System

Abstract

To provide a system.SOLUTION: A system includes means for receiving a project objective completion date, and setting the deadline of each task by performing an inverse calculation, means for receiving information of departments in charge and persons in charge and allocating a person in charge to each task, means for receiving a storage destination of related materials and authority required and giving the authority required to the person in charge, means for analyzing user's feelings when the user performs a specific task, means for performing task simplification and a reallocation proposal on the basis of the analyzed feelings, means for displaying a progress state of the project and the proposal in smart glasses worn by a user, and means for reevaluating the progress state of the project and readjusting a schedule as needed.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] In the past, when planning a new project or task, many procedures were required, such as selecting the appropriate department and person in charge, identifying where related documents were stored, obtaining the necessary permissions, and managing the schedule. These procedures required time and effort, reducing work efficiency. Furthermore, even when systems existed to support these procedures, there was little attachment or trust in the systems, and they were not widely used. [Means for solving the problem]

[0005] The present invention provides a means for introducing the relevant department and person in charge, indicating the storage location of related materials and the necessary authority, managing schedules based on backward calculations until the target completion date, setting up meetings for the person in charge, and proposing and assisting with the necessary content until the task is completed. Furthermore, by adopting a character shape that users can become attached to, the system improves user convenience and satisfaction. Furthermore, by placing employees of a specific organization as the main characters and providing support as concierges, the system improves the work efficiency and productivity of employees. [Brief explanation of the drawings]

[0006] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 2 is a sequence diagram showing a flow of processing in the data processing system according to the first embodiment of the first form example. [Figure 12]FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1 of Embodiment 1. [Figure 13] FIG. 10 is a sequence diagram showing a processing flow of a data processing system in a second embodiment of the second form example. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 of Embodiment Example 2. [Figure 15] FIG. 10 is a sequence diagram showing the flow of processing in a data processing system according to a third embodiment of the third embodiment. [Figure 16] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 3 of Embodiment 3. [Figure 17] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in the first embodiment of the first form example when an emotion engine is combined. [Figure 18] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1 of Form Example 1 when an emotion engine is combined. [Figure 19] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in the second embodiment of the second form example when an emotion engine is combined. [Figure 20] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 of Form Example 2 when an emotion engine is combined. [Figure 21] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in the third embodiment of the third form example when an emotion engine is combined. [Figure 22] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 3 of Form Example 3 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0007] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0008] First, the terms used in the following description will be explained.

[0009] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, the processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), or a TPU (TENSOR PROCESSING UNIT (registered trademark)).

[0010] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0011] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0012] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0013] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0014] [First embodiment]

[0015] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0016] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0017] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0018] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0019] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0020] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0021] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0022] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0023] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0024] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0025] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0026] Next, the specific processing by the specific processing unit 290 of the data processing device 12 will be described.

[0027] "Example 1"

[0028] When an employee of a specific organization plans a new project or task, this embodiment of the present invention automatically introduces the appropriate department and person in charge. This introduction is made based on information such as the employee's position within the organization, expertise, and past project experience. The system also presents the location of related documents and the necessary permissions. This allows employees to quickly obtain the necessary information and start the task efficiently.

[0029] "Example 2"

[0030] Furthermore, this embodiment of the present invention manages schedules and schedules meetings for the person in charge based on a backward calculation of the target completion date. This allows employees to easily understand the progress of the project and efficiently schedule necessary meetings. Specifically, the deadline for each task is set by counting backward from the target completion date, and the schedule of the person in charge is automatically adjusted based on that.

[0031] "Example 3"

[0032] Furthermore, the present invention employs character shapes that users can develop an attachment to. These character shapes are robots, relatives, etc., and improve user convenience and satisfaction. Specifically, the character shapes can be customized to suit the user's preferences and the organization's culture.

[0033] The processing flow of each embodiment will be described below.

[0034] "Example 1"

[0035] Step 1: Employees plan new projects and tasks.

[0036] Step 2: The system automatically connects you to the right department and person based on information such as your position within the organization, your expertise, and past project experience.

[0037] Step 3: The system will show you where the relevant documents are stored and the necessary permissions, allowing you to quickly retrieve the information you need and begin your task efficiently.

[0038] "Example 2"

[0039] Step 1: Employee sets a target completion date for the project.

[0040] Step 2: The system automatically creates a schedule based on backward calculations to the desired completion date.

[0041] Step 3: The system schedules meetings for the person in charge, allowing employees to easily understand the progress of the project and efficiently schedule necessary meetings.

[0042] "Example 3"

[0043] Step 1: The system adopts a character shape that users can become attached to. This character shape can be a robot, a relative, or something similar, improving user convenience and satisfaction.

[0044] Step 2: Character shapes can be customized to suit user preferences and organizational culture.

[0045] Example 1

[0046] Next, a description will be given of Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0047] With conventional project management systems, when employees planned new projects or tasks, it was difficult to quickly find the appropriate department or person in charge, and it was time-consuming to specify where related documents were stored and the necessary permissions. Furthermore, project schedule management, meeting scheduling, and proposals and assistance until task completion were not efficiently performed. This resulted in delays to the start and progress of projects, and reduced overall efficiency.

[0048] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0049] In this invention, the server includes a means for introducing the relevant department and person in charge, a means for presenting the storage location of related materials and the necessary permissions, a means for managing schedules based on backward calculations to the target completion date, a means for setting up meetings for the person in charge, a means for suggesting and providing assistance with the content needed to complete the task, a means for generating prompts using a generative AI model and selecting the appropriate department and person in charge, and a means for creating a character that employees can feel attached to. This allows employees to quickly find the appropriate department and person in charge and easily confirm the storage location of related materials and the necessary permissions. Furthermore, the server can efficiently manage project schedules, set up meetings, and suggest and provide assistance until task completion, smoothing the start and progress of projects and improving overall efficiency.

[0050] The "means of introducing the responsible department and person in charge" is a function that automatically selects and introduces the appropriate department and person in charge within the organization for the project or task that the user has planned.

[0051] The "means for presenting the storage location of related materials and the necessary permissions" is a function that provides users with information on the storage location of materials related to a project or task and the permissions required to access them.

[0052] "A means of schedule management based on backward calculations to the target completion date" is a function that automatically creates and manages schedules by counting backwards based on the completion date of a project or task.

[0053] "Means for setting up meetings for responsible parties" is a function that automatically sets up meetings for responsible parties related to projects and tasks and incorporates them into the schedule.

[0054] "Means for proposing and assisting with the necessary content to complete a task" is a function that suggests information and procedures necessary to progress a project or task, and helps users complete tasks efficiently.

[0055] "Means for generating prompt sentences using a generative AI model and selecting an appropriate department and person in charge" refers to a function that uses a generative AI model to generate prompt sentences from the project and task details entered by the user, and selects an appropriate department and person in charge based on the prompt sentences.

[0056] "Means for having a shape that allows a user to become attached to the character" is a function that has a shape of a character that is familiar to the user and that the user can become attached to.

[0057] MODE FOR CARRYING OUT THE INVENTION

[0058] This invention is a system that automatically introduces the appropriate department and person in charge when an employee of a specific organization plans a new project or task. The system selects the department and person in charge based on information such as position within the organization, expertise, and past project experience, and also presents the location of related documents and the necessary permissions. This allows employees to quickly obtain the necessary information and start tasks efficiently.

[0059] Hardware and software used

[0060] Server: Database server (e.g., MySQL (registered trademark)), application server (e.g., Apache (registered trademark) Tomcat)

[0061] Devices: PCs and mobile devices used by employees

[0062] Software: Generative AI models (e.g., OpenAI® GPT-4®), project management tools (e.g., Jira)

[0063] Specific operation of the system

[0064] 1. A user creates a new project or task

[0065] A user uses a terminal to enter details of a new project or task into a project management tool, including the project name, purpose, deadline, required resources, and other information.

[0066] Example: When a user plans a "New Product Market Research Project," the user enters the project name as "New Product Market Research," the purpose as "Understanding Market Needs," and the deadline as "End of December 2023."

[0067] 2. The server receives the input data and sends prompts to the generative AI model.

[0068] The server receives project and task details entered by the user and generates prompts based on the received data to send to the generative AI model.

[0069] Example: "Please introduce me to the department and person who would be best suited to my new product market research project."

[0070] 3. The generative AI model selects the appropriate department and person in charge

[0071] The generative AI model selects the appropriate department and person in charge based on data such as position within the organization, expertise, and past project experience.

[0072] Example: A generative AI model returns the result, "Mr. Tanaka from the Marketing Department is the best candidate."

[0073] 4. The server will provide the location of the relevant materials and the necessary permissions.

[0074] The server then presents the selected department and person in charge with the location of the relevant documents and the necessary permissions. Specifically, it retrieves the location of the relevant documents and access permission information from the database and provides it to the user.

[0075] For example: "The relevant materials are in a 'Market Research' folder on a shared drive. Access is granted to everyone in the marketing department."

[0076] 5. User checks the results and starts the task

[0077] The user checks the information provided by the server through their terminal. Specifically, they check the department and person in charge, the storage location of related documents, and access permission information on the project management tool. They access the necessary documents and start tasks efficiently.

[0078] Example: A user accesses the "Market Research" folder based on the information provided, downloads the necessary materials, and starts the project.

[0079] This system allows employees to quickly find the appropriate department and person in charge, easily confirm where related documents are stored, and easily identify the necessary permissions. It also efficiently manages project schedules, schedules meetings, and provides suggestions and assistance until tasks are completed, resulting in smoother project initiation and progress, improving overall efficiency.

[0080] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0081] Step 1:

[0082] A user creates a new project or task.

[0083] A user uses a terminal to enter details of a new project or task into a project management tool, including the project name, purpose, deadline, required resources, and other information.

[0084] Input: Project name, purpose, deadline, required resources

[0085] Output: Project data stored in a project management tool

[0086] Specific operation: A user logs in to the project management tool, clicks the Create New Project button, enters the required information, and clicks the Save button.

[0087] Step 2:

[0088] The server receives the input data and sends prompts to the generative AI model.

[0089] The server receives project and task details entered by the user and generates prompts based on the received data to send to the generative AI model.

[0090] Input: Project Data

[0091] Output: The prompt to send to the generative AI model

[0092] Specific operation: The server receives new project data from the project management tool, generates prompt sentences, and sends the generated prompt sentences to the generative AI model.

[0093] Step 3:

[0094] The generative AI model selects the appropriate department and person in charge.

[0095] The generative AI model selects the appropriate department and person in charge based on data such as position within the organization, expertise, and past project experience.

[0096] Input: Prompt statement, organizational position, expertise, and past project experience data

[0097] Output: Information about the appropriate department and person in charge

[0098] Specific operation: The generative AI model receives the prompt, retrieves relevant information from the database, selects the most appropriate department and person in charge, and returns the results to the server.

[0099] Step 4:

[0100] The server will provide the location of the relevant materials and the necessary permissions.

[0101] The server will then present the selected department and person in charge with the location of the relevant documents and the necessary permissions.

[0102] Input: Department and person in charge information

[0103] Output: Information on where related materials are stored and the necessary permissions

[0104] Specific operation: The server receives the results from the generative AI model, retrieves the storage location and access permission information for the relevant materials from the database, generates information to provide to the user, and displays it in the project management tool.

[0105] Step 5:

[0106] The user reviews the results and starts the task.

[0107] The user checks the information provided by the server through their terminal. Specifically, they check the department and person in charge, the storage location of related documents, and access permission information on the project management tool. They access the necessary documents and start tasks efficiently.

[0108] Input: Information provided by the server

[0109] Output: Task started

[0110] Specific actions: The user checks the information displayed in the project management tool, accesses related materials, downloads the necessary materials, and starts the project.

[0111] (Application example 1)

[0112] Next, a description will be given of Application Example 1 of Embodiment Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0113] In the past, when a new manufacturing process or maintenance task arose in a factory, it was difficult to quickly identify the appropriate department or person in charge, preventing efficient task initiation. Furthermore, there was insufficient information on where related documents were stored and the necessary permissions, which often delayed task progress. This resulted in a decline in overall productivity and was a serious problem in factory operations.

[0114] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0115] In this invention, the server includes means for introducing the department and person in charge, presenting the storage location of related materials and the necessary authority, schedule management based on backward calculation until the target completion date, setting up meetings for the person in charge, and proposing and assisting with the content required to complete the task, means for automatically introducing the appropriate department and person in charge when a new manufacturing process or maintenance task occurs in the factory, and means for identifying the most suitable person in charge based on information such as their position in the factory, expertise, and past project experience, and presenting the storage location of related materials and the necessary authority. This makes it possible to quickly identify the appropriate person in charge and provide related information when a new task occurs in the factory.

[0116] A "department" is a department within an organization that is responsible for carrying out a specific task or project.

[0117] A "personnel" is an individual selected to carry out a specific task or project.

[0118] "Relevant materials" are information and documents needed to complete a task or project.

[0119] "Storage location" refers to the location where relevant materials are stored.

[0120] "Permissions" are the access rights and operational privileges required to accomplish a specific task or project.

[0121] "Schedule management" means managing the progress of tasks and projects and making plans to reach the target completion date.

[0122] "Meeting arrangement" refers to planning a meeting related to a task or project and inviting participants.

[0123] A "proposal" is the presentation of specific methods or ideas for efficiently progressing a task or project.

[0124] "Assisting" means providing support to help complete a task or project.

[0125] A "manufacturing process" is a series of steps or procedures for creating a product.

[0126] "Maintenance tasks" are the work required to maintain, inspect, and repair machinery and equipment.

[0127] A "position" indicates a job or position within an organization.

[0128] "Specialized knowledge" refers to advanced knowledge and skills in a particular field.

[0129] "Project experience" refers to experience and track record related to projects that have been carried out in the past.

[0130] The system for implementing this invention has the function of automatically introducing the appropriate department and person in charge when a new manufacturing process or maintenance task occurs in a factory. The system consists of three main elements: a server, a terminal, and a user.

[0131] The server has the functions of introducing the responsible department and person in charge, showing where related documents are stored and the necessary permissions, managing the schedule based on backward calculations to the target completion date, setting up meetings for the person in charge, proposing and assisting with the content required to complete the task, etc. It also has the function of identifying the most suitable person based on information such as position within the factory, expertise, and past project experience, and showing where related documents are stored and the necessary permissions.

[0132] Terminals are devices used by each department and person in the factory, and they receive and display information from the server. Terminals include PCs, tablets, smartphones, etc.

[0133] Users are various departments and personnel within the factory, and access information provided by the server via their terminals. When a new manufacturing process or maintenance task arises, users can respond quickly based on the information from the server.

[0134] Specifically, when a new task arises in the factory, the server first inputs the task requirements. The server then retrieves employee information from the database and compares the task requirements with the employee's skills to identify the most suitable person. Once the most suitable person is identified, the server presents the location of related documents and the necessary permissions, and sends the information to the terminal. The user can receive this information through the terminal and start the task efficiently.

[0135] The hardware used includes servers, storage devices, PCs, tablets, and smartphones, and the software used includes Python and JSON libraries.

[0136] As a concrete example, consider a new manufacturing process that requires skills in mechanical engineering, programming, and project management. The server identifies the most suitable person based on these requirements and provides the location of the relevant documents and the necessary permissions.

[0137] Example prompts to input to a generative AI model:

[0138] A new manufacturing process has been developed that requires the following skills: mechanical engineering, programming, and project management. Identify the appropriate person, provide the location of the relevant documentation, and the necessary permissions.

[0139] This prompt can be used to input a generative AI model to identify the most appropriate person and suggest where relevant materials are stored and what permissions are required.

[0140] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0141] Step 1:

[0142] When a new manufacturing process or maintenance task arises in the factory, the server inputs the requirements for that task, including the required skills, job title, and expertise, thereby clarifying the specific requirements for the task.

[0143] Step 2:

[0144] The server retrieves employee information from a database, including each employee's job title, expertise, past project experience, etc. This provides data to compare with the task requirements.

[0145] Step 3:

[0146] The server compares the task requirements with the employee skills and identifies the most suitable person. Specifically, it scores employees whose skills match the task requirements and selects the employee with the highest score. This identifies the person best suited to the task.

[0147] Step 4:

[0148] Once the server identifies the most suitable person, it presents the location of the relevant documents and the necessary permissions. The location of the relevant documents is retrieved from the database, and the necessary permissions are determined based on the person's job title and skills. This provides the person with the information they need to complete the task.

[0149] Step 5:

[0150] The server then sends the identified person in charge and related information to the terminal. The terminal is a device used by the person in charge, such as a PC, tablet, or smartphone, allowing the person in charge to receive the necessary information.

[0151] Step 6:

[0152] The user receives information provided by the server through their terminal and efficiently starts the task. The user checks the storage location of related materials and the necessary permissions, and makes the necessary preparations to complete the task. This allows the task to proceed quickly and efficiently.

[0153] Step 7:

[0154] The user provides feedback on the progress of the task to the server, which then manages the schedule based on the feedback and suggests additional meetings or other tasks as necessary, thereby continuously supporting the progress of the task.

[0155] Example 2

[0156] Next, a description will be given of Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0157] In project management, it is difficult to efficiently manage schedules and schedule meetings based on backward calculations to the target completion date. Furthermore, there is a lack of systems that allow easy understanding of project progress and efficient scheduling of necessary meetings. Furthermore, there is a need for a method to automatically generate project progress reports using generative AI models.

[0158] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0159] In this invention, the server includes a means for a user to input a target completion date for the project, a means for the server to receive the target completion date and set a deadline for each task by calculating backwards, a means for the server to adjust the schedules of the people in charge and set meetings, a means for the server to send prompts to the generative AI model and generate a progress report, and a means for the server to provide the generated report to the user. This makes it possible to easily grasp the progress of the project and efficiently set up necessary meetings.

[0160] A "department" is a department within an organization that is responsible for a particular project or task.

[0161] A "person in charge" is an individual who is responsible for a particular task or project.

[0162] "Relevant materials" are documents and files containing information or data necessary to carry out a project or task.

[0163] "Repository" is the location or system where relevant materials are stored.

[0164] "Necessary privileges" are the authorizations and authentications required to access relevant materials and systems.

[0165] The "desired completion date" is the ultimate date by which a project or task should be completed.

[0166] "Counting backwards" is a calculation method that sets deadlines for each task by working backwards from the completion date of the goal.

[0167] "Schedule management" is the process of planning and managing the progress of projects and tasks.

[0168] "Meeting setup" is the process of scheduling a meeting for a specific date and time and notifying participants.

[0169] A "task" is a discrete task or activity required to complete a project.

[0170] A "suggestion" refers to a recommended method or means for completing a task.

[0171] "Assistance" refers to providing help or support to complete a task.

[0172] "User" refers to an individual or organization that uses the system to manage projects.

[0173] A "server" is a computer that is the core of a system and is a device that processes and stores data.

[0174] A "generative AI model" is a model that uses artificial intelligence to automatically perform specific tasks.

[0175] A "prompt" is text containing instructions or questions that are input to a generative AI model.

[0176] A "progress report" is a report summarizing the progress of a project or task.

[0177] A "character shape" is a shape that has an appearance or design that users can relate to.

[0178] The present invention is a system for efficiently managing schedules and setting up meetings for project managers based on backward calculations to the target completion date in a project management system. Specific embodiments of this system will be described below.

[0179] System configuration

[0180] This system includes a terminal used by the user, a server that processes data, and a generative AI model. The terminal is a device such as a PC or smartphone, and the server is a computer that processes and stores data. The generative AI model is a model that uses artificial intelligence to automatically perform specific tasks.

[0181] Hardware and software used

[0182] Devices: PC, smartphone

[0183] Server: A high-performance computer (e.g., a cloud server)

[0184] Database: MySQL

[0185] Schedule management library: pandas

[0186] Meeting Settings Library: datetime

[0187] Generative AI model: OpenAI GPT-3 (registered trademark)

[0188] Calendar API: Google(R) Calendar API

[0189] Program processing

[0190] A user uses a terminal to access the web interface of the project management system. The user enters the target completion date of the project and clicks the "Submit" button. The server receives the target completion date sent by the user and retrieves all tasks of the project and their required times from the database. The server calculates the deadline for each task by counting backward from the target completion date and stores the results in the database.

[0191] The server then retrieves the schedule of each person using the Google Calendar API, schedules meetings based on the deadlines of each task, and sends meeting invitations based on the person's free time.

[0192] The server sends prompts to the generative AI model to generate progress reports, which are then provided to the user, who can view them using their device.

[0193] Specific examples

[0194] For example, consider a case where a user is managing a "new product development project." The user sets the project's target completion date as "December 31, 2023." The server calculates backwards from this date and sets the deadline for each task. For example, it calculates that the "market research" task needs to be completed by October 31, 2023.

[0195] Next, the server adjusts the schedule of the person in charge and sets a meeting for the "Market Research" task on "October 15, 2023." This meeting setting is done by obtaining free time from the person in charge's Google Calendar.

[0196] An example of a prompt to be input to the generative AI model is as follows:

[0197] Project Name: New Product Development

[0198] Objective completion date: December 31, 2023

[0199] Task: Market research

[0200] Task Deadline: October 31, 2023

[0201] Person in charge: Taro Tanaka

[0202] Meeting Date: October 15, 2023

[0203] Based on this prompt, the generative AI model generates a project progress report detailing the progress of each task and next steps.

[0204] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0205] Step 1:

[0206] The user enters the desired completion date for the project.

[0207] The user opens a browser on their device and accesses the web interface of the project management system. After logging in, a form for entering the project's target completion date is displayed. The user enters "December 31, 2023" and clicks the "Submit" button. The entered target completion date is sent to the server.

[0208] Step 2:

[0209] The server receives the target completion date and sets the deadline for each task by counting backwards.

[0210] The server receives the target completion date "December 31, 2023" sent by the user. Next, the server retrieves all the project's tasks and their required times from the database. For example, suppose "market research" takes 30 days, "design" takes 45 days, and "development" takes 60 days. The server calculates the deadline for each task by counting backwards from the target completion date, and sets the deadline for "market research" as "October 31, 2023," the deadline for "design" as "November 15, 2023," and the deadline for "development" as "December 1, 2023." These deadlines are saved in the database.

[0211] Step 3:

[0212] The server coordinates the schedules of the people in charge and sets up meetings.

[0213] The server uses the Google Calendar API to obtain the schedule of the person in charge. For example, it obtains the schedule of the person in charge, "Taro Tanaka," and sets a meeting for the "Market Research" task on "October 15, 2023." The server checks the person in charge's free time and sends a meeting invitation via Google Calendar. The meeting setting information is saved in a database.

[0214] Step 4:

[0215] The server sends prompts to the generative AI model and generates progress reports.

[0216] The server sends the following prompt to the generative AI model:

[0217] Project Name: New Product Development

[0218] Objective completion date: December 31, 2023

[0219] Task: Market research

[0220] Task Deadline: October 31, 2023

[0221] Person in charge: Taro Tanaka

[0222] Meeting Date: October 15, 2023

[0223] The generative AI model uses this prompt to generate a project progress report, which is then returned to the server.

[0224] Step 5:

[0225] The server provides the generated report to the user.

[0226] The server provides progress reports received from the generative AI model to the user, who then uses a browser on their device to access the project management system dashboard and view the reports, which detail the progress of each task and next steps to take.

[0227] (Application example 2)

[0228] Next, a description will be given of Application Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0229] Conventional schedule management systems lack the functionality to set deadlines for each task by counting backward from the target completion date and automatically adjust the schedules of the people in charge, making it difficult to easily grasp the progress of a project. In addition, schedule management for maintenance and part replacement of work equipment in factories is often done manually, making efficient operation difficult.

[0230] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for introducing the responsible department and person in charge, presenting the storage location of related materials and the necessary authority, schedule management based on backward calculations until the target completion date, setting up meetings for the person in charge, and proposing and assisting with the necessary content until the task is completed; means for managing the work schedule of work equipment in the factory and setting up deadlines for each task by backward calculations; means for automatically adjusting schedules for work equipment maintenance and part replacement and setting up necessary meetings; and means for having a shape that can be attached to as a character. This makes it easy to understand the progress of the project and enables efficient schedule management and meeting setting.

[0231] A "department" is a department within an organization that is responsible for a particular task or project.

[0232] A "person in charge" is an individual in charge of a particular task or project.

[0233] "Relevant materials" are documents and files that contain information or data necessary to complete a task or project.

[0234] "Repository" is the location or system where relevant materials are stored.

[0235] "Necessary privileges" are the authorizations and authentications required to access relevant materials and systems.

[0236] The "desired completion date" is the date by which a particular task or project is intended to be completed.

[0237] "Counting backwards" is a method of setting deadlines for each task by working backwards from the date of completion of the goal.

[0238] Schedule management is the process of planning and coordinating the progress of tasks and projects.

[0239] "Meeting scheduling" refers to scheduling meetings necessary to progress a task or project.

[0240] A "task" is an operation or activity that must be performed to achieve a specific purpose.

[0241] A "suggestion" is an idea or method that can help accomplish a task or project.

[0242] "Assistance" refers to providing the means or support to help complete a task or project.

[0243] "Factory equipment" refers to machines and devices used in factories.

[0244] "Maintenance" refers to the maintenance work required to maintain the normal operation of work equipment.

[0245] "Parts replacement" is the process of replacing worn out parts of work equipment with new parts.

[0246] "A shape that allows users to become attached to the character" refers to a design and shape that users find familiar.

[0247] A system for carrying out this invention is configured as follows: The server includes means for introducing the department and person in charge, presenting the storage location of related materials and the necessary authority, managing the schedule by counting backward until the target completion date, setting up meetings for the person in charge, and proposing and assisting with the content necessary to complete the task, means for managing the work schedule of work equipment in the factory and setting the deadline for each task by counting backward, means for automatically adjusting the schedule for maintenance and part replacement of the work equipment and setting the necessary meetings, and means for having a shape that can be attached to as a character.

[0248] The server runs a program using Python. The program calculates the deadline based on the number of days required for each task and sets the date of the meeting. Specifically, the server receives a list of tasks, calculates the number of days required for each task, and sets the deadline for each task by counting backward from the target completion date. It also schedules a meeting for the day before the deadline for each task.

[0249] The hardware used is a smartphone or tablet, and users access the schedule management system through these devices. The software runs programs using Python, and data processing includes back-calculating deadlines based on the number of days required for tasks and setting meeting dates.

[0250] As a concrete example, the following prompt sentence is input to the generative AI model:

[0251] "I want to develop a schedule management application for factory robots. It should have the ability to set deadlines for each task by counting backwards from the target completion date and automatically adjust the schedules of the people in charge. Please create a program using Python that calculates task deadlines and sets meeting dates."

[0252] An example output from a generative AI model might look like this:

[0253] "This application manages the work schedules of robots in the factory and sets deadlines for each task by counting backwards. It also automatically adjusts schedules for robot maintenance and part replacement, and sets necessary meetings. Using Python, we created a program that counts backwards from deadlines based on the number of days required for each task and sets meeting dates."

[0254] In this way, users can easily grasp the progress of the project and efficiently manage schedules and schedule meetings.

[0255] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0256] Step 1:

[0257] The server receives a list of tasks and their intended completion dates from the user. The input includes the name of each task, the number of days required, and the intended completion date. The server receives this data and stores it in an internal database.

[0258] Step 2:

[0259] The server calculates the deadline for each task by counting backward from the target completion date. The target completion date and the number of days required for each task are used as input. The server sets the deadline for each task by subtracting the number of days required for each task from the target completion date. The output is the deadline for each task.

[0260] Step 3:

[0261] The server schedules meetings on the day before each task's due date. The server uses the due date of each task as input. The server sets the meeting date by one day before each task's due date. The server gets the meeting date as output.

[0262] Step 4:

[0263] The server automatically adjusts the schedule for maintenance and part replacement of work equipment in the factory. The number of days required for maintenance and part replacement of work equipment and the deadline are used as input. The server calculates and sets the optimal schedule based on this data. The maintenance and part replacement schedule is obtained as output.

[0264] Step 5:

[0265] The server notifies the user of the schedule and meeting dates. The deadlines for each task and the meeting dates are used as input. The server sends this data to the user's terminal and notifies them. As output, the user can check the schedule and meeting dates.

[0266] Step 6:

[0267] The user checks the schedule and meeting dates through the terminal and makes adjustments as necessary. The schedule and meeting dates sent from the server are used as input. The user checks the progress of tasks based on this data and makes necessary adjustments. The adjusted schedule is obtained as output.

[0268] Example 3

[0269] Next, a description will be given of a third embodiment of the third embodiment. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0270] Conventional systems have made it difficult to efficiently perform tasks such as introducing the relevant departments and personnel, presenting the storage locations of related documents and the necessary permissions, managing schedules, setting up meetings, and proposing and assisting with task completion. It has also been difficult to provide character shapes that users can develop an attachment to the system. Furthermore, it has not been possible to generate character shapes that can be customized to suit the user's preferences and organizational culture. To solve these issues, a means is needed to generate prompt sentences using a generative AI model and generate detailed specifications for character shapes.

[0271] The specific processing by the specific processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means.

[0272] In this invention, the server includes means for introducing the responsible department and person in charge, presenting the storage location of related materials and necessary permissions, managing the schedule based on backward calculation until the target completion date, setting up meetings for the person in charge, and proposing and assisting with the content required to complete the task, means for generating a character shape that can be customized to suit the user's preferences and the organization's culture, means for generating prompt sentences using a generative AI model and generating detailed specifications for the character shape, means for sending the generated character shape data to a terminal and displaying it to the user, and means for collecting feedback from the user and updating the character shape.This enables work efficiency to be improved and user satisfaction to be increased.

[0273] A "department" is a department within an organization that is responsible for a particular task or project.

[0274] A "person in charge" is an individual who is responsible for a particular task or project.

[0275] "Relevant materials" are documents and data necessary for the execution of a task or project.

[0276] "Repository" is the location or system where relevant materials are stored.

[0277] "Necessary privileges" are the authorizations and authentications required to access relevant materials and systems.

[0278] "Schedule management" refers to planning and adjusting the progress of work or projects by working backwards to the desired completion date.

[0279] "Meeting arrangement" refers to planning a meeting related to work or a project and inviting participants.

[0280] "Proposing and assisting with the necessary content to complete a task" refers to providing the information and support necessary to carry out a task or project.

[0281] A "character shape" is a shape that a user can become attached to, and includes shapes such as robots and relatives.

[0282] A "generative AI model" is a model that uses artificial intelligence to perform specific tasks, such as generating prompts and generating detailed specifications for character shapes.

[0283] A "prompt" is text that is input to a generative AI model and contains instructions for generating detailed specifications for a character's shape.

[0284] "Character shape data" refers to data that includes detailed specifications of the character shape generated by the generative AI model.

[0285] A "terminal" is a device that receives character shape data and displays it to the user.

[0286] "Feedback" refers to opinions and requests provided by users that are used to improve and customize character shapes.

[0287] This invention is a system that introduces the department and person in charge, shows the storage location of related documents and the necessary authority, manages schedules based on backward calculations until the target completion date, sets up meetings for the person in charge, and suggests and assists with the content required to complete the task.It also includes a function to generate character shapes that can be customized to suit the user's preferences and the organization's culture.

[0288] Server Operation

[0289] The server first receives input data from the user, including information about the user's preferences and organizational culture. The server generates a prompt based on this data. The prompt is then fed into a generative AI model (e.g., OpenAI's GPT-4) and used to generate detailed specifications for the character's shape.

[0290] The generated character shape data is sent from the server to the device. The device receives this data and displays it to the user. The user can check the character shape and provide feedback. The server inputs this feedback back into the generative AI model and updates the character shape.

[0291] Device behavior

[0292] The device receives the character shape data sent from the server. The received data is stored in the device's local storage. The device uses a 3D rendering engine to display the character shape on the screen. The user uses an interface to check this display and provide feedback. The device collects the user's feedback and sends it to the server.

[0293] User Actions

[0294] The user checks the character shape displayed on the device. They operate the device's UI components to input specific improvements and requests. For example, they provide feedback such as "I want the face to be more friendly" or "I want the robot's shape to be a bit more futuristic." The user presses the "Submit" button to send the feedback data to the server.

[0295] Specific examples

[0296] Example prompts to be input to the generative AI model

[0297] "The user wants a friendly robot character shape. The robot should have round eyes, a smiling face, and a blue body. Also, since the user's organization is related to education, the robot should be holding a book, which symbolizes knowledge."

[0298] By inputting this prompt into the generative AI model, a character shape that matches the user's wishes is generated. The generated character shape is sent from the server to the device and displayed to the user. The user can check the shape and provide further feedback if necessary.

[0299] In this way, the efficiency of the work and the satisfaction of the users are improved. The flow of the identification process in the third embodiment will be described with reference to FIG.

[0300] Step 1:

[0301] The server receives input data from the user. The input data includes information about the user's preferences and the organization's culture. Specifically, the server receives an HTTP request, saves the user's input data in a database, analyzes the input data, and prepares it for generating a prompt.

[0302] Step 2:

[0303] The server generates a prompt sentence based on the received user data. Specifically, the server runs a Python script, analyzes the user data, and generates a prompt sentence. The input data is analyzed and a prompt sentence is created to be input into the generative AI model. The generated prompt sentence is obtained as the output.

[0304] Step 3:

[0305] The server invokes the generative AI model and provides the generated prompt sentence as input. Specifically, the server sends an API request to the generative AI model to obtain the character shape specification. Using the prompt sentence as input, the server obtains the detailed character shape specification as output.

[0306] Step 4:

[0307] The server generates detailed data for the character's shape based on the data returned from the generative AI model. Specifically, the server analyzes the acquired data and executes scripts to generate 3D models and image data. The server uses the character's shape specifications as input and obtains character shape data as output.

[0308] Step 5:

[0309] The server sends the generated character shape data to the terminal. Specifically, the server generates an HTTP response and sends the response including the character shape data to the terminal. The character shape data is used as input, and data sent to the terminal is obtained as output.

[0310] Step 6:

[0311] The device receives the character shape data sent from the server. Specifically, the device receives the HTTP response and saves the character shape data in local storage. The data from the server is used as input, and the data saved in local storage is obtained as output.

[0312] Step 7:

[0313] The device displays the received character shape data to the user. Specifically, the device uses a 3D rendering engine to display the character shape on the screen. It uses the data in the local storage as input and obtains the character shape displayed to the user as output.

[0314] Step 8:

[0315] The user checks the character shape displayed on the device and provides feedback. Specifically, the user operates the device's UI components and inputs specific improvements and requests. The user's opinions and requests are used as input, and feedback data is obtained as output.

[0316] Step 9:

[0317] The terminal sends the collected user feedback to the server. Specifically, the terminal generates an HTTP request and sends data including the user feedback to the server. The feedback data is used as input, and the data sent to the server is obtained as output.

[0318] Step 10:

[0319] The server receives feedback from the user and updates the character shape. Specifically, the server analyzes the feedback data and updates the character shape again using the generative AI model. The feedback data is used as input, and updated character shape data is obtained as output.

[0320] (Application example 3)

[0321] Next, a description will be given of Application Example 3 of Form Example 3. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0322] Conventional food delivery services have faced problems such as low user satisfaction due to the impersonal nature of the systems used to confirm orders and receive delivery status notifications. Additionally, it has been difficult for users to develop an attachment to the service, making it difficult to encourage repeat use.

[0323] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 3 is realized by the following means.

[0324] In this invention, the server includes means for introducing the department and person in charge, presenting the storage location of related materials and the necessary authority, managing the schedule based on backward calculations until the target completion date, setting up meetings for the person in charge, and proposing and assisting with the necessary content until the task is completed, means for having a shape that can be attached to as a character, and means for displaying a character-shaped avatar that can be customized to suit the user's preferences, and for confirming orders and notifying of delivery status. This makes it possible for users to become attached to the service, improves satisfaction, and encourages repeat use.

[0325] A "department" is a department or section that is responsible for a specific job or task.

[0326] A "person in charge" is an individual in charge of a particular job or task.

[0327] "Relevant materials" means documents or files containing information or data necessary to carry out a job or task.

[0328] "Repository" refers to the location or system where relevant materials are stored.

[0329] "Required authority" refers to the access rights and operational rights required to carry out a specific job or task.

[0330] "Schedule management" refers to planning and adjusting the progress of work and tasks by working backwards to the desired completion date.

[0331] "Meeting arrangement" refers to planning and coordinating a meeting where people in charge gather to discuss and share information.

[0332] "Proposing and assisting with the necessary content to complete a task" refers to proposing the information and procedures necessary to complete a job or task and supporting their execution.

[0333] "Shapes that allow users to become attached to the character" refers to designs and shapes that are familiar to users and that they can become attached to.

[0334] A "customizable character avatar" is a character whose appearance and functions can be changed to suit the user's preferences.

[0335] "Order confirmation" refers to checking the order details placed by the User to ensure their accuracy.

[0336] "Delivery status notification" refers to informing users of the current status of their ordered items.

[0337] The system for implementing this invention consists of three main elements: a server, a terminal, and a user. The following explains how each element functions.

[0338] server

[0339] The server has functions to introduce the department and person in charge, show the storage location of related documents and the necessary permissions, manage the schedule based on backward calculations until the target completion date, set up meetings for the person in charge, and suggest and assist with the necessary content until the task is completed.It also provides a means of having a shape that can be attached to as a character, displays a character-shaped avatar that can be customized to the user's preferences, and has functions to confirm orders and notify delivery status.

[0340] Specifically, the server is implemented using a programming language such as Python, and the database uses MySQL, PostgreSQL, etc. The server's role is to receive requests from users and return appropriate data.

[0341] Terminal

[0342] A terminal is a device that is directly operated by the user, such as a smartphone or tablet. The terminal displays data sent from the server and provides an interface that the user can operate. In particular, a character-shaped avatar that can be customized to suit the user's preferences is displayed on the terminal, and the terminal confirms orders and notifies delivery status.

[0343] Applications on devices are developed using cross-platform frameworks such as React Native and Flutter (registered trademark), which allows for efficient development of applications that run on multiple platforms, including iOS and ANDROID (registered trademark).

[0344] User

[0345] Users use a terminal to use the food delivery service. They place an order through the application and select a customizable character-shaped avatar. The avatar confirms the order, notifies the delivery status, and provides a friendly interface to the user.

[0346] As a concrete example, consider the case where the user is "Taro" and the avatar he has chosen is a "robot character." In this case, the application would behave as follows:

[0347] When you launch the application, a "robot character" will appear and say, "A robot character will help you with your order!"

[0348] When you confirm your order, the message "Robot character: Taro, your order has been confirmed" will be displayed.

[0349] When you update the delivery status, it will say "Robot character: Current delivery status is 'In delivery'" or "Robot character: Current delivery status is 'Delivered'."

[0350] Example prompts to input to a generative AI model:

[0351] "In a food delivery application, please implement a function where a character-shaped avatar selected by the user can confirm the order and notify the delivery status. The user's name is 'Taro' and the avatar selected is a 'robot character.'"

[0352] The flow of the specific processing in Application Example 3 will be described with reference to FIG.

[0353] Step 1:

[0354] The user starts the device and opens the food delivery application.

[0355] Input: User operation (application launch)

[0356] Output: The initial screen of the application is displayed.

[0357] Specific operation: The terminal displays the initial screen of the application and prompts the user to log in.

[0358] Step 2:

[0359] The user enters login information and clicks the login button.

[0360] Input: User login information (username, password)

[0361] Output: Login authentication result (success or failure)

[0362] Specific operation: The terminal sends the entered login information to the server, and the server refers to the database for authentication. If authentication is successful, the user's profile information is obtained.

[0363] Step 3:

[0364] The server obtains the user's profile information and sends it to the terminal.

[0365] Input: User login information

[0366] Output: User profile information (name, past orders, etc.)

[0367] Specific operation: The server retrieves the user's profile information from the database and sends it to the terminal. The terminal displays the retrieved information.

[0368] Step 4:

[0369] The user selects an avatar and places an order.

[0370] Input: User avatar selection, order details

[0371] Output: Selected avatar, order confirmation screen

[0372] Specific operation: The terminal sends the avatar selected by the user and the order details to the server. The server confirms the order details and sends an order confirmation screen to the terminal.

[0373] Step 5:

[0374] The server accepts the order and sends an order confirmation screen to the terminal.

[0375] Input: User's order details

[0376] Output: Order confirmation screen

[0377] Specific operation: The server saves the order details in a database, generates an order confirmation screen and sends it to the terminal, which then displays the order confirmation screen.

[0378] Step 6:

[0379] The user checks the order confirmation screen and confirms the order.

[0380] Input: User operation (pressing the order confirmation button)

[0381] Output: Order confirmation notification

[0382] Specific operation: The terminal transmits the user's operation to the server, the server confirms the order, sends a notification of the order confirmation to the terminal, and the terminal displays the notification.

[0383] Step 7:

[0384] The server manages the delivery status and notifies the terminal.

[0385] Input: Delivery status update

[0386] Output: Delivery status notification

[0387] Specific operation: The server monitors the delivery status in real time and sends updates to the device, which displays a notification of the delivery status.

[0388] Step 8:

[0389] The device displays a customizable character-shaped avatar and notifies you of delivery status.

[0390] Input: Delivery status notification

[0391] Output: Delivery status notification by avatar

[0392] Specific operation: The terminal displays the selected avatar and notifies the delivery status. The avatar provides a friendly interface for the user.

[0393] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0394] "Example 1"

[0395] The invention incorporating an emotion engine recognizes the user's emotions and adjusts the system's response accordingly. Specifically, the emotion engine recognizes emotions from the user's tone of voice, facial expressions, and choice of words. For example, if the system determines that the user is feeling stressed, it responds more politely or sends the user a message encouraging relaxation. If the system determines that the user is feeling happy, it responds according to the user's emotions, such as sending a message sharing that joy.

[0396] "Example 2"

[0397] The emotion engine also learns changes in the user's emotions and optimizes the system's response based on that. For example, if the system determines that a user feels stressed when performing a specific task, it will make suggestions to make the task easier or to delegate the task to another user. In this way, the emotion engine understands the user's emotions and optimizes the system's response accordingly, thereby improving user satisfaction.

[0398] "Example 3"

[0399] Furthermore, the emotion engine uses voice recognition and facial recognition technologies to recognize the user's emotions. For example, it infers emotions from the tone, strength, and speed of the user's voice when they speak to the system. It also infers emotions from facial expressions captured on a camera. By combining these technologies, it becomes possible to more accurately recognize the user's emotions and respond accordingly.

[0400] The processing flow of each embodiment will be described below.

[0401] "Example 1"

[0402] Step 1: User interaction begins. This occurs when the user makes a request to the system or the system periodically checks the user's status.

[0403] Step 2: The emotion engine recognizes the user's emotions from their tone of voice, facial expressions, and language. This emotion recognition is performed using voice recognition and facial recognition technology.

[0404] Step 3: The system adjusts its response to the user based on the emotions recognized by the emotion engine. For example, if the system determines that the user is feeling stressed, it may respond more politely or send a message encouraging the user to relax.

[0405] "Example 2"

[0406] Step 1: User interaction begins.

[0407] Step 2: The emotion engine recognizes the user's emotion.

[0408] Step 3: The emotion engine learns the user's emotional changes and optimizes the system's response based on them. For example, if the system determines that a user feels stressed when performing a certain task, it will make suggestions to make the task easier or to delegate the task to another user.

[0409] "Example 3"

[0410] Step 1: User interaction begins.

[0411] Step 2: The emotion engine recognizes the user's emotions. This emotion recognition is performed using voice recognition and facial recognition technology.

[0412] Step 3: The system adjusts the user's response based on the emotions recognized by the emotion engine. This response adjustment is made according to the user's emotions, improving user satisfaction.

[0413] Example 1

[0414] Next, a description will be given of Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0415] Conventional project management systems require manual selection of the responsible department and person in charge, presentation of storage locations for related documents, and responses based on the user's emotions, resulting in inefficiency and a heavy burden on the user. Furthermore, the inability to respond to user emotions can increase user stress and dissatisfaction. To solve these problems, a system is needed that automatically selects the responsible department and person in charge, automatically presents storage locations for related documents, and responds based on the user's emotions.

[0416] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0417] In this invention, the server includes means for introducing the department and person in charge, presenting the storage location of related materials and the necessary authorities, managing the schedule based on backward calculations until the target completion date, setting up meetings for the person in charge, and proposing and assisting with the content required to complete the task, means for having a shape that can be attached to as a character, means for recognizing the user's emotions and adjusting the system's response accordingly, and means for selecting the department and person in charge based on information such as position within the organization, expertise, past project experience, etc. This allows the user to efficiently proceed with projects and tasks and enables responses according to the user's emotions.

[0418] "Introducing the department and person in charge" means automatically selecting the most suitable department and person in charge for the project or task that the user has planned and presenting them to the user.

[0419] "Indicating where related materials are stored and the necessary permissions" means presenting to the user where materials related to a project or task are stored and the necessary permissions to access them.

[0420] "Schedule management based on counting backwards to the target completion date" means creating and managing a schedule by counting backwards based on the completion date of a project or task.

[0421] "Meeting schedule for responsible parties" means automatically setting up meetings between responsible parties involved in projects or tasks and incorporating them into the schedule.

[0422] "Proposal and assistance with the content required to complete a task" means proposing to the user the information and procedures required to complete a project or task and providing assistance with their execution.

[0423] A "shape that allows a user to become attached to the character" refers to a character that has a shape that is familiar to the user and that the user can become attached to.

[0424] "Means for recognizing the user's emotions and adjusting the system's response accordingly" means recognizing the user's emotions from their tone of voice, facial expressions, choice of words, etc., and changing the system's response according to those emotions.

[0425] "Method of selecting a responsible department and person in charge based on information such as position within the organization, expertise, and past project experience" means obtaining information such as position, expertise, and past project experience from an internal database within the organization, and using that information to select the most appropriate department and person in charge.

[0426] This invention is a system that automatically introduces the appropriate department and person in charge when an employee of a specific organization plans a new project or task, and also shows the location of related documents and the necessary permissions.It also has the function of recognizing the user's emotions and adjusting the system's response accordingly.

[0427] Hardware and software used

[0428] server:

[0429] The server uses a database management system (e.g., MySQL) to manage information such as organizational position, expertise, and past project experience. It also uses a machine learning library (e.g., scikit-learn) to run an algorithm to select the department and person in charge. It also uses an emotion engine (e.g., Microsoft® Azure® Emotion API) to recognize user emotions.

[0430] Device:

[0431] The terminal provides an interface for users to input project and task details, and displays the information sent from the server, allowing users to perform the necessary operations.

[0432] User:

[0433] The user uses the terminal to enter details of a new project or task and then progresses the project or task based on the information provided by the server.

[0434] Program processing

[0435] The server receives project and task details entered by the user and retrieves relevant information from the organization's database. Based on the retrieved information, it selects the appropriate department and person in charge, and presents the user with the location of relevant documents and the necessary permissions. It also uses an emotion engine to recognize the user's emotions and respond accordingly.

[0436] Specific examples

[0437] When a user creates a new marketing campaign, the system works as follows:

[0438] 1. A user uses a device to type "Design a new marketing campaign" and enters details (e.g., campaign objectives, required skill sets, deadline).

[0439] 2. The server retrieves the marketing department employees' job titles, expertise, and past project experience from a MySQL database.

[0440] 3. The server runs a machine learning model built using the scikit-learn library to select the most suitable employee from the marketing department.

[0441] 4. The server sends a link to a specific folder in Google Drive and editing permissions to the user's device.

[0442] 5. The server uses the Microsoft Azure Emotion API to determine whether the user is stressed based on their tone of voice.

[0443] 6. The server sends a message to the user's device saying, "Relax, you have all the information you need."

[0444] Prompt Sentence Examples

[0445] "I've developed a new marketing campaign. Can you introduce me to the appropriate department and person? Also, where can I find the relevant materials and what permissions do I need?"

[0446] In this way, the system allows servers, terminals, and users to work together to efficiently advance projects and tasks.

[0447] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0448] Step 1:

[0449] The user enters project and task details.

[0450] Input: The user uses a terminal to input details such as the project name, purpose, required skill set, deadline, etc.

[0451] What happens: The user types "design a new marketing campaign" into a form on their device, then enters details such as the campaign's objectives, required skill sets, and deadline.

[0452] Output: The terminal sends the input information to the server.

[0453] Step 2:

[0454] The server retrieves relevant information from an internal database.

[0455] Input: The server receives project and task details submitted by the user.

[0456] What happens: The server queries a MySQL database to get the job titles, expertise, and past project experience of employees in the marketing department.

[0457] Output: The server stores the retrieved information in its internal memory.

[0458] Step 3:

[0459] The server will select the appropriate department and person in charge.

[0460] Input: The server uses information about job title, expertise, and past project experience retrieved from a database.

[0461] How it works: The server runs a machine learning model built using the scikit-learn library to select the most suitable employee from the marketing department.

[0462] Output: The server generates information about the selected department and person in charge.

[0463] Step 4:

[0464] The server will provide the location of the relevant materials and the necessary permissions.

[0465] Input: The server uses the selected department and person information.

[0466] Specific operation: The server uses the Google Drive API to generate a link to the folder where the relevant materials are stored and edit permissions.

[0467] Output: The server sends the link to the storage location of the relevant material and the necessary permission information to the user's terminal.

[0468] Step 5:

[0469] The server uses an emotion engine to recognize the user's emotion.

[0470] Input: The server receives data such as the user's tone of voice, facial expressions, and language.

[0471] Specific operation: The server uses the Microsoft Azure Emotion API to analyze the user's emotions.

[0472] Output: The server recognizes the user's emotional state and stores the result in its internal memory.

[0473] Step 6:

[0474] The server responds according to the user's feelings.

[0475] Input: The server uses the recognized emotional state of the user.

[0476] What it does: If the user is stressed, the server generates a message like "Relax, you have all the information you need." If the user is happy, the server generates a message like "Good luck! Keep it up!"

[0477] Output: The server sends the generated message to the user's terminal.

[0478] (Application example 1)

[0479] Next, a description will be given of Application Example 1 of Embodiment Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0480] In conventional project management systems, selecting the appropriate department and person in charge is often done manually, which takes time and effort. Furthermore, because a uniform approach is taken without considering the user's feelings, this can increase user stress and dissatisfaction. Furthermore, when factory workers start a new project, they often don't know how to proceed, making efficient project management difficult.

[0481] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means. In this invention, the server includes means for introducing the responsible department and person in charge, presenting the storage location of related materials and the necessary authorities, managing the schedule based on backward calculations until the target completion date, setting up meetings for the person in charge, and proposing and assisting with the content necessary to complete the task, means for having a shape that can be attached to as a character, means for recognizing the user's emotions using an emotion engine and responding accordingly, and means for automatically assigning the appropriate responsible department and person in charge based on the details of the project. This enables flexible responses according to the user's emotions, realizes the rapid selection of the appropriate responsible department and person in charge, and enables efficient project management.

[0482] "Introducing the responsible department and person in charge" is a function that automatically selects the department and person in charge that are best suited to a specific project or task and presents them to the user.

[0483] "Indicating where related materials are stored and the necessary permissions" is a function that shows users where materials related to a project or task are stored and the permissions required to access those materials.

[0484] "Schedule management based on backward calculations to the target completion date" is a function that calculates backwards the necessary work based on the completion date of a project or task, and creates an efficient schedule.

[0485] "Meeting settings for responsible parties" is a function that automatically sets up meetings between responsible parties related to projects and tasks and incorporates them into the schedule.

[0486] "Suggesting and assisting with what is needed to complete a task" is a function that supports users by suggesting the information and procedures needed to complete a project or task.

[0487] A "shape that allows a user to become attached to the character" refers to a character that has a shape that is familiar to the user and that the user can become attached to.

[0488] "Means for recognizing the user's emotions using an emotion engine and responding accordingly" is a function that recognizes emotions from the user's tone of voice, facial expression, etc., and responds appropriately according to those emotions.

[0489] "A means of automatically assigning the appropriate department and person in charge based on the details of the project" is a function that automatically selects and assigns the most appropriate department and person in charge based on the content and requirements of the project.

[0490] The following system configuration is used as an embodiment of the present invention. The system includes means for introducing the department and person in charge, presenting the storage location of related materials and the necessary authorities, managing the schedule based on backward calculations until the target completion date, setting up meetings for the person in charge, and proposing and assisting with the content required to complete the task, means for providing a shape that can be attached to as a character, means for recognizing the user's emotions using an emotion engine and responding accordingly, and means for automatically assigning the appropriate department and person in charge based on the details of the project.

[0491] System Program

[0492] The system program is configured as follows:

[0493] 1. Introduction of the department and person in charge:

[0494] The server receives detailed information about projects and tasks and selects the most appropriate department and person to handle the project based on past project data and the expertise of the person in charge.

[0495] 2. Indicate where relevant materials are stored and the necessary permissions:

[0496] The server tells the user where the materials related to the project are stored and what permissions are required to access them.

[0497] 3. Schedule management based on backward calculations to the target completion date:

[0498] The server calculates backwards the required work based on the project completion date to create an efficient schedule.

[0499] 4. Meeting schedule for the person in charge:

[0500] The server automatically sets up and schedules meetings between people involved in the project.

[0501] 5. Suggestions and assistance with tasks required to complete the task:

[0502] The server supports users by suggesting the information and steps needed to complete a project or task.

[0503] 6. Shapes that allow you to become attached to the character:

[0504] The terminal displays the shape of a character that the user can easily relate to and become attached to.

[0505] 7. Using an emotion engine to recognize user emotions and respond accordingly:

[0506] The server recognizes the user's emotions from their tone of voice and facial expressions, and responds appropriately according to those emotions.

[0507] 8. How to automatically assign the right department and person based on project details:

[0508] The server automatically selects and assigns the most appropriate department and person in charge based on the project content and requirements.

[0509] Hardware and Software

[0510] Hardware: Cameras and microphones mounted on factory robots are used to capture workers' facial expressions and tone of voice.

[0511] software:

[0512] The emotion_recognition module analyzes the captured data and recognizes the emotions of the workers.

[0513] The project_assignment module automatically assigns the appropriate department and person based on project details.

[0514] Specific examples

[0515] For example, if a factory worker says, "I want to launch a new product line, but I don't know where to start," the server will recognize from the worker's tone of voice and facial expression that the worker is stressed. The server will respond, "Relax. We'll provide the support you need," and at the same time automatically assign the department and person best suited to launch the new product line.

[0516] Prompt Sentence Examples

[0517] I want to start a new project but I don't know where to start.

[0518] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0519] Step 1:

[0520] The user inputs information to launch a new project or task. Specifically, the user inputs a prompt such as, "I want to launch a new product line, but I don't know where to start." This input is sent to the server via the device's microphone and keyboard.

[0521] Step 2:

[0522] The server receives the input prompt and uses an emotion engine to recognize the user's emotions. Specifically, it analyzes the voice and text data to identify the user's emotions, such as whether they are stressed or happy. This process outputs the user's emotional state.

[0523] Step 3:

[0524] The server then determines the appropriate response based on the recognized emotion. For example, if the user is feeling stressed, the server generates a message such as, "Relax. We'll provide the support you need." This message takes the user's emotional state as input and processes it to output an appropriate response.

[0525] Step 4:

[0526] The server automatically assigns the appropriate department and person in charge based on detailed project information. Specifically, it references past project data and the expertise of the person in charge to select the most appropriate department and person in charge. This process outputs information about the department and person in charge.

[0527] Step 5:

[0528] The server presents the user with the storage location and required permissions for documents related to the project. Specifically, it searches a database of related documents to identify the storage location and access permissions for the relevant documents. This process outputs the document storage location and permission information.

[0529] Step 6:

[0530] The server calculates the necessary work backwards based on the project completion date to create an efficient schedule. Specifically, it uses project management software to calculate the start and end dates of each task. This process outputs the schedule information.

[0531] Step 7:

[0532] The server automatically schedules meetings between project participants and incorporates them into the schedule. Specifically, it references the participants' calendars to identify dates and times when everyone is available. This process outputs the date, time, and location of the meeting.

[0533] Step 8:

[0534] The server supports users by suggesting the information and procedures needed to complete a project or task. Specifically, it uses project management software to list the necessary resources and procedures. This process outputs the proposal.

[0535] Step 9:

[0536] The terminal displays the shape of a character that the user can easily relate to and become attached to. Specifically, it displays an animation of the character on the display to encourage interaction with the user. This process outputs the display of the character.

[0537] Example 2

[0538] Next, a description will be given of Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0539] Conventional schedule management systems make it difficult to grasp the progress of a project and schedule meetings efficiently. Furthermore, they do not take into account the user's feelings, leading to problems such as stress and a decrease in user satisfaction. This makes it difficult to efficiently progress a project and improve user satisfaction.

[0540] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0541] In this invention, the server includes means for introducing the responsible department and person in charge, presenting the storage location of related materials and necessary permissions, schedule management based on backward calculations until the target completion date, setting up meetings for the person in charge, and proposing and assisting with the content necessary to complete the task, means for collecting user emotion data and learning changes in emotion using a machine learning model, and means for optimizing the system's response based on the learning results and notifying the user of the proposed content. This makes it possible to easily grasp the progress of the project, efficiently set up meetings, and further improve user satisfaction by taking the user's emotions into consideration when responding.

[0542] A "department" is a department within an organization that is responsible for a particular task or project.

[0543] A "person in charge" is an individual who is responsible for a particular task or project.

[0544] "Relevant materials" are documents and files containing information or data necessary to carry out a project or task.

[0545] "Repository" is the location or system where relevant materials are stored.

[0546] "Required privileges" are the authorizations or authentications required to access specific materials or systems.

[0547] The "desired completion date" is the date by which the project or task is scheduled to be completed.

[0548] "Counting backwards" is a method of calculating the deadline for each task by working backwards from the completion date of the goal.

[0549] Schedule management is the process of planning and coordinating the progress of projects and tasks.

[0550] "Meeting scheduling" refers to planning and scheduling meetings related to a project or task.

[0551] "Proposing what is needed to complete a task" refers to proposing the steps and resources needed to complete a task.

[0552] "Assistance" refers to providing support to help complete a task or project.

[0553] "User" means an individual or member of an organization who uses the system.

[0554] "Emotion data" is information that indicates the user's emotional state, and is collected from facial expressions, voice, and the like.

[0555] A "machine learning model" is an algorithm that learns patterns based on data and makes predictions and classifications.

[0556] "Changes in emotions" refers to changes in a user's emotional state over time and in different situations.

[0557] "Learning results" are the knowledge and patterns that a machine learning model has acquired based on data.

[0558] "Optimizing the system's response" refers to adjusting the system's behavior and suggestions to be optimal based on the learning results.

[0559] "Suggestions" are specific actions or advice that the system provides to the user.

[0560] "Notification" is the act of the system conveying information to the user.

[0561] The present invention is a system for optimizing project management and user response based on emotions. A specific embodiment of this system will be described below.

[0562] Scheduling and meeting scheduling

[0563] 1. Enter the desired completion date

[0564] The user enters the desired completion date of the project into the system. For example, the user enters "December 31, 2023."

[0565] 2. Calculate task deadlines backwards

[0566] The server calculates the deadline for each task by counting backwards from the target completion date. This calculation uses the Python datetime library. For example, it calculates "the deadline for Task A is December 15, 2023, and the deadline for Task B is December 20, 2023."

[0567] 3. Save task deadlines

[0568] The server saves the calculated deadlines for each task in the database (MySQL). Specifically, it uses an SQL INSERT statement to save the deadlines as "Task A's deadline is December 15, 2023, and Task B's deadline is December 20, 2023."

[0569] 4. Automatically adjust schedules

[0570] The server automatically adjusts the schedule of the person in charge based on the deadlines of the saved tasks. Using the Google Calendar API, it adds the following to the person in charge's calendar: "The deadline for Task A is December 15, 2023, and the deadline for Task B is December 20, 2023."

[0571] 5. Schedule Update Notification

[0572] The device notifies the person in charge of the schedule update, using the Slack API to notify the person in charge that "The deadline for Task A has been set to December 15, 2023."

[0573] Response optimization using an emotion engine

[0574] 1. Entering emotion data

[0575] Input emotional data when the user performs a specific task. Emotional data is collected from the user's facial expressions and voice using emotion recognition software (e.g., Affectiva).

[0576] 2. Learning Emotion Data

[0577] The server inputs the collected emotion data into a machine learning model (e.g., TENSORFLOW (registered trademark)) to learn changes in the user's emotions. For example, the server learns that "the user feels stressed when performing task C."

[0578] 3. Optimizing response

[0579] The server optimizes the system's response based on the learning results, for example, "To simplify task C, we suggest splitting it into subtasks."

[0580] 4. Notification of Proposal Content

[0581] The device notifies the user of the proposal, using an email sending API (e.g., SendGrid) to notify the user, "To simplify task C, we suggest splitting it into subtasks."

[0582] Specific examples

[0583] When the user enters the desired completion date as "December 31, 2023," the server calculates that "the deadline for Task A is December 15, 2023, and the deadline for Task B is December 20, 2023," and saves this in the MySQL database.

[0584] The server uses the Google Calendar API to add the following to the person in charge's calendar: "The deadline for Task A is December 15, 2023, and the deadline for Task B is December 20, 2023," and the device notifies the person in charge using the Slack API.

[0585] If the emotion recognition software determines that the user feels stressed when performing Task C, the server inputs the data into a TensorFlow model to generate a response such as "Suggest splitting Task C into subtasks to make it easier."

[0586] The device uses the SendGrid API to notify the user via email, "To simplify task C, we suggest splitting it into subtasks."

[0587] Prompt Sentence Examples

[0588] "If the project's target completion date is December 31, 2023, how can I calculate the due dates of each task backwards and automatically adjust the schedules of the people responsible?"

[0589] "If you determine that a user is experiencing stress when performing a particular task, how can you provide suggestions to make that task easier?"

[0590] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0591] Scheduling and meeting scheduling

[0592] Step 1: Enter the desired completion date

[0593] The user enters the project's target completion date into the system.

[0594] Input: Objective completion date (e.g. December 31, 2023)

[0595] Output: The target completion date is saved in the system.

[0596] Specific operation: The user enters "December 31, 2023" into the system's input form and presses the submit button.

[0597] Step 2: Calculate task deadlines backwards

[0598] The server calculates the deadline for each task by counting backward from the target completion date.

[0599] Input: Objective completion date (e.g. December 31, 2023)

[0600] Output: Deadline for each task (e.g., Task A is due December 15, 2023, Task B is due December 20, 2023)

[0601] Specific operation: The server uses Python's datetime library to calculate the deadline for each task backward from the target completion date.

[0602] Step 3: Save the task deadline

[0603] The server stores the calculated deadline for each task in a database.

[0604] Input: Deadline for each task (e.g., Task A is due December 15, 2023, Task B is due December 20, 2023)

[0605] Output: Task deadlines stored in the database

[0606] Specific operation: The server uses an SQL INSERT statement to save the following to the MySQL database: "The deadline for Task A is December 15, 2023, and the deadline for Task B is December 20, 2023."

[0607] Step 4: Automatically adjust schedule

[0608] The server automatically adjusts the schedule of the person in charge based on the deadlines of the saved tasks.

[0609] Input: Task deadline stored in the database

[0610] Output: Due date of task added to assignee's calendar

[0611] Specific operation: The server uses the Google Calendar API to add the following to the person in charge's calendar: "The deadline for Task A is December 15, 2023, and the deadline for Task B is December 20, 2023."

[0612] Step 5: Notification of schedule updates

[0613] The terminal notifies the person in charge of schedule updates.

[0614] Input: Due date of the task added to the assignee's calendar

[0615] Output: Notification sent to assignee

[0616] Specific behavior: The device uses the Slack API to notify the person in charge that "The deadline for Task A has been set to December 15, 2023."

[0617] Response optimization using an emotion engine

[0618] Step 1: Enter emotion data

[0619] The user inputs emotion data when performing a specific task.

[0620] Input: User's emotional data (e.g., facial expressions and voice)

[0621] Output: Emotion data stored in the system

[0622] What it does: Use emotion recognition software (e.g., Affectiva) to collect emotion data from the user's facial expressions and voice.

[0623] Step 2: Learning emotion data

[0624] The server inputs the collected emotion data into a machine learning model to learn changes in the user's emotions.

[0625] Input: Collected emotion data

[0626] Output: Learning result (e.g., user feels stressed when performing task C)

[0627] Specific operation: The server inputs emotion data into the TensorFlow model and learns changes in the user's emotions.

[0628] Step 3: Optimize your response

[0629] The server optimizes the system's response based on the learning results.

[0630] Input: Learning results

[0631] Output: Optimized response (e.g., suggestions to simplify task C)

[0632] Specific operation: Based on the learning results, the server generates a response such as "Suggest splitting task C into subtasks to simplify it."

[0633] Step 4: Notification of proposal

[0634] The terminal notifies the user of the content of the proposal.

[0635] Input: Optimized response

[0636] Output: Notification of the suggestion sent to the user

[0637] Specific behavior: The device uses an email sending API (e.g., SendGrid) to notify the user, "To simplify task C, we suggest splitting it into subtasks."

[0638] (Application example 2)

[0639] Next, a description will be given of Application Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0640] In conventional schedule management systems, task deadlines are often set manually based on backward calculations until the target completion date, and meetings are scheduled for the responsible parties, making efficient project management difficult. Furthermore, tasks are not redistributed or simplified with consideration for the feelings of the workers, which increases worker stress and reduces productivity. Furthermore, there is a lack of a way to grasp the progress of a project in real time and efficiently schedule necessary meetings.

[0641] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0642] In this invention, the server includes means for introducing the department and person in charge, presenting the storage location of related materials and necessary authorities, schedule management based on backward calculations until the target completion date, setting up meetings for the person in charge, and proposing and assisting with the necessary content until the task is completed; means for having a shape that can be attached to as a character; means for using an emotion engine to learn changes in the user's emotions and suggesting simplification or reallocation of tasks when stress is felt; and means for grasping the progress of the project in real time through smart glasses and efficiently setting up necessary meetings. This enables efficient project management and stress reduction for workers.

[0643] A "department" is a department within an organization that is responsible for a particular task or project.

[0644] A "person in charge" is an individual who is responsible for a particular task or project.

[0645] "Relevant materials" are documents and files containing information or data necessary to carry out a project or task.

[0646] "Repository" is the location or system where relevant materials are stored.

[0647] "Necessary privileges" are the authorizations and authentications required to access relevant materials and systems.

[0648] The "target completion date" is the date by which a project or task should be completed.

[0649] "Counting backwards" is a method of setting deadlines for each task by working backwards from the date of completion of the goal.

[0650] "Schedule management" is the process of planning and managing the progress of tasks and projects.

[0651] "Meeting scheduling" refers to planning and scheduling meetings related to a project or task.

[0652] "Suggesting what is needed to complete a task" refers to providing the information and steps needed to complete a task.

[0653] "Assistance means" are methods and tools used to assist in the completion of a task or project.

[0654] A "shape that allows users to become attached to the character" is a design with a shape that users can feel familiar with.

[0655] The "emotion engine" is a technology that learns changes in the user's emotions and optimizes the system's response based on that.

[0656] "Smart glasses" are glasses-type devices that have the function of displaying information.

[0657] "Real-time understanding" refers to instantly checking the current situation and progress.

[0658] "Task simplification" refers to suggesting methods or steps to make a task easier.

[0659] "Redistribution" refers to reassigning a specific task to another person.

[0660] The system for implementing this invention uses the following hardware and software: The hardware includes smart glasses, a server, and a user terminal, while the software includes an emotion engine, a schedule management module, and a smart glasses interface.

[0661] The server provides the means to introduce the department and person in charge, indicate where related materials are stored and the necessary permissions, manage the schedule based on backward calculations until the target completion date, set up meetings for the person in charge, and propose and assist with the content required to complete the task, making it possible to efficiently manage the progress of the project.

[0662] The emotion engine learns the user's emotional changes and suggests simplification or reallocation of tasks if the user feels stressed. The user provides emotional data through the smart glasses, and the emotion engine analyzes the data. For example, if the user feels stressed while performing a specific task, the emotion engine suggests reallocating the task to another person.

[0663] Smart glasses provide a means to grasp the progress of projects in real time and efficiently schedule necessary meetings. Users can check the progress of projects through smart glasses, schedule necessary meetings, and manage the progress of tasks.

[0664] As a concrete example, consider a scenario in which a factory worker is wearing smart glasses. If the worker feels stressed while performing a particular task, the smart glasses will display a message saying, "You are feeling stressed. Would you like to simplify or reallocate the task 'Assembly'?" If the worker responds "Yes," the system will reallocate the task to another worker.

[0665] Examples of prompts to input to a generative AI model include:

[0666] "Develop a smart glasses application that sets task deadlines by counting backward from the project's intended completion date and monitors the worker's emotions. Include a function that suggests simplifying or reallocating tasks if the worker feels stressed."

[0667] In this way, efficient project management and reduced worker stress are achieved.

[0668] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0669] Step 1:

[0670] The server takes the project's target completion date as input and calculates backward to set the deadline for each task. This outputs a specific deadline for each task. The server automatically adjusts the schedule, taking into account task dependencies and priorities.

[0671] Step 2:

[0672] The server receives information about the department and person in charge as input and assigns the appropriate person to each task. This outputs the person in charge information for each task. The server selects the most appropriate person in charge, taking into account the person's skill set and current workload.

[0673] Step 3:

[0674] The server receives the storage location of the relevant materials and the necessary permissions as input, and grants the necessary permissions to the person in charge, allowing the person in charge to access the relevant materials. The server manages permissions based on the security policy.

[0675] Step 4:

[0676] The user wears smart glasses and checks the progress of the project in real time. The smart glasses receive data from the server as input and display the progress to the user, allowing the user to understand the progress of the current task.

[0677] Step 5:

[0678] The smart glasses collect emotional data while the user is performing a specific task. The emotion engine receives this emotional data as input and analyzes the user's emotional changes. The output is whether the user is feeling stressed.

[0679] Step 6:

[0680] If the emotion engine detects user stress, the server will propose task simplification or reallocation. The server receives current task information and the user's emotion data as input and outputs the optimal solution, thereby reducing the user's stress.

[0681] Step 7:

[0682] The user confirms the suggestions from the server through the smart glasses and responds. The user's response is sent as input to the server, which then reallocates or simplifies the tasks based on the input, thereby optimizing the progress of the tasks.

[0683] Step 8:

[0684] The server reassess the overall project progress and readjusts the schedule as necessary. The server receives the latest task information and the status of each person involved as input and outputs an updated schedule. This ensures that the project progress is always optimal.

[0685] Example 3

[0686] Next, a description will be given of a third embodiment of the third embodiment. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0687] With conventional systems, it was difficult to accurately recognize the user's emotions and respond appropriately. It was also difficult to adopt a character shape that users could feel attached to. This resulted in problems that reduced user convenience and satisfaction.

[0688] The specific processing by the specific processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means.

[0689] In this invention, the server includes means for introducing the department and person in charge, presenting the storage location of related materials and necessary permissions, managing the schedule based on a calculation of the target completion date, setting up meetings for the person in charge, and proposing and assisting with the necessary content until the task is completed; means for providing a shape that can be attached to the character; means for collecting and analyzing the user's voice data using voice recognition technology; means for collecting and analyzing the user's face data using face recognition technology; means for integrating the voice data and face data to estimate the user's emotions; means for generating an appropriate response based on the estimated emotions; and means for presenting the generated response to the user. This makes it possible to accurately recognize the user's emotions and provide an appropriate response accordingly. Furthermore, by adopting a character shape that the user can become attached to, user convenience and satisfaction can be improved.

[0690] A "department" is a department within an organization that is responsible for a particular task or project.

[0691] A "person in charge" is an individual who is responsible for a particular task or project.

[0692] "Relevant materials" are documents and files containing information and data necessary for the performance of a task or project.

[0693] "Repository" is the location or system where relevant materials are stored.

[0694] "Necessary privileges" are the authorizations and authentications required to access relevant materials and systems.

[0695] "Schedule management" is the process of making a plan to reach a target completion date, and then monitoring and adjusting the progress.

[0696] "Meeting arrangement" refers to the preparation and arrangement for holding a meeting at a specific date and time.

[0697] A "task" is a discrete task or activity performed to achieve a specific purpose.

[0698] A "proposal" refers to presenting a solution or idea to a specific problem or issue.

[0699] "Assistance" refers to providing support for specific tasks or activities and helping them to proceed smoothly.

[0700] "Character shape" refers to an appearance or shape designed to allow users to feel attached to the character.

[0701] "Speech recognition technology" is a technology that analyzes voice data and converts it into text or semantic information.

[0702] "Facial recognition technology" is a technology that analyzes facial features from image data to identify individuals and estimate their emotions.

[0703] "Voice data" refers to data that is a digital recording of a user's speech.

[0704] "Facial data" refers to image or video data of a user's face.

[0705] "Emotion estimation" is the process of analyzing voice and facial data to infer a user's emotional state.

[0706] "Response generation" is the process of creating appropriate responses or actions based on inferred emotions.

[0707] "Presenting" refers to showing or hearing the generated response to the user.

[0708] The present invention relates to a system that employs a character shape that a user can become attached to, recognizes the user's emotions, and responds appropriately. Specific embodiments of this system will be described below.

[0709] System configuration

[0710] Hardware

[0711] Device: A device with a microphone, camera, and speaker.

[0712] Server: A computer with high-performance data processing capabilities

[0713] software

[0714] Speech recognition software: Google Cloud Speech-to-Text

[0715] Facial Recognition Software: Microsoft Azure Face API

[0716] Generative AI model: An AI model for generating appropriate responses based on user emotions

[0717] Data processing and calculation

[0718] Audio data collection and analysis

[0719] The device uses a built-in microphone to collect the user's voice in real time, which is then sent digitally to a server, which then uses Google Cloud Speech-to-Text to convert the voice data into text and analyze characteristics such as tone, intensity, and speed of the voice.

[0720] Facial data collection and analysis

[0721] The device uses a built-in camera to capture a picture of the user's face. The captured facial image data is sent to a server, which then analyzes the facial data using the Microsoft Azure Face API and estimates emotions from facial features.

[0722] Emotion integration and estimation

[0723] The server integrates the results of voice and face recognition to more accurately estimate the user's emotions. For example, if the server detects "tired" from the voice and recognizes a "fatigued" facial expression, it determines that the user is tired.

[0724] Response generation and presentation

[0725] The server uses a generative AI model to generate an appropriate response based on the estimated emotion. The generated response is presented to the user via the device as voice or text. For example, the response could be "Please take it easy today" through a speaker.

[0726] Specific examples

[0727] The process flow when the user says "I'm very tired today" will be specifically described.

[0728] 1. The user says, "I'm very tired today."

[0729] 2. The device collects the user's voice using a microphone.

[0730] 3. The device takes a picture of the user's face with its camera.

[0731] 4. The server converts the voice data into text using Google Cloud Speech-to-Text, and estimates the level of fatigue based on the tone, strength, and speed of the voice.

[0732] 5. The server analyzes the facial data using the Microsoft Azure Face API and estimates the emotion of fatigue from the facial expression.

[0733] 6. The server combines the voice and facial data and determines that the user is tired.

[0734] 7. The server uses the generative AI model to generate a response: "Take it easy today."

[0735] 8. The device tells the user through the speaker, "Take it easy today."

[0736] Prompt Sentence Examples

[0737] Example prompts to input to the generative AI model:

[0738] Describe how the system would respond if the user said, "I'm very tired today."

[0739] By inputting this prompt sentence into the generative AI model, the system response can be specifically simulated. The flow of the identification process in the third embodiment will be described with reference to FIG.

[0740] Step 1:

[0741] The user initiates an interaction with the system.

[0742] Specific action: The user speaks to the system, such as "Hello" or "I'm very tired today."

[0743] Input: User's voice

[0744] Output: Audio data

[0745] Step 2:

[0746] The terminal collects the user's voice using a microphone.

[0747] Specific operation: The device's microphone collects the user's speech in real time and stores it as digital audio data.

[0748] Input: User's voice

[0749] Output: Digital audio data

[0750] Step 3:

[0751] The device takes a picture of the user's face with a camera.

[0752] Specific operation: The device's camera takes a picture of the user's face and saves it as image data.

[0753] Input: User's face

[0754] Output: Image data

[0755] Step 4:

[0756] The server analyzes the voice data using voice recognition software.

[0757] How it works: The server uses Google Cloud Speech-to-Text to convert the audio data into text and analyzes characteristics such as tone, strength, and speed of the voice.

[0758] Input: Digital audio data

[0759] Output: Text data and audio feature data

[0760] Step 5:

[0761] The server analyzes the facial data using facial recognition software.

[0762] Specific operation: The server uses the Microsoft Azure Face API to analyze facial data and estimate emotions from facial features.

[0763] Input: Image data

[0764] Output: Facial expression feature data and emotion estimation data

[0765] Step 6:

[0766] The server integrates the voice data and facial data to estimate the user's emotions.

[0767] Specific operation: The server integrates the results of voice and face recognition to more accurately estimate the user's emotions. For example, if the server estimates "tired" from the voice and recognizes a "fatigued" expression from the face, it determines that the user is tired.

[0768] Input: Text data, voice feature data, facial expression feature data, emotion estimation data

[0769] Output: Integrated emotion estimation data

[0770] Step 7:

[0771] The server generates an appropriate response based on the estimated emotion.

[0772] Specific behavior: The server uses the generative AI model to generate an appropriate response based on the estimated emotion. For example, if the server determines that the user is tired, it generates the response "Take it easy and rest today."

[0773] Input: Integrated emotion estimation data

[0774] Output: The generated response data

[0775] Step 8:

[0776] The terminal presents the generated response to the user.

[0777] Specific operation: The device presents the response sent from the server to the user as voice or text, for example, saying "Please take a good rest today" through the speaker.

[0778] Input: Generated response data

[0779] Output: Response presented to the user (audio or text)

[0780] (Application example 3)

[0781] Next, a description will be given of Application Example 3 of Form Example 3. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0782] Conventional systems make it difficult for users to receive appropriate support when searching for products in physical stores, and one problem is that they lack the ability to respond to the user's emotions. Another issue is that users cannot develop an attachment to the system, which reduces the frequency of use. To solve these problems, a system that recognizes the user's emotions and responds accordingly is needed.

[0783] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 3 is realized by the following means.

[0784] In this invention, the server includes means for introducing the responsible department and person in charge, presenting the storage location of related materials and the necessary authority, managing the schedule based on backward calculations until the target completion date, setting up meetings for the person in charge, and proposing and assisting with the necessary content until the task is completed, means for providing a shape that can be attached to as a character, means for recognizing the user's emotions using voice recognition technology and face recognition technology and responding accordingly, and means for providing appropriate support in a physical store based on the user's emotions. This enables the user to receive appropriate support according to their emotions when searching for products in a physical store, and also increases their attachment to the system.

[0785] A "department in charge" is a department or section in charge of a specific task or project.

[0786] A "person in charge" is an individual in charge of a particular task or project.

[0787] "Related materials" refers to documents and data related to a business or project.

[0788] "Repository" refers to the location or system where relevant materials are stored.

[0789] "Required authority" refers to the access rights and operational rights required to carry out a specific task or project.

[0790] "Schedule management" is the process of making a plan to reach a target completion date, and then monitoring and adjusting the progress.

[0791] "Meeting arrangement" refers to the preparation and arrangement for holding a meeting at a specific date and time.

[0792] A "task" is an operation or activity required to achieve a specific purpose.

[0793] A "proposal" refers to presenting a solution or improvement plan for a specific problem or issue.

[0794] "Assistance" refers to providing support to assist with a specific task or project.

[0795] A "character" is an entity with a shape or design that users can become attached to.

[0796] "Speech recognition technology" is a technology that converts speech into text and understands its content.

[0797] "Facial recognition technology" is a technology that detects faces from images taken with a camera and analyzes their facial expressions and features.

[0798] "Emotion recognition" refers to estimating a user's emotions from their tone of voice and facial expressions.

[0799] "Brick and mortar store" means a retail or service location that is located in a physical location.

[0800] "Support" means providing the user with the assistance or advice they need to achieve a specific goal.

[0801] A system for carrying out this invention has the following configuration: The system includes means for introducing the department and person in charge, presenting the storage location of related materials and the necessary authority, managing the schedule based on backward calculations until the target completion date, setting up meetings for the person in charge, and proposing and assisting with the content required to complete the task, means for providing a shape that can be attached to as a character, means for recognizing the user's emotions using voice recognition technology and face recognition technology and responding accordingly, and means for providing appropriate support based on the user's emotions in a physical store.

[0802] Hardware and software used

[0803] Hardware

[0804] Camera: Used to utilize facial recognition technology, capturing images of the user's facial expressions and acquiring image data to estimate emotions.

[0805] Microphone: Used to utilize voice recognition technology, collect the user's voice and obtain voice data to estimate emotions.

[0806] software

[0807] OpenCV: A library used to implement facial recognition technology, detecting faces in images captured by a camera and analyzing their facial expressions.

[0808] SpeechRecognition: A library used to implement speech recognition technology, converting audio data collected by a microphone into text and analyzing its content.

[0809] Transformers: A library used to implement emotion recognition models, which estimate user emotions based on data obtained from speech and facial recognition.

[0810] Data processing and calculation

[0811] Facial Recognition

[0812] The video captured by the camera is processed using OpenCV to detect faces, and the detected facial image data is input into an emotion recognition model to estimate emotions.

[0813] Voice Recognition

[0814] The voice data collected by the microphone is converted into text using the SpeechRecognition library, and the text is input into an emotion recognition model to estimate the emotion.

[0815] Responding according to emotions

[0816] Based on the estimated emotion, the system responds appropriately to the user. For example, if the user has a troubled expression, the system will suggest, "Is there something I can help you with?"

[0817] Specific examples

[0818] When a user is searching for a product in a physical store, the robot will ask, "What product are you looking for today?" If the user looks troubled, the robot will suggest, "Is there something I can help you with?"

[0819] Prompt Sentence Examples

[0820] If the user looks troubled, the robot will suggest, "Is there something I can help you with?"

[0821] In this way, the system can recognize the user's emotions and provide appropriate support accordingly, enabling users to receive appropriate support according to their emotions when searching for products in a physical store, and increasing their attachment to the system.

[0822] The flow of the specific processing in Application Example 3 will be described with reference to FIG.

[0823] Step 1:

[0824] The server uses a camera to capture the user's face. The input is video data from the camera, and the output is facial image data. Specifically, the camera captures the user's face in real time and sends the video data to the server.

[0825] Step 2:

[0826] The server uses OpenCV to detect faces from the facial image data. The input is the facial image data obtained in step 1, and the output is the area information of the detected face. Specifically, it applies the OpenCV face detection algorithm to identify the position and size of the face.

[0827] Step 3:

[0828] The server inputs the detected facial region information into an emotion recognition model to estimate the user's emotion. The input is facial region information, and the output is an estimated emotion label. Specifically, the emotion recognition model is executed using the Transformers library to estimate the emotion from the user's facial expression.

[0829] Step 4:

[0830] The server collects the user's voice using a microphone. The input is voice data from the microphone, and the output is voice data. Specifically, the microphone captures the user's speech in real time and sends the voice data to the server.

[0831] Step 5:

[0832] The server converts the voice data into text using the SpeechRecognition library. The input is the voice data obtained in step 4, and the output is text data. Specifically, it applies a voice recognition algorithm to convert the voice data into a string of characters.

[0833] Step 6:

[0834] The server inputs text data into an emotion recognition model to estimate the user's emotion. The input is text data, and the output is an estimated emotion label. Specifically, the server uses the Transformers library to run the emotion recognition model and estimate the emotion from the user's speech.

[0835] Step 7:

[0836] The server integrates the emotion labels obtained from facial and voice recognition to determine the final user emotion. The input is the emotion labels from facial and voice recognition, and the output is the integrated emotion label. Specifically, it compares both emotion labels and selects the emotion if they match, or selects the emotion with the higher priority if they differ.

[0837] Step 8:

[0838] The server responds appropriately to the user based on the integrated emotion label. The input is the integrated emotion label, and the output is a response message to the user. Specifically, it generates a prompt sentence according to the emotion label and responds to the user by voice or text.

[0839] In this way, the system can recognize the user's emotions and provide appropriate support accordingly.

[0840] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0841] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0842] Another example of generative AI is Gemini (registered trademark) (Internet search engine). <url: https: gemini.google.com ?hl="ja">) are mentioned.

[0843] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0844] [Second embodiment]

[0845] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0846] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0847] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0848] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0849] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0850] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0851] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0852] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0853] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0854] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0855] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0856] Next, the specific processing by the specific processing unit 290 of the data processing device 12 will be described.

[0857] "Example 1"

[0858] When an employee of a specific organization plans a new project or task, this embodiment of the present invention automatically introduces the appropriate department and person in charge. This introduction is made based on information such as the employee's position within the organization, expertise, and past project experience. The system also presents the location of related documents and the necessary permissions. This allows employees to quickly obtain the necessary information and start the task efficiently.

[0859] "Example 2"

[0860] Furthermore, this embodiment of the present invention manages schedules and schedules meetings for the person in charge based on a backward calculation of the target completion date. This allows employees to easily understand the progress of the project and efficiently schedule necessary meetings. Specifically, the deadline for each task is set by counting backward from the target completion date, and the schedule of the person in charge is automatically adjusted based on that.

[0861] "Example 3"

[0862] Furthermore, the present invention employs character shapes that users can develop an attachment to. These character shapes are robots, relatives, etc., and improve user convenience and satisfaction. Specifically, the character shapes can be customized to suit the user's preferences and the organization's culture.

[0863] The processing flow of each embodiment will be described below.

[0864] "Example 1"

[0865] Step 1: Employees plan new projects and tasks.

[0866] Step 2: The system automatically connects you to the right department and person based on information such as your position within the organization, your expertise, and past project experience.

[0867] Step 3: The system will show you where the relevant documents are stored and the necessary permissions, allowing you to quickly retrieve the information you need and begin your task efficiently.

[0868] "Example 2"

[0869] Step 1: Employee sets a target completion date for the project.

[0870] Step 2: The system automatically creates a schedule based on backward calculations to the desired completion date.

[0871] Step 3: The system schedules meetings for the person in charge, allowing employees to easily understand the progress of the project and efficiently schedule necessary meetings.

[0872] "Example 3"

[0873] Step 1: The system adopts a character shape that users can become attached to. This character shape can be a robot, a relative, or something similar, improving user convenience and satisfaction.

[0874] Step 2: Character shapes can be customized to suit user preferences and organizational culture.

[0875] Example 1

[0876] Next, a description will be given of Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0877] With conventional project management systems, when employees planned new projects or tasks, it was difficult to quickly find the appropriate department or person in charge, and it was time-consuming to specify where related documents were stored and the necessary permissions. Furthermore, project schedule management, meeting scheduling, and proposals and assistance until task completion were not efficiently performed. This resulted in delays to the start and progress of projects, and reduced overall efficiency.

[0878] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0879] In this invention, the server includes a means for introducing the relevant department and person in charge, a means for presenting the storage location of related materials and the necessary permissions, a means for managing schedules based on backward calculations to the target completion date, a means for setting up meetings for the person in charge, a means for suggesting and providing assistance with the content needed to complete the task, a means for generating prompts using a generative AI model and selecting the appropriate department and person in charge, and a means for creating a character that employees can feel attached to. This allows employees to quickly find the appropriate department and person in charge and easily confirm the storage location of related materials and the necessary permissions. Furthermore, the server can efficiently manage project schedules, set up meetings, and suggest and provide assistance until task completion, smoothing the start and progress of projects and improving overall efficiency.

[0880] The "means of introducing the responsible department and person in charge" is a function that automatically selects and introduces the appropriate department and person in charge within the organization for the project or task that the user has planned.

[0881] The "means for presenting the storage location of related materials and the necessary permissions" is a function that provides users with information on the storage location of materials related to a project or task and the permissions required to access them.

[0882] "A means of schedule management based on backward calculations to the target completion date" is a function that automatically creates and manages schedules by counting backwards based on the completion date of a project or task.

[0883] "Means for setting up meetings for responsible parties" is a function that automatically sets up meetings for responsible parties related to projects and tasks and incorporates them into the schedule.

[0884] "Means for proposing and assisting with the necessary content to complete a task" is a function that suggests information and procedures necessary to progress a project or task, and helps users complete tasks efficiently.

[0885] "Means for generating prompt sentences using a generative AI model and selecting an appropriate department and person in charge" refers to a function that uses a generative AI model to generate prompt sentences from the project and task details entered by the user, and selects an appropriate department and person in charge based on the prompt sentences.

[0886] "Means for having a shape that allows a user to become attached to the character" is a function that has a shape of a character that is familiar to the user and that the user can become attached to.

[0887] MODE FOR CARRYING OUT THE INVENTION

[0888] This invention is a system that automatically introduces the appropriate department and person in charge when an employee of a specific organization plans a new project or task. The system selects the department and person in charge based on information such as position within the organization, expertise, and past project experience, and also presents the location of related documents and the necessary permissions. This allows employees to quickly obtain the necessary information and start tasks efficiently.

[0889] Hardware and software used

[0890] Server: Database server (e.g. MySQL), application server (e.g. Apache Tomcat)

[0891] Devices: PCs and mobile devices used by employees

[0892] Software: Generative AI models (e.g., OpenAI GPT-4), project management tools (e.g., Jira)

[0893] Specific operation of the system

[0894] 1. A user creates a new project or task

[0895] A user uses a terminal to enter details of a new project or task into a project management tool, including the project name, purpose, deadline, required resources, and other information.

[0896] Example: When a user plans a "New Product Market Research Project," the user enters the project name as "New Product Market Research," the purpose as "Understanding Market Needs," and the deadline as "End of December 2023."

[0897] 2. The server receives the input data and sends prompts to the generative AI model.

[0898] The server receives project and task details entered by the user and generates prompts based on the received data to send to the generative AI model.

[0899] Example: "Please introduce me to the department and person who would be best suited to my new product market research project."

[0900] 3. The generative AI model selects the appropriate department and person in charge

[0901] The generative AI model selects the appropriate department and person in charge based on data such as position within the organization, expertise, and past project experience.

[0902] Example: A generative AI model returns the result, "Mr. Tanaka from the Marketing Department is the best candidate."

[0903] 4. The server will provide the location of the relevant materials and the necessary permissions.

[0904] The server then presents the selected department and person in charge with the location of the relevant documents and the necessary permissions. Specifically, it retrieves the location of the relevant documents and access permission information from the database and provides it to the user.

[0905] For example: "The relevant materials are in a 'Market Research' folder on a shared drive. Access is granted to everyone in the marketing department."

[0906] 5. User checks the results and starts the task

[0907] The user checks the information provided by the server through their terminal. Specifically, they check the department and person in charge, the storage location of related documents, and access permission information on the project management tool. They access the necessary documents and start tasks efficiently.

[0908] Example: A user accesses the "Market Research" folder based on the information provided, downloads the necessary materials, and starts the project.

[0909] This system allows employees to quickly find the appropriate department and person in charge, easily confirm where related documents are stored, and easily identify the necessary permissions. It also efficiently manages project schedules, schedules meetings, and provides suggestions and assistance until tasks are completed, resulting in smoother project initiation and progress, improving overall efficiency.

[0910] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0911] Step 1:

[0912] A user creates a new project or task.

[0913] A user uses a terminal to enter details of a new project or task into a project management tool, including the project name, purpose, deadline, required resources, and other information.

[0914] Input: Project name, purpose, deadline, required resources

[0915] Output: Project data stored in a project management tool

[0916] Specific operation: A user logs in to the project management tool, clicks the Create New Project button, enters the required information, and clicks the Save button.

[0917] Step 2:

[0918] The server receives the input data and sends prompts to the generative AI model.

[0919] The server receives project and task details entered by the user and generates prompts based on the received data to send to the generative AI model.

[0920] Input: Project Data

[0921] Output: The prompt to send to the generative AI model

[0922] Specific operation: The server receives new project data from the project management tool, generates prompt sentences, and sends the generated prompt sentences to the generative AI model.

[0923] Step 3:

[0924] The generative AI model selects the appropriate department and person in charge.

[0925] The generative AI model selects the appropriate department and person in charge based on data such as position within the organization, expertise, and past project experience.

[0926] Input: Prompt statement, organizational position, expertise, and past project experience data

[0927] Output: Information about the appropriate department and person in charge

[0928] Specific operation: The generative AI model receives the prompt, retrieves relevant information from the database, selects the most appropriate department and person in charge, and returns the results to the server.

[0929] Step 4:

[0930] The server will provide the location of the relevant materials and the necessary permissions.

[0931] The server will then present the selected department and person in charge with the location of the relevant documents and the necessary permissions.

[0932] Input: Department and person in charge information

[0933] Output: Information on where related materials are stored and the necessary permissions

[0934] Specific operation: The server receives the results from the generative AI model, retrieves the storage location and access permission information for the relevant materials from the database, generates information to provide to the user, and displays it in the project management tool.

[0935] Step 5:

[0936] The user reviews the results and starts the task.

[0937] The user checks the information provided by the server through their terminal. Specifically, they check the department and person in charge, the storage location of related documents, and access permission information on the project management tool. They access the necessary documents and start tasks efficiently.

[0938] Input: Information provided by the server

[0939] Output: Task started

[0940] Specific actions: The user checks the information displayed in the project management tool, accesses related materials, downloads the necessary materials, and starts the project.

[0941] (Application example 1)

[0942] Next, a description will be given of Application Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0943] In the past, when a new manufacturing process or maintenance task arose in a factory, it was difficult to quickly identify the appropriate department or person in charge, preventing efficient task initiation. Furthermore, there was insufficient information on where related documents were stored and the necessary permissions, which often delayed task progress. This resulted in a decline in overall productivity and was a serious problem in factory operations.

[0944] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0945] In this invention, the server includes means for introducing the department and person in charge, presenting the storage location of related materials and the necessary authority, schedule management based on backward calculation until the target completion date, setting up meetings for the person in charge, and proposing and assisting with the content required to complete the task, means for automatically introducing the appropriate department and person in charge when a new manufacturing process or maintenance task occurs in the factory, and means for identifying the most suitable person in charge based on information such as their position in the factory, expertise, and past project experience, and presenting the storage location of related materials and the necessary authority. This makes it possible to quickly identify the appropriate person in charge and provide related information when a new task occurs in the factory.

[0946] A "department" is a department within an organization that is responsible for carrying out a specific task or project.

[0947] A "personnel" is an individual selected to carry out a specific task or project.

[0948] "Relevant materials" are information and documents needed to complete a task or project.

[0949] "Storage location" refers to the location where relevant materials are stored.

[0950] "Permissions" are the access rights and operational privileges required to accomplish a specific task or project.

[0951] "Schedule management" means managing the progress of tasks and projects and making plans to reach the target completion date.

[0952] "Meeting arrangement" refers to planning a meeting related to a task or project and inviting participants.

[0953] A "proposal" is the presentation of specific methods or ideas for efficiently progressing a task or project.

[0954] "Assisting" means providing support to help complete a task or project.

[0955] A "manufacturing process" is a series of steps or procedures for creating a product.

[0956] "Maintenance tasks" are the work required to maintain, inspect, and repair machinery and equipment.

[0957] A "position" indicates a job or position within an organization.

[0958] "Specialized knowledge" refers to advanced knowledge and skills in a particular field.

[0959] "Project experience" refers to experience and track record related to projects that have been carried out in the past.

[0960] The system for implementing this invention has the function of automatically introducing the appropriate department and person in charge when a new manufacturing process or maintenance task occurs in a factory. The system consists of three main elements: a server, a terminal, and a user.

[0961] The server has the functions of introducing the responsible department and person in charge, showing where related documents are stored and the necessary permissions, managing the schedule based on backward calculations to the target completion date, setting up meetings for the person in charge, proposing and assisting with the content required to complete the task, etc. It also has the function of identifying the most suitable person based on information such as position within the factory, expertise, and past project experience, and showing where related documents are stored and the necessary permissions.

[0962] Terminals are devices used by each department and person in the factory, and they receive and display information from the server. Terminals include PCs, tablets, smartphones, etc.

[0963] Users are various departments and personnel within the factory, and access information provided by the server via their terminals. When a new manufacturing process or maintenance task arises, users can respond quickly based on the information from the server.

[0964] Specifically, when a new task arises in the factory, the server first inputs the task requirements. The server then retrieves employee information from the database and compares the task requirements with the employee's skills to identify the most suitable person. Once the most suitable person is identified, the server presents the location of related documents and the necessary permissions, and sends the information to the terminal. The user can receive this information through the terminal and start the task efficiently.

[0965] The hardware used includes servers, storage devices, PCs, tablets, and smartphones, and the software used includes Python and JSON libraries.

[0966] As a concrete example, consider a new manufacturing process that requires skills in mechanical engineering, programming, and project management. The server identifies the most suitable person based on these requirements and provides the location of the relevant documents and the necessary permissions.

[0967] Example prompts to input to a generative AI model:

[0968] A new manufacturing process has been developed that requires the following skills: mechanical engineering, programming, and project management. Identify the appropriate person, provide the location of the relevant documentation, and the necessary permissions.

[0969] This prompt can be used to input a generative AI model to identify the most appropriate person and suggest where relevant materials are stored and what permissions are required.

[0970] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0971] Step 1:

[0972] When a new manufacturing process or maintenance task arises in the factory, the server inputs the requirements for that task, including the required skills, job title, and expertise, thereby clarifying the specific requirements for the task.

[0973] Step 2:

[0974] The server retrieves employee information from a database, including each employee's job title, expertise, past project experience, etc. This provides data to compare with the task requirements.

[0975] Step 3:

[0976] The server compares the task requirements with the employee skills and identifies the most suitable person. Specifically, it scores employees whose skills match the task requirements and selects the employee with the highest score. This identifies the person best suited to the task.

[0977] Step 4:

[0978] Once the server identifies the most suitable person, it presents the location of the relevant documents and the necessary permissions. The location of the relevant documents is retrieved from the database, and the necessary permissions are determined based on the person's job title and skills. This provides the person with the information they need to complete the task.

[0979] Step 5:

[0980] The server then sends the identified person in charge and related information to the terminal. The terminal is a device used by the person in charge, such as a PC, tablet, or smartphone, allowing the person in charge to receive the necessary information.

[0981] Step 6:

[0982] The user receives information provided by the server through their terminal and efficiently starts the task. The user checks the storage location of related materials and the necessary permissions, and makes the necessary preparations to complete the task. This allows the task to proceed quickly and efficiently.

[0983] Step 7:

[0984] The user provides feedback on the progress of the task to the server, which then manages the schedule based on the feedback and suggests additional meetings or other tasks as necessary, thereby continuously supporting the progress of the task.

[0985] Example 2

[0986] Next, a description will be given of Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0987] In project management, it is difficult to efficiently manage schedules and schedule meetings based on backward calculations to the target completion date. Furthermore, there is a lack of systems that allow easy understanding of project progress and efficient scheduling of necessary meetings. Furthermore, there is a need for a method to automatically generate project progress reports using generative AI models.

[0988] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0989] In this invention, the server includes a means for a user to input a target completion date for the project, a means for the server to receive the target completion date and set a deadline for each task by calculating backwards, a means for the server to adjust the schedules of the people in charge and set meetings, a means for the server to send prompts to the generative AI model and generate a progress report, and a means for the server to provide the generated report to the user. This makes it possible to easily grasp the progress of the project and efficiently set up necessary meetings.

[0990] A "department" is a department within an organization that is responsible for a particular project or task.

[0991] A "person in charge" is an individual who is responsible for a particular task or project.

[0992] "Relevant materials" are documents and files containing information or data necessary to carry out a project or task.

[0993] "Repository" is the location or system where relevant materials are stored.

[0994] "Necessary privileges" are the authorizations and authentications required to access relevant materials and systems.

[0995] The "desired completion date" is the ultimate date by which a project or task should be completed.

[0996] "Counting backwards" is a calculation method that sets deadlines for each task by working backwards from the completion date of the goal.

[0997] "Schedule management" is the process of planning and managing the progress of projects and tasks.

[0998] "Meeting setup" is the process of scheduling a meeting for a specific date and time and notifying participants.

[0999] A "task" is a discrete task or activity required to complete a project.

[1000] A "suggestion" refers to a recommended method or means for completing a task.

[1001] "Assistance" refers to providing help or support to complete a task.

[1002] "User" refers to an individual or organization that uses the system to manage projects.

[1003] A "server" is a computer that is the core of a system and is a device that processes and stores data.

[1004] A "generative AI model" is a model that uses artificial intelligence to automatically perform specific tasks.

[1005] A "prompt" is text containing instructions or questions that are input to a generative AI model.

[1006] A "progress report" is a report summarizing the progress of a project or task.

[1007] A "character shape" is a shape that has an appearance or design that users can relate to.

[1008] The present invention is a system for efficiently managing schedules and setting up meetings for project managers based on backward calculations to the target completion date in a project management system. Specific embodiments of this system will be described below.

[1009] System configuration

[1010] This system includes a terminal used by the user, a server that processes data, and a generative AI model. The terminal is a device such as a PC or smartphone, and the server is a computer that processes and stores data. The generative AI model is a model that uses artificial intelligence to automatically perform specific tasks.

[1011] Hardware and software used

[1012] Devices: PC, smartphone

[1013] Server: A high-performance computer (e.g., a cloud server)

[1014] Database: MySQL

[1015] Schedule management library: pandas

[1016] Meeting Settings Library: datetime

[1017] Generative AI model: OpenAI GPT-3

[1018] Calendar API: Google Calendar API

[1019] Program processing

[1020] A user uses a terminal to access the web interface of the project management system. The user enters the target completion date of the project and clicks the "Submit" button. The server receives the target completion date sent by the user and retrieves all tasks of the project and their required times from the database. The server calculates the deadline for each task by counting backward from the target completion date and stores the results in the database.

[1021] The server then retrieves the schedule of each person using the Google Calendar API, schedules meetings based on the deadlines of each task, and sends meeting invitations based on the person's free time.

[1022] The server sends prompts to the generative AI model to generate progress reports, which are then provided to the user, who can view them using their device.

[1023] Specific examples

[1024] For example, consider a case where a user is managing a "new product development project." The user sets the project's target completion date as "December 31, 2023." The server calculates backwards from this date and sets the deadline for each task. For example, it calculates that the "market research" task needs to be completed by October 31, 2023.

[1025] Next, the server adjusts the schedule of the person in charge and sets a meeting for the "Market Research" task on "October 15, 2023." This meeting setting is done by obtaining free time from the person in charge's Google Calendar.

[1026] An example of a prompt to be input to the generative AI model is as follows:

[1027] Project Name: New Product Development

[1028] Objective completion date: December 31, 2023

[1029] Task: Market research

[1030] Task Deadline: October 31, 2023

[1031] Person in charge: Taro Tanaka

[1032] Meeting Date: October 15, 2023

[1033] Based on this prompt, the generative AI model generates a project progress report detailing the progress of each task and next steps.

[1034] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1035] Step 1:

[1036] The user enters the desired completion date for the project.

[1037] The user opens a browser on their device and accesses the web interface of the project management system. After logging in, a form for entering the project's target completion date is displayed. The user enters "December 31, 2023" and clicks the "Submit" button. The entered target completion date is sent to the server.

[1038] Step 2:

[1039] The server receives the target completion date and sets the deadline for each task by counting backwards.

[1040] The server receives the target completion date "December 31, 2023" sent by the user. Next, the server retrieves all the project's tasks and their required times from the database. For example, suppose "market research" takes 30 days, "design" takes 45 days, and "development" takes 60 days. The server calculates the deadline for each task by counting backwards from the target completion date, and sets the deadline for "market research" as "October 31, 2023," the deadline for "design" as "November 15, 2023," and the deadline for "development" as "December 1, 2023." These deadlines are saved in the database.

[1041] Step 3:

[1042] The server coordinates the schedules of the people in charge and sets up meetings.

[1043] The server uses the Google Calendar API to obtain the schedule of the person in charge. For example, it obtains the schedule of the person in charge, "Taro Tanaka," and sets a meeting for the "Market Research" task on "October 15, 2023." The server checks the person in charge's free time and sends a meeting invitation via Google Calendar. The meeting setting information is saved in a database.

[1044] Step 4:

[1045] The server sends prompts to the generative AI model and generates progress reports.

[1046] The server sends the following prompt to the generative AI model:

[1047] Project Name: New Product Development

[1048] Objective completion date: December 31, 2023

[1049] Task: Market research

[1050] Task Deadline: October 31, 2023

[1051] Person in charge: Taro Tanaka

[1052] Meeting Date: October 15, 2023

[1053] The generative AI model uses this prompt to generate a project progress report, which is then returned to the server.

[1054] Step 5:

[1055] The server provides the generated report to the user.

[1056] The server provides progress reports received from the generative AI model to the user, who then uses a browser on their device to access the project management system dashboard and view the reports, which detail the progress of each task and next steps to take.

[1057] (Application example 2)

[1058] Next, a description will be given of Application Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1059] Conventional schedule management systems lack the functionality to set deadlines for each task by counting backward from the target completion date and automatically adjust the schedules of the people in charge, making it difficult to easily grasp the progress of a project. In addition, schedule management for maintenance and part replacement of work equipment in factories is often done manually, making efficient operation difficult.

[1060] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for introducing the responsible department and person in charge, presenting the storage location of related materials and the necessary authority, schedule management based on backward calculations until the target completion date, setting up meetings for the person in charge, and proposing and assisting with the necessary content until the task is completed; means for managing the work schedule of work equipment in the factory and setting up deadlines for each task by backward calculations; means for automatically adjusting schedules for work equipment maintenance and part replacement and setting up necessary meetings; and means for having a shape that can be attached to as a character. This makes it easy to understand the progress of the project and enables efficient schedule management and meeting setting.

[1061] A "department" is a department within an organization that is responsible for a particular task or project.

[1062] A "person in charge" is an individual in charge of a particular task or project.

[1063] "Relevant materials" are documents and files that contain information or data necessary to complete a task or project.

[1064] "Repository" is the location or system where relevant materials are stored.

[1065] "Necessary privileges" are the authorizations and authentications required to access relevant materials and systems.

[1066] The "desired completion date" is the date by which a particular task or project is intended to be completed.

[1067] "Counting backwards" is a method of setting deadlines for each task by working backwards from the date of completion of the goal.

[1068] Schedule management is the process of planning and coordinating the progress of tasks and projects.

[1069] "Meeting scheduling" refers to scheduling meetings necessary to progress a task or project.

[1070] A "task" is an operation or activity that must be performed to achieve a specific purpose.

[1071] A "suggestion" is an idea or method that can help accomplish a task or project.

[1072] "Assistance" refers to providing the means or support to help complete a task or project.

[1073] "Factory equipment" refers to machines and devices used in factories.

[1074] "Maintenance" refers to the maintenance work required to maintain the normal operation of work equipment.

[1075] "Parts replacement" is the process of replacing worn out parts of work equipment with new parts.

[1076] "A shape that allows users to become attached to the character" refers to a design and shape that users find familiar.

[1077] A system for carrying out this invention is configured as follows: The server includes means for introducing the department and person in charge, presenting the storage location of related materials and the necessary authority, managing the schedule by counting backward until the target completion date, setting up meetings for the person in charge, and proposing and assisting with the content necessary to complete the task, means for managing the work schedule of work equipment in the factory and setting the deadline for each task by counting backward, means for automatically adjusting the schedule for maintenance and part replacement of the work equipment and setting the necessary meetings, and means for having a shape that can be attached to as a character.

[1078] The server runs a program using Python. The program calculates the deadline based on the number of days required for each task and sets the date of the meeting. Specifically, the server receives a list of tasks, calculates the number of days required for each task, and sets the deadline for each task by counting backward from the target completion date. It also schedules a meeting for the day before the deadline for each task.

[1079] The hardware used is a smartphone or tablet, and users access the schedule management system through these devices. The software runs programs using Python, and data processing includes back-calculating deadlines based on the number of days required for tasks and setting meeting dates.

[1080] As a concrete example, the following prompt sentence is input to the generative AI model:

[1081] "I want to develop a schedule management application for factory robots. It should have the ability to set deadlines for each task by counting backwards from the target completion date and automatically adjust the schedules of the people in charge. Please create a program using Python that calculates task deadlines and sets meeting dates."

[1082] An example output from a generative AI model might look like this:

[1083] "This application manages the work schedules of robots in the factory and sets deadlines for each task by counting backwards. It also automatically adjusts schedules for robot maintenance and part replacement, and sets necessary meetings. Using Python, we created a program that counts backwards from deadlines based on the number of days required for each task and sets meeting dates."

[1084] In this way, users can easily grasp the progress of the project and efficiently manage schedules and schedule meetings.

[1085] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1086] Step 1:

[1087] The server receives a list of tasks and their intended completion dates from the user. The input includes the name of each task, the number of days required, and the intended completion date. The server receives this data and stores it in an internal database.

[1088] Step 2:

[1089] The server calculates the deadline for each task by counting backward from the target completion date. The target completion date and the number of days required for each task are used as input. The server sets the deadline for each task by subtracting the number of days required for each task from the target completion date. The output is the deadline for each task.

[1090] Step 3:

[1091] The server schedules meetings on the day before each task's due date. The server uses the due date of each task as input. The server sets the meeting date by one day before each task's due date. The server gets the meeting date as output.

[1092] Step 4:

[1093] The server automatically adjusts the schedule for maintenance and part replacement of work equipment in the factory. The number of days required for maintenance and part replacement of work equipment and the deadline are used as input. The server calculates and sets the optimal schedule based on this data. The maintenance and part replacement schedule is obtained as output.

[1094] Step 5:

[1095] The server notifies the user of the schedule and meeting dates. The deadlines for each task and the meeting dates are used as input. The server sends this data to the user's terminal and notifies them. As output, the user can check the schedule and meeting dates.

[1096] Step 6:

[1097] The user checks the schedule and meeting dates through the terminal and makes adjustments as necessary. The schedule and meeting dates sent from the server are used as input. The user checks the progress of tasks based on this data and makes necessary adjustments. The adjusted schedule is obtained as output.

[1098] Example 3

[1099] Next, a description will be given of Example 3 of Form Example 3. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1100] Conventional systems have made it difficult to efficiently perform tasks such as introducing the relevant departments and personnel, presenting the storage locations of related documents and the necessary permissions, managing schedules, setting up meetings, and proposing and assisting with task completion. It has also been difficult to provide character shapes that users can develop an attachment to the system. Furthermore, it has not been possible to generate character shapes that can be customized to suit the user's preferences and organizational culture. To solve these issues, a means is needed to generate prompt sentences using a generative AI model and generate detailed specifications for character shapes.

[1101] The specific processing by the specific processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means.

[1102] In this invention, the server includes means for introducing the responsible department and person in charge, presenting the storage location of related materials and necessary permissions, managing the schedule based on backward calculation until the target completion date, setting up meetings for the person in charge, and proposing and assisting with the content required to complete the task, means for generating a character shape that can be customized to suit the user's preferences and the organization's culture, means for generating prompt sentences using a generative AI model and generating detailed specifications for the character shape, means for sending the generated character shape data to a terminal and displaying it to the user, and means for collecting feedback from the user and updating the character shape.This enables work efficiency to be improved and user satisfaction to be increased.

[1103] A "department" is a department within an organization that is responsible for a particular task or project.

[1104] A "person in charge" is an individual who is responsible for a particular task or project.

[1105] "Relevant materials" are documents and data necessary for the execution of a task or project.

[1106] "Repository" is the location or system where relevant materials are stored.

[1107] "Necessary privileges" are the authorizations and authentications required to access relevant materials and systems.

[1108] "Schedule management" refers to planning and adjusting the progress of work or projects by working backwards to the desired completion date.

[1109] "Meeting arrangement" refers to planning a meeting related to work or a project and inviting participants.

[1110] "Proposing and assisting with the necessary content to complete a task" refers to providing the information and support necessary to carry out a task or project.

[1111] A "character shape" is a shape that a user can become attached to, and includes shapes such as robots and relatives.

[1112] A "generative AI model" is a model that uses artificial intelligence to perform specific tasks, such as generating prompts and generating detailed specifications for character shapes.

[1113] A "prompt" is text that is input to a generative AI model and contains instructions for generating detailed specifications for a character's shape.

[1114] "Character shape data" refers to data that includes detailed specifications of the character shape generated by the generative AI model.

[1115] A "terminal" is a device that receives character shape data and displays it to the user.

[1116] "Feedback" refers to opinions and requests provided by users that are used to improve and customize character shapes.

[1117] This invention is a system that introduces the department and person in charge, shows the storage location of related documents and the necessary authority, manages schedules based on backward calculations until the target completion date, sets up meetings for the person in charge, and suggests and assists with the content required to complete the task.It also includes a function to generate character shapes that can be customized to suit the user's preferences and the organization's culture.

[1118] Server Operation

[1119] The server first receives input data from the user, including information about the user's preferences and organizational culture. The server generates a prompt based on this data. The prompt is then fed into a generative AI model (e.g., OpenAI's GPT-4) and used to generate detailed specifications for the character's shape.

[1120] The generated character shape data is sent from the server to the device. The device receives this data and displays it to the user. The user can check the character shape and provide feedback. The server inputs this feedback back into the generative AI model and updates the character shape.

[1121] Device behavior

[1122] The device receives the character shape data sent from the server. The received data is stored in the device's local storage. The device uses a 3D rendering engine to display the character shape on the screen. The user uses an interface to check this display and provide feedback. The device collects the user's feedback and sends it to the server.

[1123] User Actions

[1124] The user checks the character shape displayed on the device. They operate the device's UI components to input specific improvements and requests. For example, they provide feedback such as "I want the face to be more friendly" or "I want the robot's shape to be a bit more futuristic." The user presses the "Submit" button to send the feedback data to the server.

[1125] Specific examples

[1126] Example prompts to be input to the generative AI model

[1127] "The user wants a friendly robot character shape. The robot should have round eyes, a smiling face, and a blue body. Also, since the user's organization is related to education, the robot should be holding a book, which symbolizes knowledge."

[1128] By inputting this prompt into the generative AI model, a character shape that matches the user's wishes is generated. The generated character shape is sent from the server to the device and displayed to the user. The user can check the shape and provide further feedback if necessary.

[1129] In this way, the efficiency of the work and the satisfaction of the users are improved. The flow of the identification process in the third embodiment will be described with reference to FIG.

[1130] Step 1:

[1131] The server receives input data from the user. The input data includes information about the user's preferences and the organization's culture. Specifically, the server receives an HTTP request, saves the user's input data in a database, analyzes the input data, and prepares it for generating a prompt.

[1132] Step 2:

[1133] The server generates a prompt sentence based on the received user data. Specifically, the server runs a Python script, analyzes the user data, and generates a prompt sentence. The input data is analyzed and a prompt sentence is created to be input into the generative AI model. The generated prompt sentence is obtained as the output.

[1134] Step 3:

[1135] The server invokes the generative AI model and provides the generated prompt sentence as input. Specifically, the server sends an API request to the generative AI model to obtain the character shape specification. Using the prompt sentence as input, the server obtains the detailed character shape specification as output.

[1136] Step 4:

[1137] The server generates detailed data for the character's shape based on the data returned from the generative AI model. Specifically, the server analyzes the acquired data and executes scripts to generate 3D models and image data. The server uses the character's shape specifications as input and obtains character shape data as output.

[1138] Step 5:

[1139] The server sends the generated character shape data to the terminal. Specifically, the server generates an HTTP response and sends the response including the character shape data to the terminal. The character shape data is used as input, and data sent to the terminal is obtained as output.

[1140] Step 6:

[1141] The device receives the character shape data sent from the server. Specifically, the device receives the HTTP response and saves the character shape data in local storage. The data from the server is used as input, and the data saved in local storage is obtained as output.

[1142] Step 7:

[1143] The device displays the received character shape data to the user. Specifically, the device uses a 3D rendering engine to display the character shape on the screen. It uses the data in the local storage as input and obtains the character shape displayed to the user as output.

[1144] Step 8:

[1145] The user checks the character shape displayed on the device and provides feedback. Specifically, the user operates the device's UI components and inputs specific improvements and requests. The user's opinions and requests are used as input, and feedback data is obtained as output.

[1146] Step 9:

[1147] The terminal sends the collected user feedback to the server. Specifically, the terminal generates an HTTP request and sends data including the user feedback to the server. The feedback data is used as input, and the data sent to the server is obtained as output.

[1148] Step 10:

[1149] The server receives feedback from the user and updates the character shape. Specifically, the server analyzes the feedback data and updates the character shape again using the generative AI model. The feedback data is used as input, and updated character shape data is obtained as output.

[1150] (Application example 3)

[1151] Next, a description will be given of Application Example 3 of Form Example 3. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1152] Conventional food delivery services have faced problems such as low user satisfaction due to the impersonal nature of the systems used to confirm orders and receive delivery status notifications. Additionally, it has been difficult for users to develop an attachment to the service, making it difficult to encourage repeat use.

[1153] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 3 is realized by the following means.

[1154] In this invention, the server includes means for introducing the department and person in charge, presenting the storage location of related materials and the necessary authority, managing the schedule based on backward calculations until the target completion date, setting up meetings for the person in charge, and proposing and assisting with the necessary content until the task is completed, means for having a shape that can be attached to as a character, and means for displaying a character-shaped avatar that can be customized to suit the user's preferences, and for confirming orders and notifying of delivery status. This makes it possible for users to become attached to the service, improves satisfaction, and encourages repeat use.

[1155] A "department" is a department or section that is responsible for a specific job or task.

[1156] A "person in charge" is an individual in charge of a particular job or task.

[1157] "Relevant materials" means documents or files containing information or data necessary to carry out a job or task.

[1158] "Repository" refers to the location or system where relevant materials are stored.

[1159] "Required authority" refers to the access rights and operational rights required to carry out a specific job or task.

[1160] "Schedule management" refers to planning and adjusting the progress of work and tasks by working backwards to the desired completion date.

[1161] "Meeting arrangement" refers to planning and coordinating a meeting where people in charge gather to discuss and share information.

[1162] "Proposing and assisting with the necessary content to complete a task" refers to proposing the information and procedures necessary to complete a job or task and supporting their execution.

[1163] "Shapes that allow users to become attached to the character" refers to designs and shapes that are familiar to users and that they can become attached to.

[1164] A "customizable character avatar" is a character whose appearance and functions can be changed to suit the user's preferences.

[1165] "Order confirmation" refers to checking the order details placed by the User to ensure their accuracy.

[1166] "Delivery status notification" refers to informing users of the current status of their ordered items.

[1167] The system for implementing this invention consists of three main elements: a server, a terminal, and a user. The following explains how each element functions.

[1168] server

[1169] The server has functions to introduce the department and person in charge, show the storage location of related documents and the necessary permissions, manage the schedule based on backward calculations until the target completion date, set up meetings for the person in charge, and suggest and assist with the necessary content until the task is completed.It also provides a means of having a shape that can be attached to as a character, displays a character-shaped avatar that can be customized to the user's preferences, and has functions to confirm orders and notify delivery status.

[1170] Specifically, the server is implemented using a programming language such as Python, and the database uses MySQL, PostgreSQL, etc. The server's role is to receive requests from users and return appropriate data.

[1171] Terminal

[1172] A terminal is a device that is directly operated by the user, such as a smartphone or tablet. The terminal displays data sent from the server and provides an interface that the user can operate. In particular, a character-shaped avatar that can be customized to suit the user's preferences is displayed on the terminal, and the terminal confirms orders and notifies delivery status.

[1173] Applications on devices are developed using cross-platform frameworks such as React Native and Flutter, which allow for efficient development of applications that run on multiple platforms, including iOS and Android.

[1174] User

[1175] Users use a terminal to use the food delivery service. They place an order through the application and select a customizable character-shaped avatar. The avatar confirms the order, notifies the delivery status, and provides a friendly interface to the user.

[1176] As a concrete example, consider the case where the user is "Taro" and the avatar he has chosen is a "robot character." In this case, the application would behave as follows:

[1177] When you launch the application, a "robot character" will appear and say, "A robot character will help you with your order!"

[1178] When you confirm your order, the message "Robot character: Taro, your order has been confirmed" will be displayed.

[1179] When you update the delivery status, it will say "Robot character: Current delivery status is 'In delivery'" or "Robot character: Current delivery status is 'Delivered'."

[1180] Example prompts to input to a generative AI model:

[1181] "In a food delivery application, please implement a function where a character-shaped avatar selected by the user can confirm the order and notify the delivery status. The user's name is 'Taro' and the avatar selected is a 'robot character.'"

[1182] The flow of the specific processing in Application Example 3 will be described with reference to FIG.

[1183] Step 1:

[1184] The user starts the device and opens the food delivery application.

[1185] Input: User operation (application launch)

[1186] Output: The initial screen of the application is displayed.

[1187] Specific operation: The terminal displays the initial screen of the application and prompts the user to log in.

[1188] Step 2:

[1189] The user enters login information and clicks the login button.

[1190] Input: User login information (username, password)

[1191] Output: Login authentication result (success or failure)

[1192] Specific operation: The terminal sends the entered login information to the server, and the server refers to the database for authentication. If authentication is successful, the user's profile information is obtained.

[1193] Step 3:

[1194] The server obtains the user's profile information and sends it to the terminal.

[1195] Input: User login information

[1196] Output: User profile information (name, past orders, etc.)

[1197] Specific operation: The server retrieves the user's profile information from the database and sends it to the terminal. The terminal displays the retrieved information.

[1198] Step 4:

[1199] The user selects an avatar and places an order.

[1200] Input: User avatar selection, order details

[1201] Output: Selected avatar, order confirmation screen

[1202] Specific operation: The terminal sends the avatar selected by the user and the order details to the server. The server confirms the order details and sends an order confirmation screen to the terminal.

[1203] Step 5:

[1204] The server accepts the order and sends an order confirmation screen to the terminal.

[1205] Input: User's order details

[1206] Output: Order confirmation screen

[1207] Specific operation: The server saves the order details in a database, generates an order confirmation screen and sends it to the terminal, which then displays the order confirmation screen.

[1208] Step 6:

[1209] The user checks the order confirmation screen and confirms the order.

[1210] Input: User operation (pressing the order confirmation button)

[1211] Output: Order confirmation notification

[1212] Specific operation: The terminal transmits the user's operation to the server, the server confirms the order, sends a notification of the order confirmation to the terminal, and the terminal displays the notification.

[1213] Step 7:

[1214] The server manages the delivery status and notifies the terminal.

[1215] Input: Delivery status update

[1216] Output: Delivery status notification

[1217] Specific operation: The server monitors the delivery status in real time and sends updates to the device, which displays a notification of the delivery status.

[1218] Step 8:

[1219] The device displays a customizable character-shaped avatar and notifies you of delivery status.

[1220] Input: Delivery status notification

[1221] Output: Delivery status notification by avatar

[1222] Specific operation: The terminal displays the selected avatar and notifies the delivery status. The avatar provides a friendly interface for the user.

[1223] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1224] "Example 1"

[1225] The invention incorporating an emotion engine recognizes the user's emotions and adjusts the system's response accordingly. Specifically, the emotion engine recognizes emotions from the user's tone of voice, facial expressions, and choice of words. For example, if the system determines that the user is feeling stressed, it responds more politely or sends the user a message encouraging relaxation. If the system determines that the user is feeling happy, it responds according to the user's emotions, such as sending a message sharing that joy.

[1226] "Example 2"

[1227] The emotion engine also learns changes in the user's emotions and optimizes the system's response based on that. For example, if the system determines that a user feels stressed when performing a specific task, it will make suggestions to make the task easier or to delegate the task to another user. In this way, the emotion engine understands the user's emotions and optimizes the system's response accordingly, thereby improving user satisfaction.

[1228] "Example 3"

[1229] Furthermore, the emotion engine uses voice recognition and facial recognition technologies to recognize the user's emotions. For example, it infers emotions from the tone, strength, and speed of the user's voice when they speak to the system. It also infers emotions from facial expressions captured on a camera. By combining these technologies, it becomes possible to more accurately recognize the user's emotions and respond accordingly.

[1230] The processing flow of each embodiment will be described below.

[1231] "Example 1"

[1232] Step 1: User interaction begins. This occurs when the user makes a request to the system or the system periodically checks the user's status.

[1233] Step 2: The emotion engine recognizes the user's emotions from their tone of voice, facial expressions, and language. This emotion recognition is performed using voice recognition and facial recognition technology.

[1234] Step 3: The system adjusts its response to the user based on the emotions recognized by the emotion engine. For example, if the system determines that the user is feeling stressed, it may respond more politely or send a message encouraging the user to relax.

[1235] "Example 2"

[1236] Step 1: User interaction begins.

[1237] Step 2: The emotion engine recognizes the user's emotion.

[1238] Step 3: The emotion engine learns the user's emotional changes and optimizes the system's response based on them. For example, if the system determines that a user feels stressed when performing a certain task, it will make suggestions to make the task easier or to delegate the task to another user.

[1239] "Example 3"

[1240] Step 1: User interaction begins.

[1241] Step 2: The emotion engine recognizes the user's emotions. This emotion recognition is performed using voice recognition and facial recognition technology.

[1242] Step 3: The system adjusts the user's response based on the emotions recognized by the emotion engine. This response adjustment is made according to the user's emotions, improving user satisfaction.

[1243] Example 1

[1244] Next, a description will be given of Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1245] Conventional project management systems require manual selection of the responsible department and person in charge, presentation of storage locations for related documents, and responses based on the user's emotions, resulting in inefficiency and a heavy burden on the user. Furthermore, the inability to respond to user emotions can increase user stress and dissatisfaction. To solve these problems, a system is needed that automatically selects the responsible department and person in charge, automatically presents storage locations for related documents, and responds based on the user's emotions.

[1246] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1247] In this invention, the server includes means for introducing the department and person in charge, presenting the storage location of related materials and the necessary authorities, managing the schedule based on backward calculations until the target completion date, setting up meetings for the person in charge, and proposing and assisting with the content required to complete the task, means for having a shape that can be attached to as a character, means for recognizing the user's emotions and adjusting the system's response accordingly, and means for selecting the department and person in charge based on information such as position within the organization, expertise, past project experience, etc. This allows the user to efficiently proceed with projects and tasks and enables responses according to the user's emotions.

[1248] "Introducing the department and person in charge" means automatically selecting the most suitable department and person in charge for the project or task that the user has planned and presenting them to the user.

[1249] "Indicating where related materials are stored and the necessary permissions" means presenting to the user where materials related to a project or task are stored and the necessary permissions to access them.

[1250] "Schedule management based on counting backwards to the target completion date" means creating and managing a schedule by counting backwards based on the completion date of a project or task.

[1251] "Meeting schedule for responsible parties" means automatically setting up meetings between responsible parties involved in projects or tasks and incorporating them into the schedule.

[1252] "Proposal and assistance with the content required to complete a task" means proposing to the user the information and procedures required to complete a project or task and providing assistance with their execution.

[1253] A "shape that allows a user to become attached to the character" refers to a character that has a shape that is familiar to the user and that the user can become attached to.

[1254] "Means for recognizing the user's emotions and adjusting the system's response accordingly" means recognizing the user's emotions from their tone of voice, facial expressions, choice of words, etc., and changing the system's response according to those emotions.

[1255] "Method of selecting a responsible department and person in charge based on information such as position within the organization, expertise, and past project experience" means obtaining information such as position, expertise, and past project experience from an internal database within the organization, and using that information to select the most appropriate department and person in charge.

[1256] This invention is a system that automatically introduces the appropriate department and person in charge when an employee of a specific organization plans a new project or task, and also shows the location of related documents and the necessary permissions.It also has the function of recognizing the user's emotions and adjusting the system's response accordingly.

[1257] Hardware and software used

[1258] server:

[1259] The server uses a database management system (e.g., MySQL) to manage information such as organizational position, expertise, and past project experience, a machine learning library (e.g., scikit-learn) to run an algorithm to select the department and person in charge, and an emotion engine (e.g., Microsoft Azure Emotion API) to recognize user emotions.

[1260] Device:

[1261] The terminal provides an interface for users to input project and task details, and displays the information sent from the server, allowing users to perform the necessary operations.

[1262] User:

[1263] The user uses the terminal to enter details of a new project or task and then progresses the project or task based on the information provided by the server.

[1264] Program processing

[1265] The server receives project and task details entered by the user and retrieves relevant information from the organization's database. Based on the retrieved information, it selects the appropriate department and person in charge, and presents the user with the location of relevant documents and the necessary permissions. It also uses an emotion engine to recognize the user's emotions and respond accordingly.

[1266] Specific examples

[1267] When a user creates a new marketing campaign, the system works as follows:

[1268] 1. A user uses a device to type "Design a new marketing campaign" and enters details (e.g., campaign objectives, required skill sets, deadline).

[1269] 2. The server retrieves the marketing department employees' job titles, expertise, and past project experience from a MySQL database.

[1270] 3. The server runs a machine learning model built using the scikit-learn library to select the most suitable employee from the marketing department.

[1271] 4. The server sends a link to the specific folder in Google Drive and editing permissions to the user's device.

[1272] 5. The server uses the Microsoft Azure Emotion API to determine whether the user is stressed based on their tone of voice.

[1273] 6. The server sends a message to the user's device saying, "Relax, you have all the information you need."

[1274] Prompt Sentence Examples

[1275] "I've developed a new marketing campaign. Can you introduce me to the appropriate department and person? Also, where can I find the relevant materials and what permissions do I need?"

[1276] In this way, the system allows servers, terminals, and users to work together to efficiently advance projects and tasks.

[1277] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1278] Step 1:

[1279] The user enters project and task details.

[1280] Input: The user uses a terminal to input details such as the project name, purpose, required skill set, deadline, etc.

[1281] What happens: The user types "design a new marketing campaign" into a form on their device, then enters details such as the campaign's objectives, required skill sets, and deadline.

[1282] Output: The terminal sends the entered information to the server.

[1283] Step 2:

[1284] The server retrieves relevant information from an internal database.

[1285] Input: The server receives project and task details submitted by the user.

[1286] What happens: The server queries a MySQL database to get the job titles, expertise, and past project experience of employees in the marketing department.

[1287] Output: The server stores the retrieved information in its internal memory.

[1288] Step 3:

[1289] The server will select the appropriate department and person in charge.

[1290] Input: The server uses information about job title, expertise, and past project experience retrieved from a database.

[1291] How it works: The server runs a machine learning model built using the scikit-learn library to select the most suitable employee from the marketing department.

[1292] Output: The server generates information about the selected department and person in charge.

[1293] Step 4:

[1294] The server will provide the location of the relevant materials and the necessary permissions.

[1295] Input: The server uses the selected department and person information.

[1296] Specific operation: The server uses the Google Drive API to generate a link to the folder where the relevant materials are stored and edit permissions.

[1297] Output: The server sends the link to the storage location of the relevant material and the necessary permission information to the user's terminal.

[1298] Step 5:

[1299] The server uses an emotion engine to recognize the user's emotion.

[1300] Input: The server receives data such as the user's tone of voice, facial expressions, and language.

[1301] Specific operation: The server uses the Microsoft Azure Emotion API to analyze the user's emotions.

[1302] Output: The server recognizes the user's emotional state and stores the result in its internal memory.

[1303] Step 6:

[1304] The server responds according to the user's feelings.

[1305] Input: The server uses the recognized emotional state of the user.

[1306] What it does: If the user is stressed, the server generates a message like "Relax, you have all the information you need." If the user is happy, the server generates a message like "Good luck! Keep it up!"

[1307] Output: The server sends the generated message to the user's terminal.

[1308] (Application example 1)

[1309] Next, a description will be given of Application Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1310] In conventional project management systems, selecting the appropriate department and person in charge is often done manually, which takes time and effort. Furthermore, because a uniform approach is taken without considering the user's feelings, this can increase user stress and dissatisfaction. Furthermore, when factory workers start a new project, they often don't know how to proceed, making efficient project management difficult.

[1311] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means. In this invention, the server includes means for introducing the responsible department and person in charge, presenting the storage location of related materials and the necessary authorities, managing the schedule based on backward calculations until the target completion date, setting up meetings for the person in charge, and proposing and assisting with the content necessary to complete the task, means for having a shape that can be attached to as a character, means for recognizing the user's emotions using an emotion engine and responding accordingly, and means for automatically assigning the appropriate responsible department and person in charge based on the details of the project. This enables flexible responses according to the user's emotions, realizes the rapid selection of the appropriate responsible department and person in charge, and enables efficient project management.

[1312] "Introducing the responsible department and person in charge" is a function that automatically selects the department and person in charge that are best suited to a specific project or task and presents them to the user.

[1313] "Indicating where related materials are stored and the necessary permissions" is a function that shows users where materials related to a project or task are stored and the permissions required to access those materials.

[1314] "Schedule management based on backward calculations to the target completion date" is a function that calculates backwards the necessary work based on the completion date of a project or task, and creates an efficient schedule.

[1315] "Meeting settings for responsible parties" is a function that automatically sets up meetings between responsible parties related to projects and tasks and incorporates them into the schedule.

[1316] "Suggesting and assisting with what is needed to complete a task" is a function that supports users by suggesting the information and procedures needed to complete a project or task.

[1317] A "shape that allows a user to become attached to the character" refers to a character that has a shape that is familiar to the user and that the user can become attached to.

[1318] "Means for recognizing the user's emotions using an emotion engine and responding accordingly" is a function that recognizes emotions from the user's tone of voice, facial expression, etc., and responds appropriately according to those emotions.

[1319] "A means of automatically assigning the appropriate department and person in charge based on the details of the project" is a function that automatically selects and assigns the most appropriate department and person in charge based on the content and requirements of the project.

[1320] The following system configuration is used as an embodiment of the present invention. The system includes means for introducing the department and person in charge, presenting the storage location of related materials and the necessary authorities, managing the schedule based on backward calculations until the target completion date, setting up meetings for the person in charge, and proposing and assisting with the content required to complete the task, means for providing a shape that can be attached to as a character, means for recognizing the user's emotions using an emotion engine and responding accordingly, and means for automatically assigning the appropriate department and person in charge based on the details of the project.

[1321] System Program

[1322] The system program is configured as follows:

[1323] 1. Introduction of the department and staff in charge:

[1324] The server receives detailed information about projects and tasks and selects the most appropriate department and person to handle the project based on past project data and the expertise of the person in charge.

[1325] 2. Indicate where relevant materials are stored and the necessary permissions:

[1326] The server tells the user where the materials related to the project are stored and what permissions are required to access them.

[1327] 3. Schedule management based on backward calculations to the target completion date:

[1328] The server calculates backwards the required work based on the project completion date to create an efficient schedule.

[1329] 4. Meeting schedule for the person in charge:

[1330] The server automatically sets up and schedules meetings between people involved in the project.

[1331] 5. Suggestions and assistance with tasks required to complete the task:

[1332] The server supports users by suggesting the information and steps needed to complete a project or task.

[1333] 6. Shapes that allow you to become attached to the character:

[1334] The terminal displays the shape of a character that the user can easily relate to and become attached to.

[1335] 7. Using an emotion engine to recognize user emotions and respond accordingly:

[1336] The server recognizes the user's emotions from their tone of voice and facial expressions, and responds appropriately according to those emotions.

[1337] 8. How to automatically assign the right department and person based on project details:

[1338] The server automatically selects and assigns the most appropriate department and person in charge based on the project content and requirements.

[1339] Hardware and Software

[1340] Hardware: Cameras and microphones mounted on factory robots are used to capture workers' facial expressions and tone of voice.

[1341] software:

[1342] The emotion_recognition module analyzes the captured data and recognizes the emotions of the workers.

[1343] The project_assignment module automatically assigns the appropriate department and person based on project details.

[1344] Specific examples

[1345] For example, if a factory worker says, "I want to launch a new product line, but I don't know where to start," the server will recognize from the worker's tone of voice and facial expression that the worker is stressed. The server will respond, "Relax. We'll provide the support you need," and at the same time automatically assign the department and person best suited to launch the new product line.

[1346] Prompt Sentence Examples

[1347] I want to start a new project but I don't know where to start.

[1348] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1349] Step 1:

[1350] The user inputs information to launch a new project or task. Specifically, the user inputs a prompt such as, "I want to launch a new product line, but I don't know where to start." This input is sent to the server via the device's microphone and keyboard.

[1351] Step 2:

[1352] The server receives the input prompt and uses an emotion engine to recognize the user's emotions. Specifically, it analyzes the voice and text data to identify the user's emotions, such as whether they are stressed or happy. This process outputs the user's emotional state.

[1353] Step 3:

[1354] The server then determines the appropriate response based on the recognized emotion. For example, if the user is feeling stressed, the server generates a message such as, "Relax. We'll provide the support you need." This message takes the user's emotional state as input and processes it to output an appropriate response.

[1355] Step 4:

[1356] The server automatically assigns the appropriate department and person in charge based on detailed project information. Specifically, it references past project data and the expertise of the person in charge to select the most appropriate department and person in charge. This process outputs information about the department and person in charge.

[1357] Step 5:

[1358] The server presents the user with the storage location and required permissions for documents related to the project. Specifically, it searches a database of related documents to identify the storage location and access permissions for the relevant documents. This process outputs the storage location and permission information for the documents.

[1359] Step 6:

[1360] The server calculates the necessary work backwards based on the project completion date to create an efficient schedule. Specifically, it uses project management software to calculate the start and end dates of each task. This process outputs the schedule information.

[1361] Step 7:

[1362] The server automatically schedules meetings between project participants and incorporates them into the schedule. Specifically, it references the participants' calendars to identify dates and times when everyone is available. This process outputs the date, time, and location of the meeting.

[1363] Step 8:

[1364] The server supports users by suggesting the information and procedures needed to complete a project or task. Specifically, it uses project management software to list the necessary resources and procedures. This process outputs the proposal.

[1365] Step 9:

[1366] The terminal displays the shape of a character that the user can easily relate to and become attached to. Specifically, it displays an animation of the character on the display to encourage interaction with the user. This process outputs the display of the character.

[1367] Example 2

[1368] Next, a description will be given of Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1369] Conventional schedule management systems make it difficult to grasp the progress of a project and schedule meetings efficiently. Furthermore, they do not take into account the user's feelings, leading to problems such as stress and a decrease in user satisfaction. This makes it difficult to efficiently progress a project and improve user satisfaction.

[1370] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1371] In this invention, the server includes means for introducing the responsible department and person in charge, presenting the storage location of related materials and necessary permissions, schedule management based on backward calculations until the target completion date, setting up meetings for the person in charge, and proposing and assisting with the content necessary to complete the task, means for collecting user emotion data and learning changes in emotion using a machine learning model, and means for optimizing the system's response based on the learning results and notifying the user of the proposed content. This makes it possible to easily grasp the progress of the project, efficiently set up meetings, and further improve user satisfaction by taking the user's emotions into consideration when responding.

[1372] A "department" is a department within an organization that is responsible for a particular task or project.

[1373] A "person in charge" is an individual who is responsible for a particular task or project.

[1374] "Relevant materials" are documents and files containing information or data necessary to carry out a project or task.

[1375] "Repository" is the location or system where relevant materials are stored.

[1376] "Required privileges" are the authorizations or authentications required to access specific materials or systems.

[1377] The "desired completion date" is the date by which the project or task is scheduled to be completed.

[1378] "Counting backwards" is a method of calculating the deadline for each task by working backwards from the completion date of the goal.

[1379] Schedule management is the process of planning and coordinating the progress of projects and tasks.

[1380] "Meeting scheduling" refers to planning and scheduling meetings related to a project or task.

[1381] "Proposing what is needed to complete a task" refers to proposing the steps and resources needed to complete a task.

[1382] "Assistance" refers to providing support to help complete a task or project.

[1383] "User" means an individual or member of an organization who uses the system.

[1384] "Emotion data" is information that indicates the user's emotional state, and is collected from facial expressions, voice, and the like.

[1385] A "machine learning model" is an algorithm that learns patterns based on data and makes predictions and classifications.

[1386] "Changes in emotions" refers to changes in a user's emotional state over time and in different situations.

[1387] "Learning results" are the knowledge and patterns that a machine learning model has acquired based on data.

[1388] "Optimizing the system's response" refers to adjusting the system's behavior and suggestions to be optimal based on the learning results.

[1389] "Suggestions" are specific actions or advice that the system provides to the user.

[1390] "Notification" is the act of the system conveying information to the user.

[1391] The present invention is a system for optimizing project management and user response based on emotions. A specific embodiment of this system will be described below.

[1392] Scheduling and meeting scheduling

[1393] 1. Enter the desired completion date

[1394] The user enters the desired completion date of the project into the system. For example, the user enters "December 31, 2023."

[1395] 2. Calculate task deadlines backwards

[1396] The server calculates the deadline for each task by counting backwards from the target completion date. This calculation uses the Python datetime library. For example, it calculates "the deadline for Task A is December 15, 2023, and the deadline for Task B is December 20, 2023."

[1397] 3. Save task deadlines

[1398] The server saves the calculated deadlines for each task in the database (MySQL). Specifically, it uses an SQL INSERT statement to save the deadlines as "Task A's deadline is December 15, 2023, and Task B's deadline is December 20, 2023."

[1399] 4. Automatically adjust schedules

[1400] The server automatically adjusts the schedule of the person in charge based on the deadlines of the saved tasks. Using the Google Calendar API, it adds the following to the person in charge's calendar: "The deadline for Task A is December 15, 2023, and the deadline for Task B is December 20, 2023."

[1401] 5. Schedule Update Notification

[1402] The device notifies the person in charge of the schedule update, using the Slack API to notify the person in charge that "The deadline for Task A has been set to December 15, 2023."

[1403] Response optimization using an emotion engine

[1404] 1. Entering emotion data

[1405] Input emotional data when the user performs a specific task. Emotional data is collected from the user's facial expressions and voice using emotion recognition software (e.g., Affectiva).

[1406] 2. Learning Emotion Data

[1407] The server inputs the collected emotion data into a machine learning model (e.g., TensorFlow) to learn changes in the user's emotions. For example, it learns that "the user feels stressed when performing task C."

[1408] 3. Optimizing response

[1409] The server optimizes the system's response based on the learning results, for example, "To simplify task C, we suggest splitting it into subtasks."

[1410] 4. Notification of Proposal Content

[1411] The device notifies the user of the proposal, using an email sending API (e.g., SendGrid) to notify the user, "To simplify task C, we suggest splitting it into subtasks."

[1412] Specific examples

[1413] When the user enters the desired completion date as "December 31, 2023," the server calculates that "the deadline for Task A is December 15, 2023, and the deadline for Task B is December 20, 2023," and saves this in the MySQL database.

[1414] The server uses the Google Calendar API to add the following to the person in charge's calendar: "The deadline for Task A is December 15, 2023, and the deadline for Task B is December 20, 2023," and the device notifies the person in charge using the Slack API.

[1415] If the emotion recognition software determines that the user feels stressed when performing Task C, the server inputs the data into a TensorFlow model to generate a response such as "Suggest splitting Task C into subtasks to make it easier."

[1416] The device uses the SendGrid API to notify the user via email, "To simplify task C, we suggest splitting it into subtasks."

[1417] Prompt Sentence Examples

[1418] "If the project's target completion date is December 31, 2023, how can I calculate the due dates of each task backwards and automatically adjust the schedules of the people responsible?"

[1419] "If you determine that a user is experiencing stress when performing a particular task, how can you provide suggestions to make that task easier?"

[1420] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1421] Scheduling and meeting scheduling

[1422] Step 1: Enter the desired completion date

[1423] The user enters the project's target completion date into the system.

[1424] Input: Objective completion date (e.g. December 31, 2023)

[1425] Output: The target completion date is saved in the system.

[1426] Specific operation: The user enters "December 31, 2023" into the system's input form and presses the submit button.

[1427] Step 2: Calculate task deadlines backwards

[1428] The server calculates the deadline for each task by counting backward from the target completion date.

[1429] Input: Objective completion date (e.g. December 31, 2023)

[1430] Output: Deadline for each task (e.g., Task A is due December 15, 2023, Task B is due December 20, 2023)

[1431] Specific operation: The server uses Python's datetime library to calculate the deadline for each task backward from the target completion date.

[1432] Step 3: Save the task deadline

[1433] The server stores the calculated deadline for each task in a database.

[1434] Input: Deadline for each task (e.g., Task A is due December 15, 2023, Task B is due December 20, 2023)

[1435] Output: Task deadlines stored in the database

[1436] Specific operation: The server uses an SQL INSERT statement to save the following to the MySQL database: "The deadline for Task A is December 15, 2023, and the deadline for Task B is December 20, 2023."

[1437] Step 4: Automatically adjust schedule

[1438] The server automatically adjusts the schedule of the person in charge based on the deadlines of the saved tasks.

[1439] Input: Task deadline stored in the database

[1440] Output: Due date of task added to assignee's calendar

[1441] Specific operation: The server uses the Google Calendar API to add the following to the person in charge's calendar: "The deadline for Task A is December 15, 2023, and the deadline for Task B is December 20, 2023."

[1442] Step 5: Notification of schedule updates

[1443] The terminal notifies the person in charge of schedule updates.

[1444] Input: Due date of the task added to the assignee's calendar

[1445] Output: Notification sent to assignee

[1446] Specific behavior: The device uses the Slack API to notify the person in charge that "The deadline for Task A has been set to December 15, 2023."

[1447] Response optimization using an emotion engine

[1448] Step 1: Input emotion data

[1449] The user inputs emotion data when performing a specific task.

[1450] Input: User's emotional data (e.g., facial expressions and voice)

[1451] Output: Emotion data stored in the system

[1452] What it does: Use emotion recognition software (e.g., Affectiva) to collect emotion data from the user's facial expressions and voice.

[1453] Step 2: Learning emotion data

[1454] The server inputs the collected emotion data into a machine learning model to learn changes in the user's emotions.

[1455] Input: Collected emotion data

[1456] Output: Learning result (e.g., user feels stressed when performing task C)

[1457] Specific operation: The server inputs emotion data into the TensorFlow model and learns changes in the user's emotions.

[1458] Step 3: Optimize your response

[1459] The server optimizes the system's response based on the learning results.

[1460] Input: Learning results

[1461] Output: Optimized response (e.g., suggestions to simplify task C)

[1462] Specific operation: Based on the learning results, the server generates a response such as "Suggest splitting task C into subtasks to simplify it."

[1463] Step 4: Notification of proposal

[1464] The terminal notifies the user of the content of the proposal.

[1465] Input: Optimized response

[1466] Output: Notification of the suggestion sent to the user

[1467] Specific behavior: The device uses an email sending API (e.g., SendGrid) to notify the user, "To simplify task C, we suggest splitting it into subtasks."

[1468] (Application example 2)

[1469] Next, a description will be given of Application Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1470] In conventional schedule management systems, task deadlines are often set manually based on backward calculations until the target completion date, and meetings are scheduled for the responsible parties, making efficient project management difficult. Furthermore, tasks are not redistributed or simplified with consideration for the feelings of the workers, which increases worker stress and reduces productivity. Furthermore, there is a lack of a way to grasp the progress of a project in real time and efficiently schedule necessary meetings.

[1471] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1472] In this invention, the server includes means for introducing the department and person in charge, presenting the storage location of related materials and necessary authorities, schedule management based on backward calculations until the target completion date, setting up meetings for the person in charge, and proposing and assisting with the necessary content until the task is completed; means for having a shape that can be attached to as a character; means for using an emotion engine to learn changes in the user's emotions and suggesting simplification or reallocation of tasks when stress is felt; and means for grasping the progress of the project in real time through smart glasses and efficiently setting up necessary meetings. This enables efficient project management and stress reduction for workers.

[1473] A "department" is a department within an organization that is responsible for a particular task or project.

[1474] A "person in charge" is an individual who is responsible for a particular task or project.

[1475] "Relevant materials" are documents and files containing information or data necessary to carry out a project or task.

[1476] "Repository" is the location or system where relevant materials are stored.

[1477] "Necessary privileges" are the authorizations and authentications required to access relevant materials and systems.

[1478] The "target completion date" is the date by which a project or task should be completed.

[1479] "Counting backwards" is a method of setting deadlines for each task by working backwards from the date of completion of the goal.

[1480] "Schedule management" is the process of planning and managing the progress of tasks and projects.

[1481] "Meeting scheduling" refers to planning and scheduling meetings related to a project or task.

[1482] "Suggesting what is needed to complete a task" refers to providing the information and steps needed to complete a task.

[1483] "Assistance means" are methods and tools used to assist in the completion of a task or project.

[1484] A "shape that allows users to become attached to the character" is a design with a shape that users can feel familiar with.

[1485] The "emotion engine" is a technology that learns changes in the user's emotions and optimizes the system's response based on that.

[1486] "Smart glasses" are glasses-type devices that have the function of displaying information.

[1487] "Real-time understanding" refers to instantly checking the current situation and progress.

[1488] "Task simplification" refers to suggesting methods or steps to make a task easier.

[1489] "Redistribution" refers to reassigning a specific task to another person.

[1490] The system for implementing this invention uses the following hardware and software: The hardware includes smart glasses, a server, and a user terminal, while the software includes an emotion engine, a schedule management module, and a smart glasses interface.

[1491] The server provides the means to introduce the department and person in charge, indicate where related materials are stored and the necessary permissions, manage the schedule based on backward calculations until the target completion date, set up meetings for the person in charge, and propose and assist with the content required to complete the task, making it possible to efficiently manage the progress of the project.

[1492] The emotion engine learns the user's emotional changes and suggests simplification or reallocation of tasks if the user feels stressed. The user provides emotional data through the smart glasses, and the emotion engine analyzes the data. For example, if the user feels stressed while performing a specific task, the emotion engine suggests reallocating the task to another person.

[1493] Smart glasses provide a means to grasp the progress of projects in real time and efficiently schedule necessary meetings. Users can check the progress of projects through smart glasses, schedule necessary meetings, and manage the progress of tasks.

[1494] As a concrete example, consider a scenario in which a factory worker is wearing smart glasses. If the worker feels stressed while performing a particular task, the smart glasses will display a message saying, "You are feeling stressed. Would you like to simplify or reallocate the task 'Assembly'?" If the worker responds "Yes," the system will reallocate the task to another worker.

[1495] Examples of prompts to input to a generative AI model include:

[1496] "Develop a smart glasses application that sets task deadlines by counting backward from the project's intended completion date and monitors the worker's emotions. Include a function that suggests simplifying or reallocating tasks if the worker feels stressed."

[1497] In this way, efficient project management and reduced worker stress are achieved.

[1498] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1499] Step 1:

[1500] The server receives the project's target completion date as input and calculates backward to set the deadline for each task. This outputs a specific deadline for each task. The server automatically adjusts the schedule, taking into account task dependencies and priorities.

[1501] Step 2:

[1502] The server receives information about the department and person in charge as input and assigns the appropriate person to each task. This outputs the person in charge information for each task. The server selects the most appropriate person in charge, taking into account the person's skill set and current workload.

[1503] Step 3:

[1504] The server receives the storage location of the relevant materials and the necessary permissions as input, and grants the necessary permissions to the person in charge, allowing the person in charge to access the relevant materials. The server manages permissions based on the security policy.

[1505] Step 4:

[1506] The user wears smart glasses and checks the progress of the project in real time. The smart glasses receive data from the server as input and display the progress to the user, allowing the user to understand the progress of the current task.

[1507] Step 5:

[1508] The smart glasses collect emotional data while the user is performing a specific task. The emotion engine receives this emotional data as input and analyzes the user's emotional changes. The output is whether the user is feeling stressed.

[1509] Step 6:

[1510] If the emotion engine detects user stress, the server will propose task simplification or reallocation. The server receives current task information and the user's emotion data as input and outputs the optimal solution, thereby reducing the user's stress.

[1511] Step 7:

[1512] The user confirms the suggestions from the server through the smart glasses and responds. The user's response is sent as input to the server, which then reallocates or simplifies the tasks based on the input, thereby optimizing the progress of the tasks.

[1513] Step 8:

[1514] The server reassess the overall project progress and readjusts the schedule as necessary. The server receives the latest task information and the status of each person involved as input and outputs an updated schedule. This ensures that the project progress is always optimal.

[1515] Example 3

[1516] Next, a description will be given of Example 3 of Form Example 3. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1517] With conventional systems, it was difficult to accurately recognize the user's emotions and respond appropriately. It was also difficult to adopt a character shape that users could feel attached to. This resulted in problems that reduced user convenience and satisfaction.

[1518] The specific processing by the specific processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means.

[1519] In this invention, the server includes means for introducing the department and person in charge, presenting the storage location of related materials and necessary permissions, managing the schedule based on a calculation of the target completion date, setting up meetings for the person in charge, and proposing and assisting with the necessary content until the task is completed; means for providing a shape that can be attached to the character; means for collecting and analyzing the user's voice data using voice recognition technology; means for collecting and analyzing the user's face data using face recognition technology; means for integrating the voice data and face data to estimate the user's emotions; means for generating an appropriate response based on the estimated emotions; and means for presenting the generated response to the user. This makes it possible to accurately recognize the user's emotions and provide an appropriate response accordingly. Furthermore, by adopting a character shape that the user can become attached to, user convenience and satisfaction can be improved.

[1520] A "department" is a department within an organization that is responsible for a particular task or project.

[1521] A "person in charge" is an individual who is responsible for a particular task or project.

[1522] "Relevant materials" are documents and files containing information and data necessary for the performance of a task or project.

[1523] "Repository" is the location or system where relevant materials are stored.

[1524] "Necessary privileges" are the authorizations and authentications required to access relevant materials and systems.

[1525] "Schedule management" is the process of making a plan to reach a target completion date, and then monitoring and adjusting the progress.

[1526] "Meeting arrangement" refers to the preparation and arrangement for holding a meeting at a specific date and time.

[1527] A "task" is a discrete task or activity performed to achieve a specific purpose.

[1528] A "proposal" refers to presenting a solution or idea to a specific problem or issue.

[1529] "Assistance" refers to providing support for specific tasks or activities and helping them to proceed smoothly.

[1530] "Character shape" refers to an appearance or shape designed to allow users to feel attached to the character.

[1531] "Speech recognition technology" is a technology that analyzes voice data and converts it into text or semantic information.

[1532] "Facial recognition technology" is a technology that analyzes facial features from image data to identify individuals and estimate their emotions.

[1533] "Voice data" refers to data that is a digital recording of a user's speech.

[1534] "Facial data" refers to image or video data of a user's face.

[1535] "Emotion estimation" is the process of analyzing voice and facial data to infer a user's emotional state.

[1536] "Response generation" is the process of creating appropriate responses or actions based on inferred emotions.

[1537] "Presenting" refers to showing or hearing the generated response to the user.

[1538] The present invention relates to a system that employs a character shape that a user can become attached to, recognizes the user's emotions, and responds appropriately. Specific embodiments of this system will be described below.

[1539] System configuration

[1540] Hardware

[1541] Device: A device with a microphone, camera, and speaker.

[1542] Server: A computer with high-performance data processing capabilities

[1543] software

[1544] Speech recognition software: Google Cloud Speech-to-Text

[1545] Facial Recognition Software: Microsoft Azure Face API

[1546] Generative AI model: An AI model for generating appropriate responses based on user emotions

[1547] Data processing and calculation

[1548] Audio data collection and analysis

[1549] The device uses a built-in microphone to collect the user's voice in real time, which is then sent digitally to a server, which then uses Google Cloud Speech-to-Text to convert the voice data into text and analyze characteristics such as tone, intensity, and speed of the voice.

[1550] Facial data collection and analysis

[1551] The device uses a built-in camera to capture a picture of the user's face. The captured facial image data is sent to a server, which then analyzes the facial data using the Microsoft Azure Face API and estimates emotions from facial features.

[1552] Emotion integration and estimation

[1553] The server integrates the results of voice and face recognition to more accurately estimate the user's emotions. For example, if the server detects "tired" from the voice and recognizes a "fatigued" facial expression, it determines that the user is tired.

[1554] Response generation and presentation

[1555] The server uses a generative AI model to generate an appropriate response based on the estimated emotion. The generated response is presented to the user via the device as voice or text. For example, the response could be "Please take it easy today" through a speaker.

[1556] Specific examples

[1557] The process flow when the user says "I'm very tired today" will be specifically described.

[1558] 1. The user says, "I'm very tired today."

[1559] 2. The device collects the user's voice using a microphone.

[1560] 3. The device takes a picture of the user's face with its camera.

[1561] 4. The server converts the voice data into text using Google Cloud Speech-to-Text, and estimates the level of fatigue based on the tone, strength, and speed of the voice.

[1562] 5. The server analyzes the facial data using the Microsoft Azure Face API and estimates the emotion of fatigue from the facial expression.

[1563] 6. The server combines the voice and facial data and determines that the user is tired.

[1564] 7. The server uses the generative AI model to generate a response: "Take it easy today."

[1565] 8. The device tells the user through the speaker, "Take it easy today."

[1566] Prompt Sentence Examples

[1567] Example prompts to input to the generative AI model:

[1568] Describe how the system would respond if the user said, "I'm very tired today."

[1569] By inputting this prompt sentence into the generative AI model, the system response can be specifically simulated. The flow of the identification process in the third embodiment will be described with reference to FIG.

[1570] Step 1:

[1571] The user initiates an interaction with the system.

[1572] Specific action: The user speaks to the system, such as "Hello" or "I'm very tired today."

[1573] Input: User's voice

[1574] Output: Audio data

[1575] Step 2:

[1576] The terminal collects the user's voice using a microphone.

[1577] Specific operation: The device's microphone collects the user's speech in real time and stores it as digital audio data.

[1578] Input: User's voice

[1579] Output: Digital audio data

[1580] Step 3:

[1581] The device takes a picture of the user's face with a camera.

[1582] Specific operation: The device's camera takes a picture of the user's face and saves it as image data.

[1583] Input: User's face

[1584] Output: Image data

[1585] Step 4:

[1586] The server analyzes the voice data using voice recognition software.

[1587] How it works: The server uses Google Cloud Speech-to-Text to convert the audio data into text and analyzes characteristics such as tone, strength, and speed of the voice.

[1588] Input: Digital audio data

[1589] Output: Text data and audio feature data

[1590] Step 5:

[1591] The server analyzes the facial data using facial recognition software.

[1592] Specific operation: The server uses the Microsoft Azure Face API to analyze facial data and estimate emotions from facial features.

[1593] Input: Image data

[1594] Output: Facial expression feature data and emotion estimation data

[1595] Step 6:

[1596] The server integrates the voice data and facial data to estimate the user's emotions.

[1597] Specific operation: The server integrates the results of voice and face recognition to more accurately estimate the user's emotions. For example, if the server estimates "tired" from the voice and recognizes a "fatigued" expression from the face, it determines that the user is tired.

[1598] Input: Text data, voice feature data, facial expression feature data, emotion estimation data

[1599] Output: Integrated emotion estimation data

[1600] Step 7:

[1601] The server generates an appropriate response based on the estimated emotion.

[1602] Specific behavior: The server uses the generative AI model to generate an appropriate response based on the estimated emotion. For example, if the server determines that the user is tired, it generates the response "Take it easy and rest today."

[1603] Input: Integrated emotion estimation data

[1604] Output: The generated response data

[1605] Step 8:

[1606] The terminal presents the generated response to the user.

[1607] Specific operation: The device presents the response sent from the server to the user as voice or text, for example, saying "Please take a good rest today" through the speaker.

[1608] Input: Generated response data

[1609] Output: Response presented to the user (audio or text)

[1610] (Application example 3)

[1611] Next, a description will be given of Application Example 3 of Form Example 3. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1612] Conventional systems make it difficult for users to receive appropriate support when searching for products in physical stores, and one problem is that they lack the ability to respond to the user's emotions. Another issue is that users cannot develop an attachment to the system, which reduces the frequency of use. To solve these problems, a system that recognizes the user's emotions and responds accordingly is needed.

[1613] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 3 is realized by the following means.

[1614] In this invention, the server includes means for introducing the responsible department and person in charge, presenting the storage location of related materials and the necessary authority, managing the schedule based on backward calculations until the target completion date, setting up meetings for the person in charge, and proposing and assisting with the necessary content until the task is completed, means for providing a shape that can be attached to as a character, means for recognizing the user's emotions using voice recognition technology and face recognition technology and responding accordingly, and means for providing appropriate support in a physical store based on the user's emotions. This enables the user to receive appropriate support according to their emotions when searching for products in a physical store, and also increases their attachment to the system.

[1615] A "department in charge" is a department or section in charge of a specific task or project.

[1616] A "person in charge" is an individual in charge of a particular task or project.

[1617] "Related materials" refers to documents and data related to a business or project.

[1618] "Repository" refers to the location or system where relevant materials are stored.

[1619] "Required authority" refers to the access rights and operational rights required to carry out a specific task or project.

[1620] "Schedule management" is the process of making a plan to reach a target completion date, and then monitoring and adjusting the progress.

[1621] "Meeting arrangement" refers to the preparation and arrangement for holding a meeting at a specific date and time.

[1622] A "task" is an operation or activity required to achieve a specific purpose.

[1623] A "proposal" refers to presenting a solution or improvement plan for a specific problem or issue.

[1624] "Assistance" refers to providing support to assist with a specific task or project.

[1625] A "character" is an entity with a shape or design that users can become attached to.

[1626] "Speech recognition technology" is a technology that converts speech into text and understands its content.

[1627] "Facial recognition technology" is a technology that detects faces from images taken with a camera and analyzes their facial expressions and features.

[1628] "Emotion recognition" refers to estimating a user's emotions from their tone of voice and facial expressions.

[1629] "Brick and mortar store" means a retail or service location that is located in a physical location.

[1630] "Support" means providing the user with the assistance or advice they need to achieve a specific goal.

[1631] A system for carrying out this invention has the following configuration: The system includes means for introducing the department and person in charge, presenting the storage location of related materials and the necessary authority, managing the schedule based on backward calculations until the target completion date, setting up meetings for the person in charge, and proposing and assisting with the content required to complete the task, means for providing a shape that can be attached to as a character, means for recognizing the user's emotions using voice recognition technology and face recognition technology and responding accordingly, and means for providing appropriate support based on the user's emotions in a physical store.

[1632] Hardware and software used

[1633] Hardware

[1634] Camera: Used to utilize facial recognition technology, capturing images of the user's facial expressions and acquiring image data to estimate emotions.

[1635] Microphone: Used to utilize voice recognition technology, collect the user's voice and obtain voice data to estimate emotions.

[1636] software

[1637] OpenCV: A library used to implement facial recognition technology, detecting faces in images captured by a camera and analyzing their facial expressions.

[1638] SpeechRecognition: A library used to implement speech recognition technology, converting audio data collected by a microphone into text and analyzing its content.

[1639] Transformers: A library used to implement emotion recognition models, which estimate user emotions based on data obtained from speech and facial recognition.

[1640] Data processing and calculation

[1641] Facial Recognition

[1642] The video captured by the camera is processed using OpenCV to detect faces, and the detected facial image data is input into an emotion recognition model to estimate emotions.

[1643] Voice Recognition

[1644] The voice data collected by the microphone is converted into text using the SpeechRecognition library, and the text is input into an emotion recognition model to estimate the emotion.

[1645] Responding according to emotions

[1646] Based on the estimated emotion, the system responds appropriately to the user. For example, if the user has a troubled expression, the system will suggest, "Is there something I can help you with?"

[1647] Specific examples

[1648] When a user is searching for a product in a physical store, the robot will ask, "What product are you looking for today?" If the user looks troubled, the robot will suggest, "Is there something I can help you with?"

[1649] Prompt Sentence Examples

[1650] If the user looks troubled, the robot will suggest, "Is there something I can help you with?"

[1651] In this way, the system can recognize the user's emotions and provide appropriate support accordingly, enabling users to receive appropriate support according to their emotions when searching for products in a physical store, and increasing their attachment to the system.

[1652] The flow of the specific processing in Application Example 3 will be described with reference to FIG.

[1653] Step 1:

[1654] The server uses a camera to capture the user's face. The input is video data from the camera, and the output is facial image data. Specifically, the camera captures the user's face in real time and sends the video data to the server.

[1655] Step 2:

[1656] The server uses OpenCV to detect faces from the facial image data. The input is the facial image data obtained in step 1, and the output is the area information of the detected face. Specifically, it applies the OpenCV face detection algorithm to identify the position and size of the face.

[1657] Step 3:

[1658] The server inputs the detected facial region information into an emotion recognition model to estimate the user's emotion. The input is facial region information, and the output is an estimated emotion label. Specifically, the emotion recognition model is executed using the Transformers library to estimate the emotion from the user's facial expression.

[1659] Step 4:

[1660] The server collects the user's voice using a microphone. The input is voice data from the microphone, and the output is voice data. Specifically, the microphone captures the user's speech in real time and sends the voice data to the server.

[1661] Step 5:

[1662] The server converts the voice data into text using the SpeechRecognition library. The input is the voice data obtained in step 4, and the output is text data. Specifically, it applies a voice recognition algorithm to convert the voice data into a string of characters.

[1663] Step 6:

[1664] The server inputs text data into an emotion recognition model to estimate the user's emotion. The input is text data, and the output is an estimated emotion label. Specifically, the server uses the Transformers library to run the emotion recognition model and estimate the emotion from the user's speech.

[1665] Step 7:

[1666] The server integrates the emotion labels obtained from facial and voice recognition to determine the final user emotion. The input is the emotion labels from facial and voice recognition, and the output is the integrated emotion label. Specifically, it compares both emotion labels and selects the emotion if they match, or selects the emotion with the higher priority if they differ.

[1667] Step 8:

[1668] The server responds appropriately to the user based on the integrated emotion label. The input is the integrated emotion label, and the output is a response message to the user. Specifically, it generates a prompt sentence according to the emotion label and responds to the user by voice or text.

[1669] In this way, the system can recognize the user's emotions and provide appropriate support accordingly.

[1670] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1671] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in the data format of voice data, text data, etc. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1672] Another example of generative AI is Gemini (internet search engine). <url: https: gemini.google.com ?hl="ja">) are mentioned.

[1673] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[1674] [Third embodiment]

[1675] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1676] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[1677] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1678] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[1679] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1680] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1681] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1682] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1683] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1684] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1685] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1686] Next, the specific processing by the specific processing unit 290 of the data processing device 12 will be described.

[1687] "Example 1"

[1688] When an employee of a specific organization plans a new project or task, this embodiment of the present invention automatically introduces the appropriate department and person in charge. This introduction is made based on information such as the employee's position within the organization, expertise, and past project experience. The system also presents the location of related documents and the necessary permissions. This allows employees to quickly obtain the necessary information and start the task efficiently.

[1689] "Example 2"

[1690] Furthermore, this embodiment of the present invention manages schedules and schedules meetings for the person in charge based on a backward calculation of the target completion date. This allows employees to easily understand the progress of the project and efficiently schedule necessary meetings. Specifically, the deadline for each task is set by counting backward from the target completion date, and the schedule of the person in charge is automatically adjusted based on that.

[1691] "Example 3"

[1692] Furthermore, the present invention employs character shapes that users can develop an attachment to. These character shapes are robots, relatives, etc., and improve user convenience and satisfaction. Specifically, the character shapes can be customized to suit the user's preferences and the organization's culture.

[1693] The processing flow of each embodiment will be described below.

[1694] "Example 1"

[1695] Step 1: Employees plan new projects and tasks.

[1696] Step 2: The system automatically connects you to the right department and person based on information such as your position within the organization, your expertise, and past project experience.

[1697] Step 3: The system will show you where the relevant documents are stored and the necessary permissions, allowing you to quickly retrieve the information you need and begin your task efficiently.

[1698] "Example 2"

[1699] Step 1: Employee sets a target completion date for the project.

[1700] Step 2: The system automatically creates a schedule based on backward calculations to the desired completion date.

[1701] Step 3: The system schedules meetings for the person in charge, allowing employees to easily understand the progress of the project and efficiently schedule necessary meetings.

[1702] "Example 3"

[1703] Step 1: The system adopts a character shape that users can become attached to. This character shape can be a robot, a relative, or something similar, improving user convenience and satisfaction.

[1704] Step 2: Character shapes can be customized to suit user preferences and organizational culture.

[1705] Example 1

[1706] Next, a description will be given of Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1707] With conventional project management systems, when employees planned new projects or tasks, it was difficult to quickly find the appropriate department or person in charge, and it was time-consuming to specify where related documents were stored and the necessary permissions. Furthermore, project schedule management, meeting scheduling, and proposals and assistance until task completion were not efficiently performed. This resulted in delays to the start and progress of projects, and reduced overall efficiency.

[1708] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1709] In this invention, the server includes a means for introducing the relevant department and person in charge, a means for presenting the storage location of related materials and the necessary permissions, a means for managing schedules based on backward calculations to the target completion date, a means for setting up meetings for the person in charge, a means for suggesting and providing assistance with the content needed to complete the task, a means for generating prompts using a generative AI model and selecting the appropriate department and person in charge, and a means for creating a character that employees can feel attached to. This allows employees to quickly find the appropriate department and person in charge and easily confirm the storage location of related materials and the necessary permissions. Furthermore, the server can efficiently manage project schedules, set up meetings, and suggest and provide assistance until task completion, smoothing the start and progress of projects and improving overall efficiency.

[1710] The "means of introducing the responsible department and person in charge" is a function that automatically selects and introduces the appropriate department and person in charge within the organization for the project or task that the user has planned.

[1711] The "means for presenting the storage location of related materials and the necessary permissions" is a function that provides users with information on the storage location of materials related to a project or task and the permissions required to access them.

[1712] "A means of schedule management based on backward calculations to the target completion date" is a function that automatically creates and manages schedules by counting backwards based on the completion date of a project or task.

[1713] "Means for setting up meetings for responsible parties" is a function that automatically sets up meetings for responsible parties related to projects and tasks and incorporates them into the schedule.

[1714] "Means for proposing and assisting with the necessary content to complete a task" is a function that suggests information and procedures necessary to progress a project or task, and helps users complete tasks efficiently.

[1715] "Means for generating prompt sentences using a generative AI model and selecting an appropriate department and person in charge" refers to a function that uses a generative AI model to generate prompt sentences from the project and task details entered by the user, and selects an appropriate department and person in charge based on the prompt sentences.

[1716] "Means for having a shape that allows a user to become attached to the character" is a function that has a shape of a character that is familiar to the user and that the user can become attached to.

[1717] MODE FOR CARRYING OUT THE INVENTION

[1718] This invention is a system that automatically introduces the appropriate department and person in charge when an employee of a specific organization plans a new project or task. The system selects the department and person in charge based on information such as position within the organization, expertise, and past project experience, and also presents the location of related documents and the necessary permissions. This allows employees to quickly obtain the necessary information and start tasks efficiently.

[1719] Hardware and software used

[1720] Server: Database server (e.g. MySQL), application server (e.g. Apache Tomcat)

[1721] Devices: PCs and mobile devices used by employees

[1722] Software: Generative AI models (e.g., OpenAI GPT-4), project management tools (e.g., Jira)

[1723] Specific operation of the system

[1724] 1. A user creates a new project or task

[1725] A user uses a terminal to enter details of a new project or task into a project management tool, including the project name, purpose, deadline, required resources, and other information.

[1726] Example: When a user plans a "New Product Market Research Project," the user enters the project name as "New Product Market Research," the purpose as "Understanding Market Needs," and the deadline as "End of December 2023."

[1727] 2. The server receives the input data and sends prompts to the generative AI model.

[1728] The server receives project and task details entered by the user and generates prompts based on the received data to send to the generative AI model.

[1729] Example: "Please introduce me to the department and person who would be best suited to my new product market research project."

[1730] 3. The generative AI model selects the appropriate department and person in charge

[1731] The generative AI model selects the appropriate department and person in charge based on data such as position within the organization, expertise, and past project experience.

[1732] Example: A generative AI model returns the result, "Mr. Tanaka from the Marketing Department is the best candidate."

[1733] 4. The server will provide the location of the relevant materials and the necessary permissions.

[1734] The server then presents the selected department and person in charge with the location of the relevant documents and the necessary permissions. Specifically, it retrieves the location of the relevant documents and access permission information from the database and provides it to the user.

[1735] For example: "The relevant materials are in a 'Market Research' folder on a shared drive. Access is granted to everyone in the marketing department."

[1736] 5. User checks the results and starts the task

[1737] The user checks the information provided by the server through their terminal. Specifically, they check the department and person in charge, the storage location of related documents, and access permission information on the project management tool. They access the necessary documents and start tasks efficiently.

[1738] Example: A user accesses the "Market Research" folder based on the information provided, downloads the necessary materials, and starts the project.

[1739] This system allows employees to quickly find the appropriate department and person in charge, easily confirm where related documents are stored, and easily identify the necessary permissions. It also efficiently manages project schedules, schedules meetings, and provides suggestions and assistance until tasks are completed, resulting in smoother project initiation and progress, improving overall efficiency.

[1740] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1741] Step 1:

[1742] A user creates a new project or task.

[1743] A user uses a terminal to enter details of a new project or task into a project management tool, including the project name, purpose, deadline, required resources, and other information.

[1744] Input: Project name, purpose, deadline, required resources

[1745] Output: Project data stored in a project management tool

[1746] Specific operation: A user logs in to the project management tool, clicks the Create New Project button, enters the required information, and clicks the Save button.

[1747] Step 2:

[1748] The server receives the input data and sends prompts to the generative AI model.

[1749] The server receives project and task details entered by the user and generates prompts based on the received data to send to the generative AI model.

[1750] Input: Project Data

[1751] Output: The prompt to send to the generative AI model

[1752] Specific operation: The server receives new project data from the project management tool, generates prompt sentences, and sends the generated prompt sentences to the generative AI model.

[1753] Step 3:

[1754] The generative AI model selects the appropriate department and person in charge.

[1755] The generative AI model selects the appropriate department and person in charge based on data such as position within the organization, expertise, and past project experience.

[1756] Input: Prompt statement, organizational position, expertise, and past project experience data

[1757] Output: Information about the appropriate department and person in charge

[1758] Specific operation: The generative AI model receives the prompt, retrieves relevant information from the database, selects the most appropriate department and person in charge, and returns the results to the server.

[1759] Step 4:

[1760] The server will provide the location of the relevant materials and the necessary permissions.

[1761] The server will then present the selected department and person in charge with the location of the relevant documents and the necessary permissions.

[1762] Input: Department and person in charge information

[1763] Output: Information on where related materials are stored and the necessary permissions

[1764] Specific operation: The server receives the results from the generative AI model, retrieves the storage location and access permission information for the relevant materials from the database, generates information to provide to the user, and displays it in the project management tool.

[1765] Step 5:

[1766] The user reviews the results and starts the task.

[1767] The user checks the information provided by the server through their terminal. Specifically, they check the department and person in charge, the storage location of related documents, and access permission information on the project management tool. They access the necessary documents and start tasks efficiently.

[1768] Input: Information provided by the server

[1769] Output: Task started

[1770] Specific actions: The user checks the information displayed in the project management tool, accesses related materials, downloads the necessary materials, and starts the project.

[1771] (Application example 1)

[1772] Next, a description will be given of Application Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1773] In the past, when a new manufacturing process or maintenance task arose in a factory, it was difficult to quickly identify the appropriate department or person in charge, preventing efficient task initiation. Furthermore, there was insufficient information on where related documents were stored and the necessary permissions, which often delayed task progress. This resulted in a decline in overall productivity and was a serious problem in factory operations.

[1774] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1775] In this invention, the server includes means for introducing the department and person in charge, presenting the storage location of related materials and the necessary authority, schedule management based on backward calculation until the target completion date, setting up meetings for the person in charge, and proposing and assisting with the content required to complete the task, means for automatically introducing the appropriate department and person in charge when a new manufacturing process or maintenance task occurs in the factory, and means for identifying the most suitable person in charge based on information such as their position in the factory, expertise, and past project experience, and presenting the storage location of related materials and the necessary authority. This makes it possible to quickly identify the appropriate person in charge and provide related information when a new task occurs in the factory.

[1776] A "department" is a department within an organization that is responsible for carrying out a specific task or project.

[1777] A "personnel" is an individual selected to carry out a specific task or project.

[1778] "Relevant materials" are information and documents needed to complete a task or project.

[1779] "Storage location" refers to the location where relevant materials are stored.

[1780] "Permissions" are the access rights and operational privileges required to accomplish a specific task or project.

[1781] "Schedule management" means managing the progress of tasks and projects and making plans to reach the target completion date.

[1782] "Meeting arrangement" refers to planning a meeting related to a task or project and inviting participants.

[1783] A "proposal" is the presentation of specific methods or ideas for efficiently progressing a task or project.

[1784] "Assisting" means providing support to help complete a task or project.

[1785] A "manufacturing process" is a series of steps or procedures for creating a product.

[1786] "Maintenance tasks" are the work required to maintain, inspect, and repair machinery and equipment.

[1787] A "position" indicates a job or position within an organization.

[1788] "Specialized knowledge" refers to advanced knowledge and skills in a particular field.

[1789] "Project experience" refers to experience and track record related to projects that have been carried out in the past.

[1790] The system for implementing this invention has the function of automatically introducing the appropriate department and person in charge when a new manufacturing process or maintenance task occurs in a factory. The system consists of three main elements: a server, a terminal, and a user.

[1791] The server has the functions of introducing the responsible department and person in charge, showing where related documents are stored and the necessary permissions, managing the schedule based on backward calculations to the target completion date, setting up meetings for the person in charge, proposing and assisting with the content required to complete the task, etc. It also has the function of identifying the most suitable person based on information such as position within the factory, expertise, and past project experience, and showing where related documents are stored and the necessary permissions.

[1792] Terminals are devices used by each department and person in the factory, and they receive and display information from the server. Terminals include PCs, tablets, smartphones, etc.

[1793] Users are various departments and personnel within the factory, and access information provided by the server via their terminals. When a new manufacturing process or maintenance task arises, users can respond quickly based on the information from the server.

[1794] Specifically, when a new task arises in the factory, the server first inputs the task requirements. The server then retrieves employee information from the database and compares the task requirements with the employee's skills to identify the most suitable person. Once the most suitable person is identified, the server presents the location of related documents and the necessary permissions, and sends the information to the terminal. The user can receive this information through the terminal and start the task efficiently.

[1795] The hardware used includes servers, storage devices, PCs, tablets, and smartphones, and the software used includes Python and JSON libraries.

[1796] As a concrete example, consider a new manufacturing process that requires skills in mechanical engineering, programming, and project management. The server identifies the most suitable person based on these requirements and provides the location of the relevant documents and the necessary permissions.

[1797] Example prompts to input to the generative AI model:

[1798] A new manufacturing process has been developed that requires the following skills: mechanical engineering, programming, and project management. Identify the appropriate person, provide the location of the relevant documentation, and the necessary permissions.

[1799] This prompt can be used to input a generative AI model to identify the most appropriate person and suggest where relevant materials are stored and what permissions are required.

[1800] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1801] Step 1:

[1802] When a new manufacturing process or maintenance task arises in the factory, the server inputs the requirements for that task, including the required skills, job title, and expertise, thereby clarifying the specific requirements for the task.

[1803] Step 2:

[1804] The server retrieves employee information from a database, including each employee's job title, expertise, past project experience, etc. This provides data to compare with the task requirements.

[1805] Step 3:

[1806] The server compares the task requirements with the employee skills and identifies the most suitable person. Specifically, it scores employees whose skills match the task requirements and selects the employee with the highest score. This identifies the person best suited to the task.

[1807] Step 4:

[1808] Once the server identifies the most suitable person, it presents the location of the relevant documents and the necessary permissions. The location of the relevant documents is retrieved from the database, and the necessary permissions are determined based on the person's job title and skills. This provides the person with the information they need to complete the task.

[1809] Step 5:

[1810] The server then sends the identified person in charge and related information to the terminal. The terminal is a device used by the person in charge, such as a PC, tablet, or smartphone, allowing the person in charge to receive the necessary information.

[1811] Step 6:

[1812] The user receives information provided by the server through their terminal and efficiently starts the task. The user checks the storage location of related materials and the necessary permissions, and makes the necessary preparations to complete the task. This allows the task to proceed quickly and efficiently.

[1813] Step 7:

[1814] The user provides feedback on the progress of the task to the server, which then manages the schedule based on the feedback and suggests additional meetings or other tasks as necessary, thereby continuously supporting the progress of the task.

[1815] Example 2

[1816] Next, a description will be given of Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1817] In project management, it is difficult to efficiently manage schedules and schedule meetings based on backward calculations to the target completion date. Furthermore, there is a lack of systems that allow easy understanding of project progress and efficient scheduling of necessary meetings. Furthermore, there is a need for a method to automatically generate project progress reports using generative AI models.

[1818] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1819] In this invention, the server includes a means for a user to input a target completion date for the project, a means for the server to receive the target completion date and set a deadline for each task by calculating backwards, a means for the server to adjust the schedules of the people in charge and set meetings, a means for the server to send prompts to the generative AI model and generate a progress report, and a means for the server to provide the generated report to the user. This makes it possible to easily grasp the progress of the project and efficiently set up necessary meetings.

[1820] A "department" is a department within an organization that is responsible for a particular project or task.

[1821] A "person in charge" is an individual who is responsible for a particular task or project.

[1822] "Relevant materials" are documents and files containing information or data necessary to carry out a project or task.

[1823] "Repository" is the location or system where relevant materials are stored.

[1824] "Necessary privileges" are the authorizations and authentications required to access relevant materials and systems.

[1825] The "desired completion date" is the ultimate date by which a project or task should be completed.

[1826] "Counting backwards" is a calculation method that sets deadlines for each task by working backwards from the completion date of the goal.

[1827] "Schedule management" is the process of planning and managing the progress of projects and tasks.

[1828] "Meeting setup" is the process of scheduling a meeting for a specific date and time and notifying participants.

[1829] A "task" is a discrete task or activity required to complete a project.

[1830] A "suggestion" refers to a recommended method or means for completing a task.

[1831] "Assistance" refers to providing help or support to complete a task.

[1832] "User" refers to an individual or organization that uses the system to manage projects.

[1833] A "server" is a computer that is the core of a system and is a device that processes and stores data.

[1834] A "generative AI model" is a model that uses artificial intelligence to automatically perform specific tasks.

[1835] A "prompt" is text containing instructions or questions that are input to a generative AI model.

[1836] A "progress report" is a report summarizing the progress of a project or task.

[1837] A "character shape" is a shape that has an appearance or design that users can relate to.

[1838] The present invention is a system for efficiently managing schedules and setting up meetings for project managers based on backward calculations to the target completion date in a project management system. Specific embodiments of this system will be described below.

[1839] System configuration

[1840] This system includes a terminal used by the user, a server that processes data, and a generative AI model. The terminal is a device such as a PC or smartphone, and the server is a computer that processes and stores data. The generative AI model is a model that uses artificial intelligence to automatically perform specific tasks.

[1841] Hardware and software used

[1842] Devices: PC, smartphone

[1843] Server: A high-performance comput...

Claims

1. A way to receive the project's target completion date and work backwards to set deadlines for each task, A means of receiving information on the responsible department and person in charge and assigning a person in charge to each task, A means of receiving the storage location of relevant documents and the necessary authority, and granting the necessary authority to the person in charge; A means for analyzing a user's emotions while the user is performing a specific task; A means for proposing task simplification and reallocation based on the analyzed emotion; means for displaying the progress of the project and the proposals on smart glasses worn by a user; a means for reassessing the progress of said projects and rescheduling them as necessary; A system including:

2. The system according to claim 1 , wherein the system has the form of a robot that can be attached to as a character.

3. The system according to claim 1 , wherein the system supports employees of a particular organization as a concierge, with the employees playing a central role.

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