system

Abstract

We provide the system. [Solution] An input means for entering project contract information, a database means for storing and managing the generated contract, and a generation means for automatically generating the contract. A means for inputting requests from the owner and saving those requests in a database, and a means for notifying that information, A means to automatically generate project schedules and monitor and notify progress in real time, A means of assigning tasks to each staff member and monitoring and notifying them of their progress, A means of analyzing project risks and sending alerts to stakeholders, A system that includes educational tools to provide training modules for production managers.

Description

Technical Field

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

Background Art

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

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In the process of anime production, there is a problem that the burden of production progress is large, and due to deficiencies in contract management and progress management, an extra workload is imposed on animators. Specifically, the problems are that the client's requirements and contract contents are not properly communicated to the animators, and project delays occur due to inadequate risk management. Also, inefficiency due to the lack of experience of the production progress staff is a major problem.

Means for Solving the Problems

[0005] This invention streamlines contract management by providing an input means for entering project contract information, a database means for storing and managing generated contracts, and a generation means for automatically generating contracts. Furthermore, it eliminates shortcomings in communicating requests to animators by using a communication means to store owner requests in a database and notify them hierarchically. In addition, it prevents project delays and workload concentration by providing a means for automatically generating project schedules and monitoring progress, as well as a notification means for analyzing risks and sending alerts to stakeholders. Moreover, it builds a system that improves inefficiencies stemming from lack of experience by providing educational modules for production managers.

[0006] A "project" is a series of activities carried out to produce a specific deliverable within a specific timeframe, based on a defined objective.

[0007] "Contract information" refers to data that records the terms agreed upon between the parties involved in the execution of a project, including details such as conditions, responsibilities, and compensation.

[0008] "Input means" refers to an interface or device used by a user to provide specific information to a system.

[0009] A "database system" is a system or solution for efficiently storing and organizing information in a searchable state.

[0010] "Generation means" refers to a device or process that automatically creates a specific format or document based on input information.

[0011] The term "owner" refers to an individual or organization that is involved in a project and has formal authority and interest in its deliverables.

[0012] "Communication means" refers to a method or device for sending and receiving information, and which has the function of transferring data over a network.

[0013] A "schedule" is a plan that outlines the timing and sequence of each task in a project, and its purpose is time management.

[0014] "Progress" is an indicator that shows the completion status or degree of progress of tasks in a project.

[0015] "Risk" refers to potential obstacles or uncertainties that may arise in a project and could have undesirable consequences.

[0016] A "notification method" is a technology or method for conveying specific information to relevant parties, and may function as an alert or reminder.

[0017] "Educational tools" refer to systems and methods, including educational materials and programs, that are provided with the aim of improving specific skills or knowledge. [Brief explanation of the drawing]

[0018] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8]It is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] It shows an emotion map to which a plurality of emotions are mapped. [Figure 10] It shows an emotion map to which a plurality of emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Example 2 when an emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when an emotion engine is combined.

Embodiments for Carrying Out the Invention

[0019] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0020] First, the terms used in the following description will be explained.

[0021] In the following embodiments, the signed processor (hereinafter simply referred to as "processor") may be one arithmetic unit or a combination of a plurality of arithmetic units. Also, the processor may be one type of arithmetic unit or a combination of a plurality of types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0022] In the following embodiments, signed RAM (Random Access Memory) is a memory that temporarily stores information and is used as work memory by the processor.

[0023] In the following embodiments, the signed storage is one or more non-volatile storage devices that store various programs and various parameters. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes.

[0024] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0025] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0026] [First Embodiment]

[0027] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0028] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0029] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0030] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0031] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0032] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0033] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0034] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0035] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0036] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0037] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0038] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0039] This invention describes the construction of a system that streamlines project management in animation production and reduces the workload of animators. This system primarily involves three entities—a server, terminals, and users—working in coordination with each other, with the aim of sequentially and efficiently performing contract management, progress management, risk notification, and educational support.

[0040] First, users use a terminal to input project-related contract information. This information includes working conditions, responsibilities, and compensation. The entered information is collected by the server, and a contract is automatically generated based on a contract generation template. This reduces manual work in contract management and enables efficient management.

[0041] Next, the user inputs requests from the owner via a terminal during the production process. The server then stores these requests in a database and notifies the relevant staff of any changes or new requests according to established rules. This ensures that necessary information is quickly and accurately conveyed to the animators, reducing errors and wasted time.

[0042] Furthermore, the server automatically generates a schedule for the entire project and assigns tasks based on it. Progress is monitored in real time, and timely updates are provided to stakeholders. This includes reminder notifications if a task is behind schedule. A specific example is the function that automatically sends reminder emails to animators as deadlines approach.

[0043] In project risk management, the server analyzes progress logs to identify potential risk factors. If potential malfunctions or delays are detected, it sends alerts to stakeholders to support the smooth progress of the project. Specific examples include automatically suggesting alternative plans if resource shortages or schedule conflicts are found.

[0044] Furthermore, users can access educational modules from their devices. This allows production managers to enhance the necessary skills and improve the efficiency of project management. Specific examples include materials on streamlining task management, enabling users to gain experience through repeated learning.

[0045] In summary, this system contributes to solving a wide range of problems in anime production, achieving smoother production progress and reducing the workload of animators.

[0046] The following describes the processing flow.

[0047] Step 1:

[0048] The user enters the project-related contract terms via their device. These terms include scope of work, compensation, and deadlines.

[0049] Step 2:

[0050] The terminal processes the entered contract information as digital data and sends it to the server.

[0051] Step 3:

[0052] The server automatically generates a contract template based on the received contract information and saves the generated contract to the database.

[0053] Step 4:

[0054] The user enters requests from the owner into the terminal. These requests may concern new designs or changes to specific scenes.

[0055] Step 5:

[0056] The terminal sends the entered request to the server and instructs it to save the information to the database.

[0057] Step 6:

[0058] The server notifies the relevant animator staff of requests stored in the database and provides a reply function if confirmation is required.

[0059] Step 7:

[0060] The server performs calculations based on past project data and configured task durations to automatically generate the overall project schedule.

[0061] Step 8:

[0062] The server assigns each task to animators according to a calculated schedule and notifies them of the assignment details via their terminals.

[0063] Step 9:

[0064] Users use a terminal to input the completion status of their assigned tasks and report progress data to the server.

[0065] Step 10:

[0066] The server analyzes the reported progress data and generates an alert to notify relevant parties if there are any problems with the progress.

[0067] Step 11:

[0068] The server automatically performs a risk analysis and sends notifications suggesting necessary countermeasures if potential risks exist in an ongoing project.

[0069] Step 12:

[0070] Users access educational modules through their devices to learn the knowledge and skills necessary for production management. This information is used for self-improvement and skill development purposes.

[0071] (Example 1)

[0072] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0073] In animation production project management, managing contract details, real-time monitoring of progress, rapid information sharing, and early detection and response to project risks are crucial. However, relying solely on manual processes and individual management can easily lead to errors, decreased work efficiency, and delays in information transmission. This increases the workload on animators and managers, resulting in project delays and a decline in quality. Furthermore, the lack of educational resources to support the technical skill development of production managers also poses a problem for long-term project execution. These challenges need to be addressed efficiently.

[0074] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0075] In this invention, the server includes means for storing project contract details in a storage device and automatically generating contract documents, means for storing the client's work requests in a recording device and notifying relevant parties, and means for automatically generating project plans and monitoring and notifying progress in real time. This enables more efficient project management, rapid information dissemination, early detection of risks, and provision of training for skill improvement.

[0076] A "project" refers to a set of activities or tasks planned to achieve a specific goal.

[0077] "Contract terms" refers to the formal agreements regarding the project, including conditions, responsibilities, and compensation.

[0078] A "terminal device" refers to an electronic device used by a user to input data and interact with a system.

[0079] A "storage device" refers to a physical or logical device used to store data within a system.

[0080] A "server processing unit" refers to a central control unit that processes, stores, receives, and manages data.

[0081] The term "client" refers to the person or organization that directs the specific content or changes to the project.

[0082] "Work requirements" refer to the specific wishes and instructions for a project provided by the client.

[0083] A "communication device" refers to a device used to send and receive information both within and outside a system.

[0084] An "activity plan" refers to the overall plan that includes details of tasks and schedules created to manage the progress of a project.

[0085] "Control device" refers to the equipment and software within a system used for various management and control functions of a project.

[0086] "Participants" refers to the staff and individuals involved in the progress of the project.

[0087] A "monitoring and control system" refers to a device that monitors the progress of a project and makes adjustments as needed.

[0088] An "analysis device" refers to a device used to analyze data and identify potential problems or risks.

[0089] An "educational support device" refers to a device or software that provides educational content to improve the user's skills.

[0090] "Skill improvement materials" refer to learning materials and content designed to improve the skills of production managers and staff.

[0091] The system for implementing this invention mainly consists of three components: a server, a terminal, and a user. Its purpose is to streamline project management in animation production and reduce the workload of animators.

[0092] First, the user enters the project contract details using a terminal. This terminal is a hardware device equipped with a specialized interface, designed to allow users to intuitively input data. The information entered by the user is sent from the terminal to the server. Upon receiving it, the server stores it in a secure storage device. This storage device utilizes a database management system, allowing for efficient management of stored information and retrieval as needed. Simultaneously, the server automatically generates the contract document. For this purpose, a generation AI model is used, and an automatic conversion program documents the contract details according to the format.

[0093] Furthermore, users input work requests from clients via a terminal. This is also processed on the terminal, and the data is immediately transmitted to the server. The server processes this data and utilizes communication devices to send notifications to the relevant personnel. This system is also designed to ensure that information is shared with all parties involved in real time.

[0094] The server also automatically generates a project activity plan and monitors its progress. This plan is created by the system, and tasks are assigned to each participant. Project progress is monitored in real time, and progress notifications and reminders are sent as needed.

[0095] Furthermore, the server uses analysis equipment to analyze potential risk factors that may arise during the project's progress. If malfunctions or delays are detected, alerts are issued to the relevant parties. This allows problems to be addressed before they become major obstacles.

[0096] Furthermore, production managers can access educational support devices from their terminals. These devices provide learning materials to improve users' skills and are configured to enhance learning effectiveness with a user-friendly interface.

[0097] As a concrete example, a possible prompt statement might be, "Please tell me what kind of contract management system should be designed to reduce the workload of animators." Based on this prompt statement, the generating AI model assists in designing the contract management system and executes a process to transform the information. This ensures that the entire system operates efficiently and effectively.

[0098] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0099] Step 1:

[0100] The user uses a terminal to input project contract details. These details include working conditions, responsibilities, and compensation. The entered data is temporarily processed within the terminal and organized according to a specified format. The terminal then sends the organized data to the server. The output is formatted contract information.

[0101] Step 2:

[0102] The server stores the contract information received from the terminal in a database. During storage, a generation AI model is used to format the content based on a contract document template, automatically generating the contract document. The output is the formatted contract document.

[0103] Step 3:

[0104] The user enters project work requests using a terminal. The entered requests are converted into a data format by the terminal and sent to the server. The converted work requests are then output.

[0105] Step 4:

[0106] The server stores the work request in a database and sends notifications to the relevant personnel. The server uses a notification communication device to send the request details to the relevant parties. This process enables rapid and accurate information sharing. The output is a notification message.

[0107] Step 5:

[0108] The server automatically generates a project activity plan. It utilizes a generative AI model, learned from past project data and work requests, to create an optimized plan. The plan is assigned to each participant and notified via their terminal. The output includes a detailed activity plan and a list of assigned personnel.

[0109] Step 6:

[0110] The server monitors project progress in real time and analyzes progress data. During monitoring, it sends reminders to tasks that are behind schedule. Progress data is reported to stakeholders via terminals. The output is a progress report.

[0111] Step 7:

[0112] The server analyzes project progress logs and identifies risk factors. Using the analysis system, if a risk is detected, it issues a warning to relevant parties and notifies them of countermeasures. The output includes a risk alert and suggested countermeasures.

[0113] Step 8:

[0114] Users access educational support devices via a terminal and utilize skill-building materials. These materials are provided in an interactive format to support user learning. The output is learning outcomes and improved skills.

[0115] (Application Example 1)

[0116] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0117] In today's highly developed and diversified manufacturing environments, there is a growing need to improve the operational efficiency of robots and minimize errors and delays. However, conventional management systems often rely on manual processes for robot operation contracts and scheduling, making efficient information transfer and early detection of anomalies difficult.

[0118] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0119] In this invention, the server includes an input / output device for inputting project contract information, a data structure for storing and managing the generated contract, a generation device for automatically generating the contract, a device for inputting requests from the client and saving those requests in the data structure, a communication device for notifying the client of the information, and a device for automatically generating a project plan and monitoring and notifying the client of its progress in real time. This enables more efficient management of robot operations and a rapid response to unforeseen circumstances.

[0120] An "input / output device" is an interface for users to input information and an interface for systems to output information.

[0121] A "data structure" is a collection of data organized to efficiently store and manage information.

[0122] A "generation device" is a device that has the function of automatically creating documents or information based on a specific format.

[0123] A "communication device" is a device that implements technologies for sending and receiving information between various devices inside and outside a system.

[0124] A "plan" is a schedule that shows the chronological arrangement of activities within a project.

[0125] "Progress" is an indicator that shows the extent to which activities based on the plan are being carried out.

[0126] "Mobile terminal" refers to a portable communication device, mainly including smartphones.

[0127] "Uncertainty" refers to unstable factors or events that may occur in the future, and is synonymous with risk.

[0128] The system based on this invention is constructed using a combination of multiple hardware and software components. The system consists of a server, terminals (e.g., smartphones and tablets), and users. The system is primarily operated in the following manner:

[0129] The user first inputs project-related contract information through the terminal's input / output device. This input information is then formatted based on a pre-programmed template and stored in the server's data structure. This standardizes contract information and enables consistent data management.

[0130] Next, the user communicates with the server via an open API to automatically generate a project plan. The server monitors the project's progress in real time and sends notifications to the user's device based on the progress. This utilizes a cloud-based database and a progress analysis engine equipped with machine learning algorithms.

[0131] Furthermore, the server detects uncertainties within the project and sends alerts to stakeholders. Here, it is possible to predict potential risks from historical data using generative AI models.

[0132] Furthermore, new robot operators can easily acquire the necessary knowledge because they can access educational modules through their devices. This provides users with the opportunity to efficiently improve their skills through self-study.

[0133] As a concrete example, one manufacturing plant uses a smartphone app to manage daily robot operations. Furthermore, examples of supported prompts include instructions such as, "Please describe a system that monitors the progress of robot management in the factory in real time and sends immediate alerts to address any abnormalities."

[0134] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0135] Step 1:

[0136] The user uses a terminal to enter project contract information. The entered information is formatted according to a standardized template and sent to the server. The server stores this data in a data structure and prepares it for contract generation.

[0137] Step 2:

[0138] The user requests project plan generation from the server via an open API through their device. The server automatically generates a plan based on the received contract and progress information and returns the plan data to the device. During this process, machine learning algorithms are used to efficiently handle scheduling.

[0139] Step 3:

[0140] As the user executes the plan, the server monitors the project's progress in real time. When progress data is sent to the server, the server analyzes the necessary progress information and notifies the terminal of the latest progress. If inconsistencies are detected at this time, the server also selects a corrective plan.

[0141] Step 4:

[0142] The server analyzes uncertainties within the project. Using generative AI models and comparing them to historical data, it identifies potential risks and sends alerts to stakeholders. This risk notification is delivered via email or push notification.

[0143] Step 5:

[0144] Users can access educational modules via their devices and efficiently acquire the necessary skills. The server sends the latest learning materials and progress test results to the devices and records the user's learning progress.

[0145] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0146] This invention proposes a new system construction that combines an emotion engine, with the aim of improving operational efficiency in anime production projects. This system aims to improve efficiency and employee satisfaction by recognizing the user's emotional state and flexibly adapting project management based on that state. It primarily involves a mechanism that interacts with three parties: the server, the terminal, and the user.

[0147] In this system's implementation, the user first uses a terminal to input project contract information. During this process, the emotion engine analyzes information such as the user's facial expressions, voice tone, and input speed. Based on this data, the emotion engine determines whether the user is stressed or calm, and provides appropriate feedback and support information based on that emotional state.

[0148] Next, during the process of the user entering requests from the owner, the emotion engine analyzes the user's emotions. Based on this information, the server can adjust how the requests are communicated. For example, if the user is feeling anxious, a confirmation message for the request will be added. The emotion engine also predicts how the communication of important requests will affect the user's emotions and manages to send notifications at the optimal time.

[0149] Furthermore, the emotion engine is also effective in task management as a project progresses. The server uses emotion data to customize task assignments and notification methods in a format that best suits the user's current mental state, thereby improving work efficiency. For example, if the emotion engine determines that the user is motivated, it will arrange to send a message of praise.

[0150] Finally, the training modules provided to production managers are customized using emotion engine data. Users can access content on their devices in a format optimized to their learning pace and current emotional state. This maximizes learning effectiveness and promotes employee skill development.

[0151] This system, which incorporates an emotion engine, enables project management that is sensitive to the user's emotions, thereby improving both operational efficiency and employee satisfaction.

[0152] The following describes the processing flow.

[0153] Step 1:

[0154] The user enters project contract information via a terminal. The emotion engine analyzes the user's facial expressions and tone of voice while they are entering information, and evaluates the user's emotional state in real time.

[0155] Step 2:

[0156] The device detects the user's emotional state and displays corresponding feedback on the screen. For example, if the user is feeling stressed, it might provide a message such as, "Relax and continue."

[0157] Step 3:

[0158] Based on the emotional data received from the emotion engine, the server re-verifies whether the contract details have been entered accurately and provides supplementary information about the automatically generated contract as needed.

[0159] Step 4:

[0160] The user enters the owner's request into the terminal. The emotion engine then re-analyzes the user's emotions at the time the request was entered.

[0161] Step 5:

[0162] The server adjusts the request notification method based on the analysis results. For example, if the user expresses concern, it may simplify the request notification or suggest additional verification procedures.

[0163] Step 6:

[0164] When the server sends notifications to staff regarding the owner's requests, it takes emotional data into consideration and presents the notification in the most acceptable format.

[0165] Step 7:

[0166] When managing project schedules, the server uses sentiment data to customize task assignments. For example, it assigns challenging tasks to highly motivated users.

[0167] Step 8:

[0168] Users report their progress via their devices. The emotion engine analyzes the emotional state at the time of reporting and sends the data to the server to consider subsequent actions.

[0169] Step 9:

[0170] Users take educational modules. During this process, the emotion engine tracks changes in emotions while learning and adjusts the content to optimize the learning pace and maintain motivation.

[0171] Step 10:

[0172] Based on the sentiment data collected so far, the server forms a feedback loop across the entire system to continuously optimize the user experience.

[0173] (Example 2)

[0174] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0175] In anime production projects, failing to consider the emotional state of participants during project management can easily lead to increased stress and decreased motivation, resulting in reduced work efficiency and employee satisfaction. Furthermore, the lack of feedback and training tailored to the individual emotional state of employees makes effective project management and skill development difficult.

[0176] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0177] In this invention, the server includes emotion analysis means for analyzing the emotional state of project participants and reflecting that information in project management; management means for adaptively adjusting project schedules and task notification methods based on emotional state; and education delivery means for customizing educational content for production staff using emotional data. This enables project management and education customization that takes into account the emotional state of participants, thereby improving work efficiency and employee satisfaction.

[0178] "Emotional analysis tools" are methods for analyzing the emotional states of project participants and incorporating that information into project management.

[0179] "Analysis means" refers to a method for receiving user input data and quantifying the emotional state using an emotion engine.

[0180] "Management measures" are means of adaptively adjusting project schedules and task notification methods based on emotional states.

[0181] "Educational delivery methods" refer to means of customizing educational content for production managers using emotional data.

[0182] "Information provision means" refers to methods for providing feedback and supplementary information according to the user's emotional state to support project management.

[0183] This system is designed to take into account the emotional states of participants in anime production projects and to achieve efficient project management. It primarily operates through collaboration between three parties: users, servers, and terminals.

[0184] First, the user uses a terminal to input project contract information and requests from the owner. The terminal has an emotion engine built in, which uses speech recognition and facial recognition technology to analyze the user's facial expressions, voice tone, input speed, etc., and identify their emotional state.

[0185] Next, the server optimizes project management based on the analyzed emotional state. The emotional analysis tool quantifies the user's stress level and motivation, and uses this information to adjust project schedules and task notification methods. In this process, it is possible to generate emotionally appropriate feedback and supportive information using a generative AI model.

[0186] Furthermore, educational content for production staff is also managed on the server side. The server utilizes emotional data and, through educational delivery methods, customizes and provides optimized educational modules tailored to the user's learning pace and current emotional state.

[0187] As a concrete example, if the emotion engine detects an increase in the user's stress level while they are entering contract information, the server will display input assistance messages or notifications prompting them to take a short break through the terminal. Another example of a prompt using a generative AI model is, "Generate an appropriate feedback message to provide if the user is feeling anxious."

[0188] This system, centered on sentiment analysis, makes project management more flexible and effective. A key feature of this system is its ability to achieve both improved operational efficiency and increased employee satisfaction.

[0189] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0190] Step 1:

[0191] The user enters project contract information using a terminal. The terminal retrieves the input data and sends it to the emotion engine. The input information includes the contract information itself, as well as data related to the user's facial expressions and voice tone. The terminal detects this data and prepares it to be sent to the server.

[0192] Step 2:

[0193] The server processes the data received from the terminal. First, it uses an emotion engine to analyze the user's emotional state. Specifically, it uses facial recognition and speech recognition technology to quantify whether the user is stressed or calm. The results of this analysis are recorded on the server as emotion data useful for project management.

[0194] Step 3:

[0195] The server adjusts project management methods based on emotional data. In this step, task scheduling and notification methods are customized based on emotional data. For example, if a user is stressed, notifications may be withheld or supplementary support messages added. This information is also fed into a generative AI model to generate appropriate feedback messages.

[0196] Step 4:

[0197] The generated feedback and adjusted task information are communicated to the user via the device. The device displays the information received from the server, allowing the user to take the next action accordingly. Specific actions include reviewing messages displayed on the screen and responding to them.

[0198] Step 5:

[0199] The server customizes the educational content. It uses emotional data to optimize educational modules for production managers. The server generates data based on the user's learning pace and emotional state, and uses this to individually adjust the educational content. Feedback and new learning tasks are provided to the user through the device.

[0200] This series of processes allows users to receive project management and training tailored to their emotional state. This improves work efficiency and employee satisfaction.

[0201] (Application Example 2)

[0202] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0203] The problem that this invention aims to solve is that uniform project management and work progress without considering the emotional state of workers in factories and other workplaces leads to a decrease in work efficiency and worker satisfaction. Furthermore, because methods for improving the work environment are uniform, it is difficult to respond to the motivation and stress levels of individual workers, which is another problem.

[0204] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0205] In this invention, the server includes an input device for inputting project contract information, a storage device for storing and managing generated contract documents, a generation device means for automatically generating contract documents, an emotion detection device for recognizing emotional states, an emotion adaptation device means for adapting project management based on emotions, and a device means for adjusting the operation of the device using emotion data. This enables flexible project management and work adjustments in accordance with the emotional state of workers, thereby improving work efficiency and worker motivation.

[0206] An "input device" is a device or system used by users to input contract information related to a project.

[0207] A "storage device" is a storage device used to store and manage generated contract documents and other data.

[0208] A "generation device" is a device or program that automatically creates contract documents based on input data.

[0209] A "communication device" is a device that uses communication technology to notify users of information and requests.

[0210] A "plan" is a framework or schedule for automatically generating the steps and schedules necessary for the progress of a project.

[0211] "Tasks" refer to the specific work or tasks assigned to individual team members within a project.

[0212] "Risk" refers to analyzing the risks and problems that may arise during the project's progress.

[0213] A "warning" is a message or notification intended to draw the attention of relevant parties to a detected hazard.

[0214] The term "educational program" refers to the learning content and training provided to production staff.

[0215] An "emotion detection device" is a device or system that analyzes facial expressions and voice data to recognize the emotional state of workers and other individuals.

[0216] An "emotional adaptation device" is a device or program used to optimize project management and work progress based on detected emotional data.

[0217] "Emotional data" refers to data that indicates the emotional state of workers and other personnel, and is used as information for project management.

[0218] A "device for adjusting operation" is a device or software that adjusts the operation of a machine or system in real time based on emotional data.

[0219] The system for carrying out this invention consists of an emotion detection device, an emotion adaptation device, an input device, a memory device, a generation device, a communication device, and a device for adjusting operation. Each of these devices is designed to interact with the user's terminal and the server.

[0220] The server uses an emotion detection device to analyze the worker's facial expressions and voice data in real time to recognize their emotional state. This emotional data is stored in memory, and a generation device automatically generates necessary instructions. The server also uses an emotion adaptation device to optimize project management and task progress based on the recognized emotional data. In this process, if a worker is experiencing stress, the system adjusts the pace of work and sends encouraging notifications to improve the work environment.

[0221] The user's terminal inputs contract information and owner requests related to the project via an input device and sends them to the server. The communication device notifies multiple personnel of the input information in real time, ensuring accurate information transmission.

[0222] For example, in a manufacturing plant, if an emotion detection device detects that a worker has been working for a long time and is fatigued, the server adjusts the machine's operating speed via a control device and sends a notification such as "You need a break." In this way, it is possible to reduce the burden on workers and provide an efficient work environment.

[0223] An example of a prompt message for the generating AI model could be: "Generate an effective support message for workers in a high-stress environment."

[0224] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0225] Step 1:

[0226] The server uses an emotion detection device to acquire the worker's facial expressions and voice data in real time. It receives raw data from cameras and microphones as input and feeds it into emotion analysis software. Data processing involves feature point extraction and voice frequency analysis to generate emotional state data. In this process, the server obtains an output that recognizes the emotional state (e.g., stress level, euphoria, etc.).

[0227] Step 2:

[0228] The server uses the obtained emotional state data to activate an emotional adaptation device, optimizing project management and task progress. It receives emotional state data as input and compares it with past data in a database to develop an optimization strategy suitable for the current work environment. For data processing, it uses an algorithm to adjust work progress with the aim of reducing worker stress, and generates an adjusted task schedule as output.

[0229] Step 3:

[0230] Users input project-related contract information and owner requests into a terminal via an input device. The input is received in text or multiple-choice format. The server receives this information and notifies project stakeholders using a communication device. The output consists of confirmed contract information and requests, which serve as fundamental data for project progress.

[0231] Step 4:

[0232] The server uses a device to adjust the operation of machines and systems dynamically based on emotional states. It uses emotional state data and work progress data as input to generate commands for operation adjustment. Specifically, it may issue instructions to reduce work speed when stress levels are high, and the output includes adjusted machine operation and suggestions for improving the work environment.

[0233] Step 5:

[0234] The user inputs an appropriate prompt sentence to a generative AI model, which automatically generates support messages tailored to the user's emotional state. The prompt sentence used as input is, "Generate an effective support message for workers in a high-stress environment." The server executes the generative AI model and provides the user with the generated support message as output.

[0235] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0236] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0237] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0238] [Second Embodiment]

[0239] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0240] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0241] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0242] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0243] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0244] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0245] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0246] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0247] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0248] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0249] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0250] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0251] This invention describes the construction of a system that streamlines project management in animation production and reduces the workload of animators. This system primarily involves three entities—a server, terminals, and users—working in coordination with each other, with the aim of sequentially and efficiently performing contract management, progress management, risk notification, and educational support.

[0252] First, users use a terminal to input project-related contract information. This information includes working conditions, responsibilities, and compensation. The entered information is collected by the server, and a contract is automatically generated based on a contract generation template. This reduces manual work in contract management and enables efficient management.

[0253] Next, the user inputs requests from the owner via a terminal during the production process. The server then stores these requests in a database and notifies the relevant staff of any changes or new requests according to established rules. This ensures that necessary information is quickly and accurately conveyed to the animators, reducing errors and wasted time.

[0254] Furthermore, the server automatically generates a schedule for the entire project and assigns tasks based on it. Progress is monitored in real time, and timely updates are provided to stakeholders. This includes reminder notifications if a task is behind schedule. A specific example is the function that automatically sends reminder emails to animators as deadlines approach.

[0255] In project risk management, the server analyzes progress logs to identify potential risk factors. If potential malfunctions or delays are detected, it sends alerts to stakeholders to support the smooth progress of the project. Specific examples include automatically suggesting alternative plans if resource shortages or schedule conflicts are found.

[0256] Furthermore, users can access educational modules from their devices. This allows production managers to enhance the necessary skills and improve the efficiency of project management. Specific examples include materials on streamlining task management, enabling users to gain experience through repeated learning.

[0257] In summary, this system contributes to solving a wide range of problems in anime production, achieving smoother production progress and reducing the workload of animators.

[0258] The following describes the processing flow.

[0259] Step 1:

[0260] The user enters the project-related contract terms via their device. These terms include scope of work, compensation, and deadlines.

[0261] Step 2:

[0262] The terminal processes the entered contract information as digital data and sends it to the server.

[0263] Step 3:

[0264] The server automatically generates a contract template based on the received contract information and saves the generated contract to the database.

[0265] Step 4:

[0266] The user enters requests from the owner into the terminal. These requests may concern new designs or changes to specific scenes.

[0267] Step 5:

[0268] The terminal sends the entered request to the server and instructs it to save the information to the database.

[0269] Step 6:

[0270] The server notifies the relevant animator staff of requests stored in the database and provides a reply function if confirmation is required.

[0271] Step 7:

[0272] The server calculates based on past project data and set task periods to automatically generate the schedule for the entire project.

[0273] Step 8:

[0274] The server assigns each task to the animator according to the calculated schedule and notifies the details of the assignment via the terminal.

[0275] Step 9:

[0276] The user uses the terminal to input the completion status of the assigned task and reports the progress data to the server.

[0277] Step 10:

[0278] The server analyzes the reported progress data and generates an alert and notifies the relevant personnel if there is a problem with the progress.

[0279] Step 11:

[0280] If there are potential risks in the ongoing project, the server automatically conducts a risk analysis and sends a notification proposing necessary countermeasures.

[0281] Step 12:

[0282] The user accesses the educational module through the terminal and learns the knowledge and skills necessary for production progress. This information is used for self-improvement and skill enhancement purposes.

[0283] (Example 1)

[0284] Next, Example 1 will be described. In the following description, the data processing device 12 is referred to as the "server", and the smart glasses 214 are referred to as the "terminal".

[0285] In the project management of anime production, it is very important to manage the contract content, monitor the progress in real time, share information quickly, and detect and respond to project risks at an early stage. However, if these processes rely too much on manual work or individual management, mistakes are likely to occur, work efficiency will decline, and information transmission will be delayed. As a result, the burden on animators and administrators increases, leading to project delays and quality degradation. Furthermore, the lack of educational means to support the improvement of the technical skills of production managers also poses a problem in the execution of long-term projects. It is necessary to solve these problems efficiently.

[0286] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0287] In this invention, the server includes means for storing the contract content of a project in a storage device and automatically generating a contract document, means for storing the work requirements of the requester in a recording device and notifying the relevant parties, and means for automatically generating a project plan, monitoring the progress in real time, and notifying. As a result, it becomes possible to improve the efficiency of project management, enable rapid information transmission, detect risks at an early stage, and provide education for skill improvement.

[0288] A "project" refers to a set of a series of activities and tasks planned to achieve a specific goal.

[0289] "Contract content" refers to official agreement matters including conditions, responsibilities, rewards, etc. related to a project.

[0290] A "terminal device" refers to an electronic device used by a user to input data and interact with the system.

[0291] A "storage device" refers to a physical or logical device for storing data within a system.

[0292] A "server processing device" refers to a central control device that processes, stores, receives, and manages data.

[0293] The term "client" refers to the person or organization that directs the specific content or changes to the project.

[0294] "Work requirements" refer to the specific wishes and instructions for a project provided by the client.

[0295] A "communication device" refers to a device used to send and receive information both within and outside a system.

[0296] An "activity plan" refers to the overall plan that includes details of tasks and schedules created to manage the progress of a project.

[0297] "Control device" refers to the equipment and software within a system used for various management and control functions of a project.

[0298] "Participants" refers to the staff and individuals involved in the progress of the project.

[0299] A "monitoring and control system" refers to a device that monitors the progress of a project and makes adjustments as needed.

[0300] An "analysis device" refers to a device used to analyze data and identify potential problems or risks.

[0301] An "educational support device" refers to a device or software that provides educational content to improve the user's skills.

[0302] "Skill improvement materials" refer to learning materials and content designed to improve the skills of production managers and staff.

[0303] The system for implementing this invention mainly consists of three components: a server, a terminal, and a user. Its purpose is to streamline project management in animation production and reduce the workload of animators.

[0304] First, the user uses the terminal to input the contract details of the project. This terminal is a hardware device equipped with a specialized interface and is designed to make it intuitive and easy for the user to input data. The information input by the user is sent from the terminal to the server. When the server receives this, it stores it in a secure storage device. This storage device utilizes a database management system and can efficiently manage the stored information and retrieve it as needed. At the same time, the server automatically generates a contract document. For this purpose, a generation AI model is used, and the contract details are documented based on the format by an automatic conversion program.

[0305] Furthermore, the user inputs the work requirements of the requester from the terminal. This is also processed by the terminal, and the data is immediately sent to the server. The server processes the data and utilizes a communication device to send notifications to the relevant personnel. This is also designed to share information with the relevant parties in real time.

[0306] In addition, the server automatically generates an activity plan for the project and monitors the progress. This plan is created by the system, and tasks are assigned to each person involved. The progress of the project is monitored in real time, and progress status notifications and reminders are sent as needed.

[0307] Furthermore, the server uses an analysis device to analyze the risk factors that may occur during the progress of the project. If defects or delays are detected, warnings are issued to the relevant parties. This enables countermeasures to be taken before the problem becomes a major obstacle.

[0308] And the production manager can access the education assistance device from the terminal. This device provides teaching materials for improving the user's skills and is configured with an easy-to-use interface to enhance the learning effect.

[0309] As a concrete example, a possible prompt statement might be, "Please tell me what kind of contract management system should be designed to reduce the workload of animators." Based on this prompt statement, the generating AI model assists in designing the contract management system and executes a process to transform the information. This ensures that the entire system operates efficiently and effectively.

[0310] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0311] Step 1:

[0312] The user uses a terminal to input project contract details. These details include working conditions, responsibilities, and compensation. The entered data is temporarily processed within the terminal and organized according to a specified format. The terminal then sends the organized data to the server. The output is formatted contract information.

[0313] Step 2:

[0314] The server stores the contract information received from the terminal in a database. During storage, a generation AI model is used to format the content based on a contract document template, automatically generating the contract document. The output is the formatted contract document.

[0315] Step 3:

[0316] The user enters project work requests using a terminal. The entered requests are converted into a data format by the terminal and sent to the server. The converted work requests are then output.

[0317] Step 4:

[0318] The server stores the work request in a database and sends notifications to the relevant personnel. The server uses a notification communication device to send the request details to the relevant parties. This process enables rapid and accurate information sharing. The output is a notification message.

[0319] Step 5:

[0320] The server automatically generates a project activity plan. It utilizes a generative AI model, learned from past project data and work requests, to create an optimized plan. The plan is assigned to each participant and notified via their terminal. The output includes a detailed activity plan and a list of assigned personnel.

[0321] Step 6:

[0322] The server monitors project progress in real time and analyzes progress data. During monitoring, it sends reminders to tasks that are behind schedule. Progress data is reported to stakeholders via terminals. The output is a progress report.

[0323] Step 7:

[0324] The server analyzes project progress logs and identifies risk factors. Using the analysis system, if a risk is detected, it issues a warning to relevant parties and notifies them of countermeasures. The output includes a risk alert and suggested countermeasures.

[0325] Step 8:

[0326] Users access educational support devices via a terminal and utilize skill-building materials. These materials are provided in an interactive format to support user learning. The output is learning outcomes and improved skills.

[0327] (Application Example 1)

[0328] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0329] In today's highly developed and diversified manufacturing environments, there is a growing need to improve the operational efficiency of robots and minimize errors and delays. However, conventional management systems often rely on manual processes for robot operation contracts and scheduling, making efficient information transfer and early detection of anomalies difficult.

[0330] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0331] In this invention, the server includes an input / output device for inputting project contract information, a data structure for storing and managing the generated contract, a generation device for automatically generating the contract, a device for inputting requests from the client and saving those requests in the data structure, a communication device for notifying the client of the information, and a device for automatically generating a project plan and monitoring and notifying the client of its progress in real time. This enables more efficient management of robot operations and a rapid response to unforeseen circumstances.

[0332] An "input / output device" is an interface for users to input information and an interface for systems to output information.

[0333] A "data structure" is a collection of data organized to efficiently store and manage information.

[0334] A "generation device" is a device that has the function of automatically creating documents or information based on a specific format.

[0335] A "communication device" is a device that implements technologies for sending and receiving information between various devices inside and outside a system.

[0336] A "plan" is a schedule that shows the chronological arrangement of activities within a project.

[0337] "Progress" is an indicator that shows the extent to which activities based on the plan are being carried out.

[0338] "Mobile terminal" refers to a portable communication device, mainly including smartphones.

[0339] "Uncertainty" refers to unstable factors or events that may occur in the future, and is synonymous with risk.

[0340] The system based on this invention is constructed using a combination of multiple hardware and software components. The system consists of a server, terminals (e.g., smartphones and tablets), and users. The system is primarily operated in the following manner:

[0341] The user first inputs project-related contract information through the terminal's input / output device. This input information is then formatted based on a pre-programmed template and stored in the server's data structure. This standardizes contract information and enables consistent data management.

[0342] Next, the user communicates with the server via an open API to automatically generate a project plan. The server monitors the project's progress in real time and sends notifications to the user's device based on the progress. This utilizes a cloud-based database and a progress analysis engine equipped with machine learning algorithms.

[0343] Furthermore, the server detects uncertainties within the project and sends alerts to stakeholders. Here, it is possible to predict potential risks from historical data using generative AI models.

[0344] Furthermore, new robot operators can easily acquire the necessary knowledge because they can access educational modules through their devices. This provides users with the opportunity to efficiently improve their skills through self-study.

[0345] As a concrete example, one manufacturing plant uses a smartphone app to manage daily robot operations. Furthermore, examples of supported prompts include instructions such as, "Please describe a system that monitors the progress of robot management in the factory in real time and sends immediate alerts to address any abnormalities."

[0346] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0347] Step 1:

[0348] The user uses a terminal to enter project contract information. The entered information is formatted according to a standardized template and sent to the server. The server stores this data in a data structure and prepares it for contract generation.

[0349] Step 2:

[0350] The user requests project plan generation from the server via an open API through their device. The server automatically generates a plan based on the received contract and progress information and returns the plan data to the device. During this process, machine learning algorithms are used to efficiently handle scheduling.

[0351] Step 3:

[0352] As the user executes the plan, the server monitors the project's progress in real time. When progress data is sent to the server, the server analyzes the necessary progress information and notifies the terminal of the latest progress. If inconsistencies are detected at this time, the server also selects a corrective plan.

[0353] Step 4:

[0354] The server analyzes uncertainties within the project. Using generative AI models and comparing them to historical data, it identifies potential risks and sends alerts to stakeholders. This risk notification is delivered via email or push notification.

[0355] Step 5:

[0356] Users can access educational modules via their devices and efficiently acquire the necessary skills. The server sends the latest learning materials and progress test results to the devices and records the user's learning progress.

[0357] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0358] This invention proposes a new system construction that combines an emotion engine, with the aim of improving operational efficiency in anime production projects. This system aims to improve efficiency and employee satisfaction by recognizing the user's emotional state and flexibly adapting project management based on that state. It primarily involves a mechanism that interacts with three parties: the server, the terminal, and the user.

[0359] In this system's implementation, the user first uses a terminal to input project contract information. During this process, the emotion engine analyzes information such as the user's facial expressions, voice tone, and input speed. Based on this data, the emotion engine determines whether the user is stressed or calm, and provides appropriate feedback and support information based on that emotional state.

[0360] Next, during the process of the user entering requests from the owner, the emotion engine analyzes the user's emotions. Based on this information, the server can adjust how the requests are communicated. For example, if the user is feeling anxious, a confirmation message for the request will be added. The emotion engine also predicts how the communication of important requests will affect the user's emotions and manages to send notifications at the optimal time.

[0361] Furthermore, the emotion engine is also effective in task management as a project progresses. The server uses emotion data to customize task assignments and notification methods in a format that best suits the user's current mental state, thereby improving work efficiency. For example, if the emotion engine determines that the user is motivated, it will arrange to send a message of praise.

[0362] Finally, the training modules provided to production managers are customized using emotion engine data. Users can access content on their devices in a format optimized to their learning pace and current emotional state. This maximizes learning effectiveness and promotes employee skill development.

[0363] This system, which incorporates an emotion engine, enables project management that is sensitive to the user's emotions, thereby improving both operational efficiency and employee satisfaction.

[0364] The following describes the processing flow.

[0365] Step 1:

[0366] The user enters project contract information via a terminal. The emotion engine analyzes the user's facial expressions and tone of voice while they are entering information, and evaluates the user's emotional state in real time.

[0367] Step 2:

[0368] The device detects the user's emotional state and displays corresponding feedback on the screen. For example, if the user is feeling stressed, it might provide a message such as, "Relax and continue."

[0369] Step 3:

[0370] Based on the emotional data received from the emotion engine, the server re-verifies whether the contract details have been entered accurately and provides supplementary information about the automatically generated contract as needed.

[0371] Step 4:

[0372] The user enters the owner's request into the terminal. The emotion engine then re-analyzes the user's emotions at the time the request was entered.

[0373] Step 5:

[0374] The server adjusts the request notification method based on the analysis results. For example, if the user expresses concern, it may simplify the request notification or suggest additional verification procedures.

[0375] Step 6:

[0376] When the server sends notifications to staff regarding the owner's requests, it takes emotional data into consideration and presents the notification in the most acceptable format.

[0377] Step 7:

[0378] When managing project schedules, the server uses sentiment data to customize task assignments. For example, it assigns challenging tasks to highly motivated users.

[0379] Step 8:

[0380] Users report their progress via their devices. The emotion engine analyzes the emotional state at the time of reporting and sends the data to the server to consider subsequent actions.

[0381] Step 9:

[0382] Users take educational modules. During this process, the emotion engine tracks changes in emotions while learning and adjusts the content to optimize the learning pace and maintain motivation.

[0383] Step 10:

[0384] Based on the sentiment data collected so far, the server forms a feedback loop across the entire system to continuously optimize the user experience.

[0385] (Example 2)

[0386] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0387] In anime production projects, failing to consider the emotional state of participants during project management can easily lead to increased stress and decreased motivation, resulting in reduced work efficiency and employee satisfaction. Furthermore, the lack of feedback and training tailored to the individual emotional state of employees makes effective project management and skill development difficult.

[0388] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0389] In this invention, the server includes emotion analysis means for analyzing the emotional state of project participants and reflecting that information in project management; management means for adaptively adjusting project schedules and task notification methods based on emotional state; and education delivery means for customizing educational content for production staff using emotional data. This enables project management and education customization that takes into account the emotional state of participants, thereby improving work efficiency and employee satisfaction.

[0390] "Emotional analysis tools" are methods for analyzing the emotional states of project participants and incorporating that information into project management.

[0391] "Analysis means" refers to a method for receiving user input data and quantifying the emotional state using an emotion engine.

[0392] "Management measures" are means of adaptively adjusting project schedules and task notification methods based on emotional states.

[0393] "Educational delivery methods" refer to means of customizing educational content for production managers using emotional data.

[0394] "Information provision means" refers to methods for providing feedback and supplementary information according to the user's emotional state to support project management.

[0395] This system is designed to take into account the emotional states of participants in anime production projects and to achieve efficient project management. It primarily operates through collaboration between three parties: users, servers, and terminals.

[0396] First, the user uses a terminal to input project contract information and requests from the owner. The terminal has an emotion engine built in, which uses speech recognition and facial recognition technology to analyze the user's facial expressions, voice tone, input speed, etc., and identify their emotional state.

[0397] Next, the server optimizes project management based on the analyzed emotional state. The emotional analysis tool quantifies the user's stress level and motivation, and uses this information to adjust project schedules and task notification methods. In this process, it is possible to generate emotionally appropriate feedback and supportive information using a generative AI model.

[0398] Furthermore, educational content for production staff is also managed on the server side. The server utilizes emotional data and, through educational delivery methods, customizes and provides optimized educational modules tailored to the user's learning pace and current emotional state.

[0399] As a concrete example, if the emotion engine detects an increase in the user's stress level while they are entering contract information, the server will display input assistance messages or notifications prompting them to take a short break through the terminal. Another example of a prompt using a generative AI model is, "Generate an appropriate feedback message to provide if the user is feeling anxious."

[0400] This system, centered on sentiment analysis, makes project management more flexible and effective. A key feature of this system is its ability to achieve both improved operational efficiency and increased employee satisfaction.

[0401] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0402] Step 1:

[0403] The user enters project contract information using a terminal. The terminal retrieves the input data and sends it to the emotion engine. The input information includes the contract information itself, as well as data related to the user's facial expressions and voice tone. The terminal detects this data and prepares it to be sent to the server.

[0404] Step 2:

[0405] The server processes the data received from the terminal. First, it uses an emotion engine to analyze the user's emotional state. Specifically, it uses facial recognition and speech recognition technology to quantify whether the user is stressed or calm. The results of this analysis are recorded on the server as emotion data useful for project management.

[0406] Step 3:

[0407] The server adjusts project management methods based on emotional data. In this step, task scheduling and notification methods are customized based on emotional data. For example, if a user is stressed, notifications may be withheld or supplementary support messages added. This information is also fed into a generative AI model to generate appropriate feedback messages.

[0408] Step 4:

[0409] The generated feedback and adjusted task information are communicated to the user via the device. The device displays the information received from the server, allowing the user to take the next action accordingly. Specific actions include reviewing messages displayed on the screen and responding to them.

[0410] Step 5:

[0411] The server customizes the educational content. It uses emotional data to optimize educational modules for production managers. The server generates data based on the user's learning pace and emotional state, and uses this to individually adjust the educational content. Feedback and new learning tasks are provided to the user through the device.

[0412] This series of processes allows users to receive project management and training tailored to their emotional state. This improves work efficiency and employee satisfaction.

[0413] (Application Example 2)

[0414] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the smart glasses 214 as the "terminal".

[0415] The problem that this invention aims to solve is that uniform project management and work progress without considering the emotional state of workers in factories and other workplaces leads to a decrease in work efficiency and worker satisfaction. Furthermore, because methods for improving the work environment are uniform, it is difficult to respond to the motivation and stress levels of individual workers, which is another problem.

[0416] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0417] In this invention, the server includes an input device for inputting project contract information, a storage device for storing and managing generated contract documents, a generation device means for automatically generating contract documents, an emotion detection device for recognizing emotional states, an emotion adaptation device means for adapting project management based on emotions, and a device means for adjusting the operation of the device using emotion data. This enables flexible project management and work adjustments in accordance with the emotional state of workers, thereby improving work efficiency and worker motivation.

[0418] An "input device" is a device or system used by users to input contract information related to a project.

[0419] A "storage device" is a storage device used to store and manage generated contract documents and other data.

[0420] A "generation device" is a device or program that automatically creates contract documents based on input data.

[0421] A "communication device" is a device that uses communication technology to notify users of information and requests.

[0422] A "plan" is a framework or schedule for automatically generating the steps and schedules necessary for the progress of a project.

[0423] "Tasks" refer to the specific work or tasks assigned to individual team members within a project.

[0424] "Risk" refers to analyzing the risks and problems that may arise during the project's progress.

[0425] A "warning" is a message or notification intended to draw the attention of relevant parties to a detected hazard.

[0426] The term "educational program" refers to the learning content and training provided to production staff.

[0427] An "emotion detection device" is a device or system that analyzes facial expressions and voice data to recognize the emotional state of workers and other individuals.

[0428] An "emotional adaptation device" is a device or program used to optimize project management and work progress based on detected emotional data.

[0429] "Emotional data" refers to data that indicates the emotional state of workers and other personnel, and is used as information for project management.

[0430] A "device for adjusting operation" is a device or software that adjusts the operation of a machine or system in real time based on emotional data.

[0431] The system for carrying out this invention consists of an emotion detection device, an emotion adaptation device, an input device, a memory device, a generation device, a communication device, and a device for adjusting operation. Each of these devices is designed to interact with the user's terminal and the server.

[0432] The server uses an emotion detection device to analyze the worker's facial expressions and voice data in real time to recognize their emotional state. This emotional data is stored in memory, and a generation device automatically generates necessary instructions. The server also uses an emotion adaptation device to optimize project management and task progress based on the recognized emotional data. In this process, if a worker is experiencing stress, the system adjusts the pace of work and sends encouraging notifications to improve the work environment.

[0433] The user's terminal inputs contract information and owner requests related to the project via an input device and sends them to the server. The communication device notifies multiple personnel of the input information in real time, ensuring accurate information transmission.

[0434] For example, in a manufacturing plant, if an emotion detection device detects that a worker has been working for a long time and is fatigued, the server adjusts the machine's operating speed via a control device and sends a notification such as "You need a break." In this way, it is possible to reduce the burden on workers and provide an efficient work environment.

[0435] An example of a prompt message for the generating AI model could be: "Generate an effective support message for workers in a high-stress environment."

[0436] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0437] Step 1:

[0438] The server uses an emotion detection device to acquire the worker's facial expressions and voice data in real time. It receives raw data from cameras and microphones as input and feeds it into emotion analysis software. Data processing involves feature point extraction and voice frequency analysis to generate emotional state data. In this process, the server obtains an output that recognizes the emotional state (e.g., stress level, euphoria, etc.).

[0439] Step 2:

[0440] The server uses the obtained emotional state data to activate an emotional adaptation device, optimizing project management and task progress. It receives emotional state data as input and compares it with past data in a database to develop an optimization strategy suitable for the current work environment. For data processing, it uses an algorithm to adjust work progress with the aim of reducing worker stress, and generates an adjusted task schedule as output.

[0441] Step 3:

[0442] Users input project-related contract information and owner requests into a terminal via an input device. The input is received in text or multiple-choice format. The server receives this information and notifies project stakeholders using a communication device. The output consists of confirmed contract information and requests, which serve as fundamental data for project progress.

[0443] Step 4:

[0444] The server uses a device to adjust the operation of machines and systems dynamically based on emotional states. It uses emotional state data and work progress data as input to generate commands for operation adjustment. Specifically, it may issue instructions to reduce work speed when stress levels are high, and the output includes adjusted machine operation and suggestions for improving the work environment.

[0445] Step 5:

[0446] The user inputs an appropriate prompt sentence to a generative AI model, which automatically generates support messages tailored to the user's emotional state. The prompt sentence used as input is, "Generate an effective support message for workers in a high-stress environment." The server executes the generative AI model and provides the user with the generated support message as output.

[0447] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0448] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0449] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0450] [Third Embodiment]

[0451] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0452] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0453] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0454] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0455] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0456] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0457] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0458] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0459] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0460] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0461] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0462] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0463] This invention describes the construction of a system that streamlines project management in animation production and reduces the workload of animators. This system primarily involves three entities—a server, terminals, and users—working in coordination with each other, with the aim of sequentially and efficiently performing contract management, progress management, risk notification, and educational support.

[0464] First, users use a terminal to input project-related contract information. This information includes working conditions, responsibilities, and compensation. The entered information is collected by the server, and a contract is automatically generated based on a contract generation template. This reduces manual work in contract management and enables efficient management.

[0465] Next, the user inputs requests from the owner via a terminal during the production process. The server then stores these requests in a database and notifies the relevant staff of any changes or new requests according to established rules. This ensures that necessary information is quickly and accurately conveyed to the animators, reducing errors and wasted time.

[0466] Furthermore, the server automatically generates a schedule for the entire project and assigns tasks based on it. Progress is monitored in real time, and timely updates are provided to stakeholders. This includes reminder notifications if a task is behind schedule. A specific example is the function that automatically sends reminder emails to animators as deadlines approach.

[0467] In project risk management, the server analyzes progress logs to identify potential risk factors. If potential malfunctions or delays are detected, it sends alerts to stakeholders to support the smooth progress of the project. Specific examples include automatically suggesting alternative plans if resource shortages or schedule conflicts are found.

[0468] Furthermore, users can access educational modules from their devices. This allows production managers to enhance the necessary skills and improve the efficiency of project management. Specific examples include materials on streamlining task management, enabling users to gain experience through repeated learning.

[0469] In summary, this system contributes to solving a wide range of problems in anime production, achieving smoother production progress and reducing the workload of animators.

[0470] The following describes the processing flow.

[0471] Step 1:

[0472] The user enters the project-related contract terms via their device. These terms include scope of work, compensation, and deadlines.

[0473] Step 2:

[0474] The terminal processes the entered contract information as digital data and sends it to the server.

[0475] Step 3:

[0476] The server automatically generates a contract template based on the received contract information and saves the generated contract to the database.

[0477] Step 4:

[0478] The user enters requests from the owner into the terminal. These requests may concern new designs or changes to specific scenes.

[0479] Step 5:

[0480] The terminal sends the entered request to the server and instructs it to save the information to the database.

[0481] Step 6:

[0482] The server notifies the relevant animator staff of requests stored in the database and provides a reply function if confirmation is required.

[0483] Step 7:

[0484] The server performs calculations based on past project data and configured task durations to automatically generate the overall project schedule.

[0485] Step 8:

[0486] The server assigns each task to animators according to a calculated schedule and notifies them of the assignment details via their terminals.

[0487] Step 9:

[0488] Users use a terminal to input the completion status of their assigned tasks and report progress data to the server.

[0489] Step 10:

[0490] The server analyzes the reported progress data and generates an alert to notify relevant parties if there are any problems with the progress.

[0491] Step 11:

[0492] The server automatically performs a risk analysis and sends notifications suggesting necessary countermeasures if potential risks exist in an ongoing project.

[0493] Step 12:

[0494] Users access educational modules through their devices to learn the knowledge and skills necessary for production management. This information is used for self-improvement and skill development purposes.

[0495] (Example 1)

[0496] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0497] In animation production project management, managing contract details, real-time monitoring of progress, rapid information sharing, and early detection and response to project risks are crucial. However, relying solely on manual processes and individual management can easily lead to errors, decreased work efficiency, and delays in information transmission. This increases the workload on animators and managers, resulting in project delays and a decline in quality. Furthermore, the lack of educational resources to support the technical skill development of production managers also poses a problem for long-term project execution. These challenges need to be addressed efficiently.

[0498] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0499] In this invention, the server includes means for storing project contract details in a storage device and automatically generating contract documents, means for storing the client's work requests in a recording device and notifying relevant parties, and means for automatically generating project plans and monitoring and notifying progress in real time. This enables more efficient project management, rapid information dissemination, early detection of risks, and provision of training for skill improvement.

[0500] A "project" refers to a set of activities or tasks planned to achieve a specific goal.

[0501] "Contract terms" refers to the formal agreements regarding the project, including conditions, responsibilities, and compensation.

[0502] A "terminal device" refers to an electronic device used by a user to input data and interact with a system.

[0503] A "storage device" refers to a physical or logical device used to store data within a system.

[0504] A "server processing unit" refers to a central control unit that processes, stores, receives, and manages data.

[0505] The term "client" refers to the person or organization that directs the specific content or changes to the project.

[0506] "Work requirements" refer to the specific wishes and instructions for a project provided by the client.

[0507] A "communication device" refers to a device used to send and receive information both within and outside a system.

[0508] An "activity plan" refers to the overall plan that includes details of tasks and schedules created to manage the progress of a project.

[0509] "Control device" refers to the equipment and software within a system used for various management and control functions of a project.

[0510] "Participants" refers to the staff and individuals involved in the progress of the project.

[0511] A "monitoring and control system" refers to a device that monitors the progress of a project and makes adjustments as needed.

[0512] An "analysis device" refers to a device used to analyze data and identify potential problems or risks.

[0513] An "educational support device" refers to a device or software that provides educational content to improve the user's skills.

[0514] "Skill improvement materials" refer to learning materials and content designed to improve the skills of production managers and staff.

[0515] The system for implementing this invention mainly consists of three components: a server, a terminal, and a user. Its purpose is to streamline project management in animation production and reduce the workload of animators.

[0516] First, the user enters the project contract details using a terminal. This terminal is a hardware device equipped with a specialized interface, designed to allow users to intuitively input data. The information entered by the user is sent from the terminal to the server. Upon receiving it, the server stores it in a secure storage device. This storage device utilizes a database management system, allowing for efficient management of stored information and retrieval as needed. Simultaneously, the server automatically generates the contract document. For this purpose, a generation AI model is used, and an automatic conversion program documents the contract details according to the format.

[0517] Furthermore, users input work requests from clients via a terminal. This is also processed on the terminal, and the data is immediately transmitted to the server. The server processes this data and utilizes communication devices to send notifications to the relevant personnel. This system is also designed to ensure that information is shared with all parties involved in real time.

[0518] The server also automatically generates a project activity plan and monitors its progress. This plan is created by the system, and tasks are assigned to each participant. Project progress is monitored in real time, and progress notifications and reminders are sent as needed.

[0519] Furthermore, the server uses analysis equipment to analyze potential risk factors that may arise during the project's progress. If malfunctions or delays are detected, alerts are issued to the relevant parties. This allows problems to be addressed before they become major obstacles.

[0520] Furthermore, production managers can access educational support devices from their terminals. These devices provide learning materials to improve users' skills and are configured to enhance learning effectiveness with a user-friendly interface.

[0521] As a concrete example, a possible prompt statement might be, "Please tell me what kind of contract management system should be designed to reduce the workload of animators." Based on this prompt statement, the generating AI model assists in designing the contract management system and executes a process to transform the information. This ensures that the entire system operates efficiently and effectively.

[0522] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0523] Step 1:

[0524] The user uses a terminal to input project contract details. These details include working conditions, responsibilities, and compensation. The entered data is temporarily processed within the terminal and organized according to a specified format. The terminal then sends the organized data to the server. The output is formatted contract information.

[0525] Step 2:

[0526] The server stores the contract information received from the terminal in a database. During storage, a generation AI model is used to format the content based on a contract document template, automatically generating the contract document. The output is the formatted contract document.

[0527] Step 3:

[0528] The user enters project work requests using a terminal. The entered requests are converted into a data format by the terminal and sent to the server. The converted work requests are then output.

[0529] Step 4:

[0530] The server stores the work request in a database and sends notifications to the relevant personnel. The server uses a notification communication device to send the request details to the relevant parties. This process enables rapid and accurate information sharing. The output is a notification message.

[0531] Step 5:

[0532] The server automatically generates a project activity plan. It utilizes a generative AI model, learned from past project data and work requests, to create an optimized plan. The plan is assigned to each participant and notified via their terminal. The output includes a detailed activity plan and a list of assigned personnel.

[0533] Step 6:

[0534] The server monitors project progress in real time and analyzes progress data. During monitoring, it sends reminders to tasks that are behind schedule. Progress data is reported to stakeholders via terminals. The output is a progress report.

[0535] Step 7:

[0536] The server analyzes project progress logs and identifies risk factors. Using the analysis system, if a risk is detected, it issues a warning to relevant parties and notifies them of countermeasures. The output includes a risk alert and suggested countermeasures.

[0537] Step 8:

[0538] Users access educational support devices via a terminal and utilize skill-building materials. These materials are provided in an interactive format to support user learning. The output is learning outcomes and improved skills.

[0539] (Application Example 1)

[0540] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0541] In today's highly developed and diversified manufacturing environments, there is a growing need to improve the operational efficiency of robots and minimize errors and delays. However, conventional management systems often rely on manual processes for robot operation contracts and scheduling, making efficient information transfer and early detection of anomalies difficult.

[0542] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0543] In this invention, the server includes an input / output device for inputting project contract information, a data structure for storing and managing the generated contract, a generation device for automatically generating the contract, a device for inputting requests from the client and saving those requests in the data structure, a communication device for notifying the client of the information, and a device for automatically generating a project plan and monitoring and notifying the client of its progress in real time. This enables more efficient management of robot operations and a rapid response to unforeseen circumstances.

[0544] An "input / output device" is an interface for users to input information and an interface for systems to output information.

[0545] A "data structure" is a collection of data organized to efficiently store and manage information.

[0546] A "generation device" is a device that has the function of automatically creating documents or information based on a specific format.

[0547] A "communication device" is a device that implements technologies for sending and receiving information between various devices inside and outside a system.

[0548] A "plan" is a schedule that shows the chronological arrangement of activities within a project.

[0549] "Progress" is an indicator that shows the extent to which activities based on the plan are being carried out.

[0550] "Mobile terminal" refers to a portable communication device, mainly including smartphones.

[0551] "Uncertainty" refers to unstable factors or events that may occur in the future, and is synonymous with risk.

[0552] The system based on this invention is constructed using a combination of multiple hardware and software components. The system consists of a server, terminals (e.g., smartphones and tablets), and users. The system is primarily operated in the following manner:

[0553] The user first inputs project-related contract information through the terminal's input / output device. This input information is then formatted based on a pre-programmed template and stored in the server's data structure. This standardizes contract information and enables consistent data management.

[0554] Next, the user communicates with the server via an open API to automatically generate a project plan. The server monitors the project's progress in real time and sends notifications to the user's device based on the progress. This utilizes a cloud-based database and a progress analysis engine equipped with machine learning algorithms.

[0555] Furthermore, the server detects uncertainties within the project and sends alerts to stakeholders. Here, it is possible to predict potential risks from historical data using generative AI models.

[0556] Furthermore, new robot operators can easily acquire the necessary knowledge because they can access educational modules through their devices. This provides users with the opportunity to efficiently improve their skills through self-study.

[0557] As a concrete example, one manufacturing plant uses a smartphone app to manage daily robot operations. Furthermore, examples of supported prompts include instructions such as, "Please describe a system that monitors the progress of robot management in the factory in real time and sends immediate alerts to address any abnormalities."

[0558] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0559] Step 1:

[0560] The user uses a terminal to enter project contract information. The entered information is formatted according to a standardized template and sent to the server. The server stores this data in a data structure and prepares it for contract generation.

[0561] Step 2:

[0562] The user requests project plan generation from the server via an open API through their device. The server automatically generates a plan based on the received contract and progress information and returns the plan data to the device. During this process, machine learning algorithms are used to efficiently handle scheduling.

[0563] Step 3:

[0564] As the user executes the plan, the server monitors the project's progress in real time. When progress data is sent to the server, the server analyzes the necessary progress information and notifies the terminal of the latest progress. If inconsistencies are detected at this time, the server also selects a corrective plan.

[0565] Step 4:

[0566] The server analyzes uncertainties within the project. Using generative AI models and comparing them to historical data, it identifies potential risks and sends alerts to stakeholders. This risk notification is delivered via email or push notification.

[0567] Step 5:

[0568] Users can access educational modules via their devices and efficiently acquire the necessary skills. The server sends the latest learning materials and progress test results to the devices and records the user's learning progress.

[0569] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0570] This invention proposes a new system construction that combines an emotion engine, with the aim of improving operational efficiency in anime production projects. This system aims to improve efficiency and employee satisfaction by recognizing the user's emotional state and flexibly adapting project management based on that state. It primarily involves a mechanism that interacts with three parties: the server, the terminal, and the user.

[0571] In this system's implementation, the user first uses a terminal to input project contract information. During this process, the emotion engine analyzes information such as the user's facial expressions, voice tone, and input speed. Based on this data, the emotion engine determines whether the user is stressed or calm, and provides appropriate feedback and support information based on that emotional state.

[0572] Next, during the process of the user entering requests from the owner, the emotion engine analyzes the user's emotions. Based on this information, the server can adjust how the requests are communicated. For example, if the user is feeling anxious, a confirmation message for the request will be added. The emotion engine also predicts how the communication of important requests will affect the user's emotions and manages to send notifications at the optimal time.

[0573] Furthermore, the emotion engine is also effective in task management as a project progresses. The server uses emotion data to customize task assignments and notification methods in a format that best suits the user's current mental state, thereby improving work efficiency. For example, if the emotion engine determines that the user is motivated, it will arrange to send a message of praise.

[0574] Finally, the training modules provided to production managers are customized using emotion engine data. Users can access content on their devices in a format optimized to their learning pace and current emotional state. This maximizes learning effectiveness and promotes employee skill development.

[0575] This system, which incorporates an emotion engine, enables project management that is sensitive to the user's emotions, thereby improving both operational efficiency and employee satisfaction.

[0576] The following describes the processing flow.

[0577] Step 1:

[0578] The user enters project contract information via a terminal. The emotion engine analyzes the user's facial expressions and tone of voice while they are entering information, and evaluates the user's emotional state in real time.

[0579] Step 2:

[0580] The device detects the user's emotional state and displays corresponding feedback on the screen. For example, if the user is feeling stressed, it might provide a message such as, "Relax and continue."

[0581] Step 3:

[0582] Based on the emotional data received from the emotion engine, the server re-verifies whether the contract details have been entered accurately and provides supplementary information about the automatically generated contract as needed.

[0583] Step 4:

[0584] The user enters the owner's request into the terminal. The emotion engine then re-analyzes the user's emotions at the time the request was entered.

[0585] Step 5:

[0586] The server adjusts the request notification method based on the analysis results. For example, if the user expresses concern, it may simplify the request notification or suggest additional verification procedures.

[0587] Step 6:

[0588] When the server sends notifications to staff regarding the owner's requests, it takes emotional data into consideration and presents the notification in the most acceptable format.

[0589] Step 7:

[0590] When managing project schedules, the server uses sentiment data to customize task assignments. For example, it assigns challenging tasks to highly motivated users.

[0591] Step 8:

[0592] Users report their progress via their devices. The emotion engine analyzes the emotional state at the time of reporting and sends the data to the server to consider subsequent actions.

[0593] Step 9:

[0594] Users take educational modules. During this process, the emotion engine tracks changes in emotions while learning and adjusts the content to optimize the learning pace and maintain motivation.

[0595] Step 10:

[0596] Based on the sentiment data collected so far, the server forms a feedback loop across the entire system to continuously optimize the user experience.

[0597] (Example 2)

[0598] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0599] In anime production projects, failing to consider the emotional state of participants during project management can easily lead to increased stress and decreased motivation, resulting in reduced work efficiency and employee satisfaction. Furthermore, the lack of feedback and training tailored to the individual emotional state of employees makes effective project management and skill development difficult.

[0600] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0601] In this invention, the server includes emotion analysis means for analyzing the emotional state of project participants and reflecting that information in project management; management means for adaptively adjusting project schedules and task notification methods based on emotional state; and education delivery means for customizing educational content for production staff using emotional data. This enables project management and education customization that takes into account the emotional state of participants, thereby improving work efficiency and employee satisfaction.

[0602] "Emotional analysis tools" are methods for analyzing the emotional states of project participants and incorporating that information into project management.

[0603] "Analysis means" refers to a method for receiving user input data and quantifying the emotional state using an emotion engine.

[0604] "Management measures" are means of adaptively adjusting project schedules and task notification methods based on emotional states.

[0605] "Educational delivery methods" refer to means of customizing educational content for production managers using emotional data.

[0606] "Information provision means" refers to methods for providing feedback and supplementary information according to the user's emotional state to support project management.

[0607] This system is designed to take into account the emotional states of participants in anime production projects and to achieve efficient project management. It primarily operates through collaboration between three parties: users, servers, and terminals.

[0608] First, the user uses a terminal to input project contract information and requests from the owner. The terminal has an emotion engine built in, which uses speech recognition and facial recognition technology to analyze the user's facial expressions, voice tone, input speed, etc., and identify their emotional state.

[0609] Next, the server optimizes project management based on the analyzed emotional state. The emotional analysis tool quantifies the user's stress level and motivation, and uses this information to adjust project schedules and task notification methods. In this process, it is possible to generate emotionally appropriate feedback and supportive information using a generative AI model.

[0610] Furthermore, educational content for production staff is also managed on the server side. The server utilizes emotional data and, through educational delivery methods, customizes and provides optimized educational modules tailored to the user's learning pace and current emotional state.

[0611] As a concrete example, if the emotion engine detects an increase in the user's stress level while they are entering contract information, the server will display input assistance messages or notifications prompting them to take a short break through the terminal. Another example of a prompt using a generative AI model is, "Generate an appropriate feedback message to provide if the user is feeling anxious."

[0612] This system, centered on sentiment analysis, makes project management more flexible and effective. A key feature of this system is its ability to achieve both improved operational efficiency and increased employee satisfaction.

[0613] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0614] Step 1:

[0615] The user enters project contract information using a terminal. The terminal retrieves the input data and sends it to the emotion engine. The input information includes the contract information itself, as well as data related to the user's facial expressions and voice tone. The terminal detects this data and prepares it to be sent to the server.

[0616] Step 2:

[0617] The server processes the data received from the terminal. First, it uses an emotion engine to analyze the user's emotional state. Specifically, it uses facial recognition and speech recognition technology to quantify whether the user is stressed or calm. The results of this analysis are recorded on the server as emotion data useful for project management.

[0618] Step 3:

[0619] The server adjusts project management methods based on emotional data. In this step, task scheduling and notification methods are customized based on emotional data. For example, if a user is stressed, notifications may be withheld or supplementary support messages added. This information is also fed into a generative AI model to generate appropriate feedback messages.

[0620] Step 4:

[0621] The generated feedback and adjusted task information are communicated to the user via the device. The device displays the information received from the server, allowing the user to take the next action accordingly. Specific actions include reviewing messages displayed on the screen and responding to them.

[0622] Step 5:

[0623] The server customizes the educational content. It uses emotional data to optimize educational modules for production managers. The server generates data based on the user's learning pace and emotional state, and uses this to individually adjust the educational content. Feedback and new learning tasks are provided to the user through the device.

[0624] This series of processes allows users to receive project management and training tailored to their emotional state. This improves work efficiency and employee satisfaction.

[0625] (Application Example 2)

[0626] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0627] The problem that this invention aims to solve is that uniform project management and work progress without considering the emotional state of workers in factories and other workplaces leads to a decrease in work efficiency and worker satisfaction. Furthermore, because methods for improving the work environment are uniform, it is difficult to respond to the motivation and stress levels of individual workers, which is another problem.

[0628] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0629] In this invention, the server includes an input device for inputting project contract information, a storage device for storing and managing generated contract documents, a generation device means for automatically generating contract documents, an emotion detection device for recognizing emotional states, an emotion adaptation device means for adapting project management based on emotions, and a device means for adjusting the operation of the device using emotion data. This enables flexible project management and work adjustments in accordance with the emotional state of workers, thereby improving work efficiency and worker motivation.

[0630] An "input device" is a device or system used by users to input contract information related to a project.

[0631] A "storage device" is a storage device used to store and manage generated contract documents and other data.

[0632] A "generation device" is a device or program that automatically creates contract documents based on input data.

[0633] A "communication device" is a device that uses communication technology to notify users of information and requests.

[0634] A "plan" is a framework or schedule for automatically generating the steps and schedules necessary for the progress of a project.

[0635] "Tasks" refer to the specific work or tasks assigned to individual team members within a project.

[0636] "Risk" refers to analyzing the risks and problems that may arise during the project's progress.

[0637] A "warning" is a message or notification intended to draw the attention of relevant parties to a detected hazard.

[0638] The term "educational program" refers to the learning content and training provided to production staff.

[0639] An "emotion detection device" is a device or system that analyzes facial expressions and voice data to recognize the emotional state of workers and other individuals.

[0640] An "emotional adaptation device" is a device or program used to optimize project management and work progress based on detected emotional data.

[0641] "Emotional data" refers to data that indicates the emotional state of workers and other personnel, and is used as information for project management.

[0642] A "device for adjusting operation" is a device or software that adjusts the operation of a machine or system in real time based on emotional data.

[0643] The system for carrying out this invention consists of an emotion detection device, an emotion adaptation device, an input device, a memory device, a generation device, a communication device, and a device for adjusting operation. Each of these devices is designed to interact with the user's terminal and the server.

[0644] The server uses an emotion detection device to analyze the worker's facial expressions and voice data in real time to recognize their emotional state. This emotional data is stored in memory, and a generation device automatically generates necessary instructions. The server also uses an emotion adaptation device to optimize project management and task progress based on the recognized emotional data. In this process, if a worker is experiencing stress, the system adjusts the pace of work and sends encouraging notifications to improve the work environment.

[0645] The user's terminal inputs contract information and owner requests related to the project via an input device and sends them to the server. The communication device notifies multiple personnel of the input information in real time, ensuring accurate information transmission.

[0646] For example, in a manufacturing plant, if an emotion detection device detects that a worker has been working for a long time and is fatigued, the server adjusts the machine's operating speed via a control device and sends a notification such as "You need a break." In this way, it is possible to reduce the burden on workers and provide an efficient work environment.

[0647] An example of a prompt message for the generating AI model could be: "Generate an effective support message for workers in a high-stress environment."

[0648] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0649] Step 1:

[0650] The server uses an emotion detection device to acquire the worker's facial expressions and voice data in real time. It receives raw data from cameras and microphones as input and feeds it into emotion analysis software. Data processing involves feature point extraction and voice frequency analysis to generate emotional state data. In this process, the server obtains an output that recognizes the emotional state (e.g., stress level, euphoria, etc.).

[0651] Step 2:

[0652] The server uses the obtained emotional state data to activate an emotional adaptation device, optimizing project management and task progress. It receives emotional state data as input and compares it with past data in a database to develop an optimization strategy suitable for the current work environment. For data processing, it uses an algorithm to adjust work progress with the aim of reducing worker stress, and generates an adjusted task schedule as output.

[0653] Step 3:

[0654] Users input project-related contract information and owner requests into a terminal via an input device. The input is received in text or multiple-choice format. The server receives this information and notifies project stakeholders using a communication device. The output consists of confirmed contract information and requests, which serve as fundamental data for project progress.

[0655] Step 4:

[0656] The server uses a device to adjust the operation of machines and systems dynamically based on emotional states. It uses emotional state data and work progress data as input to generate commands for operation adjustment. Specifically, it may issue instructions to reduce work speed when stress levels are high, and the output includes adjusted machine operation and suggestions for improving the work environment.

[0657] Step 5:

[0658] The user inputs an appropriate prompt sentence to a generative AI model, which automatically generates support messages tailored to the user's emotional state. The prompt sentence used as input is, "Generate an effective support message for workers in a high-stress environment." The server executes the generative AI model and provides the user with the generated support message as output.

[0659] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0660] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0661] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0662] [Fourth Embodiment]

[0663] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0664] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0665] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0666] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0667] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0668] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0669] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0670] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0671] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0672] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0673] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0674] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0675] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0676] This invention describes the construction of a system that streamlines project management in animation production and reduces the workload of animators. This system primarily involves three entities—a server, terminals, and users—working in coordination with each other, with the aim of sequentially and efficiently performing contract management, progress management, risk notification, and educational support.

[0677] First, users use a terminal to input project-related contract information. This information includes working conditions, responsibilities, and compensation. The entered information is collected by the server, and a contract is automatically generated based on a contract generation template. This reduces manual work in contract management and enables efficient management.

[0678] Next, the user inputs requests from the owner via a terminal during the production process. The server then stores these requests in a database and notifies the relevant staff of any changes or new requests according to established rules. This ensures that necessary information is quickly and accurately conveyed to the animators, reducing errors and wasted time.

[0679] Furthermore, the server automatically generates a schedule for the entire project and assigns tasks based on it. Progress is monitored in real time, and timely updates are provided to stakeholders. This includes reminder notifications if a task is behind schedule. A specific example is the function that automatically sends reminder emails to animators as deadlines approach.

[0680] In project risk management, the server analyzes progress logs to identify potential risk factors. If potential malfunctions or delays are detected, it sends alerts to stakeholders to support the smooth progress of the project. Specific examples include automatically suggesting alternative plans if resource shortages or schedule conflicts are found.

[0681] Furthermore, users can access educational modules from their devices. This allows production managers to enhance the necessary skills and improve the efficiency of project management. Specific examples include materials on streamlining task management, enabling users to gain experience through repeated learning.

[0682] In summary, this system contributes to solving a wide range of problems in anime production, achieving smoother production progress and reducing the workload of animators.

[0683] The following describes the processing flow.

[0684] Step 1:

[0685] The user enters the project-related contract terms via their device. These terms include scope of work, compensation, and deadlines.

[0686] Step 2:

[0687] The terminal processes the entered contract information as digital data and sends it to the server.

[0688] Step 3:

[0689] The server automatically generates a contract template based on the received contract information and saves the generated contract to the database.

[0690] Step 4:

[0691] The user enters requests from the owner into the terminal. These requests may concern new designs or changes to specific scenes.

[0692] Step 5:

[0693] The terminal sends the entered request to the server and instructs it to save the information to the database.

[0694] Step 6:

[0695] The server notifies the relevant animator staff of requests stored in the database and provides a reply function if confirmation is required.

[0696] Step 7:

[0697] The server performs calculations based on past project data and configured task durations to automatically generate the overall project schedule.

[0698] Step 8:

[0699] The server assigns each task to animators according to a calculated schedule and notifies them of the assignment details via their terminals.

[0700] Step 9:

[0701] Users use a terminal to input the completion status of their assigned tasks and report progress data to the server.

[0702] Step 10:

[0703] The server analyzes the reported progress data and generates an alert to notify relevant parties if there are any problems with the progress.

[0704] Step 11:

[0705] The server automatically performs a risk analysis and sends notifications suggesting necessary countermeasures if potential risks exist in an ongoing project.

[0706] Step 12:

[0707] Users access educational modules through their devices to learn the knowledge and skills necessary for production management. This information is used for self-improvement and skill development purposes.

[0708] (Example 1)

[0709] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0710] In animation production project management, managing contract details, real-time monitoring of progress, rapid information sharing, and early detection and response to project risks are crucial. However, relying solely on manual processes and individual management can easily lead to errors, decreased work efficiency, and delays in information transmission. This increases the workload on animators and managers, resulting in project delays and a decline in quality. Furthermore, the lack of educational resources to support the technical skill development of production managers also poses a problem for long-term project execution. These challenges need to be addressed efficiently.

[0711] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0712] In this invention, the server includes means for storing project contract details in a storage device and automatically generating contract documents, means for storing the client's work requests in a recording device and notifying relevant parties, and means for automatically generating project plans and monitoring and notifying progress in real time. This enables more efficient project management, rapid information dissemination, early detection of risks, and provision of training for skill improvement.

[0713] A "project" refers to a set of activities or tasks planned to achieve a specific goal.

[0714] "Contract terms" refers to the formal agreements regarding the project, including conditions, responsibilities, and compensation.

[0715] A "terminal device" refers to an electronic device used by a user to input data and interact with a system.

[0716] A "storage device" refers to a physical or logical device used to store data within a system.

[0717] A "server processing unit" refers to a central control unit that processes, stores, receives, and manages data.

[0718] The term "client" refers to the person or organization that directs the specific content or changes to the project.

[0719] "Work requirements" refer to the specific wishes and instructions for a project provided by the client.

[0720] A "communication device" refers to a device used to send and receive information both within and outside a system.

[0721] An "activity plan" refers to the overall plan that includes details of tasks and schedules created to manage the progress of a project.

[0722] "Control device" refers to the equipment and software within a system used for various management and control functions of a project.

[0723] "Participants" refers to the staff and individuals involved in the progress of the project.

[0724] A "monitoring and control system" refers to a device that monitors the progress of a project and makes adjustments as needed.

[0725] An "analysis device" refers to a device used to analyze data and identify potential problems or risks.

[0726] An "educational support device" refers to a device or software that provides educational content to improve the user's skills.

[0727] "Skill improvement materials" refer to learning materials and content designed to improve the skills of production managers and staff.

[0728] The system for implementing this invention mainly consists of three components: a server, a terminal, and a user. Its purpose is to streamline project management in animation production and reduce the workload of animators.

[0729] First, the user enters the project contract details using a terminal. This terminal is a hardware device equipped with a specialized interface, designed to allow users to intuitively input data. The information entered by the user is sent from the terminal to the server. Upon receiving it, the server stores it in a secure storage device. This storage device utilizes a database management system, allowing for efficient management of stored information and retrieval as needed. Simultaneously, the server automatically generates the contract document. For this purpose, a generation AI model is used, and an automatic conversion program documents the contract details according to the format.

[0730] Furthermore, users input work requests from clients via a terminal. This is also processed on the terminal, and the data is immediately transmitted to the server. The server processes this data and utilizes communication devices to send notifications to the relevant personnel. This system is also designed to ensure that information is shared with all parties involved in real time.

[0731] The server also automatically generates a project activity plan and monitors its progress. This plan is created by the system, and tasks are assigned to each participant. Project progress is monitored in real time, and progress notifications and reminders are sent as needed.

[0732] Furthermore, the server uses analysis equipment to analyze potential risk factors that may arise during the project's progress. If malfunctions or delays are detected, alerts are issued to the relevant parties. This allows problems to be addressed before they become major obstacles.

[0733] Furthermore, production managers can access educational support devices from their terminals. These devices provide learning materials to improve users' skills and are configured to enhance learning effectiveness with a user-friendly interface.

[0734] As a concrete example, a possible prompt statement might be, "Please tell me what kind of contract management system should be designed to reduce the workload of animators." Based on this prompt statement, the generating AI model assists in designing the contract management system and executes a process to transform the information. This ensures that the entire system operates efficiently and effectively.

[0735] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0736] Step 1:

[0737] The user uses a terminal to input project contract details. These details include working conditions, responsibilities, and compensation. The entered data is temporarily processed within the terminal and organized according to a specified format. The terminal then sends the organized data to the server. The output is formatted contract information.

[0738] Step 2:

[0739] The server stores the contract information received from the terminal in a database. During storage, a generation AI model is used to format the content based on a contract document template, automatically generating the contract document. The output is the formatted contract document.

[0740] Step 3:

[0741] The user enters project work requests using a terminal. The entered requests are converted into a data format by the terminal and sent to the server. The converted work requests are then output.

[0742] Step 4:

[0743] The server stores the work request in a database and sends notifications to the relevant personnel. The server uses a notification communication device to send the request details to the relevant parties. This process enables rapid and accurate information sharing. The output is a notification message.

[0744] Step 5:

[0745] The server automatically generates a project activity plan. It utilizes a generative AI model, learned from past project data and work requests, to create an optimized plan. The plan is assigned to each participant and notified via their terminal. The output includes a detailed activity plan and a list of assigned personnel.

[0746] Step 6:

[0747] The server monitors project progress in real time and analyzes progress data. During monitoring, it sends reminders to tasks that are behind schedule. Progress data is reported to stakeholders via terminals. The output is a progress report.

[0748] Step 7:

[0749] The server analyzes project progress logs and identifies risk factors. Using the analysis system, if a risk is detected, it issues a warning to relevant parties and notifies them of countermeasures. The output includes a risk alert and suggested countermeasures.

[0750] Step 8:

[0751] Users access educational support devices via a terminal and utilize skill-building materials. These materials are provided in an interactive format to support user learning. The output is learning outcomes and improved skills.

[0752] (Application Example 1)

[0753] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0754] In today's highly developed and diversified manufacturing environments, there is a growing need to improve the operational efficiency of robots and minimize errors and delays. However, conventional management systems often rely on manual processes for robot operation contracts and scheduling, making efficient information transfer and early detection of anomalies difficult.

[0755] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0756] In this invention, the server includes an input / output device for inputting project contract information, a data structure for storing and managing the generated contract, a generation device for automatically generating the contract, a device for inputting requests from the client and saving those requests in the data structure, a communication device for notifying the client of the information, and a device for automatically generating a project plan and monitoring and notifying the client of its progress in real time. This enables more efficient management of robot operations and a rapid response to unforeseen circumstances.

[0757] An "input / output device" is an interface for users to input information and an interface for systems to output information.

[0758] A "data structure" is a collection of data organized to efficiently store and manage information.

[0759] A "generation device" is a device that has the function of automatically creating documents or information based on a specific format.

[0760] A "communication device" is a device that implements technologies for sending and receiving information between various devices inside and outside a system.

[0761] A "plan" is a schedule that shows the chronological arrangement of activities within a project.

[0762] "Progress" is an indicator that shows the extent to which activities based on the plan are being carried out.

[0763] "Mobile terminal" refers to a portable communication device, mainly including smartphones.

[0764] "Uncertainty" refers to unstable factors or events that may occur in the future, and is synonymous with risk.

[0765] The system based on this invention is constructed using a combination of multiple hardware and software components. The system consists of a server, terminals (e.g., smartphones and tablets), and users. The system is primarily operated in the following manner:

[0766] The user first inputs project-related contract information through the terminal's input / output device. This input information is then formatted based on a pre-programmed template and stored in the server's data structure. This standardizes contract information and enables consistent data management.

[0767] Next, the user communicates with the server via an open API to automatically generate a project plan. The server monitors the project's progress in real time and sends notifications to the user's device based on the progress. This utilizes a cloud-based database and a progress analysis engine equipped with machine learning algorithms.

[0768] Furthermore, the server detects uncertainties within the project and sends alerts to stakeholders. Here, it is possible to predict potential risks from historical data using generative AI models.

[0769] Furthermore, new robot operators can easily acquire the necessary knowledge because they can access educational modules through their devices. This provides users with the opportunity to efficiently improve their skills through self-study.

[0770] As a concrete example, one manufacturing plant uses a smartphone app to manage daily robot operations. Furthermore, examples of supported prompts include instructions such as, "Please describe a system that monitors the progress of robot management in the factory in real time and sends immediate alerts to address any abnormalities."

[0771] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0772] Step 1:

[0773] The user uses a terminal to enter project contract information. The entered information is formatted according to a standardized template and sent to the server. The server stores this data in a data structure and prepares it for contract generation.

[0774] Step 2:

[0775] The user requests project plan generation from the server via an open API through their device. The server automatically generates a plan based on the received contract and progress information and returns the plan data to the device. During this process, machine learning algorithms are used to efficiently handle scheduling.

[0776] Step 3:

[0777] As the user executes the plan, the server monitors the project's progress in real time. When progress data is sent to the server, the server analyzes the necessary progress information and notifies the terminal of the latest progress. If inconsistencies are detected at this time, the server also selects a corrective plan.

[0778] Step 4:

[0779] The server analyzes uncertainties within the project. Using generative AI models and comparing them to historical data, it identifies potential risks and sends alerts to stakeholders. This risk notification is delivered via email or push notification.

[0780] Step 5:

[0781] Users can access educational modules via their devices and efficiently acquire the necessary skills. The server sends the latest learning materials and progress test results to the devices and records the user's learning progress.

[0782] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0783] This invention proposes a new system construction that combines an emotion engine, with the aim of improving operational efficiency in anime production projects. This system aims to improve efficiency and employee satisfaction by recognizing the user's emotional state and flexibly adapting project management based on that state. It primarily involves a mechanism that interacts with three parties: the server, the terminal, and the user.

[0784] In this system's implementation, the user first uses a terminal to input project contract information. During this process, the emotion engine analyzes information such as the user's facial expressions, voice tone, and input speed. Based on this data, the emotion engine determines whether the user is stressed or calm, and provides appropriate feedback and support information based on that emotional state.

[0785] Next, during the process of the user entering requests from the owner, the emotion engine analyzes the user's emotions. Based on this information, the server can adjust how the requests are communicated. For example, if the user is feeling anxious, a confirmation message for the request will be added. The emotion engine also predicts how the communication of important requests will affect the user's emotions and manages to send notifications at the optimal time.

[0786] Furthermore, the emotion engine is also effective in task management as a project progresses. The server uses emotion data to customize task assignments and notification methods in a format that best suits the user's current mental state, thereby improving work efficiency. For example, if the emotion engine determines that the user is motivated, it will arrange to send a message of praise.

[0787] Finally, the training modules provided to production managers are customized using emotion engine data. Users can access content on their devices in a format optimized to their learning pace and current emotional state. This maximizes learning effectiveness and promotes employee skill development.

[0788] This system, which incorporates an emotion engine, enables project management that is sensitive to the user's emotions, thereby improving both operational efficiency and employee satisfaction.

[0789] The following describes the processing flow.

[0790] Step 1:

[0791] The user enters project contract information via a terminal. The emotion engine analyzes the user's facial expressions and tone of voice while they are entering information, and evaluates the user's emotional state in real time.

[0792] Step 2:

[0793] The device detects the user's emotional state and displays corresponding feedback on the screen. For example, if the user is feeling stressed, it might provide a message such as, "Relax and continue."

[0794] Step 3:

[0795] Based on the emotional data received from the emotion engine, the server re-verifies whether the contract details have been entered accurately and provides supplementary information about the automatically generated contract as needed.

[0796] Step 4:

[0797] The user enters the owner's request into the terminal. The emotion engine then re-analyzes the user's emotions at the time the request was entered.

[0798] Step 5:

[0799] The server adjusts the request notification method based on the analysis results. For example, if the user expresses concern, it may simplify the request notification or suggest additional verification procedures.

[0800] Step 6:

[0801] When the server sends notifications to staff regarding the owner's requests, it takes emotional data into consideration and presents the notification in the most acceptable format.

[0802] Step 7:

[0803] When managing project schedules, the server uses sentiment data to customize task assignments. For example, it assigns challenging tasks to highly motivated users.

[0804] Step 8:

[0805] Users report their progress via their devices. The emotion engine analyzes the emotional state at the time of reporting and sends the data to the server to consider subsequent actions.

[0806] Step 9:

[0807] Users take educational modules. During this process, the emotion engine tracks changes in emotions while learning and adjusts the content to optimize the learning pace and maintain motivation.

[0808] Step 10:

[0809] Based on the sentiment data collected so far, the server forms a feedback loop across the entire system to continuously optimize the user experience.

[0810] (Example 2)

[0811] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0812] In anime production projects, failing to consider the emotional state of participants during project management can easily lead to increased stress and decreased motivation, resulting in reduced work efficiency and employee satisfaction. Furthermore, the lack of feedback and training tailored to the individual emotional state of employees makes effective project management and skill development difficult.

[0813] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0814] In this invention, the server includes emotion analysis means for analyzing the emotional state of project participants and reflecting that information in project management; management means for adaptively adjusting project schedules and task notification methods based on emotional state; and education delivery means for customizing educational content for production staff using emotional data. This enables project management and education customization that takes into account the emotional state of participants, thereby improving work efficiency and employee satisfaction.

[0815] "Emotional analysis tools" are methods for analyzing the emotional states of project participants and incorporating that information into project management.

[0816] "Analysis means" refers to a method for receiving user input data and quantifying the emotional state using an emotion engine.

[0817] "Management measures" are means of adaptively adjusting project schedules and task notification methods based on emotional states.

[0818] "Educational delivery methods" refer to means of customizing educational content for production managers using emotional data.

[0819] "Information provision means" refers to methods for providing feedback and supplementary information according to the user's emotional state to support project management.

[0820] This system is designed to take into account the emotional states of participants in anime production projects and to achieve efficient project management. It primarily operates through collaboration between three parties: users, servers, and terminals.

[0821] First, the user uses a terminal to input project contract information and requests from the owner. The terminal has an emotion engine built in, which uses speech recognition and facial recognition technology to analyze the user's facial expressions, voice tone, input speed, etc., and identify their emotional state.

[0822] Next, the server optimizes project management based on the analyzed emotional state. The emotional analysis tool quantifies the user's stress level and motivation, and uses this information to adjust project schedules and task notification methods. In this process, it is possible to generate emotionally appropriate feedback and supportive information using a generative AI model.

[0823] Furthermore, educational content for production staff is also managed on the server side. The server utilizes emotional data and, through educational delivery methods, customizes and provides optimized educational modules tailored to the user's learning pace and current emotional state.

[0824] As a concrete example, if the emotion engine detects an increase in the user's stress level while they are entering contract information, the server will display input assistance messages or notifications prompting them to take a short break through the terminal. Another example of a prompt using a generative AI model is, "Generate an appropriate feedback message to provide if the user is feeling anxious."

[0825] This system, centered on sentiment analysis, makes project management more flexible and effective. A key feature of this system is its ability to achieve both improved operational efficiency and increased employee satisfaction.

[0826] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0827] Step 1:

[0828] The user enters project contract information using a terminal. The terminal retrieves the input data and sends it to the emotion engine. The input information includes the contract information itself, as well as data related to the user's facial expressions and voice tone. The terminal detects this data and prepares it to be sent to the server.

[0829] Step 2:

[0830] The server processes the data received from the terminal. First, it uses an emotion engine to analyze the user's emotional state. Specifically, it uses facial recognition and speech recognition technology to quantify whether the user is stressed or calm. The results of this analysis are recorded on the server as emotion data useful for project management.

[0831] Step 3:

[0832] The server adjusts project management methods based on emotional data. In this step, task scheduling and notification methods are customized based on emotional data. For example, if a user is stressed, notifications may be withheld or supplementary support messages added. This information is also fed into a generative AI model to generate appropriate feedback messages.

[0833] Step 4:

[0834] The generated feedback and adjusted task information are communicated to the user via the device. The device displays the information received from the server, allowing the user to take the next action accordingly. Specific actions include reviewing messages displayed on the screen and responding to them.

[0835] Step 5:

[0836] The server customizes the educational content. It uses emotional data to optimize educational modules for production managers. The server generates data based on the user's learning pace and emotional state, and uses this to individually adjust the educational content. Feedback and new learning tasks are provided to the user through the device.

[0837] This series of processes allows users to receive project management and training tailored to their emotional state. This improves work efficiency and employee satisfaction.

[0838] (Application Example 2)

[0839] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0840] The problem that this invention aims to solve is that uniform project management and work progress without considering the emotional state of workers in factories and other workplaces leads to a decrease in work efficiency and worker satisfaction. Furthermore, because methods for improving the work environment are uniform, it is difficult to respond to the motivation and stress levels of individual workers, which is another problem.

[0841] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0842] In this invention, the server includes an input device for inputting project contract information, a storage device for storing and managing generated contract documents, a generation device means for automatically generating contract documents, an emotion detection device for recognizing emotional states, an emotion adaptation device means for adapting project management based on emotions, and a device means for adjusting the operation of the device using emotion data. This enables flexible project management and work adjustments in accordance with the emotional state of workers, thereby improving work efficiency and worker motivation.

[0843] An "input device" is a device or system used by users to input contract information related to a project.

[0844] A "storage device" is a storage device used to store and manage generated contract documents and other data.

[0845] A "generation device" is a device or program that automatically creates contract documents based on input data.

[0846] A "communication device" is a device that uses communication technology to notify users of information and requests.

[0847] A "plan" is a framework or schedule for automatically generating the steps and schedules necessary for the progress of a project.

[0848] "Tasks" refer to the specific work or tasks assigned to individual team members within a project.

[0849] "Risk" refers to analyzing the risks and problems that may arise during the project's progress.

[0850] A "warning" is a message or notification intended to draw the attention of relevant parties to a detected hazard.

[0851] The term "educational program" refers to the learning content and training provided to production staff.

[0852] An "emotion detection device" is a device or system that analyzes facial expressions and voice data to recognize the emotional state of workers and other individuals.

[0853] An "emotional adaptation device" is a device or program used to optimize project management and work progress based on detected emotional data.

[0854] "Emotional data" refers to data that indicates the emotional state of workers and other personnel, and is used as information for project management.

[0855] A "device for adjusting operation" is a device or software that adjusts the operation of a machine or system in real time based on emotional data.

[0856] The system for carrying out this invention consists of an emotion detection device, an emotion adaptation device, an input device, a memory device, a generation device, a communication device, and a device for adjusting operation. Each of these devices is designed to interact with the user's terminal and the server.

[0857] The server uses an emotion detection device to analyze the worker's facial expressions and voice data in real time to recognize their emotional state. This emotional data is stored in memory, and a generation device automatically generates necessary instructions. The server also uses an emotion adaptation device to optimize project management and task progress based on the recognized emotional data. In this process, if a worker is experiencing stress, the system adjusts the pace of work and sends encouraging notifications to improve the work environment.

[0858] The user's terminal inputs contract information and owner requests related to the project via an input device and sends them to the server. The communication device notifies multiple personnel of the input information in real time, ensuring accurate information transmission.

[0859] For example, in a manufacturing plant, if an emotion detection device detects that a worker has been working for a long time and is fatigued, the server adjusts the machine's operating speed via a control device and sends a notification such as "You need a break." In this way, it is possible to reduce the burden on workers and provide an efficient work environment.

[0860] An example of a prompt message for the generating AI model could be: "Generate an effective support message for workers in a high-stress environment."

[0861] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0862] Step 1:

[0863] The server uses an emotion detection device to acquire the worker's facial expressions and voice data in real time. It receives raw data from cameras and microphones as input and feeds it into emotion analysis software. Data processing involves feature point extraction and voice frequency analysis to generate emotional state data. In this process, the server obtains an output that recognizes the emotional state (e.g., stress level, euphoria, etc.).

[0864] Step 2:

[0865] The server uses the obtained emotional state data to activate an emotional adaptation device, optimizing project management and task progress. It receives emotional state data as input and compares it with past data in a database to develop an optimization strategy suitable for the current work environment. For data processing, it uses an algorithm to adjust work progress with the aim of reducing worker stress, and generates an adjusted task schedule as output.

[0866] Step 3:

[0867] Users input project-related contract information and owner requests into a terminal via an input device. The input is received in text or multiple-choice format. The server receives this information and notifies project stakeholders using a communication device. The output consists of confirmed contract information and requests, which serve as fundamental data for project progress.

[0868] Step 4:

[0869] The server uses a device to adjust the operation of machines and systems dynamically based on emotional states. It uses emotional state data and work progress data as input to generate commands for operation adjustment. Specifically, it may issue instructions to reduce work speed when stress levels are high, and the output includes adjusted machine operation and suggestions for improving the work environment.

[0870] Step 5:

[0871] The user inputs an appropriate prompt sentence to a generative AI model, which automatically generates support messages tailored to the user's emotional state. The prompt sentence used as input is, "Generate an effective support message for workers in a high-stress environment." The server executes the generative AI model and provides the user with the generated support message as output.

[0872] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0873] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0874] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0875] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0876] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0877] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0878] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0879] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0880] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0881] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0882] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0883] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0884] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0885] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[0886] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0887] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0888] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0889] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0890] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0891] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0892] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted as being incorporated by reference.

[0893] The following is further disclosed regarding the embodiments described above.

[0894] (Claim 1)

[0895] An input means for entering project contract information, a database means for storing and managing the generated contract, and a generation means for automatically generating the contract.

[0896] A means for inputting requests from the owner and saving those requests in a database, and a means for notifying that information,

[0897] A means to automatically generate project schedules and monitor and notify progress in real time,

[0898] A means of assigning tasks to each staff member and monitoring and notifying them of their progress,

[0899] A means of analyzing project risks and sending alerts to stakeholders,

[0900] A system that includes educational tools to provide training modules for production managers.

[0901] (Claim 2)

[0902] The system according to claim 1, which formats contract information based on a pre-configured template when entering project contract information.

[0903] (Claim 3)

[0904] The system according to claim 1, which hierarchically notifies multiple staff members of requests from the owner and controls them so that the requests are reflected throughout the entire project.

[0905] "Example 1"

[0906] (Claim 1)

[0907] A terminal device for inputting project contract details, means for storing and managing contract documents in a secure storage device, and server processing device means for automatically generating contract documents.

[0908] A terminal communication means for inputting work requests from clients and saving those requests to a storage device, and a communication device means for transmitting those requests to relevant parties.

[0909] A control device for automatically creating a project activity plan, monitoring its progress in real time, and notifying stakeholders,

[0910] A monitoring and control device means for assigning tasks to each worker, monitoring progress, and providing periodic updates.

[0911] An analytical device and means for analyzing the potential risks of a project and issuing warnings to relevant people,

[0912] A system including an educational support device for providing skill-enhancing materials to production managers.

[0913] (Claim 2)

[0914] The system according to claim 1, which automatically organizes contract details based on a pre-set format when entering project contract details.

[0915] (Claim 3)

[0916] The system according to claim 1, which transmits work requests from a client to multiple workers in a hierarchical manner and manages the requests so that they are reflected throughout the entire project.

[0917] "Application Example 1"

[0918] (Claim 1)

[0919] An input / output device for inputting project contract information, a data structure for storing and managing the generated contract, and a generation device means for automatically generating the contract.

[0920] A device that inputs a request from a requester and stores the request in a data structure, and a communication device means that notifies the information,

[0921] A device and means for automatically generating project plans and monitoring and notifying progress in real time,

[0922] A device for assigning tasks to each worker and monitoring and notifying them of their progress,

[0923] A device and means for analyzing project uncertainties and sending alerts to stakeholders,

[0924] An educational device that provides educational modules to project managers,

[0925] A mobile terminal means for inputting the operation sequence of a machine and monitoring the sequence and progress,

[0926] A system that includes this.

[0927] (Claim 2)

[0928] The system according to claim 1, which formats contract information based on a pre-configured template when entering project contract information.

[0929] (Claim 3)

[0930] The system according to claim 1, which hierarchically notifies multiple workers of a request from the requester and controls the system so that the request is reflected throughout the entire project.

[0931] "Example 2 of combining an emotion engine"

[0932] (Claim 1)

[0933] A means of emotional analysis that analyzes the emotional state of project participants and reflects that information in project management,

[0934] An analysis method that receives user input data and quantifies the emotional state using an emotion engine,

[0935] A management system that adaptively adjusts project schedules and task notification methods based on emotional states,

[0936] An educational delivery method that uses emotional data to customize educational content for production managers,

[0937] A system that includes information provision tools to support project management by providing feedback and supplementary information according to the user's emotional state.

[0938] (Claim 2)

[0939] The system according to claim 1, which analyzes the user's emotional state and provides formatting support when entering contract information.

[0940] (Claim 3)

[0941] The system according to claim 1, which optimizes notification timing by utilizing emotional data based on requests from the owner.

[0942] "Application example 2 of combining emotional engines"

[0943] (Claim 1)

[0944] An input device for entering project contract information, a storage device for storing and managing generated contract documents, and a generation device means for automatically generating contract documents.

[0945] A device that inputs requests from the owner and stores those requests in a storage device, and a communication device means that notifies the owner of the information.

[0946] A device and means for automatically generating project plans and monitoring and notifying progress in real time,

[0947] A device that assigns tasks to each person in charge and monitors and notifies them of their progress,

[0948] A device that analyzes the risks of a project and sends warnings to stakeholders,

[0949] An educational device and means for providing educational programs to production management personnel,

[0950] An emotion detection device that recognizes an emotional state, and an emotion adaptation device means that adapts project management based on emotions,

[0951] A device means that adjusts the operation of the device using emotional data,

[0952] A system that includes this.

[0953] (Claim 2)

[0954] The system according to claim 1, which formats contract information based on a pre-set template when entering project contract information.

[0955] (Claim 3)

[0956] The system according to claim 1, which hierarchically notifies multiple personnel of requests from the owner and manages to ensure that such requests are reflected throughout the entire project. [Explanation of Symbols]

[0957] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. An input means for entering project contract information, a database means for storing and managing the generated contracts, and a generation means for automatically generating contracts. A means for inputting requests from the owner and saving those requests in a database, and a means for notifying that information, A means to automatically generate project schedules and monitor and notify progress in real time, A means of assigning tasks to each staff member and monitoring and notifying them of their progress, A means of analyzing project risks and sending alerts to stakeholders, A system that includes educational tools to provide training modules for production managers.

2. The system according to claim 1, which formats contract information based on a pre-configured template when entering project contract information.

3. The system according to claim 1, which hierarchically notifies multiple staff members of requests from the owner and controls the system so that the requests are reflected throughout the entire project.

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