server to store and analyze feedback in a database.

[1558] 11. Emotion engine that recognizes user emotions

[1559] 12. A means of generating more appropriate advice based on user emotion data received from the emotion engine.

[1560] A natural language explanation of the program's processing.

[1561] The user logs into the device and starts the transfer mode.

[1562] The user launches a dedicated transfer application on their device and enters their login information (user ID and password). The device sends the entered login information to the server, which receives it, compares it with the database, and authenticates the user. Once authenticated, the server generates an authentication token and sends it to the device. The device saves the authentication token and displays the transfer mode screen.

[1563] The server lists the tasks to be handed over.

[1564] When a user enters handover mode, the device sends a request to the server for a list of tasks to be handed over. The server retrieves the tasks to be handed over from the database, organizes them by category, sets priorities, and sends the task list to the device. The device displays the received task list to the user. The user selects a task to process from the displayed list.

[1565] If a user is unsure how to proceed with a task, they can request advice.

[1566] If a user gets stuck while working on a task, they click the "Request Advice" button. The device sends the current task information and authentication token to the server. The server analyzes the submitted task information and searches for relevant documentation and past solutions. Based on the search results, the server generates the best advice and sends it to the device. The device then displays the received advice to the user.

[1567] Users progress through tasks and provide feedback using an emotion engine.

[1568] As the user progresses through a task following the advice, they input their current emotions using the emotion engine. The device sends this emotion data to the server. Based on the emotion data, the server generates more appropriate advice and sends it back to the device. Once the user completes the task, the device displays a feedback input screen. The user provides feedback on the effectiveness of the advice and any problems encountered during task completion. The device sends the input feedback back to the server.

[1569] The server analyzes feedback and sentiment data and uses it to improve the system.

[1570] The server stores the received feedback and sentiment data in a database and performs analysis. Based on the analysis results, the server considers ways to improve the quality of advice and makes improvements to the entire system.

[1571] Specific example

[1572] Specific examples are given below.

[1573] When User A takes over the task "Create Monthly Report"

[1574] User A launches the transfer application and clicks "Start Transfer".

[1575] The server lists past tasks and solutions related to the creation of the monthly report and sends them to the terminal.

[1576] When User A is having trouble with the report format, they click the "Request Advice" button.

[1577] The server suggests the optimal format based on past formatting examples and sends it to the terminal.

[1578] When User A creates a report following the advice, they input their current emotions using the emotion engine.

[1579] The server takes user A's emotions into consideration and provides more specific advice.

[1580] User A creates a report using the proposed format and completes the task.

[1581] After completion, User A sends feedback to the server indicating whether the advice was effective, along with their own emotional data.

[1582] The server uses this feedback and sentiment data to perform analysis in order to improve the quality of future advice.

[1583] By combining this with an emotion engine, more appropriate advice that takes into account the user's psychological state is provided, making the handover process more efficient and effective.

[1584] The following describes the processing flow.

[1585] Step 1:

[1586] The user launches a dedicated transfer application on their device. The device displays the initial screen.

[1587] Step 2:

[1588] The user enters their user ID and password. The terminal sends the entered information to the server.

[1589] Step 3:

[1590] The server authenticates the user by comparing the received user ID and password with the database. If authentication is successful, the server generates an authentication token and sends it to the terminal. If authentication fails, the server sends an error message to the terminal.

[1591] Step 4:

[1592] The device saves the authentication token and displays the transfer mode screen to the user. The user clicks the "Start Transfer" button.

[1593] Step 5:

[1594] The device sends a request to the server for the task list to be handed over. This request includes an authentication token.

[1595] Step 6:

[1596] The server retrieves the tasks to be handed over from the database, organizes them by category, and sets their priorities. It then sends the organized task list to the terminal.

[1597] Step 7:

[1598] The terminal displays a list of received tasks to the user. The user selects a task to process from the displayed list.

[1599] Step 8:

[1600] If a user gets lost while processing a task, they can click the "Request Advice" button. The device will then send the current task information and authentication token to the server.

[1601] Step 9:

[1602] The server analyzes the received task information and searches the database for relevant documents and past solutions.

[1603] Step 10:

[1604] The server generates optimal advice based on the search results and sends it to the terminal.

[1605] Step 11:

[1606] The device displays the advice it receives to the user. The user then proceeds with the task while referring to the displayed advice.

[1607] Step 12:

[1608] The user inputs their current emotion using an emotion engine. The device then sends the emotion data to the server.

[1609] Step 13:

[1610] The server analyzes the emotional data, generates additional advice that takes the user's emotional state into account, and sends it to the terminal.

[1611] Step 14:

[1612] The device displays any additional advice it has received to the user. The user then uses this advice to proceed with the task.

[1613] Step 15:

[1614] Once the user completes a task, the device displays a feedback input screen. The user provides feedback on the effectiveness of the advice and any problems encountered during task completion.

[1615] Step 16:

[1616] The device sends the input feedback and sentiment data to the server. The server stores the received feedback and sentiment data in a database.

[1617] Step 17:

[1618] The server analyzes stored feedback and sentiment data to explore ways to improve the quality of advice.

[1619] Through the above processing steps, users can efficiently perform the handover and receive necessary advice quickly and appropriately. Furthermore, the introduction of an emotion engine provides more appropriate advice that takes into account the user's psychological state.

[1620] (Example 2)

[1621] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1622] Current task management systems often fail to provide users with appropriate advice when they encounter difficulties during task completion, and furthermore, they do not offer advice that takes into account the user's emotional state, making efficient task completion difficult. Another issue is that feedback after task completion is not adequately utilized for system improvement.

[1623] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[1624] In this invention, the server includes means for the user to input information about a task, means for the terminal to transmit the user's input information to the server, means for the server to perform user authentication, means for the server to retrieve and list tasks to be handed over from a database, means for the terminal to display the task list retrieved from the server to the user, means for the user to request advice while processing a task, means for the server to generate appropriate advice regarding the task being processed and send it to the terminal, means for the terminal to display the advice retrieved from the server to the user, means for the user to input feedback after completing a task, means for the server to store and analyze the feedback in a database, means equipped with an emotion engine that recognizes the user's emotions, means for generating more appropriate advice based on the user's emotion data received from the emotion engine, means for the server to send the generated advice to the terminal, and means for the terminal to display the advice to the user. As a result, the user can receive appropriate advice while working on a task, appropriate support that takes into account their emotional state is possible, and feedback after task completion is effectively utilized for system improvement.

[1625] A "user" is someone who uses the system to input task information and provide feedback.

[1626] A "terminal" is a device that a user operates, sends input information to a server, and receives data from the server.

[1627] A "server" is a central computing system that performs user authentication, retrieves tasks from a database, generates advice, and sends it to terminals.

[1628] An "authentication token" is temporary data used to verify user authentication and maintain a session.

[1629] A "database" is a system for storing and managing task information, user feedback, and sentiment data.

[1630] A "task list" is a list of tasks to be handed over that the server retrieves from the database and displays to the user.

[1631] "Advice" refers to solutions or suggestions that a server provides to a user who is unsure how to proceed with a task.

[1632] An "emotion engine" is a system that recognizes emotions based on user input and analyzes that data.

[1633] "Feedback" refers to the opinions and evaluations of the processing results and the system that users provide after completing a task.

[1634] Specific embodiments for carrying out this invention will now be described. This system allows the user to input information about a task, and the terminal and server work together to take over and manage the task. In particular, it is characterized by providing appropriate advice when the user is unsure during task processing and by providing more accurate support using the user's emotional data.

[1635] System Configuration

[1636] This system consists of the following elements:

[1637] 1. Means by which users can input information about a task.

[1638] The user launches a dedicated handover application on their device and enters information about the task. This information includes the task name, details, and deadline.

[1639] 2. Means by which the terminal transmits user input information to the server

[1640] The terminal sends the entered task information and login information to the server using the HTTPS protocol.

[1641] 3. Means by which the server performs user authentication

[1642] The server compares the received user ID and password with the database to authenticate the user. If authentication is successful, it generates an authentication token and sends it to the terminal.

[1643] 4. A method by which the server retrieves and lists the tasks to be handed over from the database.

[1644] The server retrieves the tasks to be handed over from the database, lists them by category and priority, and sends them to the terminal.

[1645] 5. Means for displaying the task list obtained from the server by the terminal to the user.

[1646] The device displays the received task list on the user's screen. The user can select a task to process from the displayed list.

[1647] 6. Means by which users can request advice while processing a task.

[1648] If a user is unsure how to proceed with a task, they can click the "Request Advice" button to send their current task information to the server.

[1649] 7. Means for the server to generate and send appropriate advice regarding the task being processed to the terminal.

[1650] The server analyzes task information, searches for relevant documents and past solutions, generates optimal advice using an AI model, and sends it to the terminal.

[1651] 8. Means for displaying advice obtained from the server by the terminal to the user.

[1652] The device displays the received advice on the user's screen.

[1653] 9. A means for users to provide feedback after completing a task.

[1654] After completing a task, users provide feedback on the effectiveness of the advice and any problems they encountered.

[1655] 10. Means for the server to store and analyze feedback in a database.

[1656] The server stores feedback in a database, analyzes it, and uses it to improve the system.

[1657] 11. Emotion engine that recognizes user emotions

[1658] The emotion engine receives emotional data from the user and recognizes their emotional state.

[1659] 12. A means of generating more appropriate advice based on user emotion data received from the emotion engine.

[1660] The server generates more personalized advice based on the emotional data received from the emotion engine and sends it to the device.

[1661] Specific example

[1662] Specific examples are given below.

[1663] Example 1: When User A takes over the task "Create Monthly Report"

[1664] User A launches the transfer application and clicks "Start Transfer".

[1665] The server lists past tasks and solutions related to the creation of the monthly report and sends them to the terminal.

[1666] When User A is having trouble with the report format, they click the "Request Advice" button.

[1667] The server suggests the optimal format based on past formatting examples and sends it to the terminal.

[1668] When User A creates a report following the advice, they input their current emotions using the emotion engine.

[1669] The server takes user A's emotions into consideration and provides more specific advice.

[1670] User A creates a report using the proposed format and completes the task.

[1671] After completion, User A sends feedback to the server indicating whether the advice was effective, along with their own emotional data.

[1672] The server uses this feedback and sentiment data to perform analysis in order to improve the quality of future advice.

[1673] Example of a prompt

[1674] Prompt 1: "Describe a system where a user inputs information about a task and receives the best advice. In particular, explain in detail how an emotion engine is used to improve the advice."

[1675] As described above, the present invention is a system that enables more efficient and effective task management by providing advice that takes into account the user's emotional state and by effectively utilizing feedback.

[1676] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1677] Step 1: User logs in and starts transfer mode.

[1678] Input: User ID, Password

[1679] procedure:

[1680] 1. The user launches the transfer application on their device.

[1681] 2. The user enters their user ID and password on the login screen.

[1682] 3. The terminal sends the entered login information to the server using the HTTPS protocol.

[1683] 4. The server compares the received login information with the database and performs user authentication.

[1684] 5. If authentication is successful, the server generates an authentication token and sends it to the device.

[1685] 6. The device saves the authentication token and displays the transfer mode screen.

[1686] Output: Authentication token, display of the handover mode screen

[1687] Step 2: The server lists the tasks to be handed over.

[1688] Input: Authentication token, Task list request

[1689] procedure:

[1690] 1. The user clicks the "Get Task List" button on the handover mode screen.

[1691] 2. The device sends a request to the server for a task list containing an authentication token.

[1692] 3. The server verifies the authentication token and confirms that the user has the necessary permissions.

[1693] 4. The server queries the database for the tasks to be handed over and retrieves them.

[1694] 5. Organize the tasks acquired by the server by category and set their priorities.

[1695] 6. Send the organized task list to your device.

[1696] 7. Display the task list received by the device to the user.

[1697] Output: Task list

[1698] Step 3: If the user gets lost while working on the task, they should request advice.

[1699] Input: Current task information, authentication token

[1700] procedure:

[1701] 1. If a user is unsure how to proceed with a task, they can click the "Request Advice" button.

[1702] 2. The device sends the current task information and authentication token to the server.

[1703] 3. The server analyzes the received data and searches the database for relevant documents and past solutions.

[1704] 4. The server generates optimal advice based on the search results using an AI model.

[1705] 5. The server sends the generated advice to the terminal.

[1706] 6. Display the advice received by the device to the user.

[1707] Output: Advice

[1708] Step 4: The user progresses through the task and provides feedback using the emotion engine.

[1709] Input: Sentiment data, feedback information

[1710] procedure:

[1711] 1. The user proceeds with the task following the advice.

[1712] 2. The user enters their current emotional state on the emotion engine screen.

[1713] 3. The device sends emotional data to the server.

[1714] 4. The server generates more specific advice based on emotional data. A generation AI model is used as needed.

[1715] 5. The generated advice is sent to the device, and the device displays it to the user.

[1716] 6. When the user completes the task, the device displays a feedback input screen.

[1717] 7. Users provide feedback on the effectiveness of the advice and any problems they encountered while completing the task.

[1718] 8. The device sends feedback to the server.

[1719] Output: Sentiment data, feedback

[1720] Step 5: The server analyzes feedback and sentiment data and uses it to improve the system.

[1721] Input: Feedback, sentiment data

[1722] procedure:

[1723] 1. The server saves the feedback and sentiment data received from the terminal to a database.

[1724] 2. The server queries the database and parses the received data.

[1725] 3. The server will consider ways to improve the quality of advice based on the analysis results.

[1726] 4. The server implements the improvements and updates the functionality of the entire system.

[1727] Output: System improvement proposal

[1728] The above outlines the specific processing steps of this system's program, along with details of the operation and input / output for each step.

[1729] (Application Example 2)

[1730] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1731] Traditional task management systems often fail to consider the user's emotions or psychological state, simply providing formulaic advice. This has resulted in insufficient support, especially when users are facing difficult situations or experiencing stress. Furthermore, the lack of adaptive support to improve task processing efficiency degrades the user experience of the system.

[1732] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[1733] In this invention, the server includes means for acquiring and transmitting user emotion data to the server, means for generating appropriate advice based on the task being processed and the acquired emotion data and transmitting it to the terminal, and means for generating optimal advice considering the emotion data. This makes it possible to provide appropriate advice that takes into account the user's emotions and psychological state, improving the efficiency of task processing and enhancing the user experience.

[1734] A "task" is a specific task or activity that a user is required to accomplish.

[1735] User authentication is the process of verifying the identification information that a user enters to access a system, and confirming that they are a legitimate user.

[1736] "Emotional data" refers to data that represents the user's psychological state and emotions, and is acquired by an emotion recognition engine.

[1737] "Advice" refers to information and methods that users can use as a reference when carrying out a task.

[1738] "Feedback" refers to the opinions and evaluations that users provide after completing a task, regarding the effectiveness of the advice given and any problems encountered during the task.

[1739] An "emotion recognition engine" is software or algorithms that analyze a user's emotions and psychological state and generate data based on that analysis.

[1740] A "terminal" is a device that a user operates to input information or to view displayed advice.

[1741] A "database" is a system or structure used to organize and store information about tasks, users, and feedback.

[1742] "Advice generation" is the process by which a server creates instructions to provide the user with the best possible support, based on the user's task information and sentiment data.

[1743] A "server" is a central computer system that processes user input, manages tasks, and generates and provides advice.

[1744] To implement this invention, it is necessary to construct a task management system with excellent emotion recognition capabilities. This system is realized through the cooperation of a server, terminals, and users, and uses an emotion recognition engine to provide optimal advice that takes into account the user's psychological state.

[1745] System Configuration

[1746] Hardware and software

[1747] Hardware:

[1748] Device: Smartphone or head-mounted display (HMD)

[1749] Server: High-performance computer system

[1750] software:

[1751] Emotion recognition engine: Emotion recognition libraries such as Affectiva SDK

[1752] Applications: Python, Requests library, etc.

[1753] Explanation of natural language processing

[1754] User authentication and task information retrieval via the device.

[1755] The user logs into the device and sends authentication information to the server. The server generates an authentication token and sends it back to the device to authenticate the user. The server then retrieves the task to be handed over from the database and sends it to the device. The device displays this to the user, and the user selects a specific task.

[1756] Requesting and providing advice

[1757] If a user encounters difficulties while working on a task, they can request advice from their device. The server retrieves the user's emotional data and analyzes it using an emotional recognition engine. It then searches past solutions and documentation to generate the most appropriate advice, taking the emotional data into account. The generated advice is sent to the device and displayed to the user.

[1758] Use of emotional data and feedback

[1759] Users input emotional data during and after tasks and send it to the server. The server generates more appropriate advice based on the received emotional data. Additionally, users can input feedback after completing tasks, which the server stores in a database and analyzes. The analysis results are used to improve the quality of future advice generation.

[1760] Specific example

[1761] When User A performs video editing work on a new project

[1762] User A launches the task management application and logs in. The server performs authentication and retrieves and displays a list of tasks related to the project. User A selects a specific editing task. If User A encounters difficulties in choosing an effect during the editing process, they press the "Request Advice" button. The server analyzes User A's emotional data and suggests the best way to choose an effect. User A follows the suggested advice and continues editing. After completing the task, User A provides feedback on the effectiveness of the advice and sends it to the server along with their emotional data. The server analyzes this data and uses it to improve the entire system.

[1763] Example of a prompt

[1764] Example prompts for generating advice on video editing tasks:

[1765] Generate advice for when you're stuck on choosing effects while editing a new project. Your current emotion is "frustrated." Also, suggest a basic, step-by-step approach.

[1766] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1767] Step 1:

[1768] The user enters their login information (user ID and password) into the terminal and presses the submit button. The terminal sends this input information to the server. The server authenticates the user, and if the correct authentication information is provided, it generates an authentication token and sends it back to the terminal. The terminal saves this authentication token and notifies the user that the login was successful. In this step, the user ID and password are provided as input information, and an authentication token is output.

[1769] Step 2:

[1770] The terminal uses an authentication token to request a list of tasks to be handed over from the server. The server retrieves the tasks to be handed over from the database, organizes them by category, sets priorities, and sends the task list to the terminal. The terminal displays the received task list to the user, allowing the user to select which tasks to process. In this step, the authentication token and the task list request are provided as input information, and the organized task list is output.

[1771] Step 3:

[1772] When a user selects a task, detailed information about that task is displayed on the device. If the user gets lost while working on the task, they click the "Request Advice" button. The device sends the current task information and authentication token to the server. The server analyzes the task information and sentiment data, and searches for relevant documents and past solutions. In this step, task information and an authentication token are provided as input, and advice is output as a result of the analysis.

[1773] Step 4:

[1774] The server generates optimal advice based on sentiment data and sends it to the terminal. The terminal displays the received advice to the user. This information includes specific solutions and next steps. In this step, the analysis results and sentiment data are provided as input information, and appropriate advice is output.

[1775] Step 5:

[1776] As the user progresses through the task, they can request further advice as needed. Once the user completes the task, they input their current emotional data using the emotion engine, and the device sends this data to the server. The server analyzes this data, generates final feedback, and stores it. In this step, emotional data and task information are provided as input, and feedback is output as the analysis result.

[1777] Step 6:

[1778] The server stores accumulated emotional data and feedback in a database and performs analysis. Based on the analysis results, improvements are made to enhance the quality of advice. These improvements are reflected in subsequent advice generation, thereby improving the overall system performance. In this step, emotional data and feedback are provided as input information, and the system improvements are output.

[1779] 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.

[1780] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1781] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[1782] 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.

[1783] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[1784] 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.

[1785] 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.

[1786] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[1787] 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."

[1788] 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.

[1789] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[1790] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[1791] 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.

[1792] 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.

[1793] 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.

[1794] 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.

[1795] 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.

[1796] 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.

[1797] 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.

[1798] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[1799] 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 as being incorporated by reference.

[1800] The following is further disclosed regarding the embodiments described above.

[1801] (Claim 1)

[1802] A means for the user to input information about the task,

[1803] A means by which the terminal sends user input information to the server,

[1804] The means by which the server performs user authentication,

[1805] A method by which the server retrieves and lists the tasks to be handed over from the database,

[1806] A means by which the terminal displays the task list obtained from the server to the user,

[1807] A means for the user to request advice while processing a task,

[1808] A means by which the server generates appropriate advice regarding the task being processed and sends it to the terminal,

[1809] A means by which the terminal displays advice obtained from the server to the user,

[1810] A means for users to enter feedback after completing a task,

[1811] A means for the server to store and analyze feedback in a database,

[1812] A system that includes this.

[1813] (Claim 2)

[1814] The system according to claim 1, comprising means for a server to search for relevant documents and past solutions and generate optimal advice.

[1815] (Claim 3)

[1816] The system according to claim 1, which provides a server with means to improve the quality of advice based on the analysis results.

[1817] "Example 1"

[1818] (Claim 1)

[1819] A means for users to input data related to their work,

[1820] A means by which the terminal sends user input data to the server,

[1821] The means by which the server performs user authentication,

[1822] A method by which the server retrieves and lists the tasks to be handed over from the database,

[1823] A means for the terminal to display a list of tasks obtained from the server to the user,

[1824] A means for users to request advice while processing tasks,

[1825] A means by which the server generates appropriate advice regarding the task being processed and sends it to the terminal,

[1826] A means by which the terminal displays advice obtained from the server to the user,

[1827] A means for users to input feedback after completing a task,

[1828] A means for the server to store and analyze feedback in a database,

[1829] A system that includes this.

[1830] (Claim 2)

[1831] The system according to claim 1, comprising means for a server to search for relevant documents and past solutions and generate optimal advice.

[1832] (Claim 3)

[1833] The system according to claim 1, which provides a server with means to improve the quality of advice based on the analysis results.

[1834] "Application Example 1"

[1835] (Claim 1)

[1836] A means for the user to input information about the task,

[1837] A means by which the terminal sends user input information to the server,

[1838] The means by which the server performs user authentication,

[1839] A method by which the server retrieves and lists the tasks to be handed over from the database,

[1840] A means by which the terminal displays the task list obtained from the server to the user,

[1841] A means for the user to request advice while processing a task,

[1842] A means by which the server generates appropriate advice regarding the task being processed and sends it to the terminal,

[1843] A means by which the terminal displays advice obtained from the server to the user,

[1844] A means for users to enter feedback after completing a task,

[1845] A means for the server to store and analyze feedback in a database,

[1846] A means for staff at a logistics center to manage handover tasks using smartphones and request advice and procedures,

[1847] An application installed on a smartphone displays a task list retrieved from a server, providing a means for staff to request advice while sorting tasks.

[1848] A server provides a means to generate optimal advice using a recommendation algorithm based on past relevant documents and solutions,

[1849] A means by which the server performs analysis to improve the entire system based on feedback entered by staff after task completion,

[1850] A system that includes this.

[1851] (Claim 2)

[1852] The system according to claim 1, comprising means for a server to search for relevant documents and past solutions and generate optimal advice.

[1853] (Claim 3)

[1854] The system according to claim 1, which provides a server with means to improve the quality of advice based on the analysis results.

[1855] "Example 2 of combining an emotion engine"

[1856] (Claim 1)

[1857] A means for the user to input information about the task,

[1858] A means by which the terminal sends user input information to the server,

[1859] The means by which the server performs user authentication,

[1860] A method by which the server retrieves and lists the tasks to be handed over from the database,

[1861] A means by which the terminal displays the task list obtained from the server to the user,

[1862] A means for the user to request advice while processing a task,

[1863] A means by which the server generates appropriate advice regarding the task being processed and sends it to the terminal,

[1864] A means by which the terminal displays advice obtained from the server to the user,

[1865] A means for users to enter feedback after completing a task,

[1866] A means for the server to store and analyze feedback in a database,

[1867] A means equipped with an emotion engine that recognizes the user's emotions,

[1868] A means of generating more appropriate advice based on user emotion data received from an emotion engine,

[1869] A means of sending advice generated by the server to the terminal,

[1870] A means by which the device displays advice to the user,

[1871] A system that includes this.

[1872] (Claim 2)

[1873] The system according to claim 1, comprising means for a server to search for relevant documents and past solutions and generate optimal advice.

[1874] (Claim 3)

[1875] The system according to claim 1, which provides a server with means to improve the quality of advice based on the analysis results.

[1876] "Application example 2 when combining with an emotional engine"

[1877] (Claim 1)

[1878] A means for the user to input information about the task,

[1879] A means by which the terminal sends user input information to the server,

[1880] The means by which the server performs user authentication,

[1881] A method by which the server retrieves and lists the tasks to be handed over from the database,

[1882] A means by which the terminal displays the task list obtained from the server to the user,

[1883] A means for the user to request advice while processing a task,

[1884] A means by which the terminal uses a recognition engine to acquire user emotion data and send it to a server,

[1885] A means for the server to generate appropriate advice based on the task being processed and the acquired sentiment data, and send it to the terminal,

[1886] A means by which the terminal displays advice obtained from the server to the user,

[1887] A means for users to enter feedback after completing a task,

[1888] A means for the server to store and analyze feedback in a database,

[1889] A system that includes this.

[1890] (Claim 2)

[1891] The system according to claim 1, comprising means for a server to search for relevant documents and past solutions and to generate optimal advice taking sentiment data into consideration.

[1892] (Claim 3)

[1893] The system according to claim 1, which provides a server with means to improve the quality of advice based on analysis results and to make improvements that take sentiment data into consideration. [Explanation of Symbols]

[1894] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A means for the user to input information about the task, A means by which the terminal sends user input information to the server, The means by which the server performs user authentication, A method by which the server retrieves and lists the tasks to be handed over from the database, A means by which the terminal displays the task list obtained from the server to the user, A means for the user to request advice while processing a task, A means by which the server generates appropriate advice regarding the task being processed and sends it to the terminal, A means by which the terminal displays advice obtained from the server to the user, A means for users to enter feedback after completing a task, A means for the server to store and analyze feedback in a database, A system that includes this.

2. The system according to claim 1, comprising means for a server to search for relevant documents and past solutions and generate optimal advice.

3. The system according to claim 1, which provides a server with means to improve the quality of advice based on the analysis results.

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