system

Abstract

We provide the system. [Solution] Information processing means that receives basic project information and automatically generates initial tasks related to the project, A means of integration that acquires data from an external system and proposes additional tasks and schedule adjustments based on the acquired data, An interface for editing and presenting generated tasks and schedules to the user, A storage means for saving user-edited content and managing project progress, A system that includes this.

Description

Technical Field

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

Background Art

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

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] At the start of a project, the overall picture of the required tasks is unclear, and there is a problem that it is difficult to create tasks and schedules without omission. Also, an efficient method for coping with schedule changes and the occurrence of new tasks during project progress is required. To address this, a system that can perform planning and management without difficulty from the initial stage of the project is necessary.

Means for Solving the Problems

[0005] This invention provides an information processing means that uses AI to automatically generate necessary initial tasks by inputting basic project information. It also includes a linkage means that can cooperate with external systems to suggest additional tasks and schedule adjustments that may arise during meetings, etc. Furthermore, it provides an interface that allows users to easily edit the generated tasks and schedules, and a storage means that saves the modified content, thereby enabling consistent project management.

[0006] "Information processing means" refers to means that receive basic project information and have the function of automatically generating initial tasks based on said information.

[0007] A "collaboration method" is a means that acquires data from an external system and has the function of suggesting additional tasks or schedule adjustments to the user based on that data.

[0008] An "interface means" is a means that has the function of presenting the generated tasks and schedules to the user and providing operations for editing them.

[0009] A "memory device" is a means that has the function of saving the contents of tasks and schedules edited by the user and managing the progress of the project.

[0010] A "calculation tool" is a means that has the function of identifying task dependencies and creating a proposed schedule based on project management methods.

[0011] A "notification method" is a means that has the function of monitoring the progress of a project in real time and informing users of the progress of tasks. [Brief explanation of the drawing]

[0012] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2]This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] This is a sequence diagram showing the processing flow of the data processing system in Example 2, which incorporates an emotion engine. [Figure 14] This is a sequence diagram showing the processing flow of the data processing system in Application Example 2, which combines an emotion engine. [Modes for carrying out the invention]

[0013] Hereinafter, an example of an embodiment of the system relating to the technology of this disclosure will be described with reference to the attached drawings.

[0014] First, the terms used in the following description will be explained.

[0015] In the following embodiments, the labeled processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple 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.

[0016] In the following embodiments, the labeled RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0017] In the following embodiments, the labeled storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, and the like.

[0018] In the following embodiments, the labeled communication I / F (Interface) is an interface including a communication processor and an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark), and the like.

[0019] 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."

[0020] [First Embodiment]

[0021] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0022] 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.

[0023] 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).

[0024] 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.

[0025] 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.

[0026] 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.

[0027] 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.

[0028] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0029] 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.

[0030] 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.

[0031] 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.

[0032] 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".

[0033] This invention is a system aimed at improving the efficiency of project management, and is implemented as follows.

[0034] First, the user enters basic project information, namely its purpose, content, overall schedule, and the number of participants. This provides the system with an overview of the project.

[0035] The entered information is received by the terminal, and after verifying that the format is correct, it is sent to the server. Based on the received information, the server uses information processing tools and an AI agent to automatically generate relevant initial tasks. These initial tasks are based on the basic framework of project management.

[0036] Next, the server retrieves additional data from external systems. This integration method leverages data from meeting minute-taking tools and other relevant external systems to create additional tasks and schedule adjustments based on the project's progress.

[0037] Next, the terminal provides an interface to present the user with tasks and schedule proposals generated from the server. Here, the user can view the task details and edit them as needed.

[0038] Users determine the content of tasks and schedules that are modified or approved through the interface. Based on this, the server stores the edited information using storage means. This stored data forms the basis for managing project progress and improving work efficiency.

[0039] For example, when launching a new software development project, the user inputs information such as "new software development," "from initial design to implementation," "4 months," and "6 people." The server then generates tasks such as "requirements definition," "system design," "coding," and "testing," and sets a schedule. External collaborations may also suggest the addition of new testing phases.

[0040] Thus, this invention prevents overlooking tasks required for project initiation and improves the overall efficiency of projects by enabling real-time schedule management and suggestion of additional tasks.

[0041] The following describes the processing flow.

[0042] Step 1:

[0043] The user enters basic information such as the project's purpose, content, overall schedule, and number of participants into the terminal. The entered information is checked for formatting correctness, and if there are no problems, the process proceeds to the next step.

[0044] Step 2:

[0045] The terminal serializes the information received from the user and sends it to the server as an API request. During this process, the information is properly encrypted and transmitted securely.

[0046] Step 3:

[0047] Based on the received project information, the server uses information processing tools to activate an AI agent, which automatically generates relevant initial tasks. The AI ​​agent analyzes a list of common tasks and their dependencies based on the project content, and creates the optimal task set.

[0048] Step 4:

[0049] The server uses integration methods to retrieve necessary data from external systems (such as meeting minute-taking tools and planning tools). Based on the retrieved data, the AI ​​agent then proposes additional tasks and schedule adjustments.

[0050] Step 5:

[0051] The server sends the generated tasks and proposed schedules to the terminal. The terminal receives them and provides an interface to display them to the user in a visually clear manner. The interface clearly shows the details of each task, its associated deadlines, and dependencies.

[0052] Step 6:

[0053] Users can use the terminal interface to review proposed tasks and schedules, and make modifications or additions as needed. Users can also change the order of tasks using drag-and-drop functionality and add new tasks directly on the interface.

[0054] Step 7:

[0055] The terminal sends the content edited by the user to the server, which then stores it in a database using a storage device. During this process, an update is performed to ensure that the latest state of the project is reflected in all related systems.

[0056] Step 8:

[0057] The server monitors project progress in real time and notifies users of task progress at every step. Users can check the system to see when to move on to the next step and when tasks are completed.

[0058] (Example 1)

[0059] 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."

[0060] In modern project management, a common problem is insufficient planning in the initial stages and delays in adjusting plans due to external factors. Furthermore, difficulty in tracking project progress and clarifying the relationships between tasks contributes to a decrease in overall project efficiency. These challenges are particularly pronounced in complex projects, highlighting the need for appropriate management strategies.

[0061] 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.

[0062] In this invention, the server includes a calculation means for receiving information and automatically generating related tasks based on that information; a cooperation means for acquiring information from an external device and proposing supplementary tasks and adjustments to the time plan based on the acquired information; and a display means for presenting the generated tasks and time plan to the user and making them editable. This enables the automation of task planning in the initial stages and flexible plan adjustments that take external factors into consideration, thereby improving the efficiency of project management.

[0063] "Receiving information" means that a system takes in data acquired from an external source and makes it ready for processing.

[0064] "Automatically generating related tasks" means automatically identifying and generating the necessary tasks based on the received data.

[0065] "Calculation means" refers to a device or software that has the function of processing data and performing calculations.

[0066] "Acquiring information from external devices" refers to the process of taking data from other systems or services.

[0067] "Proposing supplementary tasks and adjustments to the time plan" means making revisions to the existing plan or suggesting new tasks based on the additional data acquired.

[0068] "Means of cooperation" refer to mechanisms or methods for different functions or devices to exchange information with each other.

[0069] An "editable display method" is an interface that allows users to review the presented data and make adjustments or changes as needed.

[0070] "Storing" refers to saving collected information and keeping it accessible for later use.

[0071] "Managing the progress of work" means checking the progress of tasks and controlling the overall process to ensure it is carried out smoothly according to the plan.

[0072] This invention is a system for efficiently managing projects. This system consists of multiple means, including information processing, external integration, a user interface, and memory. Specific embodiments of the system are described below.

[0073] User interaction:

[0074] Users input basic project information into the system. This information includes the project's purpose, content, overall schedule, and number of participants. Users input the information using a PC or mobile device, and the data is received by the device.

[0075] Terminal processing:

[0076] The terminal verifies that the format of the information entered by the user is correct, and if there are no formatting issues, it sends the information to the server. The terminal then displays the corrected tasks and schedules to the user via the user interface.

[0077] Server information processing:

[0078] The server automatically generates initial tasks using an AI model based on the received project information. This involves using keywords such as "requirements definition," "design," and "implementation" as prompts for the AI ​​model. The server also integrates with external data sources to acquire additional data and propose supplementary tasks and time plans. This process incorporates data from meeting minute-taking tools and other systems.

[0079] Specific example:

[0080] For example, when starting a new software development project, the user inputs basic information such as "new software development," "from initial design to implementation," "4 months," and "6 people." Based on this information, the server generates tasks such as "requirements definition," "system design," "coding," and "testing," and proposes adding new test phases from an external database used to manage the project's progress.

[0081] Example of a prompt:

[0082] "Please describe the process of automatically generating initial tasks after basic information input and generating additional tasks based on external system data using the new project management system."

[0083] This system provides users with an environment that allows them to easily manage projects and quickly coordinate tasks, thereby enabling efficient project execution.

[0084] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0085] Step 1:

[0086] The user enters basic project information. Input fields include purpose, content, schedule, and number of participants. The terminal verifies that the entered information is in the correct format. If the data is entered correctly, it is sent to the server.

[0087] Step 2:

[0088] The server automatically generates initial tasks based on the received project information. Using a generation AI model, it identifies initial tasks according to the input information and generates keywords such as "requirements definition" and "design." The server sends this prompt message to the AI ​​model and outputs an initial task list.

[0089] Step 3:

[0090] The server interacts with external devices to acquire additional data. This data includes information from tools such as meeting minute creation tools, and based on this, it proposes supplementary tasks and schedule adjustments. The server analyzes the external information to generate output for task additions and schedule modifications.

[0091] Step 4:

[0092] The terminal displays tasks and proposed schedules received from the server to the user. Through the user interface, the user can view task details and make necessary edits. When the user adjusts a task on the interface, those edits are sent to the server via the terminal.

[0093] Step 5:

[0094] The user performs final confirmation and revisions to the presented tasks. The results of the approval or revisions to the selected tasks and schedules are reflected on the server via the terminal.

[0095] Step 6:

[0096] The server stores data confirmed by users using storage means. The stored business data is used for project progress management and functions as foundational data to support the efficient execution of tasks.

[0097] (Application Example 1)

[0098] 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."

[0099] In factory production project management, while there is a need to streamline work processes and plans, there are limitations to manual task generation and scheduling. Furthermore, monitoring work progress in real time and taking prompt action is difficult, necessitating an automated management system to optimize production efficiency.

[0100] 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.

[0101] In this invention, the server includes means for recognizing basic project information and automatically generating initial tasks related to the project; means for acquiring information from external sources and proposing additional tasks and plan adjustments based on the acquired information; and means for automatically generating production processes in a factory and monitoring and adjusting the progress of the work in real time. This enables efficient management of work processes and improved production efficiency through rapid progress monitoring.

[0102] "Basic project information" refers to information necessary as a foundation for planning, such as the project's objectives, content, duration, and number of participants.

[0103] "Initial work" refers to the basic work process set up at the start of a project, and is a set of tasks necessary to understand the overall picture of the project.

[0104] "Information processing means" refers to a system or technology for automating work based on the basic information of a project.

[0105] An "external information source" is a resource used to obtain information from databases or services located outside the system.

[0106] "Integration means" refers to methods or technologies for connecting with external information sources to collect information and making it available for use within the system.

[0107] "Display means" refers to interfaces or devices that intuitively present information to the user.

[0108] "Memory means" refers to a medium or technology for storing the progress of a project or the content of revised tasks.

[0109] A "notification method" is a system or method for informing users of the progress of tasks in progress within a project.

[0110] "Generation means" refers to a method or technology for automatically constructing production processes in a factory using AI technology.

[0111] "Real-world time" refers to the exact time when a task or situation is actually occurring, and it represents a state where information is provided with immediacy.

[0112] To realize this application example, the "Smart Factory Manager" system, it is necessary to build a project management system. The server first receives basic project information, and the AI ​​agent automatically generates initial tasks using information processing tools. In this process, a server equipped with a high-performance processor is used as hardware, and machine learning modules are utilized to execute the AI ​​model.

[0113] Next, the server uses means of integrating with external information sources to acquire additional information and adjust the work plan accordingly. Data is retrieved from external APIs, and necessary transformations and calculations are performed to generate the next work steps. This allows the project to allow for flexible plan changes based on the latest information.

[0114] The terminal provides an interface that displays generated tasks and schedules to the user. Through this interface, the user can review and edit tasks. The edited information is immediately sent to the server and securely stored by the storage system.

[0115] For example, when planning the launch of a new product line in a factory, the system automatically generates tasks such as "designing the new product line," "assigning line workers," and "initial testing and adjustments." Furthermore, the progress of the process is monitored in real time, and schedule adjustments are suggested as needed.

[0116] An example of a prompt using the generation AI model is: "Based on the project name: New production line, objective: Expansion of production capacity, duration: 3 months, and number of participants: 10, generate the initial tasks and schedule for the corresponding production process." This prompt allows the system to automatically suggest relevant tasks and plans.

[0117] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0118] Step 1:

[0119] The user enters basic project information into the terminal. This information includes the project name, purpose, duration, and number of participants. The terminal checks the format of the entered information and sends it to the server in the appropriate format.

[0120] Step 2:

[0121] The server uses a generation AI model to automatically generate initial tasks based on the basic project information it receives. During this process, it takes a prompt (e.g., "Based on the project name: New Production Line, objective: Expansion of production capacity, duration: 3 months, number of participants: 10, please generate the initial tasks and schedule for the corresponding production process") as input, and outputs a list of initial tasks from the AI ​​model.

[0122] Step 3:

[0123] The server acquires additional data using means of linking with external information sources. This additional data includes information on the progress of the process and resource availability, which is obtained via API. Based on this data, data processing is performed to generate proposed adjustments to tasks and schedules.

[0124] Step 4:

[0125] The generated tasks and proposed schedules are sent to the terminal, which then displays them to the user. The terminal provides a visual interface, allowing the user to review the details of each task and make modifications as needed.

[0126] Step 5:

[0127] After a user modifies a task or schedule, the changes are sent back to the server. The server stores the modified information in its memory and uses it for future project management.

[0128] Step 6:

[0129] The server monitors project progress in real time and notifies users of task progress using notification methods. This notification is provided in real time through the terminal, helping users respond quickly as needed.

[0130] 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.

[0131] This invention provides a system that streamlines project management while taking user emotions into consideration, and is implemented as follows.

[0132] First, the user inputs basic information such as the project's objectives, content, schedule, and number of participants into the terminal. This information is collected by the terminal and then sent to the server. The server uses information processing tools to invoke an AI agent, which generates appropriate initial tasks based on the input information. In this process, task dependencies are also considered based on project management methodologies.

[0133] Furthermore, the server acquires data information from external systems. This integration allows it to connect with external systems (e.g., meeting minute-taking tools or schedule management systems) and propose additional tasks or appropriate schedule adjustments. The proposed tasks and schedules are then managed in a way that is optimal for the user.

[0134] Next, the system uses an emotion engine to analyze the user's emotions from their input data and operation history. Based on the recognized emotions, the emotion engine dynamically adjusts how information is presented. For example, if it determines that the user is feeling stressed, it simplifies the display of tasks and provides additional support information sparingly.

[0135] The generated tasks and proposed schedules are presented to the user on their terminal. The user can then review the presented tasks and edit them as needed. The server then saves the edited task details to a database using a storage device, forming the basis for project progress management.

[0136] The emotion engine further optimizes alerts and notifications based on the user's emotions. For example, if a user is showing signs of fatigue, notifications for non-urgent project tasks will be kept to a minimum. In this way, the system supports the efficient progress of projects while providing a comfortable working environment for the user.

[0137] For example, if a user expresses anxiety as a project deadline approaches, the emotion engine can adjust the display to highlight high-priority tasks and postpone other information. In this way, project management can be carried out while taking user emotions into consideration.

[0138] The following describes the processing flow.

[0139] Step 1:

[0140] Users input basic information into their terminal, including the project's objectives, content, overall schedule, and number of participants. This information is essential for understanding the overall picture of the project.

[0141] Step 2:

[0142] The terminal receives information entered by the user, verifies its integrity, and then sends it to the server. Before transmission, the information is properly formatted and securely sent via the API.

[0143] Step 3:

[0144] The server analyzes the received project information and executes information processing using an AI agent. This automatically generates an initial task list required for the project. At this stage, task dependencies based on management methods are considered.

[0145] Step 4:

[0146] The server connects to external systems using integration methods to retrieve project-related data. Based on this data, it creates additional task suggestions and schedule adjustment proposals.

[0147] Step 5:

[0148] The server uses an emotion engine to analyze the user's past activity logs and real-time behavior to recognize the user's emotional state.

[0149] Step 6:

[0150] The server dynamically adjusts how tasks and schedules are displayed based on the user's perceived emotions. If the user is feeling stressed, information is presented in a simplified format.

[0151] Step 7:

[0152] The server sends the coordinated tasks and schedule to the terminal. The terminal presents this to the user as an interface, providing an environment where the user can visually organize and edit tasks.

[0153] Step 8:

[0154] Users review the tasks and schedules presented through their device and make any necessary changes. The edits are immediately updated and sent to the server.

[0155] Step 9:

[0156] The server receives user edits and stores them in a database using a storage device. The stored information is used for project management.

[0157] Step 10:

[0158] The server monitors project progress in real time and optimizes alerts and notifications to the user based on their emotions. For example, if a user shows signs of impatience, it will prioritize notifications for high-priority tasks.

[0159] (Example 2)

[0160] 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".

[0161] In project management, there are challenges in efficiently generating initial tasks and coordinating and scheduling appropriately. Furthermore, to reduce the workload on users, it is necessary to incorporate information presentation methods that respond to their emotional state. Smooth execution of this entire workflow and proper management of project progress are essential.

[0162] 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.

[0163] In this invention, the server includes information processing means that receive basic project information and automatically generate initial work items related to the project; cooperation means that acquire data from external information sources and propose additional work items and time management adjustments based on the acquired data; and emotion analysis means that analyze the user's emotional state and dynamically adjust the information presentation method. This improves the efficiency of project management and enables the provision of a work environment that takes the user's emotions into consideration.

[0164] "Information processing means" refers to a device or system that has the function of automatically generating initial work items based on the basic information of a project.

[0165] "Integration means" refers to a device or system that includes the function of acquiring data from external information sources and proposing additional work items or time management adjustments based on that data.

[0166] "Display means" refers to a device or system that has a user interface function that presents generated work items and time management to the user and allows for further editing.

[0167] "Storage means" refers to a database or storage device that stores the work edited by the user and continuously manages the progress of the project.

[0168] An "emotion analysis tool" is a device or system that analyzes a user's operation history and input data to infer their emotional state and dynamically adjusts the information presentation method accordingly.

[0169] A "notification means" is a device or system for monitoring the progress of a project in real time and notifying users of the latest status.

[0170] A "calculation tool" is a device or system that, based on project management methodologies, identifies the relationships between work items and creates an effective time management plan.

[0171] To implement this invention, project management primarily involves collaboration between three parties: a server, a terminal, and a user. The server handles the main processing and constitutes a system incorporating information processing means, collaboration means, sentiment analysis means, and so on. Specifically, it utilizes a cloud-based computing system, generates initial work items using a generative AI model, and collaborates with external information sources via APIs. The terminal receives input from the user and transmits and receives data with the server. The user inputs basic project information through the terminal and monitors and controls its progress.

[0172] The server automatically generates initial work items using a generative AI model based on the project's basic information. In this process, it leverages existing project management methods while using AI to efficiently design tasks. For example, it generates an optimal progress schedule while considering the temporal and logical dependencies of tasks.

[0173] Furthermore, the server uses integration methods to acquire data from external sources and connects with systems such as meeting minute creation and schedule management, thereby improving the overall accuracy of project management. This allows users to receive additional work items and suggestions for adjusting time management.

[0174] Furthermore, using emotion analysis tools, the server analyzes the user's emotional state and customizes the information presentation method. For example, if the user is feeling anxious, important tasks are visually highlighted, while other information is presented simply. In this way, support is provided to ensure efficient project management.

[0175] For example, when a user expresses anxiety as a project deadline approaches, the server will highlight high-priority tasks and refrain from displaying other information.

[0176] An example of a prompt for the generating AI model would be: "I want to generate initial project management tasks. The project objective is 'launching a new product,' and the deadline is 'in 3 months.' The team will consist of 10 people. Please suggest appropriate tasks and dependencies." Based on this prompt, the server will perform the initial setup of the project management.

[0177] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0178] Step 1:

[0179] The user enters basic information such as the project's purpose, content, schedule, and the number of team members into the terminal. The terminal formats this input information into JSON format and sends it to the server. Here, the input is the basic project information, and the output is the data format sent to the server.

[0180] Step 2:

[0181] The server, upon receiving basic information transmitted from the terminal, invokes a generation AI model to automatically generate initial work items based on this information. Specifically, it performs data calculations using project management techniques to generate a list of work items that consider task dependencies. The input is the received basic information, and the output is the generated list of work items.

[0182] Step 3:

[0183] The server uses API integration to retrieve additional data from external sources. Here, it obtains external data (e.g., meeting minutes or existing schedule information) and uses it to propose additional work items and time management adjustments. The input is data obtained from external systems, and the output is an integrated adjustment proposal.

[0184] Step 4:

[0185] The server analyzes the user's emotional state using emotion analysis tools. This involves analyzing the user's operation logs and input history to evaluate the emotional state. For example, frequent user activity might indicate impatience. The input is the user's operation log, and the output is the result of the emotional state analysis.

[0186] Step 5:

[0187] The server prepares the generated work items and adjustment proposals to be displayed on the terminal in a format optimized for the user's emotional state. This display preparation process involves highlighting important tasks and simplifying information. The input is the previously analyzed emotional state and work item list, and the output is the optimized display format.

[0188] Step 6:

[0189] The terminal displays work items and proposed schedules received from the server to the user, who then reviews and edits them. The edited content is sent back from the terminal to the server and reflected in the overall system's progress management. The input is the content displayed from the server, and the output is the edited work item information.

[0190] Step 7:

[0191] The server stores the edited data in a database via storage means. It also provides real-time notifications as the project progresses, keeping users informed of the latest status. These notifications are customized based on sentiment analysis results, according to the schedule and task importance. Input is the edited work information, and output is the stored data and notification information.

[0192] (Application Example 2)

[0193] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0194] Modern project management requires efficient progress management while integrating with diverse external data and considering the emotions of stakeholders. However, existing management systems are insufficient in linking with external information and optimizing information presentation according to emotional states, resulting in challenges in project efficiency and reducing stress among stakeholders.

[0195] 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.

[0196] In this invention, the server includes data processing means for acquiring basic project information and automatically generating basic tasks related to the project; cooperation means for collecting information from external organizations and proposing additional work or time adjustments based on the collected information; and optimization means for analyzing the operator's emotions using an emotion analysis engine and dynamically adjusting the information presentation method based on the analysis results. This improves the efficiency of project progress while enabling flexible information management that responds to the emotional states of stakeholders.

[0197] "Basic project information" refers to initial information about the project, such as its purpose, content, schedule, and the number of people involved.

[0198] A "data processing system" is a mechanism that has the function of automatically generating related basic tasks based on the basic information of the input project.

[0199] "External organizations" refer to external information sources and systems that can be integrated with the project management system, and are responsible for collecting necessary data.

[0200] A "collaboration mechanism" is a system that utilizes information obtained from external organizations to propose additional tasks or schedule adjustments.

[0201] An "emotion analysis engine" refers to a computing device or algorithm that analyzes user input data and operation history to identify the user's current emotional state.

[0202] An "optimization mechanism" is a system that dynamically adjusts the method and frequency of information presentation based on the results of the emotion analysis engine.

[0203] "Information presentation method" refers to the display format, order, and quantity of information provided to the user.

[0204] "Dynamic adjustment" refers to the process of changing the way information is presented in real time, depending on the analysis results and circumstances.

[0205] This invention develops a system for efficiently managing smart city projects. First, the user inputs basic project information via smartphone. This basic information includes the project's purpose, content, schedule, and number of people involved. The terminal retrieves this information and sends it to a server.

[0206] The server analyzes the input information using data processing tools and automatically generates basic tasks related to the project using a generative AI model. Data processing utilizes either the Flask or Django framework in Python. In parallel, the server collects relevant data from external sources, and based on this data, the collaboration tools propose additional tasks and schedule adjustments. External data may include, for example, other urban development databases or weather forecast APIs.

[0207] Furthermore, the emotion analysis engine identifies the user's current emotional state based on user input data and operation history. The emotion analysis utilizes a library employing NLP (Neuro-Linguistic Programming) technology. Based on these analysis results, an optimization mechanism adjusts the information presentation method in real time. For example, if the analysis indicates that the user is experiencing stress, the displayed information is simplified, prioritizing the presentation of highly important information.

[0208] For example, when managing the progress of an urban development project, if it is discovered that some tasks are behind schedule, it is possible to immediately notify the user of this information and adjust the suggested countermeasures based on their emotional state. An example of a prompt to be input into the generating AI model would be: "Consider ways to optimize the management of a smart city project and adjust the way information is presented to take user emotions into account."

[0209] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0210] Step 1:

[0211] The terminal retrieves basic project information from the user. The user uses a smartphone application to input the project's objectives, content, schedule, and number of people involved. The entered information is formatted as digital data within the terminal and prepared for transmission to the server.

[0212] Step 2:

[0213] The terminal sends basic project information to the server. HTTP communication is used for transmission, and formatted information is sent from the terminal to the server. The server receives this information and stores it in a database. Furthermore, the information is analyzed by data processing tools and processed as foundational data for the AI ​​agent to activate the generated AI model.

[0214] Step 3:

[0215] The server automatically generates project-related tasks using a generated AI model. The received basic information is analyzed by the AI ​​agent, which automatically generates relevant tasks based on task generation rules. Project management methodologies are considered, and task dependencies are also set simultaneously. The output is a list of initial tasks and their dependencies.

[0216] Step 4:

[0217] The server collects additional data from external sources, and the integration mechanism proposes tasks and schedule adjustments based on that data. For example, it retrieves data that may affect the project from weather forecast APIs and other relevant databases. The retrieved data is analyzed and reflected in the project schedule and tasks. The output is an updated task and schedule proposal.

[0218] Step 5:

[0219] The emotion analysis engine analyzes user input data and operation history. The server feeds the user's input data and system operation history into the emotion analysis engine. Using NLP technology, it identifies the user's emotional state and records the results. The analysis results are passed to an optimization mechanism, which becomes input to adjust the way information is presented.

[0220] Step 6:

[0221] The server dynamically adjusts the information presentation method based on the sentiment analysis results. An optimization mechanism references the analysis results and changes the format and content of the information presented to the user in real time. For example, if the user is stressed, the information is simplified and the display format is changed to highlight key points. The output is the final information screen presented to the user.

[0222] 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.

[0223] 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.

[0224] 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.

[0225] [Second Embodiment]

[0226] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0227] 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.

[0228] 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).

[0229] 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.

[0230] 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.

[0231] 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).

[0232] 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.

[0233] 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.

[0234] 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.

[0235] 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.

[0236] 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.

[0237] 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".

[0238] This invention is a system aimed at improving the efficiency of project management, and is implemented as follows.

[0239] First, the user enters basic project information, namely its purpose, content, overall schedule, and the number of participants. This provides the system with an overview of the project.

[0240] The entered information is received by the terminal, and after verifying that the format is correct, it is sent to the server. Based on the received information, the server uses information processing tools and an AI agent to automatically generate relevant initial tasks. These initial tasks are based on the basic framework of project management.

[0241] Next, the server retrieves additional data from external systems. This integration method leverages data from meeting minute-taking tools and other relevant external systems to create additional tasks and schedule adjustments based on the project's progress.

[0242] Next, the terminal provides an interface to present the user with tasks and schedule proposals generated from the server. Here, the user can view the task details and edit them as needed.

[0243] Users determine the content of tasks and schedules that are modified or approved through the interface. Based on this, the server stores the edited information using storage means. This stored data forms the basis for managing project progress and improving work efficiency.

[0244] For example, when launching a new software development project, the user inputs information such as "new software development," "from initial design to implementation," "4 months," and "6 people." The server then generates tasks such as "requirements definition," "system design," "coding," and "testing," and sets a schedule. External collaborations may also suggest the addition of new testing phases.

[0245] Thus, this invention prevents overlooking tasks required for project initiation and improves the overall efficiency of projects by enabling real-time schedule management and suggestion of additional tasks.

[0246] The following describes the processing flow.

[0247] Step 1:

[0248] The user enters basic information such as the project's purpose, content, overall schedule, and number of participants into the terminal. The entered information is checked for formatting correctness, and if there are no problems, the process proceeds to the next step.

[0249] Step 2:

[0250] The terminal serializes the information received from the user and sends it to the server as an API request. During this process, the information is properly encrypted and transmitted securely.

[0251] Step 3:

[0252] Based on the received project information, the server uses information processing tools to activate an AI agent, which automatically generates relevant initial tasks. The AI ​​agent analyzes a list of common tasks and their dependencies based on the project content, and creates the optimal task set.

[0253] Step 4:

[0254] The server uses integration methods to retrieve necessary data from external systems (such as meeting minute-taking tools and planning tools). Based on the retrieved data, the AI ​​agent then proposes additional tasks and schedule adjustments.

[0255] Step 5:

[0256] The server sends the generated tasks and proposed schedules to the terminal. The terminal receives them and provides an interface to display them to the user in a visually clear manner. The interface clearly shows the details of each task, its associated deadlines, and dependencies.

[0257] Step 6:

[0258] Users can use the terminal interface to review proposed tasks and schedules, and make modifications or additions as needed. Users can also change the order of tasks using drag-and-drop functionality and add new tasks directly on the interface.

[0259] Step 7:

[0260] The terminal sends the content edited by the user to the server, which then stores it in a database using a storage device. During this process, an update is performed to ensure that the latest state of the project is reflected in all related systems.

[0261] Step 8:

[0262] The server monitors project progress in real time and notifies users of task progress at every step. Users can check the system to see when to move on to the next step and when tasks are completed.

[0263] (Example 1)

[0264] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0265] In modern project management, a common problem is insufficient planning in the initial stages and delays in adjusting plans due to external factors. Furthermore, difficulty in tracking project progress and clarifying the relationships between tasks contributes to a decrease in overall project efficiency. These challenges are particularly pronounced in complex projects, highlighting the need for appropriate management strategies.

[0266] 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.

[0267] In this invention, the server includes a calculation means for receiving information and automatically generating related tasks based on that information; a cooperation means for acquiring information from an external device and proposing supplementary tasks and adjustments to the time plan based on the acquired information; and a display means for presenting the generated tasks and time plan to the user and making them editable. This enables the automation of task planning in the initial stages and flexible plan adjustments that take external factors into consideration, thereby improving the efficiency of project management.

[0268] "Receiving information" means that a system takes in data acquired from an external source and makes it ready for processing.

[0269] "Automatically generating related tasks" means automatically identifying and generating the necessary tasks based on the received data.

[0270] "Calculation means" refers to a device or software that has the function of processing data and performing calculations.

[0271] "Acquiring information from external devices" refers to the process of taking data from other systems or services.

[0272] "Proposing supplementary tasks and adjustments to the time plan" means making revisions to the existing plan or suggesting new tasks based on the additional data acquired.

[0273] "Means of cooperation" refer to mechanisms or methods for different functions or devices to exchange information with each other.

[0274] An "editable display method" is an interface that allows users to review the presented data and make adjustments or changes as needed.

[0275] "Storing" refers to saving collected information and keeping it accessible for later use.

[0276] "Managing the progress of work" means checking the progress of business operations and controlling the overall process to ensure smooth execution based on the plan.

[0277] This invention is a system for efficiently implementing project management. This system is composed of multiple means such as information processing, external collaboration, user interface, and memory. Specific embodiments of the system will be described below.

[0278] User Interaction:

[0279] The user inputs the basic information of the project into the system. This basic information includes the purpose, content, overall schedule, and number of participants of the project. The user uses a personal computer or a mobile terminal to input the information, and the data is accepted by the terminal.

[0280] Terminal Processing:

[0281] The terminal checks that the format of the information input by the user is correct. If there is no problem with the format, the terminal sends the information to the server. The terminal displays the modified tasks and schedules to the user via the user interface.

[0282] Server Information Processing:

[0283] The server automatically generates initial tasks by utilizing the AI model generated based on the received project information. For this, keywords such as "requirement definition", "design", and "implementation" are used as prompt sentences for the AI model. The server collaborates with external data sources to obtain additional data and proposes supplementary tasks and time plans. In this process, data is imported from the minutes creation tool and other systems.

[0284] Specific Example:

[0285] For example, when starting a new software development project, the user inputs basic information such as "new software development", "from initial design to implementation", "4 months", and "6 people". Based on this information, the server generates tasks such as "requirement definition", "system design", "coding", and "testing", and makes additional proposals for new test phases from an external database utilized for project progress.

[0286] Example of prompt sentence:

[0287] "Please describe the process of automatically generating initial tasks after basic information input and generating additional tasks based on external system data using the new project management system."

[0288] This system provides an environment where users can easily manage projects and quickly adjust tasks, enabling efficient project execution.

[0289] The flow of specific processing in Example 1 will be described using Figure 11.

[0290] Step 1:

[0291] The user inputs the basic information of the project. The input items include purpose, content, schedule, and number of participants. The information entered is confirmed by the terminal for correct format. If the data is correctly input, the data is sent to the server.

[0292] Step 2:

[0293] The server automatically generates initial tasks based on the received project information. Using a generation AI model, it identifies initial tasks according to the input information and generates keywords such as "requirement definition" and "design". The server sends this prompt sentence to the AI model and outputs an initial task list.

[0294] Step 3:

[0295] The server interacts with external devices to acquire additional data. This data includes information from tools such as meeting minute creation tools, and based on this, it proposes supplementary tasks and schedule adjustments. The server analyzes the external information to generate output for task additions and schedule modifications.

[0296] Step 4:

[0297] The terminal displays tasks and proposed schedules received from the server to the user. Through the user interface, the user can view task details and make necessary edits. When the user adjusts a task on the interface, those edits are sent to the server via the terminal.

[0298] Step 5:

[0299] The user performs final confirmation and revisions to the presented tasks. The results of the approval or revisions to the selected tasks and schedules are reflected on the server via the terminal.

[0300] Step 6:

[0301] The server stores data confirmed by users using storage means. The stored business data is used for project progress management and functions as foundational data to support the efficient execution of tasks.

[0302] (Application Example 1)

[0303] 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."

[0304] In the production project management in a factory, while improving the efficiency of work processes and plans is required, there are limitations in the manual generation of tasks and schedule adjustments. Also, it is difficult to monitor the progress of work in real time and respond quickly, and an automated management system for optimizing production efficiency is necessary.

[0305] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following respective means.

[0306] In this invention, the server includes means for recognizing the basic information of a project and automatically generating initial work related to the project, means for acquiring information from an external information source and proposing additional work and plan adjustments based on the acquired information, and means for automatically generating the production process in a factory, monitoring the progress of work in real time, and making adjustments. Thereby, efficient management of work processes and improvement of production efficiency by rapid progress monitoring become possible.

[0307] The "basic information of a project" is information necessary as the basis of a plan, such as the purpose, content, period, and number of participants of the project.

[0308] The "initial work" is the basic work process set at the start of a project and is a group of tasks necessary for grasping the overall picture of the project.

[0309] The "information processing means" is a system or technology for automating the work content based on the basic information of a project.

[0310] The "external information source" is a resource for acquiring information from databases and services located outside the system.

[0311] The "coordination means" is a method or technology for connecting to an external information source, collecting information, and making it available within the system.

[0312] "Display means" refers to interfaces or devices that intuitively present information to the user.

[0313] "Memory means" refers to a medium or technology for storing the progress of a project or the content of revised tasks.

[0314] A "notification method" is a system or method for informing users of the progress of tasks in progress within a project.

[0315] "Generation means" refers to a method or technology for automatically constructing production processes in a factory using AI technology.

[0316] "Real-world time" refers to the exact time when a task or situation is actually occurring, and it represents a state where information is provided with immediacy.

[0317] To realize this application example, the "Smart Factory Manager" system, it is necessary to build a project management system. The server first receives basic project information, and the AI ​​agent automatically generates initial tasks using information processing tools. In this process, a server equipped with a high-performance processor is used as hardware, and machine learning modules are utilized to execute the AI ​​model.

[0318] Next, the server uses means of integrating with external information sources to acquire additional information and adjust the work plan accordingly. Data is retrieved from external APIs, and necessary transformations and calculations are performed to generate the next work steps. This allows the project to allow for flexible plan changes based on the latest information.

[0319] The terminal provides an interface that displays generated tasks and schedules to the user. Through this interface, the user can review and edit tasks. The edited information is immediately sent to the server and securely stored by the storage system.

[0320] For example, when planning the launch of a new product line in a factory, the system automatically generates tasks such as "designing the new product line," "assigning line workers," and "initial testing and adjustments." Furthermore, the progress of the process is monitored in real time, and schedule adjustments are suggested as needed.

[0321] An example of a prompt using the generation AI model is: "Based on the project name: New production line, objective: Expansion of production capacity, duration: 3 months, and number of participants: 10, generate the initial tasks and schedule for the corresponding production process." This prompt allows the system to automatically suggest relevant tasks and plans.

[0322] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0323] Step 1:

[0324] The user enters basic project information into the terminal. This information includes the project name, purpose, duration, and number of participants. The terminal checks the format of the entered information and sends it to the server in the appropriate format.

[0325] Step 2:

[0326] The server uses a generation AI model to automatically generate initial tasks based on the basic project information it receives. During this process, it takes a prompt (e.g., "Based on the project name: New Production Line, objective: Expansion of production capacity, duration: 3 months, number of participants: 10, please generate the initial tasks and schedule for the corresponding production process") as input, and outputs a list of initial tasks from the AI ​​model.

[0327] Step 3:

[0328] The server acquires additional data using means of linking with external information sources. This additional data includes information on the progress of the process and resource availability, which is obtained via API. Based on this data, data processing is performed to generate proposed adjustments to tasks and schedules.

[0329] Step 4:

[0330] The generated tasks and proposed schedules are sent to the terminal, which then displays them to the user. The terminal provides a visual interface, allowing the user to review the details of each task and make modifications as needed.

[0331] Step 5:

[0332] After a user modifies a task or schedule, the changes are sent back to the server. The server stores the modified information in its memory and uses it for future project management.

[0333] Step 6:

[0334] The server monitors project progress in real time and notifies users of task progress using notification methods. This notification is provided in real time through the terminal, helping users respond quickly as needed.

[0335] 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.

[0336] This invention provides a system that streamlines project management while taking user emotions into consideration, and is implemented as follows.

[0337] First, the user inputs basic information such as the project's objectives, content, schedule, and number of participants into the terminal. This information is collected by the terminal and then sent to the server. The server uses information processing tools to invoke an AI agent, which generates appropriate initial tasks based on the input information. In this process, task dependencies are also considered based on project management methodologies.

[0338] Furthermore, the server acquires data information from external systems. This integration allows it to connect with external systems (e.g., meeting minute-taking tools or schedule management systems) and propose additional tasks or appropriate schedule adjustments. The proposed tasks and schedules are then managed in a way that is optimal for the user.

[0339] Next, the system uses an emotion engine to analyze the user's emotions from their input data and operation history. Based on the recognized emotions, the emotion engine dynamically adjusts how information is presented. For example, if it determines that the user is feeling stressed, it simplifies the display of tasks and provides additional support information sparingly.

[0340] The generated tasks and proposed schedules are presented to the user on their terminal. The user can then review the presented tasks and edit them as needed. The server then saves the edited task details to a database using a storage device, forming the basis for project progress management.

[0341] The emotion engine further optimizes alerts and notifications based on the user's emotions. For example, if a user is showing signs of fatigue, notifications for non-urgent project tasks will be kept to a minimum. In this way, the system supports the efficient progress of projects while providing a comfortable working environment for the user.

[0342] For example, if a user expresses anxiety as a project deadline approaches, the emotion engine can adjust the display to highlight high-priority tasks and postpone other information. In this way, project management can be carried out while taking user emotions into consideration.

[0343] The following describes the processing flow.

[0344] Step 1:

[0345] Users input basic information into their terminal, including the project's objectives, content, overall schedule, and number of participants. This information is essential for understanding the overall picture of the project.

[0346] Step 2:

[0347] The terminal receives information entered by the user, verifies its integrity, and then sends it to the server. Before transmission, the information is properly formatted and securely sent via the API.

[0348] Step 3:

[0349] The server analyzes the received project information and executes information processing using an AI agent. This automatically generates an initial task list required for the project. At this stage, task dependencies based on management methods are considered.

[0350] Step 4:

[0351] The server connects to external systems using integration methods to retrieve project-related data. Based on this data, it creates additional task suggestions and schedule adjustment proposals.

[0352] Step 5:

[0353] The server uses an emotion engine to analyze the user's past activity logs and real-time behavior to recognize the user's emotional state.

[0354] Step 6:

[0355] The server dynamically adjusts how tasks and schedules are displayed based on the user's perceived emotions. If the user is feeling stressed, information is presented in a simplified format.

[0356] Step 7:

[0357] The server sends the coordinated tasks and schedule to the terminal. The terminal presents this to the user as an interface, providing an environment where the user can visually organize and edit tasks.

[0358] Step 8:

[0359] Users review the tasks and schedules presented through their device and make any necessary changes. The edits are immediately updated and sent to the server.

[0360] Step 9:

[0361] The server receives user edits and stores them in a database using a storage device. The stored information is used for project management.

[0362] Step 10:

[0363] The server monitors project progress in real time and optimizes alerts and notifications to the user based on their emotions. For example, if a user shows signs of impatience, it will prioritize notifications for high-priority tasks.

[0364] (Example 2)

[0365] 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".

[0366] In project management, there are challenges in efficiently generating initial tasks and coordinating and scheduling appropriately. Furthermore, to reduce the workload on users, it is necessary to incorporate information presentation methods that respond to their emotional state. Smooth execution of this entire workflow and proper management of project progress are essential.

[0367] 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.

[0368] In this invention, the server includes information processing means that receive basic project information and automatically generate initial work items related to the project; cooperation means that acquire data from external information sources and propose additional work items and time management adjustments based on the acquired data; and emotion analysis means that analyze the user's emotional state and dynamically adjust the information presentation method. This improves the efficiency of project management and enables the provision of a work environment that takes the user's emotions into consideration.

[0369] "Information processing means" refers to a device or system that has the function of automatically generating initial work items based on the basic information of a project.

[0370] "Integration means" refers to a device or system that includes the function of acquiring data from external information sources and proposing additional work items or time management adjustments based on that data.

[0371] "Display means" refers to a device or system that has a user interface function that presents generated work items and time management to the user and allows for further editing.

[0372] "Storage means" refers to a database or storage device that stores the work edited by the user and continuously manages the progress of the project.

[0373] An "emotion analysis tool" is a device or system that analyzes a user's operation history and input data to infer their emotional state and dynamically adjusts the information presentation method accordingly.

[0374] A "notification means" is a device or system for monitoring the progress of a project in real time and notifying users of the latest status.

[0375] A "calculation tool" is a device or system that, based on project management methodologies, identifies the relationships between work items and creates an effective time management plan.

[0376] To implement this invention, project management primarily involves collaboration between three parties: a server, a terminal, and a user. The server handles the main processing and constitutes a system incorporating information processing means, collaboration means, sentiment analysis means, and so on. Specifically, it utilizes a cloud-based computing system, generates initial work items using a generative AI model, and collaborates with external information sources via APIs. The terminal receives input from the user and transmits and receives data with the server. The user inputs basic project information through the terminal and monitors and controls its progress.

[0377] The server automatically generates initial work items using a generative AI model based on the project's basic information. In this process, it leverages existing project management methods while using AI to efficiently design tasks. For example, it generates an optimal progress schedule while considering the temporal and logical dependencies of tasks.

[0378] Furthermore, the server uses integration methods to acquire data from external sources and connects with systems such as meeting minute creation and schedule management, thereby improving the overall accuracy of project management. This allows users to receive additional work items and suggestions for adjusting time management.

[0379] Furthermore, using emotion analysis tools, the server analyzes the user's emotional state and customizes the information presentation method. For example, if the user is feeling anxious, important tasks are visually highlighted, while other information is presented simply. In this way, support is provided to ensure efficient project management.

[0380] For example, when a user expresses anxiety as a project deadline approaches, the server will highlight high-priority tasks and refrain from displaying other information.

[0381] An example of a prompt for the generating AI model would be: "I want to generate initial project management tasks. The project objective is 'launching a new product,' and the deadline is 'in 3 months.' The team will consist of 10 people. Please suggest appropriate tasks and dependencies." Based on this prompt, the server will perform the initial setup of the project management.

[0382] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0383] Step 1:

[0384] The user enters basic information such as the project's purpose, content, schedule, and the number of team members into the terminal. The terminal formats this input information into JSON format and sends it to the server. Here, the input is the basic project information, and the output is the data format sent to the server.

[0385] Step 2:

[0386] The server, upon receiving basic information transmitted from the terminal, invokes a generation AI model to automatically generate initial work items based on this information. Specifically, it performs data calculations using project management techniques to generate a list of work items that consider task dependencies. The input is the received basic information, and the output is the generated list of work items.

[0387] Step 3:

[0388] The server uses API integration to retrieve additional data from external sources. Here, it obtains external data (e.g., meeting minutes or existing schedule information) and uses it to propose additional work items and time management adjustments. The input is data obtained from external systems, and the output is an integrated adjustment proposal.

[0389] Step 4:

[0390] The server analyzes the user's emotional state using emotion analysis tools. This involves analyzing the user's operation logs and input history to evaluate the emotional state. For example, frequent user activity might indicate impatience. The input is the user's operation log, and the output is the result of the emotional state analysis.

[0391] Step 5:

[0392] The server prepares the generated work items and adjustment proposals to be displayed on the terminal in a format optimized for the user's emotional state. This display preparation process involves highlighting important tasks and simplifying information. The input is the previously analyzed emotional state and work item list, and the output is the optimized display format.

[0393] Step 6:

[0394] The terminal displays work items and proposed schedules received from the server to the user, who then reviews and edits them. The edited content is sent back from the terminal to the server and reflected in the overall system's progress management. The input is the content displayed from the server, and the output is the edited work item information.

[0395] Step 7:

[0396] The server stores the edited data in a database via storage means. It also provides real-time notifications as the project progresses, keeping users informed of the latest status. These notifications are customized based on sentiment analysis results, according to the schedule and task importance. Input is the edited work information, and output is the stored data and notification information.

[0397] (Application Example 2)

[0398] 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".

[0399] Modern project management requires efficient progress management while integrating with diverse external data and considering the emotions of stakeholders. However, existing management systems are insufficient in linking with external information and optimizing information presentation according to emotional states, resulting in challenges in project efficiency and reducing stress among stakeholders.

[0400] 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.

[0401] In this invention, the server includes data processing means for acquiring basic project information and automatically generating basic tasks related to the project; cooperation means for collecting information from external organizations and proposing additional work or time adjustments based on the collected information; and optimization means for analyzing the operator's emotions using an emotion analysis engine and dynamically adjusting the information presentation method based on the analysis results. This improves the efficiency of project progress while enabling flexible information management that responds to the emotional states of stakeholders.

[0402] "Basic project information" refers to initial information about the project, such as its purpose, content, schedule, and the number of people involved.

[0403] A "data processing system" is a mechanism that has the function of automatically generating related basic tasks based on the basic information of the input project.

[0404] "External organizations" refer to external information sources and systems that can be integrated with the project management system, and are responsible for collecting necessary data.

[0405] A "collaboration mechanism" is a system that utilizes information obtained from external organizations to propose additional tasks or schedule adjustments.

[0406] An "emotion analysis engine" refers to a computing device or algorithm that analyzes user input data and operation history to identify the user's current emotional state.

[0407] An "optimization mechanism" is a system that dynamically adjusts the method and frequency of information presentation based on the results of the emotion analysis engine.

[0408] "Information presentation method" refers to the display format, order, and quantity of information provided to the user.

[0409] "Dynamic adjustment" refers to the process of changing the way information is presented in real time, depending on the analysis results and circumstances.

[0410] This invention develops a system for efficiently managing smart city projects. First, the user inputs basic project information via smartphone. This basic information includes the project's purpose, content, schedule, and number of people involved. The terminal retrieves this information and sends it to a server.

[0411] The server analyzes the input information using data processing tools and automatically generates basic tasks related to the project using a generative AI model. Data processing utilizes either the Flask or Django framework in Python. In parallel, the server collects relevant data from external sources, and based on this data, the collaboration tools propose additional tasks and schedule adjustments. External data may include, for example, other urban development databases or weather forecast APIs.

[0412] Furthermore, the emotion analysis engine identifies the user's current emotional state based on user input data and operation history. The emotion analysis utilizes a library employing NLP (Neuro-Linguistic Programming) technology. Based on these analysis results, an optimization mechanism adjusts the information presentation method in real time. For example, if the analysis indicates that the user is experiencing stress, the displayed information is simplified, prioritizing the presentation of highly important information.

[0413] For example, when managing the progress of an urban development project, if it is discovered that some tasks are behind schedule, it is possible to immediately notify the user of this information and adjust the suggested countermeasures based on their emotional state. An example of a prompt to be input into the generating AI model would be: "Consider ways to optimize the management of a smart city project and adjust the way information is presented to take user emotions into account."

[0414] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0415] Step 1:

[0416] The terminal retrieves basic project information from the user. The user uses a smartphone application to input the project's objectives, content, schedule, and number of people involved. The entered information is formatted as digital data within the terminal and prepared for transmission to the server.

[0417] Step 2:

[0418] The terminal sends basic project information to the server. HTTP communication is used for transmission, and formatted information is sent from the terminal to the server. The server receives this information and stores it in a database. Furthermore, the information is analyzed by data processing tools and processed as foundational data for the AI ​​agent to activate the generated AI model.

[0419] Step 3:

[0420] The server automatically generates project-related tasks using a generated AI model. The received basic information is analyzed by the AI ​​agent, which automatically generates relevant tasks based on task generation rules. Project management methodologies are considered, and task dependencies are also set simultaneously. The output is a list of initial tasks and their dependencies.

[0421] Step 4:

[0422] The server collects additional data from external sources, and the integration mechanism proposes tasks and schedule adjustments based on that data. For example, it retrieves data that may affect the project from weather forecast APIs and other relevant databases. The retrieved data is analyzed and reflected in the project schedule and tasks. The output is an updated task and schedule proposal.

[0423] Step 5:

[0424] The emotion analysis engine analyzes user input data and operation history. The server feeds the user's input data and system operation history into the emotion analysis engine. Using NLP technology, it identifies the user's emotional state and records the results. The analysis results are passed to an optimization mechanism, which becomes input to adjust the way information is presented.

[0425] Step 6:

[0426] The server dynamically adjusts the information presentation method based on the sentiment analysis results. An optimization mechanism references the analysis results and changes the format and content of the information presented to the user in real time. For example, if the user is stressed, the information is simplified and the display format is changed to highlight key points. The output is the final information screen presented to the user.

[0427] 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.

[0428] 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.

[0429] 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.

[0430] [Third Embodiment]

[0431] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0432] 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.

[0433] 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).

[0434] 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.

[0435] 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.

[0436] 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).

[0437] 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.

[0438] 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.

[0439] 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.

[0440] 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.

[0441] 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.

[0442] 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".

[0443] This invention is a system aimed at improving the efficiency of project management, and is implemented as follows.

[0444] First, the user enters basic project information, namely its purpose, content, overall schedule, and the number of participants. This provides the system with an overview of the project.

[0445] The entered information is received by the terminal, and after verifying that the format is correct, it is sent to the server. Based on the received information, the server uses information processing tools and an AI agent to automatically generate relevant initial tasks. These initial tasks are based on the basic framework of project management.

[0446] Next, the server retrieves additional data from external systems. This integration method leverages data from meeting minute-taking tools and other relevant external systems to create additional tasks and schedule adjustments based on the project's progress.

[0447] Next, the terminal provides an interface to present the user with tasks and schedule proposals generated from the server. Here, the user can view the task details and edit them as needed.

[0448] Users determine the content of tasks and schedules that are modified or approved through the interface. Based on this, the server stores the edited information using storage means. This stored data forms the basis for managing project progress and improving work efficiency.

[0449] For example, when launching a new software development project, the user inputs information such as "new software development," "from initial design to implementation," "4 months," and "6 people." The server then generates tasks such as "requirements definition," "system design," "coding," and "testing," and sets a schedule. External collaborations may also suggest the addition of new testing phases.

[0450] Thus, this invention prevents overlooking tasks required for project initiation and improves the overall efficiency of projects by enabling real-time schedule management and suggestion of additional tasks.

[0451] The following describes the processing flow.

[0452] Step 1:

[0453] The user enters basic information such as the project's purpose, content, overall schedule, and number of participants into the terminal. The entered information is checked for formatting correctness, and if there are no problems, the process proceeds to the next step.

[0454] Step 2:

[0455] The terminal serializes the information received from the user and sends it to the server as an API request. During this process, the information is properly encrypted and transmitted securely.

[0456] Step 3:

[0457] Based on the received project information, the server uses information processing tools to activate an AI agent, which automatically generates relevant initial tasks. The AI ​​agent analyzes a list of common tasks and their dependencies based on the project content, and creates the optimal task set.

[0458] Step 4:

[0459] The server uses integration methods to retrieve necessary data from external systems (such as meeting minute-taking tools and planning tools). Based on the retrieved data, the AI ​​agent then proposes additional tasks and schedule adjustments.

[0460] Step 5:

[0461] The server sends the generated tasks and proposed schedules to the terminal. The terminal receives them and provides an interface to display them to the user in a visually clear manner. The interface clearly shows the details of each task, its associated deadlines, and dependencies.

[0462] Step 6:

[0463] Users can use the terminal interface to review proposed tasks and schedules, and make modifications or additions as needed. Users can also change the order of tasks using drag-and-drop functionality and add new tasks directly on the interface.

[0464] Step 7:

[0465] The terminal sends the content edited by the user to the server, which then stores it in a database using a storage device. During this process, an update is performed to ensure that the latest state of the project is reflected in all related systems.

[0466] Step 8:

[0467] The server monitors project progress in real time and notifies users of task progress at every step. Users can check the system to see when to move on to the next step and when tasks are completed.

[0468] (Example 1)

[0469] 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."

[0470] In modern project management, a common problem is insufficient planning in the initial stages and delays in adjusting plans due to external factors. Furthermore, difficulty in tracking project progress and clarifying the relationships between tasks contributes to a decrease in overall project efficiency. These challenges are particularly pronounced in complex projects, highlighting the need for appropriate management strategies.

[0471] 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.

[0472] In this invention, the server includes a calculation means for receiving information and automatically generating related tasks based on that information; a cooperation means for acquiring information from an external device and proposing supplementary tasks and adjustments to the time plan based on the acquired information; and a display means for presenting the generated tasks and time plan to the user and making them editable. This enables the automation of task planning in the initial stages and flexible plan adjustments that take external factors into consideration, thereby improving the efficiency of project management.

[0473] "Receiving information" means that a system takes in data acquired from an external source and makes it ready for processing.

[0474] "Automatically generating related tasks" means automatically identifying and generating the necessary tasks based on the received data.

[0475] "Calculation means" refers to a device or software that has the function of processing data and performing calculations.

[0476] "Acquiring information from external devices" refers to the process of taking data from other systems or services.

[0477] "Proposing supplementary tasks and adjustments to the time plan" means making revisions to the existing plan or suggesting new tasks based on the additional data acquired.

[0478] "Means of cooperation" refer to mechanisms or methods for different functions or devices to exchange information with each other.

[0479] An "editable display method" is an interface that allows users to review the presented data and make adjustments or changes as needed.

[0480] "Storing" refers to saving collected information and keeping it accessible for later use.

[0481] "Managing the progress of work" means checking the progress of tasks and controlling the overall process to ensure it is carried out smoothly according to the plan.

[0482] This invention is a system for efficiently managing projects. This system consists of multiple means, including information processing, external integration, a user interface, and memory. Specific embodiments of the system are described below.

[0483] User interaction:

[0484] Users input basic project information into the system. This information includes the project's purpose, content, overall schedule, and number of participants. Users input the information using a PC or mobile device, and the data is received by the device.

[0485] Terminal processing:

[0486] The terminal verifies that the format of the information entered by the user is correct, and if there are no formatting issues, it sends the information to the server. The terminal then displays the corrected tasks and schedules to the user via the user interface.

[0487] Server information processing:

[0488] The server automatically generates initial tasks using an AI model based on the received project information. This involves using keywords such as "requirements definition," "design," and "implementation" as prompts for the AI ​​model. The server also integrates with external data sources to acquire additional data and propose supplementary tasks and time plans. This process incorporates data from meeting minute-taking tools and other systems.

[0489] Specific example:

[0490] For example, when starting a new software development project, the user inputs basic information such as "new software development," "from initial design to implementation," "4 months," and "6 people." Based on this information, the server generates tasks such as "requirements definition," "system design," "coding," and "testing," and proposes adding new test phases from an external database used to manage the project's progress.

[0491] Example of a prompt:

[0492] "Please describe the process of automatically generating initial tasks after basic information input and generating additional tasks based on external system data using the new project management system."

[0493] This system provides users with an environment that allows them to easily manage projects and quickly coordinate tasks, thereby enabling efficient project execution.

[0494] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0495] Step 1:

[0496] The user enters basic project information. Input fields include purpose, content, schedule, and number of participants. The terminal verifies that the entered information is in the correct format. If the data is entered correctly, it is sent to the server.

[0497] Step 2:

[0498] The server automatically generates initial tasks based on the received project information. Using a generation AI model, it identifies initial tasks according to the input information and generates keywords such as "requirements definition" and "design." The server sends this prompt message to the AI ​​model and outputs an initial task list.

[0499] Step 3:

[0500] The server interacts with external devices to acquire additional data. This data includes information from tools such as meeting minute creation tools, and based on this, it proposes supplementary tasks and schedule adjustments. The server analyzes the external information to generate output for task additions and schedule modifications.

[0501] Step 4:

[0502] The terminal displays tasks and proposed schedules received from the server to the user. Through the user interface, the user can view task details and make necessary edits. When the user adjusts a task on the interface, those edits are sent to the server via the terminal.

[0503] Step 5:

[0504] The user performs final confirmation and revisions to the presented tasks. The results of the approval or revisions to the selected tasks and schedules are reflected on the server via the terminal.

[0505] Step 6:

[0506] The server stores data confirmed by users using storage means. The stored business data is used for project progress management and functions as foundational data to support the efficient execution of tasks.

[0507] (Application Example 1)

[0508] 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."

[0509] In factory production project management, while there is a need to streamline work processes and plans, there are limitations to manual task generation and scheduling. Furthermore, monitoring work progress in real time and taking prompt action is difficult, necessitating an automated management system to optimize production efficiency.

[0510] 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.

[0511] In this invention, the server includes means for recognizing basic project information and automatically generating initial tasks related to the project; means for acquiring information from external sources and proposing additional tasks and plan adjustments based on the acquired information; and means for automatically generating production processes in a factory and monitoring and adjusting the progress of the work in real time. This enables efficient management of work processes and improved production efficiency through rapid progress monitoring.

[0512] "Basic project information" refers to information necessary as a foundation for planning, such as the project's objectives, content, duration, and number of participants.

[0513] "Initial work" refers to the basic work process set up at the start of a project, and is a set of tasks necessary to understand the overall picture of the project.

[0514] "Information processing means" refers to a system or technology for automating work based on the basic information of a project.

[0515] An "external information source" is a resource used to obtain information from databases or services located outside the system.

[0516] "Integration means" refers to methods or technologies for connecting with external information sources to collect information and making it available for use within the system.

[0517] "Display means" refers to interfaces or devices that intuitively present information to the user.

[0518] "Memory means" refers to a medium or technology for storing the progress of a project or the content of revised tasks.

[0519] A "notification method" is a system or method for informing users of the progress of tasks in progress within a project.

[0520] "Generation means" refers to a method or technology for automatically constructing production processes in a factory using AI technology.

[0521] "Real-world time" refers to the exact time when a task or situation is actually occurring, and it represents a state where information is provided with immediacy.

[0522] To realize this application example, the "Smart Factory Manager" system, it is necessary to build a project management system. The server first receives basic project information, and the AI ​​agent automatically generates initial tasks using information processing tools. In this process, a server equipped with a high-performance processor is used as hardware, and machine learning modules are utilized to execute the AI ​​model.

[0523] Next, the server uses means of integrating with external information sources to acquire additional information and adjust the work plan accordingly. Data is retrieved from external APIs, and necessary transformations and calculations are performed to generate the next work steps. This allows the project to allow for flexible plan changes based on the latest information.

[0524] The terminal provides an interface that displays generated tasks and schedules to the user. Through this interface, the user can review and edit tasks. The edited information is immediately sent to the server and securely stored by the storage system.

[0525] For example, when planning the launch of a new product line in a factory, the system automatically generates tasks such as "designing the new product line," "assigning line workers," and "initial testing and adjustments." Furthermore, the progress of the process is monitored in real time, and schedule adjustments are suggested as needed.

[0526] An example of a prompt using the generation AI model is: "Based on the project name: New production line, objective: Expansion of production capacity, duration: 3 months, and number of participants: 10, generate the initial tasks and schedule for the corresponding production process." This prompt allows the system to automatically suggest relevant tasks and plans.

[0527] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0528] Step 1:

[0529] The user enters basic project information into the terminal. This information includes the project name, purpose, duration, and number of participants. The terminal checks the format of the entered information and sends it to the server in the appropriate format.

[0530] Step 2:

[0531] The server uses a generation AI model to automatically generate initial tasks based on the basic project information it receives. During this process, it takes a prompt (e.g., "Based on the project name: New Production Line, objective: Expansion of production capacity, duration: 3 months, number of participants: 10, please generate the initial tasks and schedule for the corresponding production process") as input, and outputs a list of initial tasks from the AI ​​model.

[0532] Step 3:

[0533] The server acquires additional data using means of linking with external information sources. This additional data includes information on the progress of the process and resource availability, which is obtained via API. Based on this data, data processing is performed to generate proposed adjustments to tasks and schedules.

[0534] Step 4:

[0535] The generated tasks and proposed schedules are sent to the terminal, which then displays them to the user. The terminal provides a visual interface, allowing the user to review the details of each task and make modifications as needed.

[0536] Step 5:

[0537] After a user modifies a task or schedule, the changes are sent back to the server. The server stores the modified information in its memory and uses it for future project management.

[0538] Step 6:

[0539] The server monitors project progress in real time and notifies users of task progress using notification methods. This notification is provided in real time through the terminal, helping users respond quickly as needed.

[0540] 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.

[0541] This invention provides a system that streamlines project management while taking user emotions into consideration, and is implemented as follows.

[0542] First, the user inputs basic information such as the project's objectives, content, schedule, and number of participants into the terminal. This information is collected by the terminal and then sent to the server. The server uses information processing tools to invoke an AI agent, which generates appropriate initial tasks based on the input information. In this process, task dependencies are also considered based on project management methodologies.

[0543] Furthermore, the server acquires data information from external systems. This integration allows it to connect with external systems (e.g., meeting minute-taking tools or schedule management systems) and propose additional tasks or appropriate schedule adjustments. The proposed tasks and schedules are then managed in a way that is optimal for the user.

[0544] Next, the system uses an emotion engine to analyze the user's emotions from their input data and operation history. Based on the recognized emotions, the emotion engine dynamically adjusts how information is presented. For example, if it determines that the user is feeling stressed, it simplifies the display of tasks and provides additional support information sparingly.

[0545] The generated tasks and proposed schedules are presented to the user on their terminal. The user can then review the presented tasks and edit them as needed. The server then saves the edited task details to a database using a storage device, forming the basis for project progress management.

[0546] The emotion engine further optimizes alerts and notifications based on the user's emotions. For example, if a user is showing signs of fatigue, notifications for non-urgent project tasks will be kept to a minimum. In this way, the system supports the efficient progress of projects while providing a comfortable working environment for the user.

[0547] For example, if a user expresses anxiety as a project deadline approaches, the emotion engine can adjust the display to highlight high-priority tasks and postpone other information. In this way, project management can be carried out while taking user emotions into consideration.

[0548] The following describes the processing flow.

[0549] Step 1:

[0550] Users input basic information into their terminal, including the project's objectives, content, overall schedule, and number of participants. This information is essential for understanding the overall picture of the project.

[0551] Step 2:

[0552] The terminal receives information entered by the user, verifies its integrity, and then sends it to the server. Before transmission, the information is properly formatted and securely sent via the API.

[0553] Step 3:

[0554] The server analyzes the received project information and executes information processing using an AI agent. This automatically generates an initial task list required for the project. At this stage, task dependencies based on management methods are considered.

[0555] Step 4:

[0556] The server connects to external systems using integration methods to retrieve project-related data. Based on this data, it creates additional task suggestions and schedule adjustment proposals.

[0557] Step 5:

[0558] The server uses an emotion engine to analyze the user's past activity logs and real-time behavior to recognize the user's emotional state.

[0559] Step 6:

[0560] The server dynamically adjusts how tasks and schedules are displayed based on the user's perceived emotions. If the user is feeling stressed, information is presented in a simplified format.

[0561] Step 7:

[0562] The server sends the coordinated tasks and schedule to the terminal. The terminal presents this to the user as an interface, providing an environment where the user can visually organize and edit tasks.

[0563] Step 8:

[0564] Users review the tasks and schedules presented through their device and make any necessary changes. The edits are immediately updated and sent to the server.

[0565] Step 9:

[0566] The server receives user edits and stores them in a database using a storage device. The stored information is used for project management.

[0567] Step 10:

[0568] The server monitors project progress in real time and optimizes alerts and notifications to the user based on their emotions. For example, if a user shows signs of impatience, it will prioritize notifications for high-priority tasks.

[0569] (Example 2)

[0570] 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."

[0571] In project management, there are challenges in efficiently generating initial tasks and coordinating and scheduling appropriately. Furthermore, to reduce the workload on users, it is necessary to incorporate information presentation methods that respond to their emotional state. Smooth execution of this entire workflow and proper management of project progress are essential.

[0572] 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.

[0573] In this invention, the server includes information processing means that receive basic project information and automatically generate initial work items related to the project; cooperation means that acquire data from external information sources and propose additional work items and time management adjustments based on the acquired data; and emotion analysis means that analyze the user's emotional state and dynamically adjust the information presentation method. This improves the efficiency of project management and enables the provision of a work environment that takes the user's emotions into consideration.

[0574] "Information processing means" refers to a device or system that has the function of automatically generating initial work items based on the basic information of a project.

[0575] "Integration means" refers to a device or system that includes the function of acquiring data from external information sources and proposing additional work items or time management adjustments based on that data.

[0576] "Display means" refers to a device or system that has a user interface function that presents generated work items and time management to the user and allows for further editing.

[0577] "Storage means" refers to a database or storage device that stores the work edited by the user and continuously manages the progress of the project.

[0578] An "emotion analysis tool" is a device or system that analyzes a user's operation history and input data to infer their emotional state and dynamically adjusts the information presentation method accordingly.

[0579] A "notification means" is a device or system for monitoring the progress of a project in real time and notifying users of the latest status.

[0580] A "calculation tool" is a device or system that, based on project management methodologies, identifies the relationships between work items and creates an effective time management plan.

[0581] To implement this invention, project management primarily involves collaboration between three parties: a server, a terminal, and a user. The server handles the main processing and constitutes a system incorporating information processing means, collaboration means, sentiment analysis means, and so on. Specifically, it utilizes a cloud-based computing system, generates initial work items using a generative AI model, and collaborates with external information sources via APIs. The terminal receives input from the user and transmits and receives data with the server. The user inputs basic project information through the terminal and monitors and controls its progress.

[0582] The server automatically generates initial work items using a generative AI model based on the project's basic information. In this process, it leverages existing project management methods while using AI to efficiently design tasks. For example, it generates an optimal progress schedule while considering the temporal and logical dependencies of tasks.

[0583] Furthermore, the server uses integration methods to acquire data from external sources and connects with systems such as meeting minute creation and schedule management, thereby improving the overall accuracy of project management. This allows users to receive additional work items and suggestions for adjusting time management.

[0584] Furthermore, using emotion analysis tools, the server analyzes the user's emotional state and customizes the information presentation method. For example, if the user is feeling anxious, important tasks are visually highlighted, while other information is presented simply. In this way, support is provided to ensure efficient project management.

[0585] For example, when a user expresses anxiety as a project deadline approaches, the server will highlight high-priority tasks and refrain from displaying other information.

[0586] An example of a prompt for the generating AI model would be: "I want to generate initial project management tasks. The project objective is 'launching a new product,' and the deadline is 'in 3 months.' The team will consist of 10 people. Please suggest appropriate tasks and dependencies." Based on this prompt, the server will perform the initial setup of the project management.

[0587] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0588] Step 1:

[0589] The user enters basic information such as the project's purpose, content, schedule, and the number of team members into the terminal. The terminal formats this input information into JSON format and sends it to the server. Here, the input is the basic project information, and the output is the data format sent to the server.

[0590] Step 2:

[0591] The server, upon receiving basic information transmitted from the terminal, invokes a generation AI model to automatically generate initial work items based on this information. Specifically, it performs data calculations using project management techniques to generate a list of work items that consider task dependencies. The input is the received basic information, and the output is the generated list of work items.

[0592] Step 3:

[0593] The server uses API integration to retrieve additional data from external sources. Here, it obtains external data (e.g., meeting minutes or existing schedule information) and uses it to propose additional work items and time management adjustments. The input is data obtained from external systems, and the output is an integrated adjustment proposal.

[0594] Step 4:

[0595] The server analyzes the user's emotional state using emotion analysis tools. This involves analyzing the user's operation logs and input history to evaluate the emotional state. For example, frequent user activity might indicate impatience. The input is the user's operation log, and the output is the result of the emotional state analysis.

[0596] Step 5:

[0597] The server prepares the generated work items and adjustment proposals to be displayed on the terminal in a format optimized for the user's emotional state. This display preparation process involves highlighting important tasks and simplifying information. The input is the previously analyzed emotional state and work item list, and the output is the optimized display format.

[0598] Step 6:

[0599] The terminal displays work items and proposed schedules received from the server to the user, who then reviews and edits them. The edited content is sent back from the terminal to the server and reflected in the overall system's progress management. The input is the content displayed from the server, and the output is the edited work item information.

[0600] Step 7:

[0601] The server stores the edited data in a database via storage means. It also provides real-time notifications as the project progresses, keeping users informed of the latest status. These notifications are customized based on sentiment analysis results, according to the schedule and task importance. Input is the edited work information, and output is the stored data and notification information.

[0602] (Application Example 2)

[0603] 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."

[0604] Modern project management requires efficient progress management while integrating with diverse external data and considering the emotions of stakeholders. However, existing management systems are insufficient in linking with external information and optimizing information presentation according to emotional states, resulting in challenges in project efficiency and reducing stress among stakeholders.

[0605] 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.

[0606] In this invention, the server includes data processing means for acquiring basic project information and automatically generating basic tasks related to the project; cooperation means for collecting information from external organizations and proposing additional work or time adjustments based on the collected information; and optimization means for analyzing the operator's emotions using an emotion analysis engine and dynamically adjusting the information presentation method based on the analysis results. This improves the efficiency of project progress while enabling flexible information management that responds to the emotional states of stakeholders.

[0607] "Basic project information" refers to initial information about the project, such as its purpose, content, schedule, and the number of people involved.

[0608] A "data processing system" is a mechanism that has the function of automatically generating related basic tasks based on the basic information of the input project.

[0609] "External organizations" refer to external information sources and systems that can be integrated with the project management system, and are responsible for collecting necessary data.

[0610] A "collaboration mechanism" is a system that utilizes information obtained from external organizations to propose additional tasks or schedule adjustments.

[0611] An "emotion analysis engine" refers to a computing device or algorithm that analyzes user input data and operation history to identify the user's current emotional state.

[0612] An "optimization mechanism" is a system that dynamically adjusts the method and frequency of information presentation based on the results of the emotion analysis engine.

[0613] "Information presentation method" refers to the display format, order, and quantity of information provided to the user.

[0614] "Dynamic adjustment" refers to the process of changing the way information is presented in real time, depending on the analysis results and circumstances.

[0615] This invention develops a system for efficiently managing smart city projects. First, the user inputs basic project information via smartphone. This basic information includes the project's purpose, content, schedule, and number of people involved. The terminal retrieves this information and sends it to a server.

[0616] The server analyzes the input information using data processing tools and automatically generates basic tasks related to the project using a generative AI model. Data processing utilizes either the Flask or Django framework in Python. In parallel, the server collects relevant data from external sources, and based on this data, the collaboration tools propose additional tasks and schedule adjustments. External data may include, for example, other urban development databases or weather forecast APIs.

[0617] Furthermore, the emotion analysis engine identifies the user's current emotional state based on user input data and operation history. The emotion analysis utilizes a library employing NLP (Neuro-Linguistic Programming) technology. Based on these analysis results, an optimization mechanism adjusts the information presentation method in real time. For example, if the analysis indicates that the user is experiencing stress, the displayed information is simplified, prioritizing the presentation of highly important information.

[0618] For example, when managing the progress of an urban development project, if it is discovered that some tasks are behind schedule, it is possible to immediately notify the user of this information and adjust the suggested countermeasures based on their emotional state. An example of a prompt to be input into the generating AI model would be: "Consider ways to optimize the management of a smart city project and adjust the way information is presented to take user emotions into account."

[0619] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0620] Step 1:

[0621] The terminal retrieves basic project information from the user. The user uses a smartphone application to input the project's objectives, content, schedule, and number of people involved. The entered information is formatted as digital data within the terminal and prepared for transmission to the server.

[0622] Step 2:

[0623] The terminal sends basic project information to the server. HTTP communication is used for transmission, and formatted information is sent from the terminal to the server. The server receives this information and stores it in a database. Furthermore, the information is analyzed by data processing tools and processed as foundational data for the AI ​​agent to activate the generated AI model.

[0624] Step 3:

[0625] The server automatically generates project-related tasks using a generated AI model. The received basic information is analyzed by the AI ​​agent, which automatically generates relevant tasks based on task generation rules. Project management methodologies are considered, and task dependencies are also set simultaneously. The output is a list of initial tasks and their dependencies.

[0626] Step 4:

[0627] The server collects additional data from external sources, and the integration mechanism proposes tasks and schedule adjustments based on that data. For example, it retrieves data that may affect the project from weather forecast APIs and other relevant databases. The retrieved data is analyzed and reflected in the project schedule and tasks. The output is an updated task and schedule proposal.

[0628] Step 5:

[0629] The emotion analysis engine analyzes user input data and operation history. The server feeds the user's input data and system operation history into the emotion analysis engine. Using NLP technology, it identifies the user's emotional state and records the results. The analysis results are passed to an optimization mechanism, which becomes input to adjust the way information is presented.

[0630] Step 6:

[0631] The server dynamically adjusts the information presentation method based on the sentiment analysis results. An optimization mechanism references the analysis results and changes the format and content of the information presented to the user in real time. For example, if the user is stressed, the information is simplified and the display format is changed to highlight key points. The output is the final information screen presented to the user.

[0632] 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.

[0633] 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.

[0634] 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.

[0635] [Fourth Embodiment]

[0636] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0637] 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.

[0638] 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).

[0639] 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.

[0640] 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.

[0641] 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).

[0642] 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.

[0643] 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.

[0644] 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.

[0645] 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.

[0646] 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.

[0647] 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.

[0648] 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".

[0649] This invention is a system aimed at improving the efficiency of project management, and is implemented as follows.

[0650] First, the user enters basic project information, namely its purpose, content, overall schedule, and the number of participants. This provides the system with an overview of the project.

[0651] The entered information is received by the terminal, and after verifying that the format is correct, it is sent to the server. Based on the received information, the server uses information processing tools and an AI agent to automatically generate relevant initial tasks. These initial tasks are based on the basic framework of project management.

[0652] Next, the server retrieves additional data from external systems. This integration method leverages data from meeting minute-taking tools and other relevant external systems to create additional tasks and schedule adjustments based on the project's progress.

[0653] Next, the terminal provides an interface to present the user with tasks and schedule proposals generated from the server. Here, the user can view the task details and edit them as needed.

[0654] Users determine the content of tasks and schedules that are modified or approved through the interface. Based on this, the server stores the edited information using storage means. This stored data forms the basis for managing project progress and improving work efficiency.

[0655] For example, when launching a new software development project, the user inputs information such as "new software development," "from initial design to implementation," "4 months," and "6 people." The server then generates tasks such as "requirements definition," "system design," "coding," and "testing," and sets a schedule. External collaborations may also suggest the addition of new testing phases.

[0656] Thus, this invention prevents overlooking tasks required for project initiation and improves the overall efficiency of projects by enabling real-time schedule management and suggestion of additional tasks.

[0657] The following describes the processing flow.

[0658] Step 1:

[0659] The user enters basic information such as the project's purpose, content, overall schedule, and number of participants into the terminal. The entered information is checked for formatting correctness, and if there are no problems, the process proceeds to the next step.

[0660] Step 2:

[0661] The terminal serializes the information received from the user and sends it to the server as an API request. During this process, the information is properly encrypted and transmitted securely.

[0662] Step 3:

[0663] Based on the received project information, the server uses information processing tools to activate an AI agent, which automatically generates relevant initial tasks. The AI ​​agent analyzes a list of common tasks and their dependencies based on the project content, and creates the optimal task set.

[0664] Step 4:

[0665] The server uses integration methods to retrieve necessary data from external systems (such as meeting minute-taking tools and planning tools). Based on the retrieved data, the AI ​​agent then proposes additional tasks and schedule adjustments.

[0666] Step 5:

[0667] The server sends the generated tasks and proposed schedules to the terminal. The terminal receives them and provides an interface to display them to the user in a visually clear manner. The interface clearly shows the details of each task, its associated deadlines, and dependencies.

[0668] Step 6:

[0669] Users can use the terminal interface to review proposed tasks and schedules, and make modifications or additions as needed. Users can also change the order of tasks using drag-and-drop functionality and add new tasks directly on the interface.

[0670] Step 7:

[0671] The terminal sends the content edited by the user to the server, which then stores it in a database using a storage device. During this process, an update is performed to ensure that the latest state of the project is reflected in all related systems.

[0672] Step 8:

[0673] The server monitors project progress in real time and notifies users of task progress at every step. Users can check the system to see when to move on to the next step and when tasks are completed.

[0674] (Example 1)

[0675] 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".

[0676] In modern project management, a common problem is insufficient planning in the initial stages and delays in adjusting plans due to external factors. Furthermore, difficulty in tracking project progress and clarifying the relationships between tasks contributes to a decrease in overall project efficiency. These challenges are particularly pronounced in complex projects, highlighting the need for appropriate management strategies.

[0677] 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.

[0678] In this invention, the server includes a calculation means for receiving information and automatically generating related tasks based on that information; a cooperation means for acquiring information from an external device and proposing supplementary tasks and adjustments to the time plan based on the acquired information; and a display means for presenting the generated tasks and time plan to the user and making them editable. This enables the automation of task planning in the initial stages and flexible plan adjustments that take external factors into consideration, thereby improving the efficiency of project management.

[0679] "Receiving information" means that a system takes in data acquired from an external source and makes it ready for processing.

[0680] "Automatically generating related tasks" means automatically identifying and generating the necessary tasks based on the received data.

[0681] "Calculation means" refers to a device or software that has the function of processing data and performing calculations.

[0682] "Acquiring information from external devices" refers to the process of taking data from other systems or services.

[0683] "Proposing supplementary tasks and adjustments to the time plan" means making revisions to the existing plan or suggesting new tasks based on the additional data acquired.

[0684] "Means of cooperation" refer to mechanisms or methods for different functions or devices to exchange information with each other.

[0685] An "editable display method" is an interface that allows users to review the presented data and make adjustments or changes as needed.

[0686] "Storing" refers to saving collected information and keeping it accessible for later use.

[0687] "Managing the progress of work" means checking the progress of tasks and controlling the overall process to ensure it is carried out smoothly according to the plan.

[0688] This invention is a system for efficiently managing projects. This system consists of multiple means, including information processing, external integration, a user interface, and memory. Specific embodiments of the system are described below.

[0689] User interaction:

[0690] Users input basic project information into the system. This information includes the project's purpose, content, overall schedule, and number of participants. Users input the information using a PC or mobile device, and the data is received by the device.

[0691] Terminal processing:

[0692] The terminal verifies that the format of the information entered by the user is correct, and if there are no formatting issues, it sends the information to the server. The terminal then displays the corrected tasks and schedules to the user via the user interface.

[0693] Server information processing:

[0694] The server automatically generates initial tasks using an AI model based on the received project information. This involves using keywords such as "requirements definition," "design," and "implementation" as prompts for the AI ​​model. The server also integrates with external data sources to acquire additional data and propose supplementary tasks and time plans. This process incorporates data from meeting minute-taking tools and other systems.

[0695] Specific example:

[0696] For example, when starting a new software development project, the user inputs basic information such as "new software development," "from initial design to implementation," "4 months," and "6 people." Based on this information, the server generates tasks such as "requirements definition," "system design," "coding," and "testing," and proposes adding new test phases from an external database used to manage the project's progress.

[0697] Example of a prompt:

[0698] "Please describe the process of automatically generating initial tasks after basic information input and generating additional tasks based on external system data using the new project management system."

[0699] This system provides users with an environment that allows them to easily manage projects and quickly coordinate tasks, thereby enabling efficient project execution.

[0700] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0701] Step 1:

[0702] The user enters basic project information. Input fields include purpose, content, schedule, and number of participants. The terminal verifies that the entered information is in the correct format. If the data is entered correctly, it is sent to the server.

[0703] Step 2:

[0704] The server automatically generates initial tasks based on the received project information. Using a generation AI model, it identifies initial tasks according to the input information and generates keywords such as "requirements definition" and "design." The server sends this prompt message to the AI ​​model and outputs an initial task list.

[0705] Step 3:

[0706] The server interacts with external devices to acquire additional data. This data includes information from tools such as meeting minute creation tools, and based on this, it proposes supplementary tasks and schedule adjustments. The server analyzes the external information to generate output for task additions and schedule modifications.

[0707] Step 4:

[0708] The terminal displays tasks and proposed schedules received from the server to the user. Through the user interface, the user can view task details and make necessary edits. When the user adjusts a task on the interface, those edits are sent to the server via the terminal.

[0709] Step 5:

[0710] The user performs final confirmation and revisions to the presented tasks. The results of the approval or revisions to the selected tasks and schedules are reflected on the server via the terminal.

[0711] Step 6:

[0712] The server stores data confirmed by users using storage means. The stored business data is used for project progress management and functions as foundational data to support the efficient execution of tasks.

[0713] (Application Example 1)

[0714] 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".

[0715] In factory production project management, while there is a need to streamline work processes and plans, there are limitations to manual task generation and scheduling. Furthermore, monitoring work progress in real time and taking prompt action is difficult, necessitating an automated management system to optimize production efficiency.

[0716] 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.

[0717] In this invention, the server includes means for recognizing basic project information and automatically generating initial tasks related to the project; means for acquiring information from external sources and proposing additional tasks and plan adjustments based on the acquired information; and means for automatically generating production processes in a factory and monitoring and adjusting the progress of the work in real time. This enables efficient management of work processes and improved production efficiency through rapid progress monitoring.

[0718] "Basic project information" refers to information necessary as a foundation for planning, such as the project's objectives, content, duration, and number of participants.

[0719] "Initial work" refers to the basic work process set up at the start of a project, and is a set of tasks necessary to understand the overall picture of the project.

[0720] "Information processing means" refers to a system or technology for automating work based on the basic information of a project.

[0721] An "external information source" is a resource used to obtain information from databases or services located outside the system.

[0722] "Integration means" refers to methods or technologies for connecting with external information sources to collect information and making it available for use within the system.

[0723] "Display means" refers to interfaces or devices that intuitively present information to the user.

[0724] "Memory means" refers to a medium or technology for storing the progress of a project or the content of revised tasks.

[0725] A "notification method" is a system or method for informing users of the progress of tasks in progress within a project.

[0726] "Generation means" refers to a method or technology for automatically constructing production processes in a factory using AI technology.

[0727] "Real-world time" refers to the exact time when a task or situation is actually occurring, and it represents a state where information is provided with immediacy.

[0728] To realize this application example, the "Smart Factory Manager" system, it is necessary to build a project management system. The server first receives basic project information, and the AI ​​agent automatically generates initial tasks using information processing tools. In this process, a server equipped with a high-performance processor is used as hardware, and machine learning modules are utilized to execute the AI ​​model.

[0729] Next, the server uses means of integrating with external information sources to acquire additional information and adjust the work plan accordingly. Data is retrieved from external APIs, and necessary transformations and calculations are performed to generate the next work steps. This allows the project to allow for flexible plan changes based on the latest information.

[0730] The terminal provides an interface that displays generated tasks and schedules to the user. Through this interface, the user can review and edit tasks. The edited information is immediately sent to the server and securely stored by the storage system.

[0731] For example, when planning the launch of a new product line in a factory, the system automatically generates tasks such as "designing the new product line," "assigning line workers," and "initial testing and adjustments." Furthermore, the progress of the process is monitored in real time, and schedule adjustments are suggested as needed.

[0732] An example of a prompt using the generation AI model is: "Based on the project name: New production line, objective: Expansion of production capacity, duration: 3 months, and number of participants: 10, generate the initial tasks and schedule for the corresponding production process." This prompt allows the system to automatically suggest relevant tasks and plans.

[0733] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0734] Step 1:

[0735] The user enters basic project information into the terminal. This information includes the project name, purpose, duration, and number of participants. The terminal checks the format of the entered information and sends it to the server in the appropriate format.

[0736] Step 2:

[0737] The server uses a generation AI model to automatically generate initial tasks based on the basic project information it receives. During this process, it takes a prompt (e.g., "Based on the project name: New Production Line, objective: Expansion of production capacity, duration: 3 months, number of participants: 10, please generate the initial tasks and schedule for the corresponding production process") as input, and outputs a list of initial tasks from the AI ​​model.

[0738] Step 3:

[0739] The server acquires additional data using means of linking with external information sources. This additional data includes information on the progress of the process and resource availability, which is obtained via API. Based on this data, data processing is performed to generate proposed adjustments to tasks and schedules.

[0740] Step 4:

[0741] The generated tasks and proposed schedules are sent to the terminal, which then displays them to the user. The terminal provides a visual interface, allowing the user to review the details of each task and make modifications as needed.

[0742] Step 5:

[0743] After a user modifies a task or schedule, the changes are sent back to the server. The server stores the modified information in its memory and uses it for future project management.

[0744] Step 6:

[0745] The server monitors project progress in real time and notifies users of task progress using notification methods. This notification is provided in real time through the terminal, helping users respond quickly as needed.

[0746] 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.

[0747] This invention provides a system that streamlines project management while taking user emotions into consideration, and is implemented as follows.

[0748] First, the user inputs basic information such as the project's objectives, content, schedule, and number of participants into the terminal. This information is collected by the terminal and then sent to the server. The server uses information processing tools to invoke an AI agent, which generates appropriate initial tasks based on the input information. In this process, task dependencies are also considered based on project management methodologies.

[0749] Furthermore, the server acquires data information from external systems. This integration allows it to connect with external systems (e.g., meeting minute-taking tools or schedule management systems) and propose additional tasks or appropriate schedule adjustments. The proposed tasks and schedules are then managed in a way that is optimal for the user.

[0750] Next, the system uses an emotion engine to analyze the user's emotions from their input data and operation history. Based on the recognized emotions, the emotion engine dynamically adjusts how information is presented. For example, if it determines that the user is feeling stressed, it simplifies the display of tasks and provides additional support information sparingly.

[0751] The generated tasks and proposed schedules are presented to the user on their terminal. The user can then review the presented tasks and edit them as needed. The server then saves the edited task details to a database using a storage device, forming the basis for project progress management.

[0752] The emotion engine further optimizes alerts and notifications based on the user's emotions. For example, if a user is showing signs of fatigue, notifications for non-urgent project tasks will be kept to a minimum. In this way, the system supports the efficient progress of projects while providing a comfortable working environment for the user.

[0753] For example, if a user expresses anxiety as a project deadline approaches, the emotion engine can adjust the display to highlight high-priority tasks and postpone other information. In this way, project management can be carried out while taking user emotions into consideration.

[0754] The following describes the processing flow.

[0755] Step 1:

[0756] Users input basic information into their terminal, including the project's objectives, content, overall schedule, and number of participants. This information is essential for understanding the overall picture of the project.

[0757] Step 2:

[0758] The terminal receives information entered by the user, verifies its integrity, and then sends it to the server. Before transmission, the information is properly formatted and securely sent via the API.

[0759] Step 3:

[0760] The server analyzes the received project information and executes information processing using an AI agent. This automatically generates an initial task list required for the project. At this stage, task dependencies based on management methods are considered.

[0761] Step 4:

[0762] The server connects to external systems using integration methods to retrieve project-related data. Based on this data, it creates additional task suggestions and schedule adjustment proposals.

[0763] Step 5:

[0764] The server uses an emotion engine to analyze the user's past activity logs and real-time behavior to recognize the user's emotional state.

[0765] Step 6:

[0766] The server dynamically adjusts how tasks and schedules are displayed based on the user's perceived emotions. If the user is feeling stressed, information is presented in a simplified format.

[0767] Step 7:

[0768] The server sends the coordinated tasks and schedule to the terminal. The terminal presents this to the user as an interface, providing an environment where the user can visually organize and edit tasks.

[0769] Step 8:

[0770] Users review the tasks and schedules presented through their device and make any necessary changes. The edits are immediately updated and sent to the server.

[0771] Step 9:

[0772] The server receives user edits and stores them in a database using a storage device. The stored information is used for project management.

[0773] Step 10:

[0774] The server monitors project progress in real time and optimizes alerts and notifications to the user based on their emotions. For example, if a user shows signs of impatience, it will prioritize notifications for high-priority tasks.

[0775] (Example 2)

[0776] 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".

[0777] In project management, there are challenges in efficiently generating initial tasks and coordinating and scheduling appropriately. Furthermore, to reduce the workload on users, it is necessary to incorporate information presentation methods that respond to their emotional state. Smooth execution of this entire workflow and proper management of project progress are essential.

[0778] 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.

[0779] In this invention, the server includes information processing means that receive basic project information and automatically generate initial work items related to the project; cooperation means that acquire data from external information sources and propose additional work items and time management adjustments based on the acquired data; and emotion analysis means that analyze the user's emotional state and dynamically adjust the information presentation method. This improves the efficiency of project management and enables the provision of a work environment that takes the user's emotions into consideration.

[0780] "Information processing means" refers to a device or system that has the function of automatically generating initial work items based on the basic information of a project.

[0781] "Integration means" refers to a device or system that includes the function of acquiring data from external information sources and proposing additional work items or time management adjustments based on that data.

[0782] "Display means" refers to a device or system that has a user interface function that presents generated work items and time management to the user and allows for further editing.

[0783] "Storage means" refers to a database or storage device that stores the work edited by the user and continuously manages the progress of the project.

[0784] An "emotion analysis tool" is a device or system that analyzes a user's operation history and input data to infer their emotional state and dynamically adjusts the information presentation method accordingly.

[0785] A "notification means" is a device or system for monitoring the progress of a project in real time and notifying users of the latest status.

[0786] A "calculation tool" is a device or system that, based on project management methodologies, identifies the relationships between work items and creates an effective time management plan.

[0787] To implement this invention, project management primarily involves collaboration between three parties: a server, a terminal, and a user. The server handles the main processing and constitutes a system incorporating information processing means, collaboration means, sentiment analysis means, and so on. Specifically, it utilizes a cloud-based computing system, generates initial work items using a generative AI model, and collaborates with external information sources via APIs. The terminal receives input from the user and transmits and receives data with the server. The user inputs basic project information through the terminal and monitors and controls its progress.

[0788] The server automatically generates initial work items using a generative AI model based on the project's basic information. In this process, it leverages existing project management methods while using AI to efficiently design tasks. For example, it generates an optimal progress schedule while considering the temporal and logical dependencies of tasks.

[0789] Furthermore, the server uses integration methods to acquire data from external sources and connects with systems such as meeting minute creation and schedule management, thereby improving the overall accuracy of project management. This allows users to receive additional work items and suggestions for adjusting time management.

[0790] Furthermore, using emotion analysis tools, the server analyzes the user's emotional state and customizes the information presentation method. For example, if the user is feeling anxious, important tasks are visually highlighted, while other information is presented simply. In this way, support is provided to ensure efficient project management.

[0791] For example, when a user expresses anxiety as a project deadline approaches, the server will highlight high-priority tasks and refrain from displaying other information.

[0792] An example of a prompt for the generating AI model would be: "I want to generate initial project management tasks. The project objective is 'launching a new product,' and the deadline is 'in 3 months.' The team will consist of 10 people. Please suggest appropriate tasks and dependencies." Based on this prompt, the server will perform the initial setup of the project management.

[0793] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0794] Step 1:

[0795] The user enters basic information such as the project's purpose, content, schedule, and the number of team members into the terminal. The terminal formats this input information into JSON format and sends it to the server. Here, the input is the basic project information, and the output is the data format sent to the server.

[0796] Step 2:

[0797] The server, upon receiving basic information transmitted from the terminal, invokes a generation AI model to automatically generate initial work items based on this information. Specifically, it performs data calculations using project management techniques to generate a list of work items that consider task dependencies. The input is the received basic information, and the output is the generated list of work items.

[0798] Step 3:

[0799] The server uses API integration to retrieve additional data from external sources. Here, it obtains external data (e.g., meeting minutes or existing schedule information) and uses it to propose additional work items and time management adjustments. The input is data obtained from external systems, and the output is an integrated adjustment proposal.

[0800] Step 4:

[0801] The server analyzes the user's emotional state using emotion analysis tools. This involves analyzing the user's operation logs and input history to evaluate the emotional state. For example, frequent user activity might indicate impatience. The input is the user's operation log, and the output is the result of the emotional state analysis.

[0802] Step 5:

[0803] The server prepares the generated work items and adjustment proposals to be displayed on the terminal in a format optimized for the user's emotional state. This display preparation process involves highlighting important tasks and simplifying information. The input is the previously analyzed emotional state and work item list, and the output is the optimized display format.

[0804] Step 6:

[0805] The terminal displays work items and proposed schedules received from the server to the user, who then reviews and edits them. The edited content is sent back from the terminal to the server and reflected in the overall system's progress management. The input is the content displayed from the server, and the output is the edited work item information.

[0806] Step 7:

[0807] The server stores the edited data in a database via storage means. It also provides real-time notifications as the project progresses, keeping users informed of the latest status. These notifications are customized based on sentiment analysis results, according to the schedule and task importance. Input is the edited work information, and output is the stored data and notification information.

[0808] (Application Example 2)

[0809] 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".

[0810] Modern project management requires efficient progress management while integrating with diverse external data and considering the emotions of stakeholders. However, existing management systems are insufficient in linking with external information and optimizing information presentation according to emotional states, resulting in challenges in project efficiency and reducing stress among stakeholders.

[0811] 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.

[0812] In this invention, the server includes data processing means for acquiring basic project information and automatically generating basic tasks related to the project; cooperation means for collecting information from external organizations and proposing additional work or time adjustments based on the collected information; and optimization means for analyzing the operator's emotions using an emotion analysis engine and dynamically adjusting the information presentation method based on the analysis results. This improves the efficiency of project progress while enabling flexible information management that responds to the emotional states of stakeholders.

[0813] "Basic project information" refers to initial information about the project, such as its purpose, content, schedule, and the number of people involved.

[0814] A "data processing system" is a mechanism that has the function of automatically generating related basic tasks based on the basic information of the input project.

[0815] "External organizations" refer to external information sources and systems that can be integrated with the project management system, and are responsible for collecting necessary data.

[0816] A "collaboration mechanism" is a system that utilizes information obtained from external organizations to propose additional tasks or schedule adjustments.

[0817] An "emotion analysis engine" refers to a computing device or algorithm that analyzes user input data and operation history to identify the user's current emotional state.

[0818] An "optimization mechanism" is a system that dynamically adjusts the method and frequency of information presentation based on the results of the emotion analysis engine.

[0819] "Information presentation method" refers to the display format, order, and quantity of information provided to the user.

[0820] "Dynamic adjustment" refers to the process of changing the way information is presented in real time, depending on the analysis results and circumstances.

[0821] This invention develops a system for efficiently managing smart city projects. First, the user inputs basic project information via smartphone. This basic information includes the project's purpose, content, schedule, and number of people involved. The terminal retrieves this information and sends it to a server.

[0822] The server analyzes the input information using data processing tools and automatically generates basic tasks related to the project using a generative AI model. Data processing utilizes either the Flask or Django framework in Python. In parallel, the server collects relevant data from external sources, and based on this data, the collaboration tools propose additional tasks and schedule adjustments. External data may include, for example, other urban development databases or weather forecast APIs.

[0823] Furthermore, the emotion analysis engine identifies the user's current emotional state based on user input data and operation history. The emotion analysis utilizes a library employing NLP (Neuro-Linguistic Programming) technology. Based on these analysis results, an optimization mechanism adjusts the information presentation method in real time. For example, if the analysis indicates that the user is experiencing stress, the displayed information is simplified, prioritizing the presentation of highly important information.

[0824] For example, when managing the progress of an urban development project, if it is discovered that some tasks are behind schedule, it is possible to immediately notify the user of this information and adjust the suggested countermeasures based on their emotional state. An example of a prompt to be input into the generating AI model would be: "Consider ways to optimize the management of a smart city project and adjust the way information is presented to take user emotions into account."

[0825] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0826] Step 1:

[0827] The terminal retrieves basic project information from the user. The user uses a smartphone application to input the project's objectives, content, schedule, and number of people involved. The entered information is formatted as digital data within the terminal and prepared for transmission to the server.

[0828] Step 2:

[0829] The terminal sends basic project information to the server. HTTP communication is used for transmission, and formatted information is sent from the terminal to the server. The server receives this information and stores it in a database. Furthermore, the information is analyzed by data processing tools and processed as foundational data for the AI ​​agent to activate the generated AI model.

[0830] Step 3:

[0831] The server automatically generates project-related tasks using a generated AI model. The received basic information is analyzed by the AI ​​agent, which automatically generates relevant tasks based on task generation rules. Project management methodologies are considered, and task dependencies are also set simultaneously. The output is a list of initial tasks and their dependencies.

[0832] Step 4:

[0833] The server collects additional data from external sources, and the integration mechanism proposes tasks and schedule adjustments based on that data. For example, it retrieves data that may affect the project from weather forecast APIs and other relevant databases. The retrieved data is analyzed and reflected in the project schedule and tasks. The output is an updated task and schedule proposal.

[0834] Step 5:

[0835] The emotion analysis engine analyzes user input data and operation history. The server feeds the user's input data and system operation history into the emotion analysis engine. Using NLP technology, it identifies the user's emotional state and records the results. The analysis results are passed to an optimization mechanism, which becomes input to adjust the way information is presented.

[0836] Step 6:

[0837] The server dynamically adjusts the information presentation method based on the sentiment analysis results. An optimization mechanism references the analysis results and changes the format and content of the information presented to the user in real time. For example, if the user is stressed, the information is simplified and the display format is changed to highlight key points. The output is the final information screen presented to the user.

[0838] 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.

[0839] 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.

[0840] In the above embodiment, an example was given in which the 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.

[0841] 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.

[0842] 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.

[0843] 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.

[0844] 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.

[0845] 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.

[0846] 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."

[0847] 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.

[0848] 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.

[0849] 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.

[0850] 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.

[0851] 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.

[0852] 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.

[0853] 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.

[0854] 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.

[0855] 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.

[0856] 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.

[0857] 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.

[0858] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0859] The following is further disclosed regarding the embodiments described above.

[0860] (Claim 1)

[0861] Information processing means that receives basic project information and automatically generates initial tasks related to the project,

[0862] A means of integration that acquires data from an external system and proposes additional tasks and schedule adjustments based on the acquired data,

[0863] An interface for editing and presenting generated tasks and schedules to the user,

[0864] A storage means for saving user-edited content and managing project progress,

[0865] A system that includes this.

[0866] (Claim 2)

[0867] The system according to claim 1, comprising a notification means for monitoring the progress of a project in real time and notifying the progress of tasks.

[0868] (Claim 3)

[0869] The system according to claim 1, comprising a calculation means for identifying task dependencies and creating a proposed schedule based on a project management methodology.

[0870] "Example 1"

[0871] (Claim 1)

[0872] A calculation means that receives information and automatically generates related tasks based on said information,

[0873] A collaborative means that acquires information from external devices and proposes supplementary tasks or adjustments to time plans based on the acquired information,

[0874] The generated tasks and time plans are presented to the user, and an editable display method is provided.

[0875] A storage means that stores user-adjusted information and manages the progress of the work,

[0876] A system that includes this.

[0877] (Claim 2)

[0878] The system according to claim 1, which includes means for sequentially monitoring the progress of work and notifying the progress of work.

[0879] (Claim 3)

[0880] The system according to claim 1, comprising a calculation means for clarifying the dependencies of tasks and creating a plan based on the method of performing the tasks.

[0881] "Application Example 1"

[0882] (Claim 1)

[0883] Information processing means that recognizes basic project information and automatically generates initial tasks related to the project,

[0884] A collaborative means of acquiring information from external sources and proposing additional work or plan adjustments based on the acquired information,

[0885] A means of displaying the generated tasks and plans, and presenting them to the user,

[0886] A storage means for accumulating user-modified content and managing project progress,

[0887] A means of monitoring project progress in real time and reporting the progress of work,

[0888] A generation method for automatically generating production processes in a factory and monitoring and adjusting the progress of work in real time,

[0889] A system that includes this.

[0890] (Claim 2)

[0891] The system according to claim 1, comprising a computation means for identifying task dependencies and constructing a plan, and an adjustment means for improving production efficiency within a factory.

[0892] (Claim 3)

[0893] The system according to claim 1, which implements a method for optimizing the work schedule of a project using a generative AI model.

[0894] "Example 2 of combining an emotion engine"

[0895] (Claim 1)

[0896] Information processing means that receives basic project information and automatically generates initial work items related to the project,

[0897] A means of collaboration that acquires data from external sources and proposes additional work items and time management adjustments based on the acquired data,

[0898] A means of displaying the generated work items and time management data, and presenting them to the user.

[0899] A storage method for saving user-edited content and managing project progress,

[0900] An emotion analysis means that analyzes the user's emotional state and dynamically adjusts the information presentation method,

[0901] A system that includes this.

[0902] (Claim 2)

[0903] The system according to claim 1, which includes a notification means for monitoring project progress in real time and informing of the progress status of work items.

[0904] (Claim 3)

[0905] The system according to claim 1, comprising a calculation means for identifying the relationships between work items and creating a time management plan based on a project management methodology.

[0906] "Application example 2 when combining with an emotional engine"

[0907] (Claim 1)

[0908] A data processing means for acquiring basic project information and automatically generating basic tasks related to the project,

[0909] A collaborative means of collecting information from external organizations and proposing additional work or time adjustments based on the collected information,

[0910] A means of communication to modify the generated tasks and schedules and present them to the operator,

[0911] A memory device that stores the changes made by the operator and manages the progress of the project,

[0912] An optimization means that analyzes the operator's emotions using an emotion analysis engine and dynamically adjusts the information presentation method based on the analysis results,

[0913] A system that includes this.

[0914] (Claim 2)

[0915] The system according to claim 1, comprising a means for monitoring the progress of a project in real time and notifying the progress of tasks, and an adjustment means for adjusting the importance and frequency of information notifications, taking into account the emotions of the operator.

[0916] (Claim 3)

[0917] The system according to claim 1, which includes an adjustment means for identifying task dependencies and creating a time plan based on a project management method, and for dynamically changing task priorities according to the emotional state of the operator. [Explanation of symbols]

[0918] 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. Information processing means that receives basic project information and automatically generates initial tasks related to the project, A means of integration that acquires data from an external system and proposes additional tasks and schedule adjustments based on the acquired data, An interface for editing and presenting generated tasks and schedules to the user, A storage means for saving user-edited content and managing project progress, A system that includes this.

2. The system according to claim 1, which includes a notification means for monitoring the progress of a project in real time and notifying the progress of tasks.

3. The system according to claim 1, comprising a calculation means for identifying task dependencies and creating a proposed schedule based on a project management methodology.

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