system

Abstract

We provide the system. [Solution] Means for acquiring communication data, Information processing means for extracting information related to achieving the goal from the aforementioned communication data, A situation determination means for evaluating the progress based on the information analyzed by the aforementioned information processing means, A means for generating alternative solutions that references a database of similar past cases to generate the optimal solution, A notification means for transmitting the aforementioned solution to the user, A system that analyzes information from logistics facilities, detects delivery delays, and includes functions to suggest additional personnel or route optimization.

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, the method including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In conventional progress management and problem - solving processes in goal management, much labor and time are required, and information analysis and presentation of appropriate solutions are subjective, so it is inefficient. Therefore, there is a need for a system that can appropriately grasp progress from a huge amount of communication information and quickly and effectively solve problems by utilizing past experience and data.

Means for Solving the Problems

[0005] This invention acquires necessary information from an email system and a schedule management system via a communication information acquisition means, and extracts and analyzes information related to goal management using an information analysis means. Furthermore, a situation evaluation means objectively evaluates the progress, and a solution generation means uses a generative artificial intelligence model to refer to a database of similar past cases and generate the optimal solution. This allows the system to quickly provide the user with a solution via a notification means and support them in achieving their goals.

[0006] A "communication information acquisition means" is a component equipped with the function of acquiring digital information from systems such as email systems and schedule management systems.

[0007] An "information analysis means" is a component equipped with the function of extracting and analyzing information related to goal management from acquired communication information.

[0008] A "situation evaluation means" is a component that has the function of objectively evaluating the progress toward achieving the goal based on information analyzed by an information analysis means.

[0009] A "database of similar past cases" is a data storage system that accumulates information on similar cases and incidents that have occurred in the past and keeps it in a referable format.

[0010] A "solution generation means" is a component that uses a generative artificial intelligence model to refer to a database of similar past cases and has the functionality to generate the optimal solution for a specific problem.

[0011] A "notification mechanism" is a component that has the functionality to appropriately communicate information about generated solutions and progress evaluations to the user.

[0012] A "generative artificial intelligence model" is a type of artificial intelligence technology that uses natural language processing and machine learning techniques to generate new information or solutions based on input information. [Brief explanation of the drawing]

[0013] [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]

[0014] An example of an embodiment of the system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0015] First, the terms used in the following description will be explained.

[0016] In the following embodiments, the numbered 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.

[0017] In the following embodiments, the numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0018] In the following embodiments, the numbered storage is one or more non-volatile storage devices that store various programs, various parameters, and the like. 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.

[0019] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0020] 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."

[0021] [First Embodiment]

[0022] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0023] 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.

[0024] 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).

[0025] 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.

[0026] 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.

[0027] 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.

[0028] 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.

[0029] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0030] 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.

[0031] 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.

[0032] 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.

[0033] 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".

[0034] As an embodiment of the present invention, a support system for progress management and problem-solving proposals using a generated AI model is described below. In this system, the server, terminal, and user each play specific roles, thereby improving the efficiency of management by objectives (MBO).

[0035] The server first uses communication information acquisition methods to periodically retrieve necessary information from email systems and schedule management systems. This information is stored and managed in a secure database. This information includes project-related email content, scheduled meetings, and deadlines.

[0036] Next, the server uses information analysis tools to analyze the collected data. This analysis includes a process of extracting important keywords and context using natural language processing techniques and identifying information relevant to the goals. This makes it easier for the server to understand the project's progress.

[0037] The situation assessment mechanism allows the server to evaluate progress based on the analyzed data. For example, it can identify whether scheduled tasks are behind schedule or where problems are likely to occur. This enables early detection of situations that jeopardize goal achievement.

[0038] The server then refers to a database of similar past cases and uses a solution generation tool to generate the optimal solution for the identified problem. This process utilizes a generative artificial intelligence model to create optimal action plans based on past success stories.

[0039] The terminal is responsible for notifying the user of information provided by the server. Through notification methods, the terminal presents the user with progress information and suggested solutions via dashboards and alerts. This allows the user to take appropriate action in a timely manner.

[0040] For example, if a project is behind schedule, the server analyzes relevant emails and meeting records and determines that a resource shortage is the cause. Based on past cases where similar resource shortages were resolved, the server generates a proposal for reallocating resources and notifies the user via their terminal. The user can then quickly adjust project members based on this proposal.

[0041] Thus, the system of the present invention provides users with the timely support necessary to efficiently achieve their MBO goals.

[0042] The following describes the processing flow.

[0043] Step 1:

[0044] The server uses a communication information acquisition method to access the email system and schedule management system through a pre-configured API and retrieve the necessary data. The information obtained here includes project-related email content, meeting dates, and task deadlines.

[0045] Step 2:

[0046] The server analyzes the data acquired using information analysis tools, employing text analysis tools (e.g., natural language processing techniques). This step extracts key keywords and context, identifying information relevant to the objectives. This helps to uncover project progress and potential problems.

[0047] Step 3:

[0048] The server uses situation assessment tools to evaluate the project's progress based on the analyzed information. This evaluation includes identifying tasks that are behind schedule and predicting potential risks. This allows the server to recognize factors that could hinder the achievement of the goals.

[0049] Step 4:

[0050] The server accesses a database of similar past cases and uses solution generation tools to generate the optimal solution for the identified problem. In this step, a generative artificial intelligence model is used to create the optimal strategy and action plan based on past successes.

[0051] Step 5:

[0052] The device uses notification methods to inform the user of progress and generated solutions. Notifications are displayed as dashboards and alerts, and the user can view detailed reports.

[0053] Step 6:

[0054] Based on notifications received through their devices, users make decisions to take suggested actions. If necessary, users can share information with their team and seek further feedback, enabling them to take action towards achieving their goals.

[0055] (Example 1)

[0056] 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."

[0057] In project management, a challenge lies in the difficulty of tracking progress toward achieving goals and identifying potential risks early on. Furthermore, it is not easy to derive concrete actions for optimizing resources and quickly resolving problems. These factors hinder efficient goal management.

[0058] 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.

[0059] In this invention, the server includes an acquisition means for acquiring communication information, an analysis means for extracting information related to goal management from the acquired communication information using natural language processing, and an evaluation means for evaluating the progress of the project and identifying risks based on the extracted information. This enables accurate understanding of the progress in project management, early detection of potential problems, and provision of optimal solutions utilizing generative AI models.

[0060] "Means for acquiring communication information" refers to devices or software that have the technical functions to collect information from sources such as email and schedule management systems.

[0061] "Analysis methods for extracting information related to goal management using natural language processing" refers to a technology that analyzes text data, detects specific keywords and contexts, and identifies information important for goal management.

[0062] "Evaluation tools for assessing project progress and identifying risks" are technologies that have analytical capabilities to determine the progress of tasks and potential problems based on collected and analyzed information.

[0063] "Generative methods for deriving optimal solutions using generative AI models" refers to technologies that utilize generative artificial intelligence to learn from similar past cases and create efficient action plans.

[0064] A "notification means" is a device or mechanism that has communication functions to effectively convey generated information or action plans to users.

[0065] This invention is a system that uses a generative AI model to monitor project progress and propose solutions to problems in project management. In implementing this invention, it is assumed that the server, terminal, and user each play different roles.

[0066] The server periodically collects information from systems such as email systems and scheduling management systems. Specifically, it accesses these systems to retrieve relevant communication information and stores it in a secure database. High-performance storage systems and security software are used for this data management.

[0067] The collected data is analyzed on the server using natural language processing software. This analysis software automatically extracts key keywords and contexts related to the project and organizes useful information from a goal management perspective.

[0068] Furthermore, the server uses a situation assessment algorithm to evaluate the project's progress based on the extracted information. Risk management software identifies task delays and potential problems, thereby clarifying the prospects for achieving the goals.

[0069] Once a problem is identified, the server uses a generative AI model to generate the optimal solution from a historical database. The generated solution is then notified to the user via their terminal. This process requires a high-performance AI engine.

[0070] The device notifies the user of progress information and solutions provided by the server using visually easy-to-understand dashboards and alerts. This allows the user to make timely and appropriate decisions.

[0071] As a concrete example, if a project is behind schedule, the server uses natural language processing to identify resource shortages as the cause. Based on similar past cases, a generative AI model proposes resource reallocation and notifies the user via their terminal. The user can then quickly adjust the schedules of team members based on this proposal.

[0072] A concrete example of a prompt message is "Check the progress of the development project and generate resource optimization suggestions." This prompt serves as a starting point for the server to evaluate the progress and appropriate resource allocation.

[0073] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0074] Step 1:

[0075] The server collects necessary information from the email system and schedule management system using communication information acquisition methods. Input requires access rights to email accounts and schedule information. This information is retrieved periodically and stored as output in a secure database. Specifically, the server logs in daily, checks for new emails and schedule events, and writes them to the database.

[0076] Step 2:

[0077] The server analyzes the data collected using information analysis tools. The input is the communication information saved in step 1. Using natural language processing (NLP) software, it extracts important keywords and context related to the project and organizes the information necessary for goal management. The output is a list of project-related keywords. Specifically, the server executes a text analysis algorithm to extract keywords such as "deadline," "progress," and "issues."

[0078] Step 3:

[0079] The server uses a situation assessment tool to evaluate the project's progress based on the analyzed information. The keyword list extracted in step 2 is used as input. This data is used to run an evaluation algorithm to identify task delays and risks. An evaluation results report is generated as output. Specifically, the server compares the scheduled completion date of a task with the current date and creates a list of delayed tasks.

[0080] Step 4:

[0081] The server uses a solution generation mechanism to refer to a database of similar past cases and generate the optimal solution. The evaluation results generated in step 3 are used as input. The generation AI model is utilized to output the optimal action plan based on the database. Specifically, the server searches for similar problem-solving cases and creates the optimal action plan proposed by the AI.

[0082] Step 5:

[0083] The terminal notifies the user based on information sent from the server. The solution generated in step 4 is received by the terminal as input. Using notification methods, progress information and suggested solutions are displayed to the user through dashboards and alerts. The output provides the user with clear instructions for action. Specifically, the terminal sends a notification to the user's device and displays the solution on the dashboard.

[0084] This series of processes enables users to make appropriate and swift decisions and efficiently achieve their goals.

[0085] (Application Example 1)

[0086] 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."

[0087] In logistics facilities, it is crucial to streamline progress management and problem resolution regarding package delivery. However, conventional systems failed to detect delays and develop appropriate countermeasures in a timely manner, leading to decreased productivity. Furthermore, manual management was inefficient and placed a burden on the overall project progress.

[0088] 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.

[0089] In this invention, the server includes means for acquiring communication data, means for processing information, means for determining the situation, means for generating alternative solutions, means for notifying, and a function for analyzing information in logistics facilities, detecting delivery delays, and proposing additional personnel or route optimization. This makes it possible to streamline package management within logistics facilities and to quickly manage progress and resolve issues.

[0090] "Communication data acquisition means" refers to a device or software that has the function of acquiring necessary data from email or a schedule management system.

[0091] "Information processing means" refers to a technology or process for extracting and analyzing meaningful information related to achieving a goal from acquired data.

[0092] "Situation assessment means" refers to methods and devices for evaluating progress based on analyzed data and identifying problems and delays.

[0093] A "means for generating alternative solutions" refers to a system or model that generates the optimal solution by referring to a database of similar past cases.

[0094] A "notification system" refers to a communication or notification system used to convey generated solutions or proposals to users.

[0095] A "logistics facility" refers to a center or building used for packaging, storing, transporting, and sorting goods.

[0096] As an embodiment of the present invention, a system that supports progress management and problem-solving of packages within a logistics facility will be described. In this system, the server, terminals, and users each play specific roles in order to improve the efficiency of the logistics process.

[0097] The server periodically retrieves data from the email system and schedule management system using communication data acquisition means. This data includes information such as delivery schedules and shipping status. The retrieved data is stored in a secure database. Next, the server uses information processing means to analyze the data and employs natural language processing techniques to extract important information related to achieving goals. Particular emphasis is placed on determining information about transportation delays and the progress of scheduled tasks.

[0098] Based on the analyzed data, the server uses a situation assessment tool to evaluate the progress within the logistics facility. This allows for, for example, the detection of delays in arriving packages and the identification of situations requiring action. For detected problems, the system utilizes an alternative solution generation tool to propose the optimal solution based on similar past cases. This process is carried out using a generative AI model, which seeks the optimal solution based on past success stories.

[0099] The generated solutions are notified to the user via a notification system through the device. The device's notification function is used to display progress information and proposed solutions through a dashboard or alerts.

[0100] For example, if a delivery at a logistics facility is delayed beyond the scheduled time, the server analyzes the cause and suggests additional personnel or route optimization. Based on this information, users can take the next steps quickly and effectively.

[0101] A concrete example of a prompt message would be, "Please tell me the best solution in case of a delivery delay." This allows the user to easily receive problem-solving solutions generated by the AI ​​model.

[0102] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0103] Step 1:

[0104] The server uses communication data acquisition methods to retrieve delivery-related data from email systems and schedule management systems. The input is periodic information retrieval requests made via APIs. The output is the retrieved email and schedule data, which is stored in a secure database. Specifically, the server communicates with external systems using data transfer protocols to collect the necessary datasets.

[0105] Step 2:

[0106] The server uses information processing tools to analyze the acquired data using natural language processing techniques. The input is the raw data acquired in the previous step. By using information processing techniques, it extracts important keywords and contexts related to achieving the goal. The output is a list of the analyzed important information. Specifically, it executes a text analysis algorithm and performs a process of identifying highly relevant words.

[0107] Step 3:

[0108] The server evaluates the progress based on the analyzed information using a situation assessment tool. The input is the information analyzed in step 2. Through this evaluation, potential problems and delays are identified. The output is listed as the evaluation results for each project and shipping operation. Specifically, to evaluate the progress, the server scores the data according to evaluation rules and applies an algorithm that highlights potential problems.

[0109] Step 4:

[0110] The server utilizes alternative solution generation mechanisms to generate solutions based on similar past cases. The input consists of the evaluation results from step 3 and a historical database. The output is a proposed solution to address the issue. A generative AI model is used to provide the optimal path. This process involves modeling algorithms based on past successes and performing specific actions to predict new solutions.

[0111] Step 5:

[0112] The terminal uses a notification system to inform the user of the generated solution. The input is the solution generated in step 4. The output is notification information in the form of a dashboard or alert presented to the user. Specifically, the system delivers notifications in a user-friendly manner based on UI / UX design, enabling the user to take the necessary actions.

[0113] Step 6:

[0114] The user requests additional information from the generated AI model using prompt statements. The input is a prompt statement such as, "What is the best solution in case of delivery delays?" The output is additional solutions and information obtained from the model. Specifically, the user uses an interface on their device to receive further recommendations and make quick decisions based on the newly provided information.

[0115] 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.

[0116] As an embodiment of the present invention, a support system for progress management and problem-solving suggestions that combines an emotion engine will be described. In this system, the server, terminal, and user each play specific roles, providing efficient goal management and support that takes the user's emotions into consideration.

[0117] The server uses communication information acquisition methods to retrieve necessary information from the email system and schedule management system. This information includes project-related emails, meeting schedules, and task deadlines. The collected information is securely stored and managed in a database.

[0118] Next, the server analyzes the acquired data using information analysis tools. Natural language processing techniques are used to extract important keywords and contexts, and identify information relevant to the objectives. This allows for a clearer understanding of the project's progress and potential problems.

[0119] The situation assessment tool objectively evaluates progress based on the analyzed information. This step involves identifying tasks that are behind schedule and risk factors. This allows for the early detection of elements that could hinder goal achievement.

[0120] The server further references a database of similar past cases and generates the optimal solution using a solution generation tool. By utilizing a generative artificial intelligence model, optimal strategies and action plans are created based on past success stories.

[0121] The emotion engine analyzes user input data and behavioral history to infer the user's emotional state. This emotional information is used to customize solutions and provide an approach tailored to the user. For example, if a user is stressed, the solution might be simplified and the instructions easier to follow.

[0122] The terminal is responsible for notifying the user of information provided by the server. Through notification methods, the terminal presents the user with progress updates and suggested solutions via dashboards and alerts. Furthermore, it adjusts the tone and detail of notifications according to the user's emotional state.

[0123] As a concrete example, if a project is behind schedule and the user is feeling anxious, the server analyzes emails and schedules to identify the need for resource reallocation. The emotion engine detects the user's anxiety and, taking this into consideration, generates a proposal for a phased task reallocation. This proposal is notified via the device, allowing the user to take action with confidence.

[0124] Thus, the system of the present invention provides users with the necessary support to efficiently achieve their MBO goals, while also taking their emotions into consideration and providing timely assistance.

[0125] The following describes the processing flow.

[0126] Step 1:

[0127] The server uses a means of acquiring communication information to access the email system and schedule management system via an API, and retrieves necessary data such as emails, meeting schedules, and task deadlines related to the project.

[0128] Step 2:

[0129] The server analyzes data acquired using information analysis tools with natural language processing tools. This extracts important keywords and contexts, and identifies information related to project progress. The analysis results are useful for understanding the progress status.

[0130] Step 3:

[0131] The server uses situation assessment tools to evaluate project progress based on the analyzed information. It identifies delayed tasks and potential risks, and clarifies factors that affect goal achievement. This evaluation directly influences subsequent solution proposals.

[0132] Step 4:

[0133] The server uses an emotion engine to analyze the user's past input data and behavioral history to infer their current emotional state. This information is used to determine whether the user is feeling stressed or relaxed.

[0134] Step 5:

[0135] The server considers emotional states, references a database of similar past cases, and uses solution generation tools to generate the optimal solution. A generative artificial intelligence model refers to past success stories and proposes a customized approach tailored to the emotional state.

[0136] Step 6:

[0137] The device uses notification methods to inform the user of the progress and the solutions generated. These notifications adjust their tone and detail according to the user's emotional state, providing information in the most acceptable way.

[0138] Step 7:

[0139] Users check notifications from their devices and decide whether to implement the suggested solutions. If necessary, users provide feedback on the suggestions, share results with the team, and take action to achieve the goals.

[0140] (Example 2)

[0141] 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".

[0142] Modern project management requires the efficient processing of vast amounts of information and the rapid, appropriate decision-making that takes emotional considerations into account. However, conventional systems have limited information acquisition and analysis capabilities, making it difficult to provide responses that address users' emotions. Therefore, there is a need to develop a system that can improve the quality of progress management and problem-solving while reducing users' emotional stress.

[0143] 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.

[0144] In this invention, the server includes a device for acquiring communication information, an information processing device, and an emotion engine using emotion analysis technology. This makes it possible to effectively collect and analyze information necessary for project management and to provide users with timely responses that take emotions into consideration.

[0145] A "device for acquiring communication information" is a device that has the function of collecting information from electronic messaging systems, schedule management systems, etc., and storing it in a database.

[0146] An "information processing device" is a device that analyzes collected information and extracts data related to goal management.

[0147] A "situation assessment device" is a device that evaluates the progress of a project based on analyzed information and identifies risks and delays.

[0148] A "countermeasure generation device" is a device that creates optimal countermeasures using an artificial intelligence model generated based on past cases.

[0149] An "emotion engine" is a system that analyzes the user's emotional state and adjusts the content of the solutions and notifications provided based on the results.

[0150] A "notification device" is a device equipped with output means for delivering and notifying users of the analyzed and generated information.

[0151] As an embodiment of this invention, a support system that combines an emotion engine to provide progress management and problem-solving suggestions is described. In this system, the server, terminal, and user each play specific roles, streamlining project management and providing support that takes the user's emotions into consideration.

[0152] The server uses a device to acquire communication information and collects necessary information from the electronic messaging system and scheduling management system. Specifically, it retrieves emails using IMAP and collects schedule information using REST APIs. The collected data is securely stored in an SQL database.

[0153] Next, the server uses an information processing device to analyze the collected data using natural language processing techniques. This process utilizes the Python NLTK library to extract important keywords and context. This reveals the project's progress and potential problems.

[0154] Furthermore, the server uses an emotion engine to analyze the user's emotional state. It infers emotions from user input and behavior logs and reflects this in solutions and notification content. For example, if a user is feeling stressed, the solution is adjusted to be easily actionable.

[0155] The device displays analysis results and suggested solutions to the user via a notification system. Notifications are delivered via push notifications and dashboards, and their content is optimized according to the user's sentiment.

[0156] As a concrete example, consider a situation where a project is behind schedule. In this case, the server identifies the need for resource reallocation from emails and schedules. The emotion engine detects the user's anxiety and generates a step-by-step task reallocation plan with the prompt, "Propose resource reallocation measures to resolve the project delay." This proposal is notified to the user via their terminal, allowing them to act with confidence.

[0157] This invention enables users to continuously monitor the status of their projects and achieve their goals through appropriate means.

[0158] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0159] Step 1:

[0160] The server uses a device to acquire communication information and retrieves data from an electronic messaging system and a scheduling management system. Specific inputs include information from a mail server and a calendar API. Based on this, it retrieves emails using IMAP and schedule information using a REST API. This data yields output that is stored in an SQL database as project tasks, meeting appointments, and associated messages.

[0161] Step 2:

[0162] The server analyzes the data using an information processing device. The input is email and schedule information collected in step 1. Using natural language processing techniques, keywords and context are extracted using the Python NLTK library. The extracted information is listed as important tasks and progress evaluation points for the project, and the analysis results are obtained as output.

[0163] Step 3:

[0164] The server uses the analysis results from the information processing device to evaluate the project progress using the status evaluation device. The input is the analysis results from step 2. To evaluate delays and risks in schedule progress, the current date is compared with the task schedule to detect delay factors. As a result, a risk assessment report is generated as output.

[0165] Step 4:

[0166] The server uses a countermeasure generation device to create the optimal countermeasure. The input is the delay and risk information identified in step 3. Using a generative AI model, it generates a prompt message, "Propose resource reallocation measures to resolve project delays," based on past success stories. This prompt message prompts the generative AI to output an effective action plan.

[0167] Step 5:

[0168] The server uses an emotion engine to analyze the user's emotional state. Input consists of the user's past input data and behavioral history. Emotion analysis detects stress, anxiety, and other emotional states. This emotional information is used to customize the solutions and notifications provided, resulting in output that includes emotional responses.

[0169] Step 6:

[0170] The terminal displays analysis results and suggested solutions to the user via a notification device. Input is analysis results and solutions provided by the server. Output uses push notifications and dashboards to communicate the situation and suggestions to the user. Notifications are adjusted in tone and content according to the user's emotional state, providing appropriate guidance.

[0171] (Application Example 2)

[0172] 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".

[0173] In modern manufacturing environments, there is a need to efficiently manage the progress of complex processes and improve productivity. Furthermore, it is necessary to identify potential problems in the process early and provide prompt solutions. Additionally, a challenge lies in considering the emotional state of on-site staff and providing optimal solutions while reducing stress.

[0174] 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.

[0175] In this invention, the server includes means for acquiring communication information, means for analyzing information, means for evaluating the situation, means for generating an optimal solution by referring to a data set of similar past cases, means for analyzing the user's emotional information and notifying the user of the solution in a format suitable for the user, and means for monitoring the operating status of factory equipment and managing the progress of the manufacturing process in real time. This enables efficient management of the manufacturing process and the provision of customized feedback tailored to the user.

[0176] "Communication information acquisition means" refers to a device or method for collecting information from electronic communication systems or time management systems.

[0177] "Information analysis means" refers to a technology or process for analyzing communication information related to goal management and extracting important data.

[0178] A "situation assessment method" is a technique for evaluating the progress of a project or manufacturing process based on analyzed information.

[0179] A "solution generation method" is a mechanism for generating the optimal solution by referring to a data set of similar past cases, and it utilizes a generative data processing model.

[0180] "Emotional analysis tools" are means of analyzing a user's emotional information and customizing solutions based on that analysis.

[0181] A "notification method" is an interface or method for communicating progress information or solutions to the user.

[0182] "Monitoring methods" refer to technologies used to monitor the operating status of factory equipment in real time and manage the progress of the manufacturing process.

[0183] This invention provides a system for improving the efficiency of manufacturing processes and reducing worker stress. This system is server-centric and includes means for acquiring communication information, analyzing information, evaluating situations, generating solutions, analyzing emotions, notification, and monitoring.

[0184] The server acquires manufacturing-related information using communication information acquisition means that collect data from electronic communication systems and time management systems. Information analysis means extracts manufacturing progress and related details from the collected data. Next, using situation evaluation means, the progress of the process is evaluated based on the extracted data, and delays and risk factors are identified.

[0185] The solution generation method uses a generative AI model based on past successful cases to propose the optimal solution. This generative AI model is used to build new strategies by referencing data sets from similar projects.

[0186] Furthermore, the server uses sentiment analysis tools to estimate the user's emotional state. This allows the suggested solutions to be customized to take the user's emotions into consideration, providing concise and easy-to-follow instructions, especially if the user is experiencing stress or anxiety.

[0187] Through notification methods, users receive progress updates and customized solutions. The device presents this information to the user in the form of a dashboard or alerts, and adjusts the tone and content of notifications based on the user's emotional state.

[0188] For example, if the line is behind schedule, the server will monitor its operational status and suggest reallocating necessary resources, while the emotion engine will detect user anxiety. The prompt in this scenario would be as follows:

[0189] "Evaluate the progress of the production line and generate optimal resource allocation proposals for efficiency improvements. Also, consider approaches to reduce staff stress based on sentiment analysis."

[0190] In this way, the present invention can significantly improve the efficiency of progress management in manufacturing sites.

[0191] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0192] Step 1:

[0193] The server uses communication information acquisition means to collect data related to the manufacturing line from the electronic communication system and time management system. This includes current task progress, downtime, and error history. The obtained data is then input into the next analysis step.

[0194] Step 2:

[0195] The server analyzes the collected data using information analysis tools. Specifically, it uses natural language processing techniques to extract important keywords and contexts and identify potential problems in the manufacturing process. The keywords and contextual information identified through this analysis are then used for the next progress evaluation.

[0196] Step 3:

[0197] The server objectively evaluates the progress based on the analyzed information using a situation assessment tool. Specifically, it identifies delayed tasks and risk factors and assesses the overall progress level of the production process. This evaluation result is used to generate solutions.

[0198] Step 4:

[0199] The server utilizes solution generation tools, references data from similar past cases, and uses generative AI models to construct optimal solutions. In this step, a new strategy or action plan is generated based on the identified problem.

[0200] Step 5:

[0201] The server uses sentiment analysis tools to analyze user feedback and operation history to infer the user's emotional state. Based on this, the proposed solution is customized to take the user's emotions into consideration.

[0202] Step 6:

[0203] The server notifies the user's device of progress and customized solutions through notification mechanisms. Notifications are displayed as dashboards or alerts, and their content and tone are adjusted according to the user's emotional state.

[0204] 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.

[0205] 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.

[0206] 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.

[0207] [Second Embodiment]

[0208] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0209] 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.

[0210] 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).

[0211] 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.

[0212] 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.

[0213] 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).

[0214] 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.

[0215] 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.

[0216] 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.

[0217] 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.

[0218] 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.

[0219] 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".

[0220] As an embodiment of the present invention, a support system for progress management and problem-solving proposals using a generated AI model is described below. In this system, the server, terminal, and user each play specific roles, thereby improving the efficiency of management by objectives (MBO).

[0221] The server first uses communication information acquisition methods to periodically retrieve necessary information from email systems and schedule management systems. This information is stored and managed in a secure database. This information includes project-related email content, scheduled meetings, and deadlines.

[0222] Next, the server uses information analysis tools to analyze the collected data. This analysis includes a process of extracting important keywords and context using natural language processing techniques and identifying information relevant to the goals. This makes it easier for the server to understand the project's progress.

[0223] The situation assessment mechanism allows the server to evaluate progress based on the analyzed data. For example, it can identify whether scheduled tasks are behind schedule or where problems are likely to occur. This enables early detection of situations that jeopardize goal achievement.

[0224] The server then refers to a database of similar past cases and uses a solution generation tool to generate the optimal solution for the identified problem. This process utilizes a generative artificial intelligence model to create optimal action plans based on past success stories.

[0225] The terminal is responsible for notifying the user of information provided by the server. Through notification methods, the terminal presents the user with progress information and suggested solutions via dashboards and alerts. This allows the user to take appropriate action in a timely manner.

[0226] For example, if a project is behind schedule, the server analyzes relevant emails and meeting records and determines that a resource shortage is the cause. Based on past cases where similar resource shortages were resolved, the server generates a proposal for reallocating resources and notifies the user via their terminal. The user can then quickly adjust project members based on this proposal.

[0227] Thus, the system of the present invention provides users with the timely support necessary to efficiently achieve their MBO goals.

[0228] The following describes the processing flow.

[0229] Step 1:

[0230] The server uses a communication information acquisition method to access the email system and schedule management system through a pre-configured API and retrieve the necessary data. The information obtained here includes project-related email content, meeting dates, and task deadlines.

[0231] Step 2:

[0232] The server analyzes the data acquired using information analysis tools, employing text analysis tools (e.g., natural language processing techniques). This step extracts key keywords and context, identifying information relevant to the objectives. This helps to uncover project progress and potential problems.

[0233] Step 3:

[0234] The server uses situation assessment tools to evaluate the project's progress based on the analyzed information. This evaluation includes identifying tasks that are behind schedule and predicting potential risks. This allows the server to recognize factors that could hinder the achievement of the goals.

[0235] Step 4:

[0236] The server accesses a database of similar past cases and uses solution generation tools to generate the optimal solution for the identified problem. In this step, a generative artificial intelligence model is used to create the optimal strategy and action plan based on past successes.

[0237] Step 5:

[0238] The device uses notification methods to inform the user of progress and generated solutions. Notifications are displayed as dashboards and alerts, and the user can view detailed reports.

[0239] Step 6:

[0240] Based on notifications received through their devices, users make decisions to take suggested actions. If necessary, users can share information with their team and seek further feedback, enabling them to take action towards achieving their goals.

[0241] (Example 1)

[0242] 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."

[0243] In project management, a challenge lies in the difficulty of understanding progress toward achieving goals and identifying potential risks early on. Furthermore, it is not easy to derive concrete actions for optimizing resources and quickly resolving problems. These factors hinder efficient goal management.

[0244] 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.

[0245] In this invention, the server includes an acquisition means for acquiring communication information, an analysis means for extracting information related to goal management from the acquired communication information using natural language processing, and an evaluation means for evaluating the progress of the project and identifying risks based on the extracted information. This enables accurate understanding of the progress in project management, early detection of potential problems, and provision of optimal solutions utilizing generative AI models.

[0246] "Means for acquiring communication information" refers to devices or software that have the technical functions to collect information from sources such as email and schedule management systems.

[0247] "Analysis methods for extracting information related to goal management using natural language processing" refers to a technology that analyzes text data, detects specific keywords and contexts, and identifies information important for goal management.

[0248] "Evaluation tools for assessing project progress and identifying risks" are technologies that have analytical capabilities to determine the progress of tasks and potential problems based on collected and analyzed information.

[0249] "Generative methods for deriving optimal solutions using generative AI models" refers to technologies that utilize generative artificial intelligence to learn from similar past cases and create efficient action plans.

[0250] A "notification means" is a device or mechanism that has communication functions to effectively convey generated information or action plans to users.

[0251] This invention is a system that uses a generative AI model to monitor project progress and propose solutions to problems in project management. In implementing this invention, it is assumed that the server, terminal, and user each play different roles.

[0252] The server periodically collects information from systems such as email systems and scheduling management systems. Specifically, it accesses these systems to retrieve relevant communication information and stores it in a secure database. High-performance storage systems and security software are used for this data management.

[0253] The collected data is analyzed on the server using natural language processing software. This analysis software automatically extracts key keywords and contexts related to the project and organizes useful information from a goal management perspective.

[0254] Furthermore, the server uses a situation assessment algorithm to evaluate the project's progress based on the extracted information. Risk management software identifies task delays and potential problems, thereby clarifying the prospects for achieving the goals.

[0255] Once a problem is identified, the server uses a generative AI model to generate the optimal solution from a historical database. The generated solution is then notified to the user via their terminal. This process requires a high-performance AI engine.

[0256] The device notifies the user of progress information and solutions provided by the server using visually easy-to-understand dashboards and alerts. This allows the user to make timely and appropriate decisions.

[0257] As a concrete example, if a project is behind schedule, the server uses natural language processing to identify resource shortages as the cause. Based on similar past cases, a generative AI model proposes resource reallocation and notifies the user via their terminal. The user can then quickly adjust the schedules of team members based on this proposal.

[0258] A concrete example of a prompt message is "Check the progress of the development project and generate resource optimization suggestions." This prompt serves as a starting point for the server to evaluate the progress and appropriate resource allocation.

[0259] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0260] Step 1:

[0261] The server collects necessary information from the email system and schedule management system using communication information acquisition methods. Input requires access rights to email accounts and schedule information. This information is retrieved periodically and stored as output in a secure database. Specifically, the server logs in daily, checks for new emails and schedule events, and writes them to the database.

[0262] Step 2:

[0263] The server analyzes the data collected using information analysis tools. The input is the communication information saved in step 1. Using natural language processing (NLP) software, it extracts important keywords and context related to the project and organizes the information necessary for goal management. The output is a list of project-related keywords. Specifically, the server executes a text analysis algorithm to extract keywords such as "deadline," "progress," and "issues."

[0264] Step 3:

[0265] The server uses a situation assessment tool to evaluate the project's progress based on the analyzed information. The keyword list extracted in step 2 is used as input. This data is used to run an evaluation algorithm to identify task delays and risks. An evaluation results report is generated as output. Specifically, the server compares the scheduled completion date of a task with the current date and creates a list of delayed tasks.

[0266] Step 4:

[0267] The server uses a solution generation mechanism to refer to a database of similar past cases and generate the optimal solution. The evaluation results generated in step 3 are used as input. The generation AI model is utilized to output the optimal action plan based on the database. Specifically, the server searches for similar problem-solving cases and creates the optimal action plan proposed by the AI.

[0268] Step 5:

[0269] The terminal notifies the user based on information sent from the server. The solution generated in step 4 is received by the terminal as input. Using notification methods, progress information and suggested solutions are displayed to the user through dashboards and alerts. The output provides the user with clear instructions for action. Specifically, the terminal sends a notification to the user's device and displays the solution on the dashboard.

[0270] This series of processes enables users to make appropriate and swift decisions and efficiently achieve their goals.

[0271] (Application Example 1)

[0272] 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."

[0273] In logistics facilities, it is crucial to streamline progress management and problem resolution regarding package delivery. However, conventional systems failed to detect delays and develop appropriate countermeasures in a timely manner, leading to decreased productivity. Furthermore, manual management was inefficient and placed a burden on the overall project progress.

[0274] 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.

[0275] In this invention, the server includes means for acquiring communication data, means for processing information, means for determining the situation, means for generating alternative solutions, means for notifying, and a function for analyzing information in logistics facilities, detecting delivery delays, and proposing additional personnel or route optimization. This makes it possible to streamline package management within logistics facilities and to quickly manage progress and resolve issues.

[0276] "Communication data acquisition means" refers to a device or software that has the function of acquiring necessary data from email or a schedule management system.

[0277] "Information processing means" refers to a technology or process for extracting and analyzing meaningful information related to achieving a goal from acquired data.

[0278] "Situation assessment means" refers to methods and devices for evaluating progress based on analyzed data and identifying problems and delays.

[0279] The "Alternative Generation Means" refers to a system or model that refers to a database of past similar cases and generates optimal solutions.

[0280] The "Notification Means" refers to a communication or notification system for transmitting the generated solutions and proposals to the user.

[0281] The "Logistics Facility" refers to a center or building for packing, storing, transporting, and sorting goods.

[0282] As an embodiment for implementing the present invention, a system for supporting the progress management and problem-solving solutions of packages in a logistics facility will be described. In this system, the server, terminal, and user each play specific roles to improve the efficiency of the logistics process.

[0283] The server regularly acquires data from the email system and the schedule management system using the communication data acquisition means. This data includes information such as delivery schedules and shipping statuses. The acquired data is stored in a secure database. Next, the server uses the information processing means to analyze the data and employs natural language processing technology to extract important information related to achieving the goals. In this process, particular importance is attached to the determination of transportation delay information and the progress of scheduled tasks.

[0284] Based on the analyzed data, the server evaluates the progress within the logistics facility by the situation judgment means. As a result, for example, it becomes possible to detect in advance whether the packages scheduled to arrive are delayed and to grasp the situations that require countermeasures. For the detected problems, the alternative generation means is utilized to propose optimal solutions from past similar cases. This process is carried out using a generation AI model to search for the optimal solutions based on past successful cases.

[0285] The generated solution is notified to the user through the terminal by the notification means. Utilizing the notification function of the terminal, progress information and the proposed solution are displayed through dashboards and alerts.

[0286] As a specific example, when delivery is delayed at a logistics facility, the server analyzes the cause and proposes additional personnel or route optimization. Based on this information, the user can execute the next action quickly and effectively.

[0287] As a specific example of the prompt sentence, "Please tell me the optimal solution when delivery delay occurs." can be cited. Thus, the user can easily receive the problem-solving solution by the generation AI model.

[0288] The flow of the specific process in Application Example 1 will be described using FIG. 12.

[0289] Step 1:

[0290] The server uses communication data acquisition means to acquire delivery-related data from an email system or a schedule management system. As an input, a periodic information acquisition request using an API is made. The output is the acquired email and schedule data, which is stored in a secure database. As a specific operation, it is a procedure for the server to communicate with an external system using a data transfer protocol and collect the necessary data set.

[0291] Step 2:

[0292] The server uses information processing means to analyze the acquired data by natural language processing technology. The input is the raw data acquired in the previous step. By using information processing technology, important keywords and contexts related to goal achievement are extracted. The output is a list of the analyzed important information. As a specific operation, a text analysis algorithm is executed to perform a process of identifying highly relevant words.

[0293] Step 3:

[0294] The server evaluates the progress based on the analyzed information using a situation assessment tool. The input is the information analyzed in step 2. Through this evaluation, potential problems and delays are identified. The output is listed as the evaluation results for each project and shipping operation. Specifically, to evaluate the progress, the server scores the data according to evaluation rules and applies an algorithm that highlights potential problems.

[0295] Step 4:

[0296] The server utilizes alternative solution generation mechanisms to generate solutions based on similar past cases. The input consists of the evaluation results from step 3 and a historical database. The output is a proposed solution to address the issue. A generative AI model is used to provide the optimal path. This process involves modeling algorithms based on past successes and performing specific actions to predict new solutions.

[0297] Step 5:

[0298] The terminal uses a notification system to inform the user of the generated solution. The input is the solution generated in step 4. The output is notification information in the form of a dashboard or alert presented to the user. Specifically, the system delivers notifications in a user-friendly manner based on UI / UX design, enabling the user to take the necessary actions.

[0299] Step 6:

[0300] The user requests additional information from the generated AI model using prompt statements. The input is a prompt statement such as, "What is the best solution in case of delivery delays?" The output is additional solutions and information obtained from the model. Specifically, the user uses an interface on their device to receive further recommendations and make quick decisions based on the newly provided information.

[0301] 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.

[0302] As an embodiment of the present invention, a support system for progress management and problem-solving suggestions that combines an emotion engine will be described. In this system, the server, terminal, and user each play specific roles, providing efficient goal management and support that takes the user's emotions into consideration.

[0303] The server uses communication information acquisition methods to retrieve necessary information from the email system and schedule management system. This information includes project-related emails, meeting schedules, and task deadlines. The collected information is securely stored and managed in a database.

[0304] Next, the server analyzes the acquired data using information analysis tools. Natural language processing techniques are used to extract important keywords and contexts, and identify information relevant to the objectives. This allows for a clearer understanding of the project's progress and potential problems.

[0305] The situation assessment tool objectively evaluates progress based on the analyzed information. This step involves identifying tasks that are behind schedule and risk factors. This allows for the early detection of elements that could hinder goal achievement.

[0306] The server further references a database of similar past cases and generates the optimal solution using a solution generation method. By utilizing a generative artificial intelligence model, optimal strategies and action plans are created based on past success stories.

[0307] The emotion engine analyzes the user's input data and behavior history to infer the user's emotional state. This emotional information is utilized to customize solutions and provide an approach tailored to the user. For example, when the user is stressed, it is considered to simplify the solution and give instructions that are easy to act on.

[0308] The terminal is responsible for notifying the user of the information provided by the server. Through the notification means, the terminal presents progress information and proposed solutions to the user via dashboards and alerts. Furthermore, the tone and details of the notification are adjusted according to the user's emotional state.

[0309] As a specific example, in a certain project where development is behind schedule and the user is feeling anxious, the server analyzes emails and schedules to identify that a reallocation of resources is necessary. The emotion engine detects the user's anxiety and generates a proposal for a step-by-step task reallocation considering this. This proposal is notified through the terminal, enabling the user to act with confidence.

[0310] In this way, the system of the present invention timely provides the support necessary for the user to efficiently achieve the MBO goals, taking emotions into account.

[0311] The following describes the processing flow.

[0312] Step 1:

[0313] The server uses communication information acquisition means to access the email system and schedule management system through the API, and obtains necessary data such as emails related to the project, meeting schedules, and task deadlines.

[0314] Step 2:

[0315] The server analyzes data acquired using information analysis tools with natural language processing tools. This extracts important keywords and contexts, and identifies information related to project progress. The analysis results are useful for understanding the progress status.

[0316] Step 3:

[0317] The server uses situation assessment tools to evaluate project progress based on the analyzed information. It identifies delayed tasks and potential risks, and clarifies factors that affect goal achievement. This evaluation directly influences subsequent solution proposals.

[0318] Step 4:

[0319] The server uses an emotion engine to analyze the user's past input data and behavioral history to infer their current emotional state. This information is used to determine whether the user is stressed or relaxed.

[0320] Step 5:

[0321] The server considers emotional states, references a database of similar past cases, and uses solution generation tools to generate the optimal solution. A generative artificial intelligence model refers to past success stories and proposes a customized approach tailored to the emotional state.

[0322] Step 6:

[0323] The device uses notification methods to inform the user of the progress and the generated solutions. These notifications adjust their tone and detail according to the user's emotional state, providing information in the most acceptable way.

[0324] Step 7:

[0325] Users check notifications from their devices and decide whether to implement the suggested solutions. If necessary, users provide feedback on the suggestions, share results with the team, and take action to achieve the goals.

[0326] (Example 2)

[0327] 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".

[0328] Modern project management requires the efficient processing of vast amounts of information and the rapid, appropriate decision-making that takes emotional considerations into account. However, conventional systems have limited information acquisition and analysis capabilities, making it difficult to provide responses that address users' emotions. Therefore, there is a need to develop a system that can improve the quality of progress management and problem-solving while reducing users' emotional stress.

[0329] 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.

[0330] In this invention, the server includes a device for acquiring communication information, an information processing device, and an emotion engine using emotion analysis technology. This makes it possible to effectively collect and analyze information necessary for project management and to provide users with timely responses that take emotions into consideration.

[0331] A "device for acquiring communication information" is a device that has the function of collecting information from electronic messaging systems, schedule management systems, etc., and storing it in a database.

[0332] An "information processing device" is a device that analyzes collected information and extracts data related to goal management.

[0333] A "situation assessment device" is a device that evaluates the progress of a project based on analyzed information and identifies risks and delays.

[0334] A "countermeasure generation device" is a device that creates optimal countermeasures using an artificial intelligence model generated based on past cases.

[0335] An "emotion engine" is a system that analyzes the user's emotional state and adjusts the content of the solutions and notifications provided based on the results.

[0336] A "notification device" is a device equipped with output means for delivering and notifying users of the analyzed and generated information.

[0337] As an embodiment of this invention, a support system that combines an emotion engine to provide progress management and problem-solving suggestions is described. In this system, the server, terminal, and user each play specific roles, streamlining project management and providing support that takes the user's emotions into consideration.

[0338] The server uses a device to acquire communication information and collects necessary information from the electronic messaging system and scheduling management system. Specifically, it retrieves emails using IMAP and collects schedule information using REST APIs. The collected data is securely stored in an SQL database.

[0339] Next, the server uses an information processing device to analyze the collected data using natural language processing techniques. This process utilizes the Python NLTK library to extract important keywords and context. This reveals the project's progress and potential problems.

[0340] Furthermore, the server uses an emotion engine to analyze the user's emotional state. It infers emotions from user input and behavior logs and reflects them in solutions and notification content. For example, if a user is feeling stressed, the solution is adjusted to be easily actionable.

[0341] The device displays analysis results and suggested solutions to the user via a notification system. Notifications are delivered via push notifications and dashboards, and their content is optimized according to the user's sentiment.

[0342] As a concrete example, consider a situation where a project is behind schedule. In this case, the server identifies the need for resource reallocation from emails and schedules. The emotion engine detects the user's anxiety and generates a step-by-step task reallocation plan with the prompt, "Propose resource reallocation measures to resolve the project delay." This proposal is notified to the user via their terminal, allowing them to act with confidence.

[0343] This invention enables users to continuously monitor the status of their projects and achieve their goals through appropriate means.

[0344] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0345] Step 1:

[0346] The server uses a device to acquire communication information and retrieves data from an electronic messaging system and a scheduling management system. Specific inputs include information from a mail server and a calendar API. Based on this, it retrieves emails using IMAP and schedule information using a REST API. This data yields output that is stored in an SQL database as project tasks, meeting appointments, and associated messages.

[0347] Step 2:

[0348] The server analyzes the data using an information processing device. The input is email and schedule information collected in step 1. Using natural language processing techniques, keywords and context are extracted using the Python NLTK library. The extracted information is listed as important tasks and progress evaluation points for the project, and the analysis results are obtained as output.

[0349] Step 3:

[0350] The server uses the analysis results from the information processing device to evaluate the project progress using the status evaluation device. The input is the analysis results from step 2. To evaluate delays and risks in schedule progress, the current date is compared with the task schedule to detect delay factors. As a result, a risk assessment report is generated as output.

[0351] Step 4:

[0352] The server uses a countermeasure generation device to create the optimal countermeasure. The input is the delay and risk information identified in step 3. Using a generative AI model, it generates a prompt message, "Propose resource reallocation measures to resolve project delays," based on past success stories. This prompt message prompts the generative AI to output an effective action plan.

[0353] Step 5:

[0354] The server uses an emotion engine to analyze the user's emotional state. Input consists of the user's past input data and behavioral history. Emotion analysis detects stress, anxiety, and other emotional states. This emotional information is used to customize the solutions and notifications provided, resulting in output that includes emotional responses.

[0355] Step 6:

[0356] The terminal displays analysis results and suggested solutions to the user via a notification device. Input is analysis results and solutions provided by the server. Output uses push notifications and dashboards to communicate the situation and suggestions to the user. Notifications are adjusted in tone and content according to the user's emotional state, providing appropriate guidance.

[0357] (Application Example 2)

[0358] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0359] In modern manufacturing environments, there is a need to efficiently manage the progress of complex processes and improve productivity. Furthermore, it is necessary to identify potential problems in the process early and provide prompt solutions. Additionally, a challenge lies in considering the emotional state of on-site staff and providing optimal solutions while reducing stress.

[0360] 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.

[0361] In this invention, the server includes means for acquiring communication information, means for analyzing information, means for evaluating the situation, means for generating an optimal solution by referring to a data set of similar past cases, means for analyzing the user's emotional information and notifying the user of the solution in a format suitable for the user, and means for monitoring the operating status of factory equipment and managing the progress of the manufacturing process in real time. This enables efficient management of the manufacturing process and the provision of customized feedback tailored to the user.

[0362] "Communication information acquisition means" refers to a device or method for collecting information from electronic communication systems or time management systems.

[0363] "Information analysis means" refers to a technology or process for analyzing communication information related to goal management and extracting important data.

[0364] A "situation assessment method" is a technique for evaluating the progress of a project or manufacturing process based on analyzed information.

[0365] A "solution generation method" is a mechanism for generating the optimal solution by referring to a data set of similar past cases, and it utilizes a generative data processing model.

[0366] "Emotional analysis tools" are means of analyzing a user's emotional information and customizing solutions based on that analysis.

[0367] A "notification method" is an interface or method for communicating progress information or solutions to the user.

[0368] "Monitoring methods" refer to technologies used to monitor the operating status of factory equipment in real time and manage the progress of the manufacturing process.

[0369] This invention provides a system for improving the efficiency of manufacturing processes and reducing worker stress. This system is server-centric and includes means for acquiring communication information, analyzing information, evaluating situations, generating solutions, analyzing emotions, notification, and monitoring.

[0370] The server acquires manufacturing-related information using communication information acquisition means that collect data from electronic communication systems and time management systems. Information analysis means extracts manufacturing progress and related details from the collected data. Next, using situation evaluation means, the progress of the process is evaluated based on the extracted data, and delays and risk factors are identified.

[0371] The solution generation method uses a generative AI model based on past successful cases to propose the optimal solution. This generative AI model is used to build new strategies by referencing data sets from similar projects.

[0372] Furthermore, the server uses sentiment analysis tools to estimate the user's emotional state. This allows the suggested solutions to be customized to take the user's emotions into consideration, providing concise and easy-to-follow instructions, especially if the user is experiencing stress or anxiety.

[0373] Through notification methods, users receive progress updates and customized solutions. The device presents this information to the user in the form of a dashboard or alerts, adjusting the tone and content of notifications based on the user's emotional state.

[0374] For example, if the line is behind schedule, the server monitors its operational status and suggests reallocating necessary resources, while the emotion engine detects user anxiety. The prompt in this scenario would be as follows:

[0375] "Evaluate the progress of the production line and generate optimal resource allocation proposals for efficiency improvements. Also, consider approaches to reduce staff stress based on sentiment analysis."

[0376] In this way, the present invention can significantly improve the efficiency of progress management in manufacturing sites.

[0377] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0378] Step 1:

[0379] The server uses communication information acquisition means to collect data related to the manufacturing line from the electronic communication system and time management system. This includes current task progress, downtime, and error history. The obtained data is then input into the next analysis step.

[0380] Step 2:

[0381] The server analyzes the collected data using information analysis tools. Specifically, it uses natural language processing techniques to extract important keywords and contexts and identify potential problems in the manufacturing process. The keywords and contextual information identified through this analysis are then used for the next progress evaluation.

[0382] Step 3:

[0383] The server objectively evaluates the progress based on the analyzed information using a situation assessment tool. Specifically, it identifies delayed tasks and risk factors and assesses the overall progress level of the production process. This evaluation result is used to generate solutions.

[0384] Step 4:

[0385] The server utilizes solution generation tools, references data from similar past cases, and uses generative AI models to construct optimal solutions. In this step, a new strategy or action plan is generated based on the identified problem.

[0386] Step 5:

[0387] The server uses sentiment analysis tools to analyze user feedback and operation history to infer the user's emotional state. Based on this, the proposed solution is customized to take the user's emotions into consideration.

[0388] Step 6:

[0389] The server notifies the user's device of progress and customized solutions through notification mechanisms. Notifications are displayed as dashboards or alerts, and their content and tone are adjusted according to the user's emotional state.

[0390] 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.

[0391] 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.

[0392] 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.

[0393] [Third Embodiment]

[0394] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0395] 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.

[0396] 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).

[0397] 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.

[0398] 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.

[0399] 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).

[0400] 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.

[0401] 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.

[0402] 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.

[0403] 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.

[0404] 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.

[0405] 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".

[0406] As an embodiment of the present invention, a support system for progress management and problem-solving proposals using a generated AI model is described below. In this system, the server, terminal, and user each play specific roles, thereby improving the efficiency of management by objectives (MBO).

[0407] The server first uses communication information acquisition methods to periodically retrieve necessary information from email systems and schedule management systems. This information is stored and managed in a secure database. This information includes project-related email content, scheduled meetings, and deadlines.

[0408] Next, the server uses information analysis tools to analyze the collected data. This analysis includes a process of extracting important keywords and context using natural language processing techniques and identifying information relevant to the goals. This makes it easier for the server to understand the project's progress.

[0409] The situation assessment mechanism allows the server to evaluate progress based on the analyzed data. For example, it can identify whether scheduled tasks are behind schedule or where problems are likely to occur. This enables early detection of situations that jeopardize goal achievement.

[0410] The server then refers to a database of similar past cases and uses a solution generation tool to generate the optimal solution for the identified problem. This process utilizes a generative artificial intelligence model to create optimal action plans based on past success stories.

[0411] The terminal is responsible for notifying the user of information provided by the server. Through notification methods, the terminal presents the user with progress information and suggested solutions via dashboards and alerts. This allows the user to take appropriate action in a timely manner.

[0412] For example, if a project is behind schedule, the server analyzes relevant emails and meeting records and determines that a resource shortage is the cause. Based on past cases where similar resource shortages were resolved, the server generates a proposal for reallocating resources and notifies the user via their terminal. The user can then quickly adjust project members based on this proposal.

[0413] Thus, the system of the present invention provides users with the timely support necessary to efficiently achieve their MBO goals.

[0414] The following describes the processing flow.

[0415] Step 1:

[0416] The server uses a communication information acquisition method to access the email system and schedule management system through a pre-configured API and retrieve the necessary data. The information obtained here includes project-related email content, meeting dates, and task deadlines.

[0417] Step 2:

[0418] The server analyzes the data acquired using information analysis tools, employing text analysis tools (e.g., natural language processing techniques). This step extracts key keywords and context, identifying information relevant to the objectives. This helps to uncover project progress and potential problems.

[0419] Step 3:

[0420] The server uses situation assessment tools to evaluate the project's progress based on the analyzed information. This evaluation includes identifying tasks that are behind schedule and predicting potential risks. This allows the server to recognize factors that could hinder the achievement of the goals.

[0421] Step 4:

[0422] The server accesses a database of similar past cases and uses solution generation tools to generate the optimal solution for the identified problem. In this step, a generative artificial intelligence model is used to create the optimal strategy and action plan based on past successes.

[0423] Step 5:

[0424] The device uses notification methods to inform the user of progress and generated solutions. Notifications are displayed as dashboards and alerts, and the user can view detailed reports.

[0425] Step 6:

[0426] Based on notifications received through their devices, users make decisions to take suggested actions. If necessary, users can share information with their team and seek further feedback, enabling them to take action towards achieving their goals.

[0427] (Example 1)

[0428] 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."

[0429] In project management, a challenge lies in the difficulty of understanding progress toward achieving goals and identifying potential risks early on. Furthermore, it is not easy to derive concrete actions for optimizing resources and quickly resolving problems. These factors hinder efficient goal management.

[0430] 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.

[0431] In this invention, the server includes an acquisition means for acquiring communication information, an analysis means for extracting information related to goal management from the acquired communication information using natural language processing, and an evaluation means for evaluating the progress of the project and identifying risks based on the extracted information. This enables accurate understanding of the progress in project management, early detection of potential problems, and provision of optimal solutions utilizing generative AI models.

[0432] "Means for acquiring communication information" refers to devices or software that have the technical functions to collect information from sources such as email and schedule management systems.

[0433] "Analysis methods for extracting information related to goal management using natural language processing" refers to a technology that analyzes text data, detects specific keywords and contexts, and identifies information important for goal management.

[0434] "Evaluation tools for assessing project progress and identifying risks" are technologies that have analytical capabilities to determine the progress of tasks and potential problems based on collected and analyzed information.

[0435] "Generative methods for deriving optimal solutions using generative AI models" refers to technologies that utilize generative artificial intelligence to learn from similar past cases and create efficient action plans.

[0436] A "notification means" is a device or mechanism that has communication functions to effectively convey generated information or action plans to users.

[0437] This invention is a system that uses a generative AI model to monitor project progress and propose solutions to problems in project management. In implementing this invention, it is assumed that the server, terminal, and user each play different roles.

[0438] The server periodically collects information from systems such as email systems and scheduling management systems. Specifically, it accesses these systems to retrieve relevant communication information and stores it in a secure database. High-performance storage systems and security software are used for this data management.

[0439] The collected data is analyzed on the server using natural language processing software. This analysis software automatically extracts key keywords and contexts related to the project and organizes useful information from a goal management perspective.

[0440] Furthermore, the server uses a situation assessment algorithm to evaluate the project's progress based on the extracted information. Risk management software identifies task delays and potential problems, thereby clarifying the prospects for achieving the goals.

[0441] Once a problem is identified, the server uses a generative AI model to generate the optimal solution from a historical database. The generated solution is then notified to the user via their terminal. This process requires a high-performance AI engine.

[0442] The device notifies the user of progress information and solutions provided by the server using visually easy-to-understand dashboards and alerts. This allows the user to make timely and appropriate decisions.

[0443] As a concrete example, if a project is behind schedule, the server uses natural language processing to identify resource shortages as the cause. Based on similar past cases, a generative AI model proposes resource reallocation and notifies the user via their terminal. The user can then quickly adjust the schedules of team members based on this proposal.

[0444] A concrete example of a prompt message is "Check the progress of the development project and generate resource optimization suggestions." This prompt serves as a starting point for the server to evaluate the progress and appropriate resource allocation.

[0445] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0446] Step 1:

[0447] The server collects necessary information from the email system and schedule management system using communication information acquisition methods. Input requires access rights to email accounts and schedule information. This information is retrieved periodically and stored as output in a secure database. Specifically, the server logs in daily, checks for new emails and schedule events, and writes them to the database.

[0448] Step 2:

[0449] The server analyzes the data collected using information analysis tools. The input is the communication information saved in step 1. Using natural language processing (NLP) software, it extracts important keywords and context related to the project and organizes the information necessary for goal management. The output is a list of project-related keywords. Specifically, the server executes a text analysis algorithm to extract keywords such as "deadline," "progress," and "issues."

[0450] Step 3:

[0451] The server uses a situation assessment tool to evaluate the project's progress based on the analyzed information. The keyword list extracted in step 2 is used as input. This data is used to run an evaluation algorithm to identify task delays and risks. An evaluation results report is generated as output. Specifically, the server compares the scheduled completion date of a task with the current date and creates a list of delayed tasks.

[0452] Step 4:

[0453] The server uses a solution generation mechanism to refer to a database of similar past cases and generate the optimal solution. The evaluation results generated in step 3 are used as input. The generation AI model is utilized to output the optimal action plan based on the database. Specifically, the server searches for similar problem-solving cases and creates the optimal action plan proposed by the AI.

[0454] Step 5:

[0455] The terminal notifies the user based on information sent from the server. The solution generated in step 4 is received by the terminal as input. Using notification methods, progress information and suggested solutions are displayed to the user through dashboards and alerts. The output provides the user with clear instructions for action. Specifically, the terminal sends a notification to the user's device and displays the solution on the dashboard.

[0456] This series of processes enables users to make appropriate and swift decisions and efficiently achieve their goals.

[0457] (Application Example 1)

[0458] 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."

[0459] In logistics facilities, it is crucial to streamline progress management and problem resolution regarding package delivery. However, conventional systems failed to detect delays and develop appropriate countermeasures in a timely manner, leading to decreased productivity. Furthermore, manual management was inefficient and placed a burden on the overall project progress.

[0460] 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.

[0461] In this invention, the server includes means for acquiring communication data, means for processing information, means for determining the situation, means for generating alternative solutions, means for notifying, and a function for analyzing information in logistics facilities, detecting delivery delays, and proposing additional personnel or route optimization. This makes it possible to streamline package management within logistics facilities and to quickly manage progress and resolve issues.

[0462] "Communication data acquisition means" refers to a device or software that has the function of acquiring necessary data from email or a schedule management system.

[0463] "Information processing means" refers to a technology or process for extracting and analyzing meaningful information related to achieving a goal from acquired data.

[0464] "Situation assessment means" refers to methods and devices for evaluating progress based on analyzed data and identifying problems and delays.

[0465] A "means for generating alternative solutions" refers to a system or model that generates the optimal solution by referring to a database of similar past cases.

[0466] A "notification system" refers to a communication or notification system used to convey generated solutions or proposals to users.

[0467] A "logistics facility" refers to a center or building used for packaging, storing, transporting, and sorting goods.

[0468] As an embodiment of the present invention, a system that supports progress management and problem-solving of packages within a logistics facility will be described. In this system, the server, terminals, and users each play specific roles in order to improve the efficiency of the logistics process.

[0469] The server periodically retrieves data from the email system and schedule management system using communication data acquisition means. This data includes information such as delivery schedules and shipping status. The retrieved data is stored in a secure database. Next, the server uses information processing means to analyze the data and employs natural language processing techniques to extract important information related to achieving goals. Particular emphasis is placed on determining information about transportation delays and the progress of scheduled tasks.

[0470] Based on the analyzed data, the server uses a situation assessment tool to evaluate the progress within the logistics facility. This allows for, for example, the detection of delays in arriving packages and the identification of situations requiring action. For detected problems, the system utilizes an alternative solution generation tool to propose the optimal solution based on similar past cases. This process is carried out using a generative AI model, which seeks the optimal solution based on past success stories.

[0471] The generated solutions are notified to the user via a notification system through the device. The device's notification function is used to display progress information and proposed solutions through a dashboard or alerts.

[0472] For example, if a delivery at a logistics facility is delayed beyond the scheduled time, the server analyzes the cause and suggests additional personnel or route optimization. Based on this information, users can take the next steps quickly and effectively.

[0473] A concrete example of a prompt message would be, "Please tell me the best solution in case of a delivery delay." This allows the user to easily receive problem-solving solutions generated by the AI ​​model.

[0474] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0475] Step 1:

[0476] The server uses communication data acquisition methods to retrieve delivery-related data from email systems and schedule management systems. The input is periodic information retrieval requests made via APIs. The output is the retrieved email and schedule data, which is stored in a secure database. Specifically, the server communicates with external systems using data transfer protocols to collect the necessary datasets.

[0477] Step 2:

[0478] The server uses information processing tools to analyze the acquired data using natural language processing techniques. The input is the raw data acquired in the previous step. By using information processing techniques, it extracts important keywords and contexts related to achieving the goal. The output is a list of the analyzed important information. Specifically, it executes a text analysis algorithm and performs a process of identifying highly relevant words.

[0479] Step 3:

[0480] The server evaluates the progress based on the analyzed information using a situation assessment tool. The input is the information analyzed in step 2. Through this evaluation, potential problems and delays are identified. The output is listed as the evaluation results for each project and shipping operation. Specifically, to evaluate the progress, the server scores the data according to evaluation rules and applies an algorithm that highlights potential problems.

[0481] Step 4:

[0482] The server utilizes alternative solution generation mechanisms to generate solutions based on similar past cases. The input consists of the evaluation results from step 3 and a historical database. The output is a proposed solution to address the issue. A generative AI model is used to provide the optimal path. This process involves modeling algorithms based on past successes and performing specific actions to predict new solutions.

[0483] Step 5:

[0484] The terminal uses a notification system to inform the user of the generated solution. The input is the solution generated in step 4. The output is notification information in the form of a dashboard or alert presented to the user. Specifically, the system delivers notifications in a user-friendly manner based on UI / UX design, enabling the user to take the necessary actions.

[0485] Step 6:

[0486] The user requests additional information from the generated AI model using prompt statements. The input is a prompt statement such as, "What is the best solution in case of delivery delays?" The output is additional solutions and information obtained from the model. Specifically, the user uses an interface on their device to receive further recommendations and make quick decisions based on the newly provided information.

[0487] 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.

[0488] As an embodiment of the present invention, a support system for progress management and problem-solving suggestions that combines an emotion engine will be described. In this system, the server, terminal, and user each play specific roles, providing efficient goal management and support that takes the user's emotions into consideration.

[0489] The server uses communication information acquisition methods to retrieve necessary information from the email system and schedule management system. This information includes project-related emails, meeting schedules, and task deadlines. The collected information is securely stored and managed in a database.

[0490] Next, the server analyzes the acquired data using information analysis tools. Natural language processing techniques are used to extract important keywords and contexts, and identify information relevant to the objectives. This allows for a clearer understanding of the project's progress and potential problems.

[0491] The situation assessment tool objectively evaluates progress based on the analyzed information. This step involves identifying tasks that are behind schedule and risk factors. This allows for the early detection of elements that could hinder goal achievement.

[0492] The server further references a database of similar past cases and generates the optimal solution using a solution generation method. By utilizing a generative artificial intelligence model, optimal strategies and action plans are created based on past success stories.

[0493] The emotion engine analyzes user input data and behavioral history to infer the user's emotional state. This emotional information is used to customize solutions and provide an approach tailored to the user. For example, if a user is stressed, the solution might be simplified and the instructions easier to follow.

[0494] The terminal is responsible for notifying the user of information provided by the server. Through notification methods, the terminal presents the user with progress updates and suggested solutions via dashboards and alerts. Furthermore, it adjusts the tone and detail of notifications according to the user's emotional state.

[0495] As a concrete example, if a project is behind schedule and the user is feeling anxious, the server analyzes emails and schedules to identify the need for resource reallocation. The emotion engine detects the user's anxiety and, taking this into consideration, generates a proposal for a phased task reallocation. This proposal is notified via the device, allowing the user to take action with confidence.

[0496] Thus, the system of the present invention provides users with the necessary support to efficiently achieve their MBO goals, while also taking their emotions into consideration and providing timely assistance.

[0497] The following describes the processing flow.

[0498] Step 1:

[0499] The server uses a means of acquiring communication information to access the email system and schedule management system via an API, and retrieves necessary data such as emails, meeting schedules, and task deadlines related to the project.

[0500] Step 2:

[0501] The server analyzes data acquired using information analysis tools with natural language processing tools. This extracts important keywords and contexts, and identifies information related to project progress. The analysis results are useful for understanding the progress status.

[0502] Step 3:

[0503] The server uses situation assessment tools to evaluate project progress based on the analyzed information. It identifies delayed tasks and potential risks, and clarifies factors that affect goal achievement. This evaluation directly influences subsequent solution proposals.

[0504] Step 4:

[0505] The server uses an emotion engine to analyze the user's past input data and behavioral history to infer their current emotional state. This information is used to determine whether the user is stressed or relaxed.

[0506] Step 5:

[0507] The server considers emotional states, references a database of similar past cases, and uses solution generation tools to generate the optimal solution. A generative artificial intelligence model refers to past success stories and proposes a customized approach tailored to the emotional state.

[0508] Step 6:

[0509] The device uses notification methods to inform the user of the progress and the generated solutions. These notifications adjust their tone and detail according to the user's emotional state, providing information in the most acceptable way.

[0510] Step 7:

[0511] Users check notifications from their devices and decide whether to implement the suggested solutions. If necessary, users provide feedback on the suggestions, share results with the team, and take action to achieve the goals.

[0512] (Example 2)

[0513] 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."

[0514] Modern project management requires the efficient processing of vast amounts of information and the rapid, appropriate decision-making that takes emotional considerations into account. However, conventional systems have limited information acquisition and analysis capabilities, making it difficult to provide responses that address users' emotions. Therefore, there is a need to develop a system that can improve the quality of progress management and problem-solving while reducing users' emotional stress.

[0515] 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.

[0516] In this invention, the server includes a device for acquiring communication information, an information processing device, and an emotion engine using emotion analysis technology. This makes it possible to effectively collect and analyze information necessary for project management and to provide users with timely responses that take emotions into consideration.

[0517] A "device for acquiring communication information" is a device that has the function of collecting information from electronic messaging systems, schedule management systems, etc., and storing it in a database.

[0518] An "information processing device" is a device that analyzes collected information and extracts data related to goal management.

[0519] A "situation assessment device" is a device that evaluates the progress of a project based on analyzed information and identifies risks and delays.

[0520] A "countermeasure generation device" is a device that creates optimal countermeasures using an artificial intelligence model generated based on past cases.

[0521] An "emotion engine" is a system that analyzes the user's emotional state and adjusts the content of the solutions and notifications provided based on the results.

[0522] A "notification device" is a device equipped with output means for delivering and notifying users of the analyzed and generated information.

[0523] As an embodiment of this invention, a support system that combines an emotion engine to provide progress management and problem-solving suggestions is described. In this system, the server, terminal, and user each play specific roles, streamlining project management and providing support that takes the user's emotions into consideration.

[0524] The server uses a device to acquire communication information and collects necessary information from the electronic messaging system and scheduling management system. Specifically, it retrieves emails using IMAP and collects schedule information using REST APIs. The collected data is securely stored in an SQL database.

[0525] Next, the server uses an information processing device to analyze the collected data using natural language processing techniques. This process utilizes the Python NLTK library to extract important keywords and context. This reveals the project's progress and potential problems.

[0526] Furthermore, the server uses an emotion engine to analyze the user's emotional state. It infers emotions from user input and behavior logs and reflects them in solutions and notification content. For example, if a user is feeling stressed, the solution is adjusted to be easily actionable.

[0527] The device displays analysis results and suggested solutions to the user via a notification system. Notifications are delivered via push notifications and dashboards, and their content is optimized according to the user's sentiment.

[0528] As a concrete example, consider a situation where a project is behind schedule. In this case, the server identifies the need for resource reallocation from emails and schedules. The emotion engine detects the user's anxiety and generates a step-by-step task reallocation plan with the prompt, "Propose resource reallocation measures to resolve the project delay." This proposal is notified to the user via their terminal, allowing them to act with confidence.

[0529] This invention enables users to continuously monitor the status of their projects and achieve their goals through appropriate means.

[0530] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0531] Step 1:

[0532] The server uses a device to acquire communication information and retrieves data from an electronic messaging system and a scheduling management system. Specific inputs include information from a mail server and a calendar API. Based on this, it retrieves emails using IMAP and schedule information using a REST API. This data yields output that is stored in an SQL database as project tasks, meeting appointments, and associated messages.

[0533] Step 2:

[0534] The server analyzes the data using an information processing device. The input is email and schedule information collected in step 1. Using natural language processing techniques, keywords and context are extracted using the Python NLTK library. The extracted information is listed as important tasks and progress evaluation points for the project, and the analysis results are obtained as output.

[0535] Step 3:

[0536] The server uses the analysis results from the information processing device to evaluate the project progress using the status evaluation device. The input is the analysis results from step 2. To evaluate delays and risks in schedule progress, the current date is compared with the task schedule to detect delay factors. As a result, a risk assessment report is generated as output.

[0537] Step 4:

[0538] The server uses a countermeasure generation device to create the optimal countermeasure. The input is the delay and risk information identified in step 3. Using a generative AI model, it generates a prompt message, "Propose resource reallocation measures to resolve project delays," based on past success stories. This prompt message prompts the generative AI to output an effective action plan.

[0539] Step 5:

[0540] The server uses an emotion engine to analyze the user's emotional state. Input consists of the user's past input data and behavioral history. Emotion analysis detects stress, anxiety, and other emotional states. This emotional information is used to customize the solutions and notifications provided, resulting in output that includes emotional responses.

[0541] Step 6:

[0542] The terminal displays analysis results and suggested solutions to the user via a notification device. Input is analysis results and solutions provided by the server. Output uses push notifications and dashboards to communicate the situation and suggestions to the user. Notifications are adjusted in tone and content according to the user's emotional state, providing appropriate guidance.

[0543] (Application Example 2)

[0544] 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."

[0545] In modern manufacturing environments, there is a need to efficiently manage the progress of complex processes and improve productivity. Furthermore, it is necessary to identify potential problems in the process early and provide prompt solutions. Additionally, a challenge lies in considering the emotional state of on-site staff and providing optimal solutions while reducing stress.

[0546] 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.

[0547] In this invention, the server includes means for acquiring communication information, means for analyzing information, means for evaluating the situation, means for generating an optimal solution by referring to a data set of similar past cases, means for analyzing the user's emotional information and notifying the user of the solution in a format suitable for the user, and means for monitoring the operating status of factory equipment and managing the progress of the manufacturing process in real time. This enables efficient management of the manufacturing process and the provision of customized feedback tailored to the user.

[0548] "Communication information acquisition means" refers to a device or method for collecting information from electronic communication systems or time management systems.

[0549] "Information analysis means" refers to a technology or process for analyzing communication information related to goal management and extracting important data.

[0550] A "situation assessment method" is a technique for evaluating the progress of a project or manufacturing process based on analyzed information.

[0551] A "solution generation method" is a mechanism for generating the optimal solution by referring to a data set of similar past cases, and it utilizes a generative data processing model.

[0552] "Emotional analysis tools" are means of analyzing a user's emotional information and customizing solutions based on that analysis.

[0553] A "notification method" is an interface or method for communicating progress information or solutions to the user.

[0554] "Monitoring methods" refer to technologies used to monitor the operating status of factory equipment in real time and manage the progress of the manufacturing process.

[0555] This invention provides a system for improving the efficiency of manufacturing processes and reducing worker stress. This system is server-centric and includes means for acquiring communication information, analyzing information, evaluating situations, generating solutions, analyzing emotions, notification, and monitoring.

[0556] The server acquires manufacturing-related information using communication information acquisition means that collect data from electronic communication systems and time management systems. Information analysis means extracts manufacturing progress and related details from the collected data. Next, using situation evaluation means, the progress of the process is evaluated based on the extracted data, and delays and risk factors are identified.

[0557] The solution generation method uses a generative AI model based on past successful cases to propose the optimal solution. This generative AI model is used to build new strategies by referencing data sets from similar projects.

[0558] Furthermore, the server uses sentiment analysis tools to estimate the user's emotional state. This allows the suggested solutions to be customized to take the user's emotions into consideration, providing concise and easy-to-follow instructions, especially if the user is experiencing stress or anxiety.

[0559] Through notification methods, users receive progress updates and customized solutions. The device presents this information to the user in the form of a dashboard or alerts, adjusting the tone and content of notifications based on the user's emotional state.

[0560] For example, if the line is behind schedule, the server monitors its operational status and suggests reallocating necessary resources, while the emotion engine detects user anxiety. The prompt in this scenario would be as follows:

[0561] "Evaluate the progress of the production line and generate optimal resource allocation proposals for efficiency improvements. Also, consider approaches to reduce staff stress based on sentiment analysis."

[0562] In this way, the present invention can significantly improve the efficiency of progress management in manufacturing sites.

[0563] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0564] Step 1:

[0565] The server uses communication information acquisition means to collect data related to the manufacturing line from the electronic communication system and time management system. This includes current task progress, downtime, and error history. The obtained data is then input into the next analysis step.

[0566] Step 2:

[0567] The server analyzes the collected data using information analysis tools. Specifically, it uses natural language processing techniques to extract important keywords and contexts and identify potential problems in the manufacturing process. The keywords and contextual information identified through this analysis are then used for the next progress evaluation.

[0568] Step 3:

[0569] The server objectively evaluates the progress based on the analyzed information using a situation assessment tool. Specifically, it identifies delayed tasks and risk factors and assesses the overall progress level of the production process. This evaluation result is used to generate solutions.

[0570] Step 4:

[0571] The server utilizes solution generation tools, references data from similar past cases, and uses generative AI models to construct optimal solutions. In this step, a new strategy or action plan is generated based on the identified problem.

[0572] Step 5:

[0573] The server uses sentiment analysis tools to analyze user feedback and operation history to infer the user's emotional state. Based on this, the proposed solution is customized to take the user's emotions into consideration.

[0574] Step 6:

[0575] The server notifies the user's device of progress and customized solutions through notification mechanisms. Notifications are displayed as dashboards or alerts, and their content and tone are adjusted according to the user's emotional state.

[0576] 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.

[0577] 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.

[0578] 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.

[0579] [Fourth Embodiment]

[0580] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0581] 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.

[0582] 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).

[0583] 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.

[0584] 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.

[0585] 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).

[0586] 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.

[0587] 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.

[0588] 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.

[0589] 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.

[0590] 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.

[0591] 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.

[0592] 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".

[0593] As an embodiment of the present invention, a support system for progress management and problem-solving proposals using a generated AI model is described below. In this system, the server, terminal, and user each play specific roles, thereby improving the efficiency of management by objectives (MBO).

[0594] The server first uses communication information acquisition methods to periodically retrieve necessary information from email systems and schedule management systems. This information is stored and managed in a secure database. This information includes project-related email content, scheduled meetings, and deadlines.

[0595] Next, the server uses information analysis tools to analyze the collected data. This analysis includes a process of extracting important keywords and context using natural language processing techniques and identifying information relevant to the goals. This makes it easier for the server to understand the project's progress.

[0596] The situation assessment mechanism allows the server to evaluate progress based on the analyzed data. For example, it can identify whether scheduled tasks are behind schedule or where problems are likely to occur. This enables early detection of situations that jeopardize goal achievement.

[0597] The server then refers to a database of similar past cases and uses a solution generation tool to generate the optimal solution for the identified problem. This process utilizes a generative artificial intelligence model to create optimal action plans based on past success stories.

[0598] The terminal is responsible for notifying the user of information provided by the server. Through notification methods, the terminal presents the user with progress information and suggested solutions via dashboards and alerts. This allows the user to take appropriate action in a timely manner.

[0599] For example, if a project is behind schedule, the server analyzes relevant emails and meeting records and determines that a resource shortage is the cause. Based on past cases where similar resource shortages were resolved, the server generates a proposal for reallocating resources and notifies the user via their terminal. The user can then quickly adjust project members based on this proposal.

[0600] Thus, the system of the present invention provides users with the timely support necessary to efficiently achieve their MBO goals.

[0601] The following describes the processing flow.

[0602] Step 1:

[0603] The server uses a communication information acquisition method to access the email system and schedule management system through a pre-configured API and retrieve the necessary data. The information obtained here includes project-related email content, meeting dates, and task deadlines.

[0604] Step 2:

[0605] The server analyzes the data acquired using information analysis tools, employing text analysis tools (e.g., natural language processing techniques). This step extracts key keywords and context, identifying information relevant to the objectives. This helps to uncover project progress and potential problems.

[0606] Step 3:

[0607] The server uses situation assessment tools to evaluate the project's progress based on the analyzed information. This evaluation includes identifying tasks that are behind schedule and predicting potential risks. This allows the server to recognize factors that could hinder the achievement of the goals.

[0608] Step 4:

[0609] The server accesses a database of similar past cases and uses solution generation tools to generate the optimal solution for the identified problem. In this step, a generative artificial intelligence model is used to create the optimal strategy and action plan based on past successes.

[0610] Step 5:

[0611] The device uses notification methods to inform the user of progress and generated solutions. Notifications are displayed as dashboards and alerts, and the user can view detailed reports.

[0612] Step 6:

[0613] Based on notifications received through their devices, users make decisions to take suggested actions. If necessary, users can share information with their team and seek further feedback, enabling them to take action towards achieving their goals.

[0614] (Example 1)

[0615] 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".

[0616] In project management, a challenge lies in the difficulty of understanding progress toward achieving goals and identifying potential risks early on. Furthermore, it is not easy to derive concrete actions for optimizing resources and quickly resolving problems. These factors hinder efficient goal management.

[0617] 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.

[0618] In this invention, the server includes an acquisition means for acquiring communication information, an analysis means for extracting information related to goal management from the acquired communication information using natural language processing, and an evaluation means for evaluating the progress of the project and identifying risks based on the extracted information. This enables accurate understanding of the progress in project management, early detection of potential problems, and provision of optimal solutions utilizing generative AI models.

[0619] "Means for acquiring communication information" refers to devices or software that have the technical functions to collect information from sources such as email and schedule management systems.

[0620] "Analysis methods for extracting information related to goal management using natural language processing" refers to a technology that analyzes text data, detects specific keywords and contexts, and identifies information important for goal management.

[0621] "Evaluation tools for assessing project progress and identifying risks" are technologies that have analytical capabilities to determine the progress of tasks and potential problems based on collected and analyzed information.

[0622] "Generative methods for deriving optimal solutions using generative AI models" refers to technologies that utilize generative artificial intelligence to learn from similar past cases and create efficient action plans.

[0623] A "notification means" is a device or mechanism that has communication functions to effectively convey generated information or action plans to users.

[0624] This invention is a system that uses a generative AI model to monitor project progress and propose solutions to problems in project management. In implementing this invention, it is assumed that the server, terminal, and user each play different roles.

[0625] The server periodically collects information from systems such as email systems and scheduling management systems. Specifically, it accesses these systems to retrieve relevant communication information and stores it in a secure database. High-performance storage systems and security software are used for this data management.

[0626] The collected data is analyzed on the server using natural language processing software. This analysis software automatically extracts key keywords and contexts related to the project and organizes useful information from a goal management perspective.

[0627] Furthermore, the server uses a situation assessment algorithm to evaluate the project's progress based on the extracted information. Risk management software identifies task delays and potential problems, thereby clarifying the prospects for achieving the goals.

[0628] Once a problem is identified, the server uses a generative AI model to generate the optimal solution from a historical database. The generated solution is then notified to the user via their terminal. This process requires a high-performance AI engine.

[0629] The device notifies the user of progress information and solutions provided by the server using visually easy-to-understand dashboards and alerts. This allows the user to make timely and appropriate decisions.

[0630] As a concrete example, if a project is behind schedule, the server uses natural language processing to identify resource shortages as the cause. Based on similar past cases, a generative AI model proposes resource reallocation and notifies the user via their terminal. The user can then quickly adjust the schedules of team members based on this proposal.

[0631] A concrete example of a prompt message is "Check the progress of the development project and generate resource optimization suggestions." This prompt serves as a starting point for the server to evaluate the progress and appropriate resource allocation.

[0632] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0633] Step 1:

[0634] The server collects necessary information from the email system and schedule management system using communication information acquisition methods. Input requires access rights to email accounts and schedule information. This information is retrieved periodically and stored as output in a secure database. Specifically, the server logs in daily, checks for new emails and schedule events, and writes them to the database.

[0635] Step 2:

[0636] The server analyzes the data collected using information analysis tools. The input is the communication information saved in step 1. Using natural language processing (NLP) software, it extracts important keywords and context related to the project and organizes the information necessary for goal management. The output is a list of project-related keywords. Specifically, the server executes a text analysis algorithm to extract keywords such as "deadline," "progress," and "issues."

[0637] Step 3:

[0638] The server uses a situation assessment tool to evaluate the project's progress based on the analyzed information. The keyword list extracted in step 2 is used as input. This data is used to run an evaluation algorithm to identify task delays and risks. An evaluation results report is generated as output. Specifically, the server compares the scheduled completion date of a task with the current date and creates a list of delayed tasks.

[0639] Step 4:

[0640] The server uses a solution generation mechanism to refer to a database of similar past cases and generate the optimal solution. The evaluation results generated in step 3 are used as input. The generation AI model is utilized to output the optimal action plan based on the database. Specifically, the server searches for similar problem-solving cases and creates the optimal action plan proposed by the AI.

[0641] Step 5:

[0642] The terminal notifies the user based on information sent from the server. The solution generated in step 4 is received by the terminal as input. Using notification methods, progress information and suggested solutions are displayed to the user through dashboards and alerts. The output provides the user with clear instructions for action. Specifically, the terminal sends a notification to the user's device and displays the solution on the dashboard.

[0643] This series of processes enables users to make appropriate and swift decisions and efficiently achieve their goals.

[0644] (Application Example 1)

[0645] 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".

[0646] In logistics facilities, it is crucial to streamline progress management and problem resolution regarding package delivery. However, conventional systems failed to detect delays and develop appropriate countermeasures in a timely manner, leading to decreased productivity. Furthermore, manual management was inefficient and placed a burden on the overall project progress.

[0647] 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.

[0648] In this invention, the server includes means for acquiring communication data, means for processing information, means for determining the situation, means for generating alternative solutions, means for notifying, and a function for analyzing information in logistics facilities, detecting delivery delays, and proposing additional personnel or route optimization. This makes it possible to streamline package management within logistics facilities and to quickly manage progress and resolve issues.

[0649] "Communication data acquisition means" refers to a device or software that has the function of acquiring necessary data from email or a schedule management system.

[0650] "Information processing means" refers to a technology or process for extracting and analyzing meaningful information related to achieving a goal from acquired data.

[0651] "Situation assessment means" refers to methods and devices for evaluating progress based on analyzed data and identifying problems and delays.

[0652] A "means for generating alternative solutions" refers to a system or model that generates the optimal solution by referring to a database of similar past cases.

[0653] A "notification system" refers to a communication or notification system used to convey generated solutions or proposals to users.

[0654] A "logistics facility" refers to a center or building used for packaging, storing, transporting, and sorting goods.

[0655] As an embodiment of the present invention, a system that supports progress management and problem-solving of packages within a logistics facility will be described. In this system, the server, terminals, and users each play specific roles in order to improve the efficiency of the logistics process.

[0656] The server periodically retrieves data from the email system and schedule management system using communication data acquisition means. This data includes information such as delivery schedules and shipping status. The retrieved data is stored in a secure database. Next, the server uses information processing means to analyze the data and employs natural language processing techniques to extract important information related to achieving goals. Particular emphasis is placed on determining information about transportation delays and the progress of scheduled tasks.

[0657] Based on the analyzed data, the server uses a situation assessment tool to evaluate the progress within the logistics facility. This allows for, for example, the detection of delays in arriving packages and the identification of situations requiring action. For detected problems, the system utilizes an alternative solution generation tool to propose the optimal solution based on similar past cases. This process is carried out using a generative AI model, which seeks the optimal solution based on past success stories.

[0658] The generated solutions are notified to the user via a notification system through the device. The device's notification function is used to display progress information and proposed solutions through a dashboard or alerts.

[0659] For example, if a delivery at a logistics facility is delayed beyond the scheduled time, the server analyzes the cause and suggests additional personnel or route optimization. Based on this information, users can take the next steps quickly and effectively.

[0660] A concrete example of a prompt message would be, "Please tell me the best solution in case of a delivery delay." This allows the user to easily receive problem-solving solutions generated by the AI ​​model.

[0661] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0662] Step 1:

[0663] The server uses communication data acquisition methods to retrieve delivery-related data from email systems and schedule management systems. The input is periodic information retrieval requests made via APIs. The output is the retrieved email and schedule data, which is stored in a secure database. Specifically, the server communicates with external systems using data transfer protocols to collect the necessary datasets.

[0664] Step 2:

[0665] The server uses information processing tools to analyze the acquired data using natural language processing techniques. The input is the raw data acquired in the previous step. By using information processing techniques, it extracts important keywords and contexts related to achieving the goal. The output is a list of the analyzed important information. Specifically, it executes a text analysis algorithm and performs a process of identifying highly relevant words.

[0666] Step 3:

[0667] The server evaluates the progress based on the analyzed information using a situation assessment tool. The input is the information analyzed in step 2. Through this evaluation, potential problems and delays are identified. The output is listed as the evaluation results for each project and shipping operation. Specifically, to evaluate the progress, the server scores the data according to evaluation rules and applies an algorithm that highlights potential problems.

[0668] Step 4:

[0669] The server utilizes alternative solution generation mechanisms to generate solutions based on similar past cases. The input consists of the evaluation results from step 3 and a historical database. The output is a proposed solution to address the issue. A generative AI model is used to provide the optimal path. This process involves modeling algorithms based on past successes and performing specific actions to predict new solutions.

[0670] Step 5:

[0671] The terminal uses a notification system to inform the user of the generated solution. The input is the solution generated in step 4. The output is notification information in the form of a dashboard or alert presented to the user. Specifically, the system delivers notifications in a user-friendly manner based on UI / UX design, enabling the user to take the necessary actions.

[0672] Step 6:

[0673] The user requests additional information from the generated AI model using prompt statements. The input is a prompt statement such as, "What is the best solution in case of delivery delays?" The output is additional solutions and information obtained from the model. Specifically, the user uses an interface on their device to receive further recommendations and make quick decisions based on the newly provided information.

[0674] 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.

[0675] As an embodiment of the present invention, a support system for progress management and problem-solving suggestions that combines an emotion engine will be described. In this system, the server, terminal, and user each play specific roles, providing efficient goal management and support that takes the user's emotions into consideration.

[0676] The server uses communication information acquisition methods to retrieve necessary information from the email system and schedule management system. This information includes project-related emails, meeting schedules, and task deadlines. The collected information is securely stored and managed in a database.

[0677] Next, the server analyzes the acquired data using information analysis tools. Natural language processing techniques are used to extract important keywords and contexts, and identify information relevant to the objectives. This allows for a clearer understanding of the project's progress and potential problems.

[0678] The situation assessment tool objectively evaluates progress based on the analyzed information. This step involves identifying tasks that are behind schedule and risk factors. This allows for the early detection of elements that could hinder goal achievement.

[0679] The server further references a database of similar past cases and generates the optimal solution using a solution generation method. By utilizing a generative artificial intelligence model, optimal strategies and action plans are created based on past success stories.

[0680] The emotion engine analyzes user input data and behavioral history to infer the user's emotional state. This emotional information is used to customize solutions and provide an approach tailored to the user. For example, if a user is stressed, the solution might be simplified and the instructions easier to follow.

[0681] The terminal is responsible for notifying the user of information provided by the server. Through notification methods, the terminal presents the user with progress updates and suggested solutions via dashboards and alerts. Furthermore, it adjusts the tone and detail of notifications according to the user's emotional state.

[0682] As a concrete example, if a project is behind schedule and the user is feeling anxious, the server analyzes emails and schedules to identify the need for resource reallocation. The emotion engine detects the user's anxiety and, taking this into consideration, generates a proposal for a phased task reallocation. This proposal is notified via the device, allowing the user to take action with confidence.

[0683] Thus, the system of the present invention provides users with the necessary support to efficiently achieve their MBO goals, while also taking their emotions into consideration and providing timely assistance.

[0684] The following describes the processing flow.

[0685] Step 1:

[0686] The server uses a means of acquiring communication information to access the email system and schedule management system via an API, and retrieves necessary data such as emails, meeting schedules, and task deadlines related to the project.

[0687] Step 2:

[0688] The server analyzes data acquired using information analysis tools with natural language processing tools. This extracts important keywords and contexts, and identifies information related to project progress. The analysis results are useful for understanding the progress status.

[0689] Step 3:

[0690] The server uses situation assessment tools to evaluate project progress based on the analyzed information. It identifies delayed tasks and potential risks, and clarifies factors that affect goal achievement. This evaluation directly influences subsequent solution proposals.

[0691] Step 4:

[0692] The server uses an emotion engine to analyze the user's past input data and behavioral history to infer their current emotional state. This information is used to determine whether the user is stressed or relaxed.

[0693] Step 5:

[0694] The server considers emotional states, references a database of similar past cases, and uses solution generation tools to generate the optimal solution. A generative artificial intelligence model refers to past success stories and proposes a customized approach tailored to the emotional state.

[0695] Step 6:

[0696] The device uses notification methods to inform the user of the progress and the generated solutions. These notifications adjust their tone and detail according to the user's emotional state, providing information in the most acceptable way.

[0697] Step 7:

[0698] Users check notifications from their devices and decide whether to implement the suggested solutions. If necessary, users provide feedback on the suggestions, share results with the team, and take action to achieve the goals.

[0699] (Example 2)

[0700] 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".

[0701] Modern project management requires the efficient processing of vast amounts of information and the rapid, appropriate decision-making that takes emotional considerations into account. However, conventional systems have limited information acquisition and analysis capabilities, making it difficult to provide responses that address users' emotions. Therefore, there is a need to develop a system that can improve the quality of progress management and problem-solving while reducing users' emotional stress.

[0702] 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.

[0703] In this invention, the server includes a device for acquiring communication information, an information processing device, and an emotion engine using emotion analysis technology. This makes it possible to effectively collect and analyze information necessary for project management and to provide users with timely responses that take emotions into consideration.

[0704] A "device for acquiring communication information" is a device that has the function of collecting information from electronic messaging systems, schedule management systems, etc., and storing it in a database.

[0705] An "information processing device" is a device that analyzes collected information and extracts data related to goal management.

[0706] A "situation assessment device" is a device that evaluates the progress of a project based on analyzed information and identifies risks and delays.

[0707] A "countermeasure generation device" is a device that creates optimal countermeasures using an artificial intelligence model generated based on past cases.

[0708] An "emotion engine" is a system that analyzes the user's emotional state and adjusts the content of the solutions and notifications provided based on the results.

[0709] A "notification device" is a device equipped with output means for delivering and notifying users of the analyzed and generated information.

[0710] As an embodiment of this invention, a support system that combines an emotion engine to provide progress management and problem-solving suggestions is described. In this system, the server, terminal, and user each play specific roles, streamlining project management and providing support that takes the user's emotions into consideration.

[0711] The server uses a device to acquire communication information and collects necessary information from the electronic messaging system and scheduling management system. Specifically, it retrieves emails using IMAP and collects schedule information using REST APIs. The collected data is securely stored in an SQL database.

[0712] Next, the server uses an information processing device to analyze the collected data using natural language processing techniques. This process utilizes the Python NLTK library to extract important keywords and context. This reveals the project's progress and potential problems.

[0713] Furthermore, the server uses an emotion engine to analyze the user's emotional state. It infers emotions from user input and behavior logs and reflects them in solutions and notification content. For example, if a user is feeling stressed, the solution is adjusted to be easily actionable.

[0714] The device displays analysis results and suggested solutions to the user via a notification system. Notifications are delivered via push notifications and dashboards, and their content is optimized according to the user's sentiment.

[0715] As a concrete example, consider a situation where a project is behind schedule. In this case, the server identifies the need for resource reallocation from emails and schedules. The emotion engine detects the user's anxiety and generates a step-by-step task reallocation plan with the prompt, "Propose resource reallocation measures to resolve the project delay." This proposal is notified to the user via their terminal, allowing them to act with confidence.

[0716] This invention enables users to continuously monitor the status of their projects and achieve their goals through appropriate means.

[0717] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0718] Step 1:

[0719] The server uses a device to acquire communication information and retrieves data from an electronic messaging system and a scheduling management system. Specific inputs include information from a mail server and a calendar API. Based on this, it retrieves emails using IMAP and schedule information using a REST API. This data yields output that is stored in an SQL database as project tasks, meeting appointments, and associated messages.

[0720] Step 2:

[0721] The server analyzes the data using an information processing device. The input is email and schedule information collected in step 1. Using natural language processing techniques, keywords and context are extracted using the Python NLTK library. The extracted information is listed as important tasks and progress evaluation points for the project, and the analysis results are obtained as output.

[0722] Step 3:

[0723] The server uses the analysis results from the information processing device to evaluate the project progress using the status evaluation device. The input is the analysis results from step 2. To evaluate delays and risks in schedule progress, the current date is compared with the task schedule to detect delay factors. As a result, a risk assessment report is generated as output.

[0724] Step 4:

[0725] The server uses a countermeasure generation device to create the optimal countermeasure. The input is the delay and risk information identified in step 3. Using a generative AI model, it generates a prompt message, "Propose resource reallocation measures to resolve project delays," based on past success stories. This prompt message prompts the generative AI to output an effective action plan.

[0726] Step 5:

[0727] The server uses an emotion engine to analyze the user's emotional state. Input consists of the user's past input data and behavioral history. Emotion analysis detects stress, anxiety, and other emotional states. This emotional information is used to customize the solutions and notifications provided, resulting in output that includes emotional responses.

[0728] Step 6:

[0729] The terminal displays analysis results and suggested solutions to the user via a notification device. Input is analysis results and solutions provided by the server. Output uses push notifications and dashboards to communicate the situation and suggestions to the user. Notifications are adjusted in tone and content according to the user's emotional state, providing appropriate guidance.

[0730] (Application Example 2)

[0731] 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".

[0732] In modern manufacturing environments, there is a need to efficiently manage the progress of complex processes and improve productivity. Furthermore, it is necessary to identify potential problems in the process early and provide prompt solutions. Additionally, a challenge lies in considering the emotional state of on-site staff and providing optimal solutions while reducing stress.

[0733] 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.

[0734] In this invention, the server includes means for acquiring communication information, means for analyzing information, means for evaluating the situation, means for generating an optimal solution by referring to a data set of similar past cases, means for analyzing the user's emotional information and notifying the user of the solution in a format suitable for the user, and means for monitoring the operating status of factory equipment and managing the progress of the manufacturing process in real time. This enables efficient management of the manufacturing process and the provision of customized feedback tailored to the user.

[0735] "Communication information acquisition means" refers to a device or method for collecting information from electronic communication systems or time management systems.

[0736] "Information analysis means" refers to a technology or process for analyzing communication information related to goal management and extracting important data.

[0737] A "situation assessment method" is a technique for evaluating the progress of a project or manufacturing process based on analyzed information.

[0738] A "solution generation method" is a mechanism for generating the optimal solution by referring to a data set of similar past cases, and it utilizes a generative data processing model.

[0739] "Emotional analysis tools" are means of analyzing a user's emotional information and customizing solutions based on that analysis.

[0740] A "notification method" is an interface or method for communicating progress information or solutions to the user.

[0741] "Monitoring methods" refer to technologies used to monitor the operating status of factory equipment in real time and manage the progress of the manufacturing process.

[0742] This invention provides a system for improving the efficiency of manufacturing processes and reducing worker stress. This system is server-centric and includes means for acquiring communication information, analyzing information, evaluating situations, generating solutions, analyzing emotions, notification, and monitoring.

[0743] The server acquires manufacturing-related information using communication information acquisition means that collect data from electronic communication systems and time management systems. Information analysis means extracts manufacturing progress and related details from the collected data. Next, using situation evaluation means, the progress of the process is evaluated based on the extracted data, and delays and risk factors are identified.

[0744] The solution generation method uses a generative AI model based on past successful cases to propose the optimal solution. This generative AI model is used to build new strategies by referencing data sets from similar projects.

[0745] Furthermore, the server uses sentiment analysis tools to estimate the user's emotional state. This allows the suggested solutions to be customized to take the user's emotions into consideration, providing concise and easy-to-follow instructions, especially if the user is experiencing stress or anxiety.

[0746] Through notification methods, users receive progress updates and customized solutions. The device presents this information to the user in the form of a dashboard or alerts, adjusting the tone and content of notifications based on the user's emotional state.

[0747] For example, if the line is behind schedule, the server monitors its operational status and suggests reallocating necessary resources, while the emotion engine detects user anxiety. The prompt in this scenario would be as follows:

[0748] "Evaluate the progress of the production line and generate optimal resource allocation proposals for efficiency improvements. Also, consider approaches to reduce staff stress based on sentiment analysis."

[0749] In this way, the present invention can significantly improve the efficiency of progress management in manufacturing sites.

[0750] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0751] Step 1:

[0752] The server uses communication information acquisition means to collect data related to the manufacturing line from the electronic communication system and time management system. This includes current task progress, downtime, and error history. The obtained data is then input into the next analysis step.

[0753] Step 2:

[0754] The server analyzes the collected data using information analysis tools. Specifically, it uses natural language processing techniques to extract important keywords and contexts and identify potential problems in the manufacturing process. The keywords and contextual information identified through this analysis are then used for the next progress evaluation.

[0755] Step 3:

[0756] The server objectively evaluates the progress based on the analyzed information using a situation assessment tool. Specifically, it identifies delayed tasks and risk factors and assesses the overall progress level of the production process. This evaluation result is used to generate solutions.

[0757] Step 4:

[0758] The server utilizes solution generation tools, references data from similar past cases, and uses generative AI models to construct optimal solutions. In this step, a new strategy or action plan is generated based on the identified problem.

[0759] Step 5:

[0760] The server uses sentiment analysis tools to analyze user feedback and operation history to infer the user's emotional state. Based on this, the proposed solution is customized to take the user's emotions into consideration.

[0761] Step 6:

[0762] The server notifies the user's device of progress and customized solutions through notification mechanisms. Notifications are displayed as dashboards or alerts, and their content and tone are adjusted according to the user's emotional state.

[0763] 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.

[0764] 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.

[0765] 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.

[0766] 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.

[0767] 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.

[0768] 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.

[0769] 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.

[0770] 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.

[0771] 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."

[0772] 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.

[0773] 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.

[0774] 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.

[0775] 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.

[0776] 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.

[0777] 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.

[0778] 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.

[0779] 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.

[0780] 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.

[0781] 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.

[0782] 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.

[0783] 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.

[0784] The following is further disclosed regarding the embodiments described above.

[0785] (Claim 1)

[0786] Means for acquiring communication information,

[0787] Information analysis means for extracting information related to goal management from the aforementioned communication information,

[0788] A status evaluation means for evaluating the progress status based on the information analyzed by the aforementioned information analysis means,

[0789] A solution generation method that generates the optimal solution by referring to a database of similar past cases,

[0790] A notification means for notifying the user of the aforementioned solution,

[0791] A system that includes this.

[0792] (Claim 2)

[0793] The system according to claim 1, wherein the communication information acquisition means acquires information from an email system and a schedule management system.

[0794] (Claim 3)

[0795] The system according to claim 1, wherein the solution generation means generates a solution using a generative artificial intelligence model.

[0796] "Example 1"

[0797] (Claim 1)

[0798] Means for obtaining communication information,

[0799] An analysis means for extracting information related to goal management from acquired communication information using natural language processing,

[0800] An evaluation method for assessing project progress and identifying risks based on extracted information,

[0801] A generation method that refers to records of similar past cases and uses a generation AI model to derive the optimal solution,

[0802] A notification mechanism to inform the user of the generated solution,

[0803] A system that includes this.

[0804] (Claim 2)

[0805] The system according to claim 1, wherein the acquisition means acquires information from a communication system and a schedule management system.

[0806] (Claim 3)

[0807] The system according to claim 1, wherein the generation means creates a solution using a generative artificial intelligence model.

[0808] "Application Example 1"

[0809] (Claim 1)

[0810] Means for acquiring communication data,

[0811] Information processing means for extracting information related to achieving the goal from the aforementioned communication data,

[0812] A situation determination means for evaluating the progress based on the information analyzed by the aforementioned information processing means,

[0813] A means for generating alternative solutions that references a database of similar past cases to generate the optimal solution,

[0814] A notification means for transmitting the aforementioned solution to the user,

[0815] A system that analyzes information from logistics facilities, detects delivery delays, and includes functions to suggest additional personnel or route optimization.

[0816] (Claim 2)

[0817] The system according to claim 1, wherein the communication data acquisition means acquires data from an email system and a schedule management system.

[0818] (Claim 3)

[0819] The system according to claim 1, wherein the alternative solution generation means generates alternative solutions using a generative artificial intelligence model.

[0820] "Example 2 of combining an emotion engine"

[0821] (Claim 1)

[0822] A device for acquiring communication information,

[0823] An information processing device that extracts information related to goal management from the aforementioned communication information,

[0824] A status evaluation device that evaluates the progress status based on the information processed by the aforementioned information processing device,

[0825] A countermeasure generation device that generates the optimal countermeasure by referring to past data of similar cases,

[0826] An emotion engine that uses emotion analysis technology to estimate the user's emotional state and adjusts the notification content based on that,

[0827] A notification device that notifies the user of the aforementioned countermeasures,

[0828] A system that includes this.

[0829] (Claim 2)

[0830] The system according to claim 1, wherein the device for acquiring the communication information acquires information from an electronic messaging system and a schedule management system.

[0831] (Claim 3)

[0832] The system according to claim 1, wherein the countermeasure generation device generates countermeasures using the artificial intelligence model it generates.

[0833] "Application example 2 when combining with an emotional engine"

[0834] (Claim 1)

[0835] Means for acquiring communication information,

[0836] Information analysis means for extracting information related to goal management from the aforementioned communication information,

[0837] A status evaluation means for evaluating the progress status based on the information analyzed by the aforementioned information analysis means,

[0838] A solution generation method that generates the optimal solution by referring to a data set of similar past cases,

[0839] A sentiment analysis means for analyzing user sentiment information and notifying the user of the aforementioned solution in a manner suitable for the user,

[0840] A notification means for notifying the user of the aforementioned solution,

[0841] A monitoring system that monitors the operating status of factory equipment and manages the progress of the manufacturing process in real time,

[0842] A system that includes this.

[0843] (Claim 2)

[0844] The system according to claim 1, wherein the communication information acquisition means acquires information from an electronic communication system and a time management system.

[0845] (Claim 3)

[0846] The system according to claim 1, wherein the solution generation means generates a solution using a generative data processing model. [Explanation of Symbols]

[0847] 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. Means for acquiring communication data, Information processing means for extracting information related to achieving the goal from the aforementioned communication data, A situation determination means for evaluating the progress based on the information analyzed by the aforementioned information processing means, A means for generating alternative solutions that references a database of similar past cases to generate the optimal solution, A notification means for transmitting the aforementioned solution to the user, A system that analyzes information from logistics facilities, detects delivery delays, and includes functions to suggest additional personnel or route optimization.

2. The system according to claim 1, wherein the communication data acquisition means acquires data from an email system and a schedule management system.

3. The system according to claim 1, wherein the alternative solution generation means generates alternative solutions using a generative artificial intelligence model.

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